<?xml version="1.0"?>
<feed xmlns="http://www.w3.org/2005/Atom" xml:lang="en">
	<id>https://wiki.gri.co/api.php?action=feedcontributions&amp;feedformat=atom&amp;user=Flc</id>
	<title>Growth Resources - User contributions [en]</title>
	<link rel="self" type="application/atom+xml" href="https://wiki.gri.co/api.php?action=feedcontributions&amp;feedformat=atom&amp;user=Flc"/>
	<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php/Special:Contributions/Flc"/>
	<updated>2026-05-19T22:22:59Z</updated>
	<subtitle>User contributions</subtitle>
	<generator>MediaWiki 1.39.3</generator>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3392</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3392"/>
		<updated>2026-05-09T16:33:09Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a crucial call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches.&amp;lt;ref&amp;gt;Research framework primarily uses Miles and Huberman&#039;s qualitative (and quantitative) methodologies, coupled with other works, notably those of Wacheux and GRI&#039;s own framework focused on assessment techniques:&amp;lt;br/&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- Miles, M. B., &amp;amp; Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). SAGE Publications.&amp;lt;br/&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- Wacheux, F. (1996). Méthodes Qualitatives de Recherche en Gestion. Economica.&amp;lt;br&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- GRI general framework. [[General_Framework|See details on the framework, methods and references here on this wiki.]]&amp;lt;/ref&amp;gt; The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
The above &amp;quot;I&amp;quot; in the text conducting the study is Frederic Lucas-Conwell. Frederic is also the founder and President of the Growth Resources Institute and the author of the tools and techniques behind the adaptive profiles used in the study. The &amp;quot;we&amp;quot; in the text sometimes refers to all involved in the work we do at GRI, and at other times to all of us as human beings.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3391</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3391"/>
		<updated>2026-05-09T16:30:52Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a crucial call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches.&amp;lt;ref&amp;gt;Research framework primarily uses Miles and Huberman&#039;s qualitative (and quantitative) methodologies, coupled with other works, notably those of Wacheux and GRI&#039;s own framework focusing on assessment techniques:&amp;lt;br/&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- Miles, M. B., &amp;amp; Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). SAGE Publications.&amp;lt;br/&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- Wacheux, F. (1996). Méthodes Qualitatives de Recherche en Gestion. Economica.&amp;lt;br&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- GRI general framework. [[General_Framework|See details on the framework, methods and references here on this wiki.]]&amp;lt;/ref&amp;gt; The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
The above &amp;quot;I&amp;quot; in the text conducting the study is Frederic Lucas-Conwell. Frederic is also the founder and President of the Growth Resources Institute and the author of the tools and techniques behind the adaptive profiles used in the study. The &amp;quot;we&amp;quot; in the text sometimes refers to all involved in the work we do at GRI, and at other times to all of us as human beings.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3390</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3390"/>
		<updated>2026-05-09T16:24:21Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a crucial call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches.&amp;lt;ref&amp;gt;Research framework primarily uses Miles and Huberman&#039;s qualitative (and quantitative) methodologies, coupled with other works, notably those of Wacheux and GRI&#039;s own framework focusing on assessment techniques:&amp;lt;br/&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- Miles, M. B., &amp;amp; Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). SAGE Publications.&amp;lt;br/&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- Wacheux, F. (1996). Méthodes Qualitatives de Recherche en Gestion. Economica.&amp;lt;br&amp;gt;&amp;amp;nbsp;&amp;amp;nbsp;- GRI general framework. [[General_Framework|See details on the framework, methods and references here on this wiki.]]&amp;lt;/ref&amp;gt; The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
The above &amp;quot;I&amp;quot; mentioned in the text conducting the study is Frederic Lucas-Conwell. Frederic is also the founder and President of the Growth Resources Institute and the author of the tools and techniques behind the adaptive profiles used in the study. The &amp;quot;we&amp;quot; in the text sometimes refers to all involved in the work we do at GRI, and at other times to all of us as human beings.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3389</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3389"/>
		<updated>2026-05-09T16:14:46Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a crucial call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches.&amp;lt;ref&amp;gt;Research framework primarily uses Miles and Huberman&#039;s qualitative (and quantitative) methodologies, coupled with other works, notably Wacheux, and our own GRI framework, focusing on assessment techniques, which led to the use of the GRI techniques. See references here:&amp;lt;br/&amp;gt; Miles, M. B., &amp;amp; Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (2nd ed.). SAGE Publications.&amp;lt;br/&amp;gt; Wacheux, F. (1996). Méthodes Qualitatives de Recherche en Gestion. Economica.&amp;lt;br&amp;gt; GRI general framework. [[See here on this wiki| General_Framework.]]&amp;lt;/ref&amp;gt; The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
The above &amp;quot;I&amp;quot; mentioned in the text conducting the study is Frederic Lucas-Conwell. Frederic is also the founder and President of the Growth Resources Institute and the author of the tools and techniques behind the adaptive profiles used in the study. The &amp;quot;we&amp;quot; in the text sometimes refers to all involved in the work we do at GRI, and at other times to all of us as human beings.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3388</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3388"/>
		<updated>2026-05-09T16:01:36Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Origin of the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a crucial call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
The above &amp;quot;I&amp;quot; mentioned in the text conducting the study is Frederic Lucas-Conwell. Frederic is also the founder and President of the Growth Resources Institute and the author of the tools and techniques behind the adaptive profiles used in the study. The &amp;quot;we&amp;quot; in the text sometimes refers to all involved in the work we do at GRI, and at other times to all of us as human beings.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3387</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3387"/>
		<updated>2026-05-08T20:30:52Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
The above &amp;quot;I&amp;quot; mentioned in the text conducting the study is Frederic Lucas-Conwell. Frederic is also the founder and President of the Growth Resources Institute and the author of the tools and techniques behind the adaptive profiles used in the study. The &amp;quot;we&amp;quot; in the text sometimes refers to all involved in the work we do at GRI, and at other times to all of us as human beings.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3386</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3386"/>
		<updated>2026-05-08T20:29:52Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
The above &amp;quot;I&amp;quot; mentioned in the text conducting the study is Frederic Lucas-Conwell. Frederic is also the founder and President of the Growth Resources Institute and the author of the tools and techniques behind the adaptive profiles used in the study. The &amp;quot;we&amp;quot; in the text sometimes refers to all involved in the work we do at GRI, and at other times to all of us as human beings.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3385</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3385"/>
		<updated>2026-05-08T20:19:16Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Origin of the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, that they both testified, they &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3384</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3384"/>
		<updated>2026-05-08T20:17:09Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Origin of the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win&amp;lt;Ref&amp;gt;See here the book: Searle, G. (2012). If Not Now, When?: One Man&#039;s Extraordinary Quest for Olympic Glory, Twenty Years After His First Gold Medal. London: Macmillan.&amp;lt;/br&amp;gt;See here the video on onlympics.com. The spark at 5:53: https://olympics.com/en/video/rowing-sydney-2000-coxless-pair-men.&amp;lt;/ref&amp;gt;&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way that they both testified  &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3383</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3383"/>
		<updated>2026-05-08T20:00:43Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way that they both testified  &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level&amp;lt;ref&amp;gt;For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;br /&gt;
&amp;lt;/ref&amp;gt;. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3382</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3382"/>
		<updated>2026-05-08T19:58:58Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Notes */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way that they both testified  &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3381</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3381"/>
		<updated>2026-05-08T19:58:36Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Results Data */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way that they both testified  &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics&amp;lt;ref&amp;gt;For the results of all races on the World Rowing website https://worldrowing.com).&amp;lt;/ref&amp;gt;. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3380</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3380"/>
		<updated>2026-05-08T19:57:51Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* References */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way that they both testified  &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3379</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3379"/>
		<updated>2026-05-08T19:55:18Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Origin of the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American Games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat to a substantial margin (yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way that they both testified  &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a huge difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3378</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3378"/>
		<updated>2026-05-08T19:51:45Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Origin of the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat with a substantial margin (Yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, they testified, both &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3377</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3377"/>
		<updated>2026-05-08T19:07:51Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Origin of the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat with a substantial margin (Yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly boosted and sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, they testified, both &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words, can make a difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3376</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3376"/>
		<updated>2026-05-08T19:06:49Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat with a substantial margin (Yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly boosted and sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, they testified, both &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words,&amp;quot; can make the difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study. &lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3375</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3375"/>
		<updated>2026-05-08T19:06:06Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Origin of the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat with a substantial margin (Yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly boosted and sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, they testified, both &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words,&amp;quot; can make the difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 race in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot, with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), and the chance to be in contact with extraordinary people at an extraordinary time ultimately led to this study. &lt;br /&gt;
&lt;br /&gt;
=Running the Study=&lt;br /&gt;
Rather than introducing new anecdotes about rowing, the project began with methodologies borrowed from the social sciences that blend qualitative and quantitative approaches. The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial.&lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles, provide feedback to the athletes, and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3374</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3374"/>
		<updated>2026-05-08T18:01:50Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Running the Study */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat with a substantial margin (Yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly boosted and sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, they testified, both &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words,&amp;quot; can make the difference. Context apparently greatly matters. Sincere, great relationships too.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), is ultimately the origin of this study. Rather than introducing new anecdotes about rowing, the project started with methodologies borrowed from the social sciences.  &lt;br /&gt;
&lt;br /&gt;
The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3373</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3373"/>
		<updated>2026-05-08T17:56:54Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* An Unprecedented Victory */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet. The number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat with a substantial margin (Yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly boosted and sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, they testified, both &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words,&amp;quot; can make the difference.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), is ultimately the origin of this study. Rather than introducing new anecdotes about rowing, the project started with methodologies borrowed from the social sciences.  &lt;br /&gt;
&lt;br /&gt;
The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3372</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3372"/>
		<updated>2026-05-08T17:54:06Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* An Unprecedented Victory */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
&lt;br /&gt;
According to our analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977, including men, women, and the Olympic level. This is a monumental achievement in rowing, setting a new world record. &lt;br /&gt;
&lt;br /&gt;
Conditions in rowing can vary significantly from race to race, but the margin between the first and second boats provides an accurate assessment of how well the winning boat performed. A winning margin of 7.16 seconds for the 2016 USA Women U23 8+, when on average, U23 and Senior confounded is 2.05 seconds, in a sport where a millisecond can make a difference, is simply astounding. As we have continued to track results since we started this study, this achievement has not been surpassed yet.&lt;br /&gt;
&lt;br /&gt;
In a sport where athletes are in such close proximity, the number of factors at play that impact results is numerous, starting well before the race, and including human factors that, by nature, are hard to capture.&lt;br /&gt;
&lt;br /&gt;
=Running the Study=  &lt;br /&gt;
&lt;br /&gt;
The study started in 2023 (yes, that&#039;s correct, seven years after the 2016 event), with the conjunction of watching rowing races in Chile at the Pan-American games (yes, it&#039;s weird!), where Colette coaxed the US mixed boat with a substantial margin (Yes! Colette is my daughter), and seeing Jean-Christophe Rolland, the President of the International Rowing Federation, awarding medals. Rolland is best known for the Sydney 2000 Olympics victory in the pair with Michel Andrieux, when he made a call of three words (yes! just three words) &amp;quot;pour nos enfants&amp;quot; that instantly boosted and sparked their decisive win.&lt;br /&gt;
&lt;br /&gt;
If a win in a rowing pair can happen so decisively with only three words, between two people led by a potential win, trapped in a shell (yes, they apparently enjoy it!), but being connected in a way, they testified, both &amp;quot;could only dream of&amp;quot;, there may be something we can learn about it, in sports but also in business. Small factors, as little as three words,&amp;quot; can make the difference.&lt;br /&gt;
 &lt;br /&gt;
Having watched the U23 2016 in person, still stunned by its results compared to all other races I have watched (Yes, quite a lot with two of my daughters and my wife rowing), coupled with my passion for business performance (Yes, I am an entrepreneur with a PhD in management science), is ultimately the origin of this study. Rather than introducing new anecdotes about rowing, the project started with methodologies borrowed from the social sciences.  &lt;br /&gt;
&lt;br /&gt;
The challenge added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
I was fortunate to obtain the team&#039;s GRI adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3371</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3371"/>
		<updated>2026-05-08T16:38:32Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Results Data */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
The other challenge we added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3370</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3370"/>
		<updated>2026-05-08T16:35:55Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Introduction */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
=An Unprecedented Victory=&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
The other challenge we added to the study: to learn from this success about how performance also occurs in competitive businesses, proved, over time, to be substantial. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3369</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3369"/>
		<updated>2026-05-08T16:26:28Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We added another challenge to the study, which, over time, proved substantial: to learn from this success about how performance also occurs in competitive businesses. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3368</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3368"/>
		<updated>2026-05-08T16:23:19Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We added another challenge to the study, which, over time, proved substantial: to learn from this success about how performance also occurs in competitive businesses. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain.&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first- and second-place 8+ boats since 1977, for men and women, U23 and senior, at the World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered from smallest to largest in each of the four categories. Although the results are comparable, analysis by category may reveal striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a concern in rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, well before the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results are comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results were due to any external factors beyond the team&#039;s efforts, such as weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results for men and women in the U23 (Under 23 years old) and senior categories at the World Championship level, including the Olympics. Since we were interested in testing how much the first boat won, only the first two results are included in the tables. Weather conditions can vary significantly from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing results with other years. However, the margin between the first and second boats does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For the results of all races on the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3367</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3367"/>
		<updated>2026-05-08T16:19:21Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We added another challenge to the study, which, over time, proved substantial: to learn from this success about how performance also occurs in competitive businesses. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts. &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are as follows: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), and Wesley Ng (coach). We are grateful for their generous participation in this study, which has spanned several years, and for the key involvement of their coxswain. &lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first and second 8+ boats since 1977, men and women, U23 and senior, at a World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered by increasing value, from the smallest to the highest, in each of the four categories. Although the results are comparable, analysis by category may evidence striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a matter of concern in the sport of rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, which was much earlier than the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results tend to be comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results would result from any external factors to the team efforts, such as the weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results of men and women at the U23 (Under 23 years old) and senior categories at a World Championship level, Olympics included. Since we were interested in testing how much the first boat won, only the two first results are included in the tables. Weather conditions can significantly vary from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing the results with other years. However, the margin between the first and second boat does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For results of all races in the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3366</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3366"/>
		<updated>2026-05-08T16:12:29Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin. &lt;br /&gt;
&lt;br /&gt;
We added another challenge to the study, which, over time, proved substantial: to learn from this success about how performance also occurs in competitive businesses. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are the following: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), Wesley Ng (coach).&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first and second 8+ boats since 1977, men and women, U23 and senior, at a World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered by increasing value, from the smallest to the highest, in each of the four categories. Although the results are comparable, analysis by category may evidence striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a matter of concern in the sport of rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, which was much earlier than the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results tend to be comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results would result from any external factors to the team efforts, such as the weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results of men and women at the U23 (Under 23 years old) and senior categories at a World Championship level, Olympics included. Since we were interested in testing how much the first boat won, only the two first results are included in the tables. Weather conditions can significantly vary from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing the results with other years. However, the margin between the first and second boat does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For results of all races in the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3365</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3365"/>
		<updated>2026-05-08T16:09:42Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin. &lt;br /&gt;
&lt;br /&gt;
We added another challenge to the study, which, over time, proved substantial: to learn from this success about how performance can also occur in competitive businesses. Although there are commonalities between sports and competitive businesses (not to mention sports businesses and, leaving aside public administrations), the sports context reveals a simple truth about the focus on being first in a short period. Rowing is a perfect sport for showing how success is built collectively, with athletes in close proximity. Rather than presenting a list of explanations, the comparison has enabled the study to focus on core concepts that drive performance in both contexts.&lt;br /&gt;
&lt;br /&gt;
The athletes, coach, and participants in the study are the following: Erin Briggs (Bow 1), Cassandra Johnson (Seat 2), Kendall Brewer (Seat 3), Gia Doonan (Seat 4), Regina Salmons (Seat 5), Sarah Dougherty (Seat 6), Georgia Ratcliff (Seat 7), Kendall Chase (Seat 8), Colette Lucas-Conwell (Coxswain), Wesley Ng (coach).&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first and second 8+ boats since 1977, men and women, U23 and senior, at a World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered by increasing value, from the smallest to the highest, in each of the four categories. Although the results are comparable, analysis by category may evidence striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a matter of concern in the sport of rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, which was much earlier than the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results tend to be comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results would result from any external factors to the team efforts, such as the weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results of men and women at the U23 (Under 23 years old) and senior categories at a World Championship level, Olympics included. Since we were interested in testing how much the first boat won, only the two first results are included in the tables. Weather conditions can significantly vary from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing the results with other years. However, the margin between the first and second boat does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For results of all races in the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3364</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3364"/>
		<updated>2026-05-08T15:27:00Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:U23 W8+ 3-2.jpg|right|thumb|500px]]&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.  &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first and second 8+ boats since 1977, men and women, U23 and senior, at a World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered by increasing value, from the smallest to the highest, in each of the four categories. Although the results are comparable, analysis by category may evidence striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a matter of concern in the sport of rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, which was much earlier than the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results tend to be comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results would result from any external factors to the team efforts, such as the weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results of men and women at the U23 (Under 23 years old) and senior categories at a World Championship level, Olympics included. Since we were interested in testing how much the first boat won, only the two first results are included in the tables. Weather conditions can significantly vary from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing the results with other years. However, the margin between the first and second boat does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For results of all races in the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3363</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3363"/>
		<updated>2026-05-08T15:25:02Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:U23 W8+ 3-2.jpg|right|thumb|500px|Colette Lucas-Conwell (Coxswain); Kendall Chase (Seat 8), Georgia Ratcliff (Seat 7), Sarah Dougherty (Seat 6), Regina Salmons (Seat 5), Gia Doonan (Seat 4), Kendall Brewer (Seat 3), Cassandra Johnson (Seat 2), Erin Briggs (Bow 1), Wesley Ng (coach)]]&lt;br /&gt;
&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.  &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first and second 8+ boats since 1977, men and women, U23 and senior, at a World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered by increasing value, from the smallest to the highest, in each of the four categories. Although the results are comparable, analysis by category may evidence striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a matter of concern in the sport of rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, which was much earlier than the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results tend to be comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results would result from any external factors to the team efforts, such as the weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results of men and women at the U23 (Under 23 years old) and senior categories at a World Championship level, Olympics included. Since we were interested in testing how much the first boat won, only the two first results are included in the tables. Weather conditions can significantly vary from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing the results with other years. However, the margin between the first and second boat does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For results of all races in the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3362</id>
		<title>Row Results</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Row_Results&amp;diff=3362"/>
		<updated>2026-05-07T15:46:10Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:U23 W8+ 3-2.jpg|right|500px]]&lt;br /&gt;
&lt;br /&gt;
This page provides information about a study conducted by GRI to analyze the results of the USA U23 Women 8+ team at the 2016 World Rowing Championships in Rotterdam, Netherlands. The overall purpose of the study is 1) to confirm that the 2016 USA Women U23 8+ team&#039;s results were uncommon by contrasting them with those of others in rowing and 2) to provide explanations from which we can learn in rowing, other sports, and business.&lt;br /&gt;
&lt;br /&gt;
According to the analysis, the 2016 USA Women U23 8+ team achieved the largest winning margin in all 8+ events at the Senior and U23 levels since 1977. This was a monumental achievement in rowing, setting a new world record.  &lt;br /&gt;
&lt;br /&gt;
We were fortunate to obtain the team&#039;s adaptive profiles and provide feedback to the athletes and coach a few days before the race. Individual interviews were conducted at the end of 2023. Analysis of the interviews and results has led to considering all factors, including those related to leadership, positive psychology, and organizational performance, that can explain the crew&#039;s exceptional winning margin.  &lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
=Margin&#039;s Plot=&lt;br /&gt;
&lt;br /&gt;
This plot illustrates the winning margin between the first and second 8+ boats since 1977, men and women, U23 and senior, at a World Championship level. The arrow shows where the results of the 2016 USA Women U23 8+ boat stand. See all the details of the data below, which were extracted from the World Rowing website. See also the details of the results of the 2016 US Women’s U23 8+ boat.&lt;br /&gt;
 &lt;br /&gt;
The margins were ordered by increasing value, from the smallest to the highest, in each of the four categories. Although the results are comparable, analysis by category may evidence striking differences between men and women, and between U23 and senior levels.&lt;br /&gt;
&lt;br /&gt;
[[File:Difference plot 2016 w8+ U23.png|center|650px]]&lt;br /&gt;
&lt;br /&gt;
==Results Analysis==&lt;br /&gt;
To determine whether the 2016 U23 USA Women 8+ result was exceptional, we needed to compare it to other results at a similar world championship level. We examined the winning margin of all 8+ events at the World Championships and Olympics for U23 Women, U23 Men, Senior Women, and Senior Men. It is worth noting that the U23 championship for men and women only began in 2005 and 2006, respectively.&lt;br /&gt;
&lt;br /&gt;
Anti-doping has been a matter of concern in the sport of rowing since the 1960s. The International Rowing Federation (FISA) was the first to introduce an anti-doping regulation in 1976, which was much earlier than the establishment of the World Anti-Doping Agency (WADA) in 1999 and the adoption of the anti-doping code at the Sydney Games in 2000. As a result, only the results from 1977 onwards are taken into account for consideration.&lt;br /&gt;
&lt;br /&gt;
Both Senior and U23 results tend to be comparable, which is why we included both. However, Junior results that are too distant from the senior level were not included.  &lt;br /&gt;
&lt;br /&gt;
Of the 17 data points collected on the U23 Women’s category, the 2016 US 8+ was the only crew to have a winning margin over 7 seconds, an incredible 3.56 seconds above the average winning margin. Furthermore, across all 122 data points collected, we found the average winning margin to be 2.05 sec, 5.11 sec less than the 7.16 sec winning margin of the 2016 USA Women’s 8+.&lt;br /&gt;
&lt;br /&gt;
We didn&#039;t find evidence that the 2016 results would result from any external factors to the team efforts, such as the weather conditions at a specific location on the water. All athletes complied with doping regulations. Other boats from Great Britain, Russia, New Zealand, Australia, and Germany were equally engaged in the race.&lt;br /&gt;
&lt;br /&gt;
==Results Data==&lt;br /&gt;
&lt;br /&gt;
The tables below show the results of men and women at the U23 (Under 23 years old) and senior categories at a World Championship level, Olympics included. Since we were interested in testing how much the first boat won, only the two first results are included in the tables. Weather conditions can significantly vary from race to race; thus, the time of the winning boat doesn&#039;t provide an accurate assessment of how well it did when comparing the results with other years. However, the margin between the first and second boat does. This does happen in other sports like sailing, but not in others such as swimming. &lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 6:13.60 || United States || 6:16.28 || 2.68 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 6:06.58 || United States || 6:08.35 || 1.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || United States || 6:09.14 || Germany || 6:13.34 || 4.2 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || United States || 6:23.03 || Great Britain || 6:27.81 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || United States || 6:16.69 || Netherlands || 6:20.43 || 3.74&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Netherlands || 6:17.93 || Great Britain || 6:22.52 || 4.59&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Canada || 6:04.61 || Netherlands || 6:06.58 || 1.97&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Canada || 6:09.89 || United States || 6:16.44 || 6.55&lt;br /&gt;
|-&lt;br /&gt;
| &amp;lt;strong&amp;gt;2016&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;United States&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:36.90&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;Great Britain&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;6:44.06&amp;lt;/strong&amp;gt; || &amp;lt;strong&amp;gt;7.16*&amp;lt;/strong&amp;gt;&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:19.49 || Russia || 6:22.02 || 2.53&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 6:07.88 || Great Britain || 6:11.76 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:16.81 || Great Britain || 6:19.15 || 2.34&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:25.92 || Germany || 6:30.47 || 4.55&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Canada || 6:03.23 || New Zealand || 6:06.02 || 2.79&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:31.97 || New Zealand || 6:36.48 || 4.51&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Great Britain || 6:20.71 || United States || 6:21.80 || 1.09&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:36.01 || Poland || 6:39.72 || 3.71&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Belarus || 6:15.20 || Germany || 6:15.43 || 0.23&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 6:06.68 || Belarus || 6:08.98 || 2.3&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 3.6&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.8&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s U23&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Great Britain || 5:29.60 || New Zealand || 5:32.59 || 2.99 &lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:24.73 || United States || 5:27.50 || 2.77 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:26.51 || United States || 5:28.90 || 2.39 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:51.71 || United States || 5:53.97 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Great Britain || 5:34.32 || United States || 5:34.55 || 0.21&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Great Britain || 5:34.30 || United States || 5:36.21 || 1.91&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 5:22.48 || Great Britain || 5:24.93 || 2.45&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Netherlands || 5:29.55 || Romania || 5:31.57 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Netherlands || 5:54.10 || Great Britain || 5:57.26 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Germany || 5:33.56 || United States || 5:36.49 || 2.93&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || New Zealand || 5:28.82 || Australia || 5:30.45 || 1.63&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || New Zealand || 5:28.63 || United States || 5:31.79 || 3.16&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 5:47.66 || Germany || 5:48.22 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 5:24.31 || Czech Republic || 5:26.21 || 1.9&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:44.78 || United States || 5:47.48 || 2.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Poland || 5:32.77 || Germany || 5:34.11 || 1.34&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 5:49.42 || Canada || 5:53.30 || 3.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Estonia || 5:33.90 || Germany || 5:34.29 || 0.39&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Canada || 5:30.72 || Germany || 5:31.78 || 1.06&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Romania || 5:50.90 || Italy || 5:51.82 || 0.92&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Women&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 6:08.10 || Canada || 6:10.83 || 2.73&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Romania || 5:54.39 || Canada || 5:58.84 || 4.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Romania || 6:01.28 || United States || 6:03.73 || 2.45 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Romania || 6:01.14 || Netherlands || 6:05.04 || 3.9&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || Canada || 5:59.13 || New Zealand || 6:00.04 || 0.91&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || New Zealand || 5:56.91 || Australia || 5:59.63 || 2.72&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || United States || 6:00.97 || Canada || 6:03.05 || 2.08&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Romania || 6:06.40 || Canada || 6:07.09 || 0.69&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || United States || 6:01.49 || Great Britain || 6:03.49 || 2&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || United States || 6:05.65 || New Zealand || 6:08.52 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || United States || 5:56.83 || Canada || 5:59.66 || 2.83&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || United States || 6:02.14 || Canada || 6:07.04 || 4.9&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || United States || 6:10.59 || Canada || 6:12.06 || 1.47&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || United States || 6:03.65 || Canada || 6:04.39 || 0.74&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || United States || 6:12.42 || Canada || 6:16.12 || 3.7&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || United States || 6:05.34 || Romania || 6:06.94 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || United States || 6:05.34 || Netherlands || 6:07.22 || 1.88&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || United States || 6:17.21 || Romania || 6:18.34 || 1.13&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || United States || 5:55.50 || Germany || 5:57.29 || 1.79&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || Australia || 5:58.10 || Romania || 5:59.50 || 1.4&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || Romania || 6:17.70 || United States || 6:19.56 || 1.86&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Germany || 6:41.23 || Romania || 6:44.63 || 3.4&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || United States || 6:04.25 || Australia || 6:05.10 || 0.85&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Australia || 6:03.66 || Romania || 6:04.96 || 1.3&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Romania || 6:06.44 || Netherlands || 6:09.39 || 2.95&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || Romania || 6:47.66 || United States || 6:48.81 || 1.15&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || Romania || 6:14.62 || United States || 6:15.81 || 1.19&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || Romania || 6:02.40 || Canada || 6:07.18 || 4.78&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Romania || 6:19.73 || Canada || 6:24.05 || 4.32&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || United States || 6:50.73 || Romania || 6:52.76 || 2.03 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || Germany || 6:07.42 || United States || 6:08.24 || 0.82&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Romania || 6:18.88 || United States || 6:20.42 || 1.54&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 6:02.62 || Romania || 6:06.26 || 3.64&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Canada || 6:28.20 || URS || 6:28.73 || 0.53&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || Romania || 5:59.26 || United States || 6:01.67 || 2.41&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || Romania || 6:07.92 || Germany || 6:08.19 || 0.27 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RDA || 6:15.17 || Romania || 6:17.44 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || Romania || 6:55.61 || United States || 6:57.27 || 1.66&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || URS || 6:08.76 || RDA || 6:09.77 || 1.01&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 6:14.00 || RDA || 6:14.89 || 0.89&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 2.1&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.2&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin:auto&amp;quot;&lt;br /&gt;
|+ Men&#039;s Senior&lt;br /&gt;
|-&lt;br /&gt;
! Year !! Winning Crew !! Time !! Second Place !! Time !! Margin(sec) &lt;br /&gt;
|-&lt;br /&gt;
| 2025 || Netherlands || 5:27.67 || Great Britain || 5:29.93 || 2.26&lt;br /&gt;
|-&lt;br /&gt;
| 2024 || Great Britain || 5:22.88 || Netherlands || 5:23.92 || 1.05 &lt;br /&gt;
|-&lt;br /&gt;
| 2023 || Great Britain || 5:24.20 || Netherlands || 5:25.23 || 1.03 &lt;br /&gt;
|-&lt;br /&gt;
| 2022 || Great Britain || 5:24.41 || Netherlands || 5:25.52 || 1.11&lt;br /&gt;
|-&lt;br /&gt;
| 2021 || New Zealand || 5:24.64 || Germany || 5:25.60 || 0.96&lt;br /&gt;
|-&lt;br /&gt;
| 2019 || Germany || 5:19.41 || Netherlands || 5:19.96 || 0.55&lt;br /&gt;
|-&lt;br /&gt;
| 2018 || Germany || 5:24.31 || Australia || 5:26.11 || 1.8&lt;br /&gt;
|-&lt;br /&gt;
| 2017 || Germany || 5:26.85 || United States || 5:28.45 || 1.6&lt;br /&gt;
|-&lt;br /&gt;
| 2016 || Great Britain || 5:29.63 || Germany || 5:30.96 || 1.33&lt;br /&gt;
|-&lt;br /&gt;
| 2015 || Great Britain || 5:35.18 || Germany || 5:36.36 || 0.18&lt;br /&gt;
|-&lt;br /&gt;
| 2014 || Great Britain || 5:24.11 || Germany || 5:24.77 || 0.66&lt;br /&gt;
|-&lt;br /&gt;
| 2013 || Great Britain || 5:30.35 || Germany || 5:30.89 || 0.54&lt;br /&gt;
|-&lt;br /&gt;
| 2012 || Germany || 5:48.75 || Canada || 5:49.98 || 1.23&lt;br /&gt;
|-&lt;br /&gt;
| 2011 || Germany || 5:28.81 || Great Britain || 5:30.83 || 2.02&lt;br /&gt;
|-&lt;br /&gt;
| 2010 || Germany || 5:33.84 || Great Britain || 5:34.46 || 0.62&lt;br /&gt;
|-&lt;br /&gt;
| 2009 || Germany || 5:24.13 || Canada || 5:27.15 || 3.02&lt;br /&gt;
|-&lt;br /&gt;
| 2008 || Canada || 5:23.89 || Great Britain || 5:25.11 || 1.22&lt;br /&gt;
|-&lt;br /&gt;
| 2007 || Canada || 5:34.92 || Germany || 5:37.19 || 2.27&lt;br /&gt;
|-&lt;br /&gt;
| 2006 || Germany || 5:21.85 || Italy || 5:23.29 || 1.44&lt;br /&gt;
|-&lt;br /&gt;
| 2005 || United States || 5:22.75 || Italy || 5:24.01 || 1.26&lt;br /&gt;
|-&lt;br /&gt;
| 2004 || United States || 5:42.48 || Netherlands || 5:43.75 || 1.27&lt;br /&gt;
|-&lt;br /&gt;
| 2003 || Canada || 6:00.44 || United States || 6:01.46 || 1.02&lt;br /&gt;
|-&lt;br /&gt;
| 2002 || Canada || 5:26.92 || Germany || 5:28.16 || 1.24&lt;br /&gt;
|-&lt;br /&gt;
| 2001 || Romania || 5:27.48 || Croatia || 5:28.47 || 0.99&lt;br /&gt;
|-&lt;br /&gt;
| 2000 || Great Britain || 5:33.08 || Australia || 5:33.88 || 0.8&lt;br /&gt;
|-&lt;br /&gt;
| 1999 || United States || 6:01.58 || Great Britain || 6:03.27 || 1.69&lt;br /&gt;
|-&lt;br /&gt;
| 1998 || United States || 5:38.78 || Germany || 5:39.48 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1997 || United States || 5:27.20 || Romania || 5:27.76 || 0.56&lt;br /&gt;
|-&lt;br /&gt;
| 1996 || Netherlands || 5:42.74 || Germany || 5:44.58 || 1.84&lt;br /&gt;
|-&lt;br /&gt;
| 1995 || Germany || 5:53.40 || Netherlands || 5:55.54 || 2.14 &lt;br /&gt;
|-&lt;br /&gt;
| 1994 || United States || 5:24.50 || Netherlands || 5:25.10 || 0.6&lt;br /&gt;
|-&lt;br /&gt;
| 1993 || Germany || 5:37.08 || Romania || 5:39.33 || 2.25&lt;br /&gt;
|-&lt;br /&gt;
| 1992 || Canada || 5:29.53 || Romania || 5:29.67 || 0.14&lt;br /&gt;
|-&lt;br /&gt;
| 1991 || Germany || 5:50.98 || Canada || 5:51.68 || 0.7&lt;br /&gt;
|-&lt;br /&gt;
| 1990 || RFA || 5:26.62 || Canada || 5:27.57 || 0.95&lt;br /&gt;
|-&lt;br /&gt;
| 1989 || RFA || 5:43.88 || RDA || 5:45.70 || 1.82 &lt;br /&gt;
|-&lt;br /&gt;
| 1988 || RFA || 5:46.05 || URS || 5:48.01 || 1.96&lt;br /&gt;
|-&lt;br /&gt;
| 1987 || United States || 5:58.83 || Germany || 6:01.94 || 3.11&lt;br /&gt;
|-&lt;br /&gt;
| 1986 || Australia || 5:33.54 || URS || 5:37.61 || 4.07&lt;br /&gt;
|-&lt;br /&gt;
| 1985 || URS || 5:33.71 || Italy || 5:34.58 || 0.87&lt;br /&gt;
|-&lt;br /&gt;
| 1984 || Canada || 5:41.32 || United States || 5:41.74 || 0.42&lt;br /&gt;
|-&lt;br /&gt;
| 1983 || New Zealand || 5:43.39 || RDA || 5:35.94 || 1.55&lt;br /&gt;
|-&lt;br /&gt;
| 1982 || New Zealand || 5:36.99 || RDA || 5:39.17 || 2.18&lt;br /&gt;
|-&lt;br /&gt;
| 1981 || URS || 6:02.30 || Great Britain || 6:04.31 || 2.01 &lt;br /&gt;
|-&lt;br /&gt;
| 1980 || RDA || 5:49.05 || Great Britain || 5:51.92 || 2.87&lt;br /&gt;
|-&lt;br /&gt;
| 1979 || RDA || 5:36.41 || New Zealand || 5:39.92 || 3.51&lt;br /&gt;
|-&lt;br /&gt;
| 1978 || RDA || 5:54.25 || RFA || 5:55.17 || 0.92 &lt;br /&gt;
|-&lt;br /&gt;
| 1977 || RDA || 5:45.36 || URS || 5:50.71 || 5.35&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Average || 1.9&lt;br /&gt;
|-&lt;br /&gt;
|      ||         ||         ||        || Standard Deviation || 1.0&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=References=&lt;br /&gt;
For results of all races in the World Rowing website https://worldrowing.com)&lt;br /&gt;
&lt;br /&gt;
For results of the 2016 U23 USA Women 8+ boat here: https://worldrowing.com/event/2016-world-rowing-under-23-championships/&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Indicators_and_Their_Measurement&amp;diff=3361</id>
		<title>Indicators and Their Measurement</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Indicators_and_Their_Measurement&amp;diff=3361"/>
		<updated>2026-05-01T05:39:17Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* (Q-) Social performance */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI Model_detailed_variables.png|right|450px]]&lt;br /&gt;
This article specifies the codes, indicators, and value attributions for the general framework’s variables. Nine are independent, four are antecedent, and three are dependent. The 16 variables are presented in the order below in the three categories.&lt;br /&gt;
 &lt;br /&gt;
The framework, its construction, and variables are presented in separate articles&amp;lt;ref&amp;gt;See more about the  variables and their measurement [[Variables and Indicators |here in this article.]]&amp;lt;br/&amp;gt;[[ Research Methodology | See more about the history of the framework and its methodology &amp;lt;u&amp;gt;here in this article&amp;lt;/u&amp;gt;.]]&amp;lt;/ref&amp;gt;. Indicators are used to test hypotheses drawn from the framework against specific techniques, users, and companies as they deploy, in accordance with a publisher&#039;s model and a consultant&#039;s facilitation. The anticipated conclusions of testing hypotheses are also based on the indicators and their measurement. The hypotheses and anticipated conclusions are discussed separately&amp;lt;ref&amp;gt;[[ Hypotheses Formulation | See more about the hypotheses formulation &amp;lt;u&amp;gt;here in this article&amp;lt;/u&amp;gt;.]]&amp;lt;br/&amp;gt;[[ Anticipated Conclusions | See more about the anticipated conclusions &amp;lt;u&amp;gt;here in this article&amp;lt;/u&amp;gt;.]]&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
=Independent Variables=&lt;br /&gt;
The nine independent variables are shown in the middle of the framework in blue (See the illustration on the right). As explained during the hypothesis formulation, when building the framework, practical (light blue) and theoretical (dark blue) variables are analyzed distinctly. The three theoretical uses are more abstract and are present transversally in the six practical ones. &lt;br /&gt;
 &lt;br /&gt;
==(O-) Organizational Development==&lt;br /&gt;
Applications of assessment techniques in organizational development, such as defining job expectations and the organization at a strategic level, as well as in mergers and acquisitions, are associated with the concept of &#039;Use in organizational development&#039;. The more varied and intense the use at the organizational level, the more it is associated with positive effects on performance.&lt;br /&gt;
&lt;br /&gt;
Seven indicators are used to measure the &#039;Use in organisational development’ variable, each with an ordinal scale of four values: very low, low, strong, and very strong. They combine to form an overall indicator called &#039;isuorga.&#039;&lt;br /&gt;
 &lt;br /&gt;
If any single indicator is very strong, it is enough to determine that &#039;isuorga&#039; is very strong. If no factor is very strong and at least one factor is strong, then &#039;isuorga&#039; is strong. If no indicator is very strong or strong and at least one indicator is low, then &#039;isuorga&#039; is low. In other cases, we will say that &#039;isuorga&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|-&lt;br /&gt;
| O-CHAN || Manage organizational changes proactively.&lt;br /&gt;
|-&lt;br /&gt;
|O-FUSI || Acquisition, takeover, or merger of companies or project teams.&lt;br /&gt;
|-&lt;br /&gt;
| O-ORGA || Organization or reorganization of the company or a team.&lt;br /&gt;
|-&lt;br /&gt;
| O-POST || Refined definition of positions, including social behaviors (PBI).&lt;br /&gt;
|-&lt;br /&gt;
| O-PROJ || Construction and organization of a project team.&lt;br /&gt;
|-&lt;br /&gt;
| O-SCIS || Systematic use on teams, divisions, or the whole organization.&lt;br /&gt;
|-&lt;br /&gt;
| O-OTHR || Other uses in organizational development&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(L-) Leadership==&lt;br /&gt;
The use in situations of leading and managing people is associated with the concept of &#039;use in leadership and management&#039;. The more varied and intense the uses of leadership and management are, the more they are associated with positive effects on performance.&lt;br /&gt;
&lt;br /&gt;
16 indicators measure the &#039;use in leadership and management&#039; variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall ‘management and leadership’ indicator called  &#039;isulead&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least two indicators are very strong, we can say that the &#039;isulead&#039; indicator is very strong. This indicates that the assessment technique is used in at least two of the listed applications. If no indicator is very strong and at least two factor are strong, then &#039;isulead&#039; is strong. If no indicator is very strong or strong and at least two indicators are low, then &#039;isulead&#039; is low. In other cases, we will say that &#039;isulead&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|-&lt;br /&gt;
| L-ADAP || Adapt to other people&#039;s styles&lt;br /&gt;
|-&lt;br /&gt;
| L-FOCO || Foster collaboration&lt;br /&gt;
|-&lt;br /&gt;
| L-AUTO || Autonomous use of the assessment technique&lt;br /&gt;
|-&lt;br /&gt;
| L-CONF || Manage conflicts and other organizational challenges, including low productivity, absenteeism, negative behavior, individual and collective conflicts, strikes, etc.&lt;br /&gt;
|-&lt;br /&gt;
| L-ENTR || Use in end-of-year interviews, and other interviews, excluding recruitment interviews&lt;br /&gt;
|-&lt;br /&gt;
| L-DEVE || Employee development&lt;br /&gt;
|-&lt;br /&gt;
| L-FEED || Feedback sessions are provided to team members&lt;br /&gt;
|-&lt;br /&gt;
| L-FIDE || Develop employees&#039; loyalty and trust&lt;br /&gt;
|-&lt;br /&gt;
| L-HUMA || Attention is paid to people and social aspects, rather than remaining distant and focusing only on technical aspects&lt;br /&gt;
|-&lt;br /&gt;
| L-INCO || Onboard new team members&lt;br /&gt;
|-&lt;br /&gt;
| L-INTE || Communicate and interact with others&lt;br /&gt;
|-&lt;br /&gt;
| L-MODW || Model the way&lt;br /&gt;
|-&lt;br /&gt;
| L-MOTI || Motivate and engage employees&lt;br /&gt;
|-&lt;br /&gt;
| L-OBJC || Set objectives&lt;br /&gt;
|-&lt;br /&gt;
| L-PRES || Manage individual stress&lt;br /&gt;
|-&lt;br /&gt;
| L-OTHR || Other uses in leadership and management&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(G-) Coaching==&lt;br /&gt;
The use of the assessment technique in coaching is associated with the concept of &#039;use in coaching&#039;. The more varied and intense the uses in coaching are, the more they are associated with positive effects on performance.&lt;br /&gt;
&lt;br /&gt;
Five indicators measure the &#039;use in coaching’ variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall ‘coaching’ indicator called  &#039;isucoch&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least one indicator is very strong, we can say that the &#039;isucoch&#039; indicator is very strong. If no indicator is very strong and at least one indicator is strong, then &#039;isucoch&#039; is strong. If no indicator is very strong or strong and at least one factor is low, then &#039;isucoch&#039; is low. In other cases, we will say that &#039;isucoch&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|- G-CONN || Establish a connection with the person, get to know them&lt;br /&gt;
|-&lt;br /&gt;
| G-SOLV || Helps prescribe a plan and solve issues&lt;br /&gt;
|-&lt;br /&gt;
| G-FEED || Provide feedback to the person&lt;br /&gt;
|-&lt;br /&gt;
| G-ASSI || Assist with managerial and other team-related aspects&lt;br /&gt;
|-&lt;br /&gt;
| G-ENBL || Enable the coachee to express themselves and ask new questions&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(S-) Recruitment==&lt;br /&gt;
The use of the assessment technique in recruitment is associated with the variable &#039;use in recruitment&#039;, which includes uses in selection, promotion, interviewing, onboarding, management of high potentials, and career planning. The more varied and intense the uses in recruitment are, the more they are associated with positive effects on performance.&lt;br /&gt;
&lt;br /&gt;
Seven indicators measure the &#039;use in recruitment&#039; variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall ‘recruitment’ indicator called  &#039;isurecr&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least one indicator is very strong, we can say that the &#039;isurecr&#039; indicator is very strong. If no indicator is very strong and at least one indicator is strong, then &#039;isurecr&#039; is strong. If no indicator is very strong or strong and at least one factor is low, then &#039;isurecr&#039; is low. In other cases, we will say that &#039;isurecr&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|- &lt;br /&gt;
| S-RECR || Analysis of people during internal or external recruitment, with or without the assistance of an external consultant, a recruitment&amp;lt;br/&amp;gt; or search firm&lt;br /&gt;
|- &lt;br /&gt;
| S-ENTR || Recruitment interview&lt;br /&gt;
|- &lt;br /&gt;
| S-HYPO || Management of high potentials&lt;br /&gt;
|- &lt;br /&gt;
| S-PLAN || Succession planning&lt;br /&gt;
|- &lt;br /&gt;
| S-PROM || Promotion and reclassification of employees&lt;br /&gt;
|- &lt;br /&gt;
| S-REFE || Validation of referencing by a third party during recruitment&lt;br /&gt;
|- &lt;br /&gt;
| S-OTHR || Other uses in selection and recruitment&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(N-) Clinical==&lt;br /&gt;
The use of the assessment technique in clinical settings is associated with the concept of &#039;use in clinical settings&#039;, which includes use in therapy, mental health treatment, and improving well-being. The more varied and intense the uses in clinical settings are, the more they are associated with positive effects on performance.&lt;br /&gt;
&lt;br /&gt;
Four indicators measure the &#039;use in clinical settings’ variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall ‘clinical’ indicator called  &#039;isuclin&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least one indicator is very strong, we can say that the &#039;isuclin&#039; indicator is very strong. If no indicator is very strong and at least one indicator is strong, then &#039;isuclin&#039; is strong. If no indicator is very strong or strong and at least one indicator is low, then &#039;isuclin&#039; is low. In other cases, we will say that &#039;isuclin&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|- &lt;br /&gt;
| N-CONN || Establish a connection with the patient, get to know them&lt;br /&gt;
|-&lt;br /&gt;
| N-SOLV || Helps prescribe a plan and solve issues&lt;br /&gt;
|-&lt;br /&gt;
| N-FEED || Provide feedback to the patient&lt;br /&gt;
|-&lt;br /&gt;
| N-OTHR || Other uses in therapy and clinical applications&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(D-) Medium Effect==&lt;br /&gt;
The use of the assessment technique for its medium effects is associated with the concept of &#039;carries a medium effect&#039;, which helps to entertain and build relationships. The more varied and intense the uses of medium effects are, the more they are associated with positive effects on performance.&lt;br /&gt;
&lt;br /&gt;
Four indicators measure the &#039;carries a medium effect’ variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall ‘medium effect’ indicator called  &#039;isumedi&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least one indicator is very strong, we can say that the &#039;isumedi&#039; indicator is very strong. If no indicator is very strong and at least one indicator is strong, then &#039;isumedi&#039; is strong. If no indicator is very strong or strong and at least one indicator is low, then &#039;isumedi&#039; is low. In other cases, we will say that &#039;isumedi&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|- &lt;br /&gt;
| D-CONN || Establish a connection with the person, get to know them&lt;br /&gt;
|-&lt;br /&gt;
| D-SOLV || Helps establish a plan and solve issues&lt;br /&gt;
|-&lt;br /&gt;
| D-FEED || Provide feedback to the person&lt;br /&gt;
|-&lt;br /&gt;
| D-ANIM || Group presentation at a company&#039;s gathering&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(A-) Self and Social Awareness==&lt;br /&gt;
The use of the assessment technique in self- and social-awareness is associated with the variable &#039;used in self- and social-awareness, which includes fostering personal growth, helping people identify their strengths, communication style, decision-making, and of others. The more varied and intense the uses in self- and social-awareness are, the more the six other practical uses are as well, and the more they are associated with positive effects on performance.&lt;br /&gt;
&lt;br /&gt;
Three indicators measure the &#039;improves self and social awareness&#039; variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall ‘improves self and social awareness&#039;’ indicator called  &#039;isucosa&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least one indicator is very strong, we can say that the &#039;isucosa&#039; indicator is very strong. If no indicator is very strong and at least one indicator is strong, then &#039;isucosa&#039; is strong. If no indicator is very strong or strong and at least one indicator is low, then &#039;isumedi&#039; is low. In other cases, we will say that &#039;isucosa&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|- &lt;br /&gt;
| A-PERS || Understanding better oneself, of one&#039;s style and limits (self-awareness), of the organization of one&#039;s time, of one&#039;s efficiency, of one&#039;s role, etc.&lt;br /&gt;
|-&lt;br /&gt;
| A-COLA || Understanding of team members, their style, strengths, limits, challenges, and talents.&lt;br /&gt;
|-&lt;br /&gt;
| A-AUTR || Understanding of other people in the organization in general, other than team members and direct reports: superiors, employees at the same hierarchical level, employees below level n-1, family, etc., of their style, strengths, limits, challenges, and talents.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(F-) Learning==&lt;br /&gt;
The learning includes initial training in the assessment technique, ongoing training in the field after initial training, and refreshers following the initial training. The &#039;quasi-autonomous learning process&#039; is all the stronger as the initial training is followed by on-the-job learning, refresher sessions, and contact with the consultant. The stronger the learning process and the more adequate the learning content is, the more they are followed by strong uses in the six practical applications in organization, leadership, coaching, recruitment, clinical and medium effects.&lt;br /&gt;
&lt;br /&gt;
Four indicators measure the value of the &#039;learning being nuanced and deep, and continuing over time’ variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall ‘improves self and social awareness’ indicator called  &#039;isulear&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least one indicator is very strong, we can say that the &#039;isulear&#039; indicator is very strong. If no indicator is very strong and at least one indicator is strong, then &#039;isulear&#039; is strong. If no indicator is very strong or strong and at least one indicator is low, then &#039;isulear&#039; is low. In other cases, we will say that &#039;isulear&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|- &lt;br /&gt;
| F-SEMI || Participation in the initial training or masterclass.&lt;br /&gt;
|-&lt;br /&gt;
| F-TERR || Continued learning after training on the job and using the training resources.&lt;br /&gt;
|-&lt;br /&gt;
| F-RAFR || Deepening learning through participation in refresher courses.&lt;br /&gt;
|-&lt;br /&gt;
| F-OTHR || General use of the assessment technique in learning.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(C-) Language and Signs==&lt;br /&gt;
Language and signs include the linguistic and symbolic aspects associated with the assessment technique. The more the language and symbols resulting from the technique can convey meaning across the six practical and three theoretical uses, the more users can benefit from them and, subsequently, their organization.&lt;br /&gt;
&lt;br /&gt;
Nine indicators make it possible to monitor the value of the &#039;results as a sign, and the language associated with it, facilitates their practical use’ variable. Each indicator is assessed on an ordinal scale of four values: very low, low, strong, and very strong. These indicators form an overall indicator called  &#039;isulasi&#039;.&lt;br /&gt;
&lt;br /&gt;
If at least two indicators are very strong, we can say that the &#039;isulasi&#039; indicator is very strong. If no indicator is very strong and at least two indicators are strong, then &#039;isulasi&#039; is strong. If no indicator is very strong or strong and at least two indicators are low, then &#039;isulasi&#039; is low. In other cases, we will say that &#039;isulasi&#039; is very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|- &lt;br /&gt;
| C-FACT || Use of the factors: 1, 2, 3, 4, factor interactions, adaptation, engagement level, and response level, or equivalent concepts when available.&lt;br /&gt;
|-&lt;br /&gt;
| C-INFE || Explicit statement of inferences from social behavior measures about individual or social skills, other qualities, or needs.&lt;br /&gt;
|-&lt;br /&gt;
| C-MORA || Reference to engagement or fit between the Natural and PBI; reference to the stability of the Natural, or equivalent concepts when available.&lt;br /&gt;
|-&lt;br /&gt;
| C-PROF || Verbal use of reference groups and profiles, and profiles such as the PBI and TBI, or equivalent concepts when available.&lt;br /&gt;
|-&lt;br /&gt;
| C-RANG || Organized to quickly access resources, individual profiles or other results and resources from the assessment technique.&lt;br /&gt;
|-&lt;br /&gt;
| C-SCSS || Explicit reference to the Natural, Role, and Effective profiles, or equivalent concepts when available.&lt;br /&gt;
|-&lt;br /&gt;
| C-VISU || Visual use of the adaptive profiles or other visual representations when available.&lt;br /&gt;
|-&lt;br /&gt;
| C-OTHR || Use in communication in general&lt;br /&gt;
|-&lt;br /&gt;
| C-REAN || Reference to any other language or symbolic aspects of the assessment.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Antecedent  Variables=&lt;br /&gt;
[[File:Antecedent Variables.png|right|300px]]&lt;br /&gt;
There are four antecedent variables, which are displayed in yellow in the framework. Testing the framework with different techniques, users, environments, publishers, and consultants requires adjusting the values of the four antecedent variables and their indicators.&lt;br /&gt;
&lt;br /&gt;
==(T-) Assessment Technique==&lt;br /&gt;
The analysis of assessment techniques highlights important qualities beyond those measured solely by psychometrics, which influence their use across different users and settings. Psychometric statistics, such as reliability and validity, are essential for understanding key aspects of assessment techniques. However, other aspects are also crucial for establishing their utility, predictive validity, and potential to improve individual and organizational performance.&lt;br /&gt;
&lt;br /&gt;
The internal qualities of the measures, such as the intensity of the behaviors being measured or the scales used, determine what can be done with them. How the results are presented, whether as reports or diagrams, influences not only how they are learned and used but also how they participate in thought processes, how comparisons between people and job expectations can be made, and how new meaning and use continue to develop from those results. New meanings and uses apply to all six practical uses and the three other theoretical ones evidenced.&lt;br /&gt;
&lt;br /&gt;
The assessment technique’s indicators were regrouped in four categories: (1) Upfront characteristics, (2) Intrinsic qualities, (3) Assessment Results, (4) Theory and Manual. The number of indicator for each sub-variable are indicated below:&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code 6b !! Sub-variable !! Nbr of Indicators&lt;br /&gt;
|-&lt;br /&gt;
| isaupfr || Upfront Characteristics || 6&lt;br /&gt;
|-&lt;br /&gt;
| isaintr || Intrinsic Qualities || 10&lt;br /&gt;
|-&lt;br /&gt;
| isaresu || Assessment Results || 6&lt;br /&gt;
|-&lt;br /&gt;
| isatheo || Theory and Manual || 6&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The four sub-variables are measured on an ordinal scale or in categories. When measured ordinally, the indicators take values of low, intermediate, or high. The four indicators &#039;isaupfr&#039;, &#039;isaintr&#039;, ‘isaresu’, and &#039;isatheo&#039; form a general indicator &#039;isatech&#039;.&lt;br /&gt;
&lt;br /&gt;
&#039;isatech&#039; is high if the T-GVAL, T-GENU, and T-ROUT indicators are all high and at least 50% of the other indicators of &#039;isaupfr&#039;, ‘insaintr,’ &#039;isaresu,&#039; and &#039;isatheo&#039;; ie, at least three indicators of &#039;isaupfr&#039;, five of &#039;isaintr&#039;, three of &#039;isaresu&#039; and three of &#039;isatheo&#039; must be high. &#039;isatech&#039; has an &#039;intermediate&#039; value if 50% of the indicators are in intermediate or high value for each of the four sub-variables. Below, ‘ isatech’ is low.&lt;br /&gt;
&lt;br /&gt;
Subvariable of &#039;isaupfr&#039;, assessing method&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code 6b !! Indicator !! Low !! Intermediate !! High&lt;br /&gt;
|-&lt;br /&gt;
| T-NATR || Nature of the Concepts || Loosely defined and measured || In between || Explicitly defined and assessed objectively&lt;br /&gt;
|-&lt;br /&gt;
| T-INTR || Means || No tool is being used || Use a paper survey, which will eventually be uploaded for scoring. || Use the internet on a laptop or a mobile device&lt;br /&gt;
|-&lt;br /&gt;
| T-FACI || Immediacy || Difficult || Average || Easy&lt;br /&gt;
|-&lt;br /&gt;
| T-NAQU || Number of items || Many questions asked &amp;gt; 40 || Average number of questions asked: &amp;lt; 39 and &amp;gt; 11. || Few questions asked &amp;lt; 10&lt;br /&gt;
|-&lt;br /&gt;
| T-TMPS || Time || Length &amp;gt; 45 min || Average. Between 10 and 45 mins || Fast. &amp;lt; 10 min on average&lt;br /&gt;
|-&lt;br /&gt;
| T-PROJ || Forced or Free || Forced scenarios || Mixed free/forced || Free scenarios&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Subvariable of &#039;isaintr&#039;, Intrinsic Qualities&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code 6b !! Indicator !! Low !! Intermediate !! High&lt;br /&gt;
|-&lt;br /&gt;
| T-NMBR || Number of Facets || One dimension || Three dimensions || More than four dimensions&lt;br /&gt;
|-&lt;br /&gt;
| T-PARC || Parsimony || Many &amp;gt; to 30 facets || Between 7 and 30 facets || Limited &amp;lt; 7 facets&lt;br /&gt;
|-&lt;br /&gt;
| T-STAB || Stability || No evidence of the measure&#039;s stability || Stability of the measures is mentioned but unverified || The measure has shown some stability over more than 3 years&lt;br /&gt;
|-&lt;br /&gt;
| T-INTN || Scale, Intensity || Nominal scales. No intensity || Ordinal scales. Indirect understanding of intensity || Continuous scales (ratio or interval), intensity&lt;br /&gt;
|-&lt;br /&gt;
| T-ORTH || Orthogonality || Large overlap between the measured dimensions || The dimensions look distinct but still overlap || Minimum overlap between the dimensions being measured&lt;br /&gt;
|-&lt;br /&gt;
| T-ADAP || Adaptation || Not measured || Inferred but not measured || Measured with intensity&lt;br /&gt;
|-&lt;br /&gt;
| T-VALI || Formal Statistics || No Statistics available || A few statistics are available, but they are not relevant in the end || Meaningful Statistics available&lt;br /&gt;
|-&lt;br /&gt;
| T-RELA || Work relatedness || Dimensions are not related to work. || The measured dimensions include both work and non-work-related dimensions. || All dimensions are work-related.&lt;br /&gt;
|-&lt;br /&gt;
| T-DISC || Non-descrimination || Discrimination against people || No precise measure of non-discrimination || Proven non-discrimination measures&lt;br /&gt;
|-&lt;br /&gt;
| T-LANG || Language || One language || Less than a dozen languages || More than a dozen test languages&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Subvariable of &#039;isaresu&#039;, Assessment Results&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code 6b !! Indicator !! Low !! Intermediate !! High&lt;br /&gt;
|-&lt;br /&gt;
| T-REPR || Representation Model || Complex, lomg, constrained || Intermediate || Simple, quick, and unconstrained&lt;br /&gt;
|-&lt;br /&gt;
| T-LISI || Conciseness || Lengthy || Intermediate || Concise&lt;br /&gt;
|-&lt;br /&gt;
| T-GVAL || General Validity || Invalid || Neutral validity || Valid&lt;br /&gt;
|-&lt;br /&gt;
| T-GENU || General Utility || Low utility with few applications and users || Intermediate general utility || High utility with many applications and users.&lt;br /&gt;
|-&lt;br /&gt;
| T-PRIV || Privacy and Security || No privacy with no security || Intermediate privacy and security || High privacy and security measures that can potentially be enforced by the publisher and client.&lt;br /&gt;
|-&lt;br /&gt;
| T-ATCH || Attachment || No emotional attachment to the technique&#039;s history or its people || Intermediate emotional attachment || Strong emotional attachment to the technique&#039;s history and people&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Subvariable of &#039;isatheo&#039;, Theory and Manual&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code 6b !! Indicator !! Low !! Intermediate !! High&lt;br /&gt;
|-&lt;br /&gt;
| T-MODL || A priori Theory || Vague || Moderately expressed || Clearly expressed&lt;br /&gt;
|-&lt;br /&gt;
| T-ROUT || Assessment&#039;s Theory || No rules available || Diffuse rules available || Availability of clear rules&lt;br /&gt;
|-&lt;br /&gt;
| T-MANU || Publications || No manual available || Some information is available on paper or the Internet || Full reference manual available in electronic or print format&lt;br /&gt;
|-&lt;br /&gt;
| T-ENVA || Environment&#039;s acccount || NO account for the environment || Kind of account for the environment, and not explicitly || Account for the environment&lt;br /&gt;
|-&lt;br /&gt;
| T-AGES || Age and Context || Old &amp;gt; 50 years || Medium - 20 years || Recent &amp;lt; 3 years&lt;br /&gt;
|-&lt;br /&gt;
| T-JOUR || Updates || No update || Occasional updates || Frequent updates&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(U-) User==&lt;br /&gt;
This ‘User’ variable measures the user’s characteristics that favor or refrain from the use of the assessment technique, as identified during the process analysis phase.&lt;br /&gt;
&lt;br /&gt;
14 indicators measure the antecedent variable, each with an ordinal scale of three values: low, intermediate, and high. They form a user indicator called &#039;isauser&#039;.&lt;br /&gt;
&lt;br /&gt;
The intensity of &#039;isauser&#039; depends on the values of the indicators that compose it. It takes at least 50% of the indicators to be high, to say that &#039;isauser&#039; is high; that is, 7 indicators. Same for the intermediate value: at least 50% of the indicators need to have an intermediate value. Below, the intensity of &#039;isauser&#039; is low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator !! Low !! Intermediate !! High&lt;br /&gt;
|- &lt;br /&gt;
| U-ATST || Attitude towards answering an assessment || Resistant || Skeptical || Positive&lt;br /&gt;
|-&lt;br /&gt;
| U-APRS || Attitude toward social behavior || Resistant || Skeptical || Positive&lt;br /&gt;
|-&lt;br /&gt;
| U-ATEP || Attitude toward the assessment technique || Confrontational || Doubtful || Open&lt;br /&gt;
|-&lt;br /&gt;
| U-ACNS || Attitude towards the facilitator || Distant || Skeptical || Open&lt;br /&gt;
|-&lt;br /&gt;
| U-HUMA || Interest in people and social aspects || Low || Moderate || High&lt;br /&gt;
|-&lt;br /&gt;
| U-ROVF || Operational vs functional role || Functional || Mixed functional/operational || Operational&lt;br /&gt;
|-&lt;br /&gt;
| U-EXPE || Leadership and management experience || &amp;lt;10 years or &amp;gt;30 years || N/A || More than 20 years&lt;br /&gt;
|-&lt;br /&gt;
| U-PRPE || Adaptive profile of the decision maker || &amp;quot;Controlling&amp;quot; || &amp;quot;Altruistic&amp;quot; || “Dominant”&lt;br /&gt;
|-&lt;br /&gt;
| U-TEST || Experience with other assessment techniques || Other assessments used || Some contacts with assessments || No experience&lt;br /&gt;
|-&lt;br /&gt;
| U-MAIT || Problems encountered in previous situations || Little difficult || Moderately difficult || Very difficult&lt;br /&gt;
|-&lt;br /&gt;
| U-DIRE || Directly concerned or not by the effects || Not concerned directly || Moderately concerned || Directly concerned&lt;br /&gt;
|-&lt;br /&gt;
| U-CONF || Confidence in using the personality assessment || Not confident || Moderately confident || Very confident&lt;br /&gt;
|-&lt;br /&gt;
| U-RECU || Recommendation provided for using the assessment || No recommendation provided || Positive recommendation provided when requested || Spontaneous recommendation provided&lt;br /&gt;
|-&lt;br /&gt;
| U-PRVH || Experience in HR, OD or Coaching || &amp;lt; 5 years || From 6 to 15 years || More than 15 years&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(E-) Environment==&lt;br /&gt;
Organizations may favor implementing a new assessment technique before it is used, or along the way, as when it is used in one department and later in others. The social and political context, and how some techniques are influential at the industry or national level, will also partially determine their use. The &#039;Environment&#039; variable regroups the characteristics identified during the process analysis under the headings &#039;organization’ and ‘environment&#039;, as their effects on using the assessment technique are similar. &lt;br /&gt;
&lt;br /&gt;
20 indicators are used to measure the &#039;Environment&#039; variable, each with an ordinal measurement on three values: low, intermediate, and high. They form an environment indicator called &#039;isaenvi&#039;.&lt;br /&gt;
&lt;br /&gt;
The intensity of &#039;isaenvi&#039; depends on the indicators that compose it. At least 50% of the indicators must be high to say that &#039;isaenvi&#039; is high. Same for the average value, which requires at least 50% of the indicators to be intermediate. Below, the intensity of &#039;isaenvi&#039; is low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator || Low || Intermediate || High&lt;br /&gt;
|-&lt;br /&gt;
| E-TAIL || Size of the company || Large: &amp;gt; 1000p and international bands || Medium: from 50 to 300p || Small: &amp;lt; 1000p&lt;br /&gt;
|-&lt;br /&gt;
| E-MATU || Organizational maturity || Start-up || Rapid organizational growth || Organisation mature&lt;br /&gt;
|-&lt;br /&gt;
| E-SECT || Industry sector || Administration || Industry || Service&lt;br /&gt;
|-&lt;br /&gt;
| E-CULT || Cultural embeddedness || Inexistence of the assessment in any situation || Episodic appearance of the assessment in a few situations || Assessment is part of the culture&lt;br /&gt;
|-&lt;br /&gt;
| E-POLI || Politicization of people&#039;s aspects || Very politicized || Moderately politicized || Weakly politicized&lt;br /&gt;
|-&lt;br /&gt;
| E-TEST || Prior use of techniques || Several techniques have been developed in different departments for different applications || Another technique is used in the organization for some applications || No other technique is used&lt;br /&gt;
|-&lt;br /&gt;
| E-PRES || Prior use of personality assessment || None || By another service || Across the organization&lt;br /&gt;
|-&lt;br /&gt;
| E-SRHU || Existence of a human resources department || No human resources department || Assistance in recruitment and provision of external advice || Human resources services are developed in various aspects&lt;br /&gt;
|-&lt;br /&gt;
| E-RHUM || Role of human resources (when applicable) || Admin role || Recruitment assistance || Involvement of the human resources department at the strategic level&lt;br /&gt;
|-&lt;br /&gt;
| E-FRUS || Interest in speaking the assessment language || Low || Moderate || High&lt;br /&gt;
|-&lt;br /&gt;
| E-RAPC || Relationship between the organization and outside consultant or facilitator || Non-existent || Episodic || Frequent&lt;br /&gt;
|-&lt;br /&gt;
| E-INTE || Global organization || None || Existence of at least one subsidiary abroad || Global organization established on all continents&lt;br /&gt;
|-&lt;br /&gt;
| E-CMPT || Environmental Competitiveness || Low competitive environment || Moderately competitive environment || Very competitive environment&lt;br /&gt;
|-&lt;br /&gt;
| E-DEVN || Long-term use of the assessment technique in the industry or country || Weakly developed at a national level || In progress. It&#039;s building || Assessment culture is firmly established at a national level&lt;br /&gt;
|-&lt;br /&gt;
| E-SYST || Adequacy of selection and promotion policies || Frequent calls to search and recruitment firms or external advice || Infrequent calls to outside firms || Strong autonomy for selection and occasional calls to outside firms&lt;br /&gt;
|-&lt;br /&gt;
| E-ADPI || Adequacy of remuneration and incentive systems || One-size-fits-all systems that ignore personality issues || Intermediate || Individual systems&lt;br /&gt;
|-&lt;br /&gt;
| E-ORGA || Adequacy of the organizational structure || Organizational processes that do not take assessment into account || Moderate consideration of personality issues in the processes || Strong consideration of the assessment in the processes&lt;br /&gt;
|-&lt;br /&gt;
| E-NIVP || Level of definition of positions with the personality assessment || Employees || Team lead and management level || Executive level&lt;br /&gt;
|-&lt;br /&gt;
| E-SYST || Systematization of the use of the assessment || Eventually, to confirm impressions || Frequent, and after the first interviews || Systematic, and before the first interview&lt;br /&gt;
|-&lt;br /&gt;
| E-NIVF || Individual with practical learning, knowledge, and experience in the assessment technique || Human resources || Management and HR ||&lt;br /&gt;
Executives, Management, and HR&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
==(B-) Publisher and Consultant==&lt;br /&gt;
This variable includes indicators on how the assessment technique is implemented within the organization by the publisher, facilitator, or consultant. Two important aspects are considered: the level of autonomy provided by the &#039;publisher and consultant&#039; and the skills offered. A deployment that allows significant autonomy and continues skill development through real-world cases encourages the use of the six practical and three theoretical application categories. Additionally, the consultant’s professional experience and the training they provide to users are essential factors that influence the technique&#039;s use.&lt;br /&gt;
&lt;br /&gt;
Nine indicators measure the variable &#039;Publisher and Consultant&#039;, each with an ordinal scale of three values: low, intermediate, and high. They form a global indicator &#039;isapuco&#039;.&lt;br /&gt;
&lt;br /&gt;
The intensity of &#039;isapuco&#039; depends on the intensity of the indicators that compose it. &#039;isapuco&#039; is high if the &#039;B-TEDI&#039; indicator is high and 50% of the other indicators are high; therefore at least four other indicators must be high in addition to &#039;B-TEDI&#039;. &#039;isapuco&#039; will have an intermediate value if 50% of the indicators have an intermediate value. Below, the intensity of &#039;isapuco&#039; is low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator || Low || Intermediate || High&lt;br /&gt;
|-&lt;br /&gt;
|- B-OTHR || Consultant&#039;s input || Low || Moderate || High&lt;br /&gt;
|-&lt;br /&gt;
| B-INTE || Consultant&#039;s involvement || Service || Hybrid || Facilitation&lt;br /&gt;
|-&lt;br /&gt;
| B-EXDE || Consultant&#039;s expertise || Low || Moderate || High&lt;br /&gt;
|-&lt;br /&gt;
| B-BASE || Availability of manuals || Unavailable || Not easily accessible || Easily accessible&lt;br /&gt;
|-&lt;br /&gt;
| B-EXPE || Accessibility of support || Inaccessible || Not easily accessible || Easily accessible&lt;br /&gt;
|-&lt;br /&gt;
| B-BUIS || Extent of assessment distribution || Confidential distribution || National distribution || Global distribution&lt;br /&gt;
|-&lt;br /&gt;
| B-TEDI || Assessment processing || Outsourced || Hybrid || Autonomous&lt;br /&gt;
|-&lt;br /&gt;
| B-TRAV || Training availability || No training  || Unsystemtic || Training available&lt;br /&gt;
|-&lt;br /&gt;
| B-PLAV || Platform availability || No platform || Limited features available || Extended features available&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Dependent Variables=&lt;br /&gt;
[[File:Dependent Variables.png|right|170px]]&lt;br /&gt;
The framework&#039;s dependent variables are represented in green as in the illustration on the right. &lt;br /&gt;
==(P-) Strategic performance==&lt;br /&gt;
Strategic performance includes the realization of behaviors on the job as they are expected within the organization in the medium- and long-term.&lt;br /&gt;
The indicator &#039;iopstra&#039; is created by comparing people’s Effective profile with the one expected in their position profiles (PBI), which are determined at a strategic level by the company&#039;s management.&lt;br /&gt;
&lt;br /&gt;
Summing the individual indicators allows defining the indicator at the team or organization level. &#039;iopstra&#039; takes a discrete value between 0 and 1.&lt;br /&gt;
* &#039;iopstra&#039; = 0: The individuals’ Effective profiles are the opposite of the social profiles expected in the teams and positions (from TBI and PBI).&lt;br /&gt;
* &#039;iopstra&#039; = 1: The individuals’ Effective profiles are perfectly aligned with the social behaviors expected in the teams and positions (From TBI and PBI).&lt;br /&gt;
&lt;br /&gt;
==(Q-) Social performance==&lt;br /&gt;
Social performance reflects aspects of engagement and being in flow at work, and thus the ability to deliver maximum performance and engagement. Social performance is observed by the objective indicator &#039;iopsoc&#039; and two subjective indicators.&lt;br /&gt;
The first objective indicator &#039;iopsoc&#039; measures the fit between the Natural and Role profiles from the adaptive profiles. The closer the Natural and Role are, the more in flow the person is. The more distant the Natural and the Role are, the more likely disengagement and negative emotions are. &lt;br /&gt;
The objective indicator ‘iopsoc’is obtained by combining the adaptation profiles’ adaptation and engagement values. &#039;iopsoc&#039; takes a discrete value between 0 and 1.&lt;br /&gt;
* &#039;iopsoc&#039; = 1: Satisfaction and engagement.&lt;br /&gt;
* &#039;iopsoc&#039; = 0: Discomfort, dissatisfaction, and disengagement.&lt;br /&gt;
Social performance is also tracked by two indicators: Q-SAUT and Q-SELF. They are measured on an ordinal scale with four values: very strong, strong, low, and very low.&lt;br /&gt;
&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|-&lt;br /&gt;
| Q-SAUT || Expression by respondents of the satisfaction of others in the organization.&lt;br /&gt;
|-&lt;br /&gt;
| Q-SELF || Expression by respondents of their own satisfaction.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The &#039;iopsoc&#039;, Q-SAUT, and Q-SELF indicators form an overall social performance indicator &#039;igpsoc&#039;. When the three indicators move in the same direction over time, the &#039;igpsoc&#039; indicator moves in the same direction. Otherwise, the value of &#039;igpsoc&#039; is indeterminate.&lt;br /&gt;
&lt;br /&gt;
==(R-) Economic Performance==&lt;br /&gt;
Economic performance includes aspects that can be quantified and most often relate to financial or production objectives.&lt;br /&gt;
&lt;br /&gt;
The economic performance indicators can include turnover, market penetration rate, return on investment, customer satisfaction survey results, absenteeism rate, etc. The indicators depend on each organization, agreed upon within the management team and, if applicable, with the board, shareholders, employees, or analysts.&lt;br /&gt;
&lt;br /&gt;
The objective economic performance indicators are grouped under the indicator &#039;iopecon&#039;.&lt;br /&gt;
&lt;br /&gt;
Economic performance is also tracked using a subjective indicator, R-ECON. The indicator is measured on an ordinal scale with four values: very strong, strong, low, and very low.&lt;br /&gt;
{|class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
! Code !! Indicator&lt;br /&gt;
|-&lt;br /&gt;
| R-ECON || Respondents&#039; appreciation of their organization&#039;s financial and production performance.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
The &#039;iopecon&#039; and M-ECON indicators form an overall economic performance indicator: &#039;igpecon&#039;. When the two indicators move in the same direction over time, &#039;igpecon&#039; does too. On the other hand, when the two indicators move in opposite directions to each other over time, &#039;igpecon&#039; remains indeterminate.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3360</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3360"/>
		<updated>2026-04-30T22:18:20Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Behavior Intelligence Quotient, or BIQ (Read Be IQ), is calculated by combining adaptive profiles’ metrics with strategic and social performance indicators, along with other, more traditional economic indicators, at the organizational level.  &lt;br /&gt;
&lt;br /&gt;
The BIQ mnemonic reflects the understanding that although measuring social behavior and the resulting adaptive profiles provide powerful, valuable, and acute information far beyond what intuition and private techniques can offer, their benefits are realized only through the people who use them. As explained below, the quotient is calculated at the organizational level. It augments the capacity of those responsible for the organization and its people to see what is otherwise subjective and blurry, and make better-informed decisions on the spot, resulting in increased engagement and alignment over time.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the BIQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about BIQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into the BIQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing the management of BIQs to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=File:GRI_Model_dep_variables.png&amp;diff=3359</id>
		<title>File:GRI Model dep variables.png</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=File:GRI_Model_dep_variables.png&amp;diff=3359"/>
		<updated>2026-04-30T22:15:16Z</updated>

		<summary type="html">&lt;p&gt;Flc: Flc uploaded a new version of File:GRI Model dep variables.png&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Acute_Intelligence_Quotient_(AIQ)&amp;diff=3358</id>
		<title>Acute Intelligence Quotient (AIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Acute_Intelligence_Quotient_(AIQ)&amp;diff=3358"/>
		<updated>2026-04-30T22:14:49Z</updated>

		<summary type="html">&lt;p&gt;Flc: Flc moved page Acute Intelligence Quotient (AIQ) to Behavior Intelligence Quotient (BIQ)&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;#REDIRECT [[Behavior Intelligence Quotient (BIQ)]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3357</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3357"/>
		<updated>2026-04-30T22:14:49Z</updated>

		<summary type="html">&lt;p&gt;Flc: Flc moved page Acute Intelligence Quotient (AIQ) to Behavior Intelligence Quotient (BIQ)&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Acute Intelligence Quotient, or AIQ, is calculated by combining adaptive profiles’ metrics with strategic and social performance indicators, along with other, more traditional economic indicators, at the organizational level.  &lt;br /&gt;
&lt;br /&gt;
The AIQ mnemonic reflects the understanding that although measuring social behavior and the resulting adaptive profiles provide powerful, valuable, and acute information far beyond what intuition and private techniques can offer, their benefits are realized only through the people who use them. As explained below, the quotient is calculated at the organizational level. It augments the capacity of those responsible for the organization and its people to see what is otherwise subjective and blurry, and make better-informed decisions on the spot, resulting in increased engagement and alignment over time.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the AIQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about AIQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into the AIQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing the management of AIQs to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=File:GRI_Model_dep_variables.png&amp;diff=3356</id>
		<title>File:GRI Model dep variables.png</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=File:GRI_Model_dep_variables.png&amp;diff=3356"/>
		<updated>2026-04-30T16:29:23Z</updated>

		<summary type="html">&lt;p&gt;Flc: Flc uploaded a new version of File:GRI Model dep variables.png&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3355</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3355"/>
		<updated>2026-04-30T16:23:02Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Introduction */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Acute Intelligence Quotient, or AIQ, is calculated by combining adaptive profiles’ metrics with strategic and social performance indicators, along with other, more traditional economic indicators, at the organizational level.  &lt;br /&gt;
&lt;br /&gt;
The AIQ mnemonic reflects the understanding that although measuring social behavior and the resulting adaptive profiles provide powerful, valuable, and acute information far beyond what intuition and private techniques can offer, their benefits are realized only through the people who use them. As explained below, the quotient is calculated at the organizational level. It augments the capacity of those responsible for the organization and its people to see what is otherwise subjective and blurry, and make better-informed decisions on the spot, resulting in increased engagement and alignment over time.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the AIQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about AIQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into the AIQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing the management of AIQs to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3354</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3354"/>
		<updated>2026-04-30T16:01:58Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Introduction */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Acute Intelligence Quotient, or AIQ, is calculated by combining adaptive profiles’ metrics with strategic and social performance indicators, along with other, more traditional economic indicators, at the organizational level.  &lt;br /&gt;
&lt;br /&gt;
The AIQ mnemonic reflects the understanding that although measuring social behavior and the resulting adaptive profiles provide powerful, valuable, and acute information far beyond what intuition and private techniques can offer, their benefits are realized only through the people who use them. As explained below, the quotient is calculated at the organizational level. It augments the capacity of those responsible for the organization and its people to see what is otherwise subjective and blurry, develop an interest in people management, and make better-informed decisions on the spot, resulting in increased engagement and alignment over time.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the AIQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about AIQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into the AIQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing the management of AIQs to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Performance_Models&amp;diff=3353</id>
		<title>Performance Models</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Performance_Models&amp;diff=3353"/>
		<updated>2026-04-30T15:21:55Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Social Performance */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:Performance_Models.png|right|400px]]&lt;br /&gt;
&lt;br /&gt;
=Introduction=&lt;br /&gt;
This article explores various models of organizational performance studied over recent decades and the increasing understanding of how individuals function and perform in organizations.&lt;br /&gt;
&lt;br /&gt;
When assessed precisely, measures of individual performance are relevant across a variety of topics related to a company’s strategy and daily operations, including attracting, recruiting, and empowering the talent it needs. They provide a new basis for understanding and improving organizational performance.&lt;br /&gt;
&lt;br /&gt;
=Performance Models=&lt;br /&gt;
Organizational performance can be approached through various models, which address aspects of its measurement and control on the one hand, and its conceptualization on the other. &lt;br /&gt;
&lt;br /&gt;
Organizational performance can be approached through various models, which address aspects of its measurement and control on the one hand, and its conceptualization on the other. &lt;br /&gt;
&lt;br /&gt;
Until the 1980s, management control research had focused on performance measures within the cybernetic model, an extension of the more popular command-and-control model that had dominated until the 1950s. Considering new individual and cultural factors alongside non-financial measures has enabled the holistic model to gradually overcome some limitations of the cybernetic model&amp;lt;ref&amp;gt;Henri, J. F. (2004). Performance measurement and Organizational Effectiveness: Bridging the gap. Managerial Finance. Vol. 30, No. 6, pp 93-123.&amp;lt;/ref&amp;gt;. Since the 2000s, thanks to capabilities from software platforms, the Internet, and later AI, Management Control System (MCS) packages have integrated and powered management control systems as integral parts of organizational management, most often aligned with holistic models. The three grand models are summarized in this table and detailed in separate articles.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|+ Performance Management&lt;br /&gt;
! Models !! Focus &lt;br /&gt;
|-&lt;br /&gt;
| [[Command_and_Control_Perspective | Command and Control]] || Traditional hierarchical top-down approach, with original management control systems for planning and controlling.&lt;br /&gt;
|- &lt;br /&gt;
| [[Cybernetic_Perspective | Cybernetic]] || Accounts for the first-order loop feedback, learning, and communication in addition to financial and production metrics.  &lt;br /&gt;
|-&lt;br /&gt;
| [[Holistic_Perspective | Holisitc]] || Holistic_Perspective | Extends the cybernetic model with a second-order feedback loop and emphasizes the relationships and interactions among the organization’s different parts, including its culture, vision, mission, and reward systems.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Regarding its conceptualization, several approaches have been proposed to categorize performance by context: research, society, leadership, organizational development, and more. For example, the models can be grouped into three categories according to their origins in economics, organizational studies, and social research&amp;lt;ref&amp;gt;Vibert C. (2004). Theories of macro organizational behavior: a handbook of ideas and explanations.&amp;lt;/ref&amp;gt;. Others have suggested categorizing them into three categories: objectives, systems, and stakeholders&amp;lt;ref&amp;gt;Campbell, J. P. (1977). On the nature of Organizational effectiveness. In P. S. Godman &amp;amp; J. M. Pennings (Eds.), New perspectives on organizational effectiveness. San Francisco: Jossey-Bass. Pp. 13-55.&amp;lt;br/&amp;gt;Zammuto, R. F. (1982). Assessing organizational effectiveness: Systems change, adaptation, and strategy. Albany, N.Y.:Suny-Albany Press.&amp;lt;br/&amp;gt;Quinn, R. E., Rohrbaugh, J. (1983). A Spatial Model of Effectiveness Criteria: Towards a Competing Values Approach to Organizational Analysis. Management Science. Vol. 29, No. 3, pp. 363-377.&amp;lt;br/&amp;gt;Cameron, K. S., Whetten, D. A. (1983). Organizational Effectiveness: One Model or Several? Preface. Orlando: Academic Press.&amp;lt;/ref&amp;gt; which is the one we adopted here. The value model was analyzed separately from the stakeholders model because it provides a distinct, overall understanding of how individuals and organizations behave. The non-performance model was added because it stands apart and continues to be a powerful model for understanding and managing performance. This grouping allows highlighting different analytical focus points, limitations, and relationships with management control systems.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|+ Performance Conceptualization&lt;br /&gt;
! Models !! Focus&lt;br /&gt;
|- &lt;br /&gt;
| [[Performance_by_Objectives|Objectives]] || Objectives are set and managed at different levels of the organization. Techniques such as cost-benefit analysis, management by objectives, individual criteria, or behavioral goals are used.&lt;br /&gt;
|-&lt;br /&gt;
| [[Systems%27_Performance|Systems]] || Systemic models emphasize the importance of an organization&#039;s means, such as inputs, outputs, resource acquisition, and processes. They include the operations research model, the structural contingency model, and the culturalist and social regulation models.&lt;br /&gt;
|-&lt;br /&gt;
| [[Stakeholders%27_Performance|Stakeholders]] || Stakeholders&#039; performance models emphasize the expectations of individuals and interest groups that are either within or surrounding the organization. It includes the organizational development model, satisfaction, and expectancy models.&lt;br /&gt;
|-&lt;br /&gt;
| [[Performance_by_Values|Values]] || Value models extend the stakeholder model to understand organizations in terms of individual values and preferences. The concept of values encompasses broad aspects of social behavior that, unlike others, can be described, measured, and shared.&lt;br /&gt;
|-&lt;br /&gt;
| [[Non_Performance|Non-performance]] || It is easier, more precise, consensual, and beneficial to address performance issues by problems and faults rather than by skills and performance criteria.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Organizational performance models have evolved over time, not to replace earlier ones but to improve them, expand their scope, and develop new models that meet current needs. Since the 2000s, with the rise of the Internet and more recently, AI, our ability to collect and analyze people&#039;s data has greatly increased. Similarly, management control systems have advanced, enhancing our capacity to better understand and manage people. How organizations can improve their performance over time is closely connected to how individuals and teams can enhance their performance.&lt;br /&gt;
&lt;br /&gt;
=Individual Performance=&lt;br /&gt;
[[File:Performance_Individual.png|right|300px]]&lt;br /&gt;
&lt;br /&gt;
As the conceptualization of organizational performance and management control systems has dramatically progressed over the past decades, so has the understanding of people and their management. Although it takes more time than in technology, research in the social sciences has had the opportunity to build, break, challenge, and test the limits of many models and techniques. Adaptive profiles emerged from research in the 1950s in the USA and gradually began to penetrate organizations of all sizes worldwide.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;blockquote&amp;gt;&#039;&#039;&#039;Adaptive profiles measure how people perform in context, their social behavior, adaptation efforts, and engagement.&#039;&#039;&#039;&amp;lt;ref&amp;gt;See more information [[Operationalizing_Performance|here on how adaptive profiles are used to operationalize performance at an individual level.]]&amp;lt;/ref&amp;gt;&amp;lt;/blockquote&amp;gt;&lt;br /&gt;
&lt;br /&gt;
Just like in the entertainment industry, actors perform in various ways, taking on different roles in different movies, influenced not only by their individual characteristics but also by how they are asked to act on stage. How does personal performance on the field actually happen, and what results does it produce? The adaptive profiles offer some answers.&lt;br /&gt;
&lt;br /&gt;
The same concept applies in sports, where team members are expected to collaborate and adapt their behavior when playing together, rather than strictly sticking to their personalities and positions on the field. In companies, different roles also require acting and adapting in various ways.&lt;br /&gt;
&lt;br /&gt;
[[File:Profile Detailed.png|right|300px]]&lt;br /&gt;
Adaptive profiles, like the one on the right, are constructed using a two-question, open-scenario, adjective format. The process helps remove biases and improve objectivity. The results are profiles that subtly show how people behave, feel, and think. They provide insights to maximize individual performance in flow, ways to support adaptation and engagement, and the conditions to prevent underperformance. The profiles are also used to enhance organizational performance&amp;lt;ref&amp;gt;The adaptive profiles are discussed [[Adaptive Profile|with greater detail in other articles on this wiki]].&amp;lt;/ref&amp;gt;.&lt;br /&gt;
   &lt;br /&gt;
Today, markets are familiar with tools that measure traits and types. These tools are widely used in recruitment and coaching. Adaptive profiles differ because they are based on factors. They add details that help improve individual assessments by eliminating major limits in how measures are represented, learned, and applied, and providing greater precision across many applications in recruitment, management, leadership, and organizational development.&amp;lt;ref&amp;gt;See more [[Assessments_Potential_Uses | here in this wiki about the various potential uses of assessment techniques.]]&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
=Organizational Performance=&lt;br /&gt;
[[File:Performance_Group.png|right|300px]]&lt;br /&gt;
&lt;br /&gt;
Adaptive profiles are also used at the position, team, company, and even industry and societal levels, to represent the performance expected for jobs and for small- to large-group activities. &lt;br /&gt;
Working with social behavior at the organizational level is especially useful and practical because behaviors are observable. We can describe, analyse, and discuss them more effectively than when working with abstract concepts that can only be inferred rather than observed. As evidenced by performance models based on values&amp;lt;ref&amp;gt;See for more information [[Performance by Values | here  in this wiki about increasing value-based performance.]]&amp;lt;/ref&amp;gt;, working on social behavior applies universally to a variety of situations, stakeholders, industries, and cultures.  &lt;br /&gt;
&lt;br /&gt;
==Social Performance==&lt;br /&gt;
&amp;lt;blockquote&amp;gt;&#039;&#039;&#039;By aggregating adaptive profiles, we can analyse a group&#039;s social performance.&#039;&#039;&#039;&amp;lt;/blockquote&amp;gt;&lt;br /&gt;
 &lt;br /&gt;
An organization and team’s success relies not only on each individual&#039;s participation but also on their ability to focus their collective efforts. Leaders and managers, as in sports with coaches and captains, play a vital role in building group cohesion, increasing team member involvement, and maintaining high levels of engagement. But how do these performances on the field actually occur, and what results do they generate? The adaptive profiles can explain that&amp;lt;ref&amp;gt; See in this article [[Acute Intelligence Quotient (AIQ)#Social_Performance_Indicators| here on how social performance indicators are calculated based on the adaptive profiles]].&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
In sports, the trust and cohesion built during training are crucial to success. The disengagement of one teammate can impact the rest of the team. During competition, coaches and captains give real-time calls and directions. Some team members may also assume leadership roles. The team’s success relies on social performance and support from leadership, the organization, and the broader community, including educators, families, sponsors, and advocates. In sports, this also includes supporters.&lt;br /&gt;
&lt;br /&gt;
==Strategic Performance==&lt;br /&gt;
&amp;lt;blockquote&amp;gt;&#039;&#039;&#039;Strategic performance, from a social behavior standpoint, can be established to determine how success will be achieved.&#039;&#039;&#039;&amp;lt;/blockquote&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
As with other characteristics of experience and skills, some social behaviors are expected in positions. The adaptive profiles enable the modeling of expected behaviors in jobs. They enable comparisons of how those behaviors occur over time for individuals in those jobs.&lt;br /&gt;
Does performance occur at the group level as intended, with appropriate fit among people and with enough diversity? The answer comes by comparing the adaptive profiles of individuals, positions, teams, and organizations. Once a company&#039;s management has defined the behaviors expected in positions and teams, aggregating profiles and calculating strategic indicators based on them formalizes the intent and helps manage performance gaps over time&amp;lt;ref&amp;gt; See in this article, [[Acute Intelligence Quotient (AIQ)#Strategic_Performance_Indicators| here on how strategic performance indicators are calculated based on the adaptive profiles]].&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Discussing these behaviors at the team and organizational levels increases the likelihood of reaching consensus. If social behaviors must be expressed differently across jobs and teams at varying levels of intensity and frequency, recruitment and management must ensure this.&lt;br /&gt;
&lt;br /&gt;
In our sports example, different social behaviors are expected of team members during competition. When training and socializing, athletes are expected to exhibit other social behaviors. How does their profile match what’s expected of them during training and while competing? Once aggregated, the adaptive profiles provide the answer.&lt;br /&gt;
&lt;br /&gt;
[[File:Performance_Models_Full.png|right|400px]]&lt;br /&gt;
&lt;br /&gt;
==Social Behavior Across Other Forms of Performance==&lt;br /&gt;
As illustrated on the right, a more nuanced understanding of social behavior provides insights into other performance models, including how they are discussed, implemented, and complement one another. Whether a company deploys command-and-control, cybernetic, or holistic management control systems, its approach to performance analysis and management is informed by the adaptive profiles. This is summarized in the table below.&lt;br /&gt;
&lt;br /&gt;
By comparing management intent with individuals’ adaptive profiles (measuring which social behaviors are present vs. absent), organizations can move beyond intuition and ensure their strategic focus—whether systemic, cybernetic, holistic, or values-based—is informed by a rigorous understanding of their most central asset: their people.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|+ Performance from a Social Behavior Standpoint&lt;br /&gt;
! Models !!  Insights from Adaptive Profiles&lt;br /&gt;
|-&lt;br /&gt;
| Objectives || Where objectives are managed through techniques such as Management by Objectives (MBO) and behavioral goals, the adaptive profile provides the individual criteria for assessing how the person will set, communicate, and meet those goals.&lt;br /&gt;
|-&lt;br /&gt;
| Systems || These models emphasize organizational means (inputs, processes, outputs). The adaptive profile provides a critical input metric—the human factor—that affects processes (e.g., collaboration) and outputs (e.g., results).&lt;br /&gt;
|-&lt;br /&gt;
| Stakeholders || These models focus on the expectations of internal and external interest groups. The adaptive profile provides an understanding of the individual and group values and behaviors that drive these stakeholders&#039; satisfaction and expectations.&lt;br /&gt;
|-&lt;br /&gt;
| Values || This is the model that the adaptive profile most directly informs, as it extends the stakeholder model by understanding organizations in terms of individual values and preferences, which are expressed through social behavior. The adaptive profile provides a framework for describing, measuring, and sharing these values across the organization.&lt;br /&gt;
|-&lt;br /&gt;
| Non-performance || This model suggests it is often easier to address performance by focusing on problems and faults rather than skills and criteria. The adaptive profile aids this by clearly identifying conditions that can prevent underperformance (e.g., high adaptation effort and disengagement) and by providing precise language (observable behavior) for problem resolution.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Performance_Models&amp;diff=3352</id>
		<title>Performance Models</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Performance_Models&amp;diff=3352"/>
		<updated>2026-04-30T15:21:22Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Strategic Performance */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[File:Performance_Models.png|right|400px]]&lt;br /&gt;
&lt;br /&gt;
=Introduction=&lt;br /&gt;
This article explores various models of organizational performance studied over recent decades and the increasing understanding of how individuals function and perform in organizations.&lt;br /&gt;
&lt;br /&gt;
When assessed precisely, measures of individual performance are relevant across a variety of topics related to a company’s strategy and daily operations, including attracting, recruiting, and empowering the talent it needs. They provide a new basis for understanding and improving organizational performance.&lt;br /&gt;
&lt;br /&gt;
=Performance Models=&lt;br /&gt;
Organizational performance can be approached through various models, which address aspects of its measurement and control on the one hand, and its conceptualization on the other. &lt;br /&gt;
&lt;br /&gt;
Organizational performance can be approached through various models, which address aspects of its measurement and control on the one hand, and its conceptualization on the other. &lt;br /&gt;
&lt;br /&gt;
Until the 1980s, management control research had focused on performance measures within the cybernetic model, an extension of the more popular command-and-control model that had dominated until the 1950s. Considering new individual and cultural factors alongside non-financial measures has enabled the holistic model to gradually overcome some limitations of the cybernetic model&amp;lt;ref&amp;gt;Henri, J. F. (2004). Performance measurement and Organizational Effectiveness: Bridging the gap. Managerial Finance. Vol. 30, No. 6, pp 93-123.&amp;lt;/ref&amp;gt;. Since the 2000s, thanks to capabilities from software platforms, the Internet, and later AI, Management Control System (MCS) packages have integrated and powered management control systems as integral parts of organizational management, most often aligned with holistic models. The three grand models are summarized in this table and detailed in separate articles.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|+ Performance Management&lt;br /&gt;
! Models !! Focus &lt;br /&gt;
|-&lt;br /&gt;
| [[Command_and_Control_Perspective | Command and Control]] || Traditional hierarchical top-down approach, with original management control systems for planning and controlling.&lt;br /&gt;
|- &lt;br /&gt;
| [[Cybernetic_Perspective | Cybernetic]] || Accounts for the first-order loop feedback, learning, and communication in addition to financial and production metrics.  &lt;br /&gt;
|-&lt;br /&gt;
| [[Holistic_Perspective | Holisitc]] || Holistic_Perspective | Extends the cybernetic model with a second-order feedback loop and emphasizes the relationships and interactions among the organization’s different parts, including its culture, vision, mission, and reward systems.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Regarding its conceptualization, several approaches have been proposed to categorize performance by context: research, society, leadership, organizational development, and more. For example, the models can be grouped into three categories according to their origins in economics, organizational studies, and social research&amp;lt;ref&amp;gt;Vibert C. (2004). Theories of macro organizational behavior: a handbook of ideas and explanations.&amp;lt;/ref&amp;gt;. Others have suggested categorizing them into three categories: objectives, systems, and stakeholders&amp;lt;ref&amp;gt;Campbell, J. P. (1977). On the nature of Organizational effectiveness. In P. S. Godman &amp;amp; J. M. Pennings (Eds.), New perspectives on organizational effectiveness. San Francisco: Jossey-Bass. Pp. 13-55.&amp;lt;br/&amp;gt;Zammuto, R. F. (1982). Assessing organizational effectiveness: Systems change, adaptation, and strategy. Albany, N.Y.:Suny-Albany Press.&amp;lt;br/&amp;gt;Quinn, R. E., Rohrbaugh, J. (1983). A Spatial Model of Effectiveness Criteria: Towards a Competing Values Approach to Organizational Analysis. Management Science. Vol. 29, No. 3, pp. 363-377.&amp;lt;br/&amp;gt;Cameron, K. S., Whetten, D. A. (1983). Organizational Effectiveness: One Model or Several? Preface. Orlando: Academic Press.&amp;lt;/ref&amp;gt; which is the one we adopted here. The value model was analyzed separately from the stakeholders model because it provides a distinct, overall understanding of how individuals and organizations behave. The non-performance model was added because it stands apart and continues to be a powerful model for understanding and managing performance. This grouping allows highlighting different analytical focus points, limitations, and relationships with management control systems.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|+ Performance Conceptualization&lt;br /&gt;
! Models !! Focus&lt;br /&gt;
|- &lt;br /&gt;
| [[Performance_by_Objectives|Objectives]] || Objectives are set and managed at different levels of the organization. Techniques such as cost-benefit analysis, management by objectives, individual criteria, or behavioral goals are used.&lt;br /&gt;
|-&lt;br /&gt;
| [[Systems%27_Performance|Systems]] || Systemic models emphasize the importance of an organization&#039;s means, such as inputs, outputs, resource acquisition, and processes. They include the operations research model, the structural contingency model, and the culturalist and social regulation models.&lt;br /&gt;
|-&lt;br /&gt;
| [[Stakeholders%27_Performance|Stakeholders]] || Stakeholders&#039; performance models emphasize the expectations of individuals and interest groups that are either within or surrounding the organization. It includes the organizational development model, satisfaction, and expectancy models.&lt;br /&gt;
|-&lt;br /&gt;
| [[Performance_by_Values|Values]] || Value models extend the stakeholder model to understand organizations in terms of individual values and preferences. The concept of values encompasses broad aspects of social behavior that, unlike others, can be described, measured, and shared.&lt;br /&gt;
|-&lt;br /&gt;
| [[Non_Performance|Non-performance]] || It is easier, more precise, consensual, and beneficial to address performance issues by problems and faults rather than by skills and performance criteria.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
Organizational performance models have evolved over time, not to replace earlier ones but to improve them, expand their scope, and develop new models that meet current needs. Since the 2000s, with the rise of the Internet and more recently, AI, our ability to collect and analyze people&#039;s data has greatly increased. Similarly, management control systems have advanced, enhancing our capacity to better understand and manage people. How organizations can improve their performance over time is closely connected to how individuals and teams can enhance their performance.&lt;br /&gt;
&lt;br /&gt;
=Individual Performance=&lt;br /&gt;
[[File:Performance_Individual.png|right|300px]]&lt;br /&gt;
&lt;br /&gt;
As the conceptualization of organizational performance and management control systems has dramatically progressed over the past decades, so has the understanding of people and their management. Although it takes more time than in technology, research in the social sciences has had the opportunity to build, break, challenge, and test the limits of many models and techniques. Adaptive profiles emerged from research in the 1950s in the USA and gradually began to penetrate organizations of all sizes worldwide.&lt;br /&gt;
&lt;br /&gt;
&amp;lt;blockquote&amp;gt;&#039;&#039;&#039;Adaptive profiles measure how people perform in context, their social behavior, adaptation efforts, and engagement.&#039;&#039;&#039;&amp;lt;ref&amp;gt;See more information [[Operationalizing_Performance|here on how adaptive profiles are used to operationalize performance at an individual level.]]&amp;lt;/ref&amp;gt;&amp;lt;/blockquote&amp;gt;&lt;br /&gt;
&lt;br /&gt;
Just like in the entertainment industry, actors perform in various ways, taking on different roles in different movies, influenced not only by their individual characteristics but also by how they are asked to act on stage. How does personal performance on the field actually happen, and what results does it produce? The adaptive profiles offer some answers.&lt;br /&gt;
&lt;br /&gt;
The same concept applies in sports, where team members are expected to collaborate and adapt their behavior when playing together, rather than strictly sticking to their personalities and positions on the field. In companies, different roles also require acting and adapting in various ways.&lt;br /&gt;
&lt;br /&gt;
[[File:Profile Detailed.png|right|300px]]&lt;br /&gt;
Adaptive profiles, like the one on the right, are constructed using a two-question, open-scenario, adjective format. The process helps remove biases and improve objectivity. The results are profiles that subtly show how people behave, feel, and think. They provide insights to maximize individual performance in flow, ways to support adaptation and engagement, and the conditions to prevent underperformance. The profiles are also used to enhance organizational performance&amp;lt;ref&amp;gt;The adaptive profiles are discussed [[Adaptive Profile|with greater detail in other articles on this wiki]].&amp;lt;/ref&amp;gt;.&lt;br /&gt;
   &lt;br /&gt;
Today, markets are familiar with tools that measure traits and types. These tools are widely used in recruitment and coaching. Adaptive profiles differ because they are based on factors. They add details that help improve individual assessments by eliminating major limits in how measures are represented, learned, and applied, and providing greater precision across many applications in recruitment, management, leadership, and organizational development.&amp;lt;ref&amp;gt;See more [[Assessments_Potential_Uses | here in this wiki about the various potential uses of assessment techniques.]]&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
=Organizational Performance=&lt;br /&gt;
[[File:Performance_Group.png|right|300px]]&lt;br /&gt;
&lt;br /&gt;
Adaptive profiles are also used at the position, team, company, and even industry and societal levels, to represent the performance expected for jobs and for small- to large-group activities. &lt;br /&gt;
Working with social behavior at the organizational level is especially useful and practical because behaviors are observable. We can describe, analyse, and discuss them more effectively than when working with abstract concepts that can only be inferred rather than observed. As evidenced by performance models based on values&amp;lt;ref&amp;gt;See for more information [[Performance by Values | here  in this wiki about increasing value-based performance.]]&amp;lt;/ref&amp;gt;, working on social behavior applies universally to a variety of situations, stakeholders, industries, and cultures.  &lt;br /&gt;
&lt;br /&gt;
==Social Performance==&lt;br /&gt;
&amp;lt;blockquote&amp;gt;&#039;&#039;&#039;By aggregating adaptive profiles, we can analyse a group&#039;s social performance.&#039;&#039;&#039;&amp;lt;/blockquote&amp;gt;&lt;br /&gt;
 &lt;br /&gt;
An organization and team’s success relies not only on each individual&#039;s participation but also on their ability to focus their collective efforts. Leaders and managers, as in sports with coaches and captains, play a vital role in building group cohesion, increasing team member involvement, and maintaining high levels of engagement. But how do these performances on the field actually occur, and what results do they generate? The adaptive profiles can explain that&amp;lt;ref&amp;gt; See in this article [[Organizational_Performance_Measurement#Social_Performance_Indicators| here on how social performance indicators are calculated based on the adaptive profiles]].&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
In sports, the trust and cohesion built during training are crucial to success. The disengagement of one teammate can impact the rest of the team. During competition, coaches and captains give real-time calls and directions. Some team members may also assume leadership roles. The team’s success relies on social performance and support from leadership, the organization, and the broader community, including educators, families, sponsors, and advocates. In sports, this also includes supporters.&lt;br /&gt;
&lt;br /&gt;
==Strategic Performance==&lt;br /&gt;
&amp;lt;blockquote&amp;gt;&#039;&#039;&#039;Strategic performance, from a social behavior standpoint, can be established to determine how success will be achieved.&#039;&#039;&#039;&amp;lt;/blockquote&amp;gt;&lt;br /&gt;
&lt;br /&gt;
&lt;br /&gt;
As with other characteristics of experience and skills, some social behaviors are expected in positions. The adaptive profiles enable the modeling of expected behaviors in jobs. They enable comparisons of how those behaviors occur over time for individuals in those jobs.&lt;br /&gt;
Does performance occur at the group level as intended, with appropriate fit among people and with enough diversity? The answer comes by comparing the adaptive profiles of individuals, positions, teams, and organizations. Once a company&#039;s management has defined the behaviors expected in positions and teams, aggregating profiles and calculating strategic indicators based on them formalizes the intent and helps manage performance gaps over time&amp;lt;ref&amp;gt; See in this article, [[Acute Intelligence Quotient (AIQ)#Strategic_Performance_Indicators| here on how strategic performance indicators are calculated based on the adaptive profiles]].&amp;lt;/ref&amp;gt;.&lt;br /&gt;
&lt;br /&gt;
Discussing these behaviors at the team and organizational levels increases the likelihood of reaching consensus. If social behaviors must be expressed differently across jobs and teams at varying levels of intensity and frequency, recruitment and management must ensure this.&lt;br /&gt;
&lt;br /&gt;
In our sports example, different social behaviors are expected of team members during competition. When training and socializing, athletes are expected to exhibit other social behaviors. How does their profile match what’s expected of them during training and while competing? Once aggregated, the adaptive profiles provide the answer.&lt;br /&gt;
&lt;br /&gt;
[[File:Performance_Models_Full.png|right|400px]]&lt;br /&gt;
&lt;br /&gt;
==Social Behavior Across Other Forms of Performance==&lt;br /&gt;
As illustrated on the right, a more nuanced understanding of social behavior provides insights into other performance models, including how they are discussed, implemented, and complement one another. Whether a company deploys command-and-control, cybernetic, or holistic management control systems, its approach to performance analysis and management is informed by the adaptive profiles. This is summarized in the table below.&lt;br /&gt;
&lt;br /&gt;
By comparing management intent with individuals’ adaptive profiles (measuring which social behaviors are present vs. absent), organizations can move beyond intuition and ensure their strategic focus—whether systemic, cybernetic, holistic, or values-based—is informed by a rigorous understanding of their most central asset: their people.&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|+ Performance from a Social Behavior Standpoint&lt;br /&gt;
! Models !!  Insights from Adaptive Profiles&lt;br /&gt;
|-&lt;br /&gt;
| Objectives || Where objectives are managed through techniques such as Management by Objectives (MBO) and behavioral goals, the adaptive profile provides the individual criteria for assessing how the person will set, communicate, and meet those goals.&lt;br /&gt;
|-&lt;br /&gt;
| Systems || These models emphasize organizational means (inputs, processes, outputs). The adaptive profile provides a critical input metric—the human factor—that affects processes (e.g., collaboration) and outputs (e.g., results).&lt;br /&gt;
|-&lt;br /&gt;
| Stakeholders || These models focus on the expectations of internal and external interest groups. The adaptive profile provides an understanding of the individual and group values and behaviors that drive these stakeholders&#039; satisfaction and expectations.&lt;br /&gt;
|-&lt;br /&gt;
| Values || This is the model that the adaptive profile most directly informs, as it extends the stakeholder model by understanding organizations in terms of individual values and preferences, which are expressed through social behavior. The adaptive profile provides a framework for describing, measuring, and sharing these values across the organization.&lt;br /&gt;
|-&lt;br /&gt;
| Non-performance || This model suggests it is often easier to address performance by focusing on problems and faults rather than skills and criteria. The adaptive profile aids this by clearly identifying conditions that can prevent underperformance (e.g., high adaptation effort and disengagement) and by providing precise language (observable behavior) for problem resolution.&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3351</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3351"/>
		<updated>2026-04-30T15:20:35Z</updated>

		<summary type="html">&lt;p&gt;Flc: Flc moved page Behavioral Intelligence Quotient (B-IQ) to Acute Intelligence Quotient (AIQ) without leaving a redirect&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Acute Intelligence Quotient, or AIQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the AIQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about AIQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into the AIQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing the management of AIQs to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3350</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3350"/>
		<updated>2026-04-30T15:18:30Z</updated>

		<summary type="html">&lt;p&gt;Flc: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Acute Intelligence Quotient, or AIQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the AIQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about AIQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into the AIQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing the management of AIQs to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3349</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3349"/>
		<updated>2026-04-30T04:44:30Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Deployment of the Measures */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Behavioral Intelligence Quotient, or B-IQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the Behavioral Intelligence Quotient (B-IQ).&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about B-IQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into B-IQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing the management of B-IQ and the adaptive profiles to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3348</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3348"/>
		<updated>2026-04-30T04:43:28Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Deployment of the Measures */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Behavioral Intelligence Quotient, or B-IQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the Behavioral Intelligence Quotient (B-IQ).&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about B-IQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039;, and their combination into B-IQ, reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing adaptive profiles to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3347</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3347"/>
		<updated>2026-04-30T04:41:14Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Lack of performance */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Behavioral Intelligence Quotient, or B-IQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the Behavioral Intelligence Quotient (B-IQ).&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about B-IQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If all economic, social, and strategic indicators decline, we can conclude that performance is lacking. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039; reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing adaptive profiles to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3346</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3346"/>
		<updated>2026-04-30T04:38:26Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Types of performance */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Behavioral Intelligence Quotient, or B-IQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined into the Behavioral Intelligence Quotient (B-IQ).&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about B-IQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If the economic, social, and strategic performances all declined, we can conclude that there is a lack of performance. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039; reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing adaptive profiles to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=File:GRI_Model_dep_variables.png&amp;diff=3345</id>
		<title>File:GRI Model dep variables.png</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=File:GRI_Model_dep_variables.png&amp;diff=3345"/>
		<updated>2026-04-30T04:28:25Z</updated>

		<summary type="html">&lt;p&gt;Flc: Flc uploaded a new version of File:GRI Model dep variables.png&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3344</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3344"/>
		<updated>2026-04-30T00:59:40Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Introduction */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
&lt;br /&gt;
This article explains how the Behavioral Intelligence Quotient, or B-IQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined to form the Behavioral Intelligence Quotient, or B-IQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about the B-IQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If the economic, social, and strategic performances all declined, we can conclude that there is a lack of performance. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039; reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing adaptive profiles to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
	<entry>
		<id>https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3343</id>
		<title>Behavior Intelligence Quotient (BIQ)</title>
		<link rel="alternate" type="text/html" href="https://wiki.gri.co/index.php?title=Behavior_Intelligence_Quotient_(BIQ)&amp;diff=3343"/>
		<updated>2026-04-30T00:59:04Z</updated>

		<summary type="html">&lt;p&gt;Flc: /* Types of performance */&lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;=Introduction=&lt;br /&gt;
[[File:GRI_Model_dep_variables.png|right|450px]]&lt;br /&gt;
Adaptive profiles, as measured at GRI, indicate how individuals function and how their environment influences their ability to adapt, engage, and perform. Once aggregated, these profiles also illustrate the overall behavior of a team, department, or company. They help identify organizational weaknesses by considering not only the organization’s internal requirements, but also its industry and market needs, and the various adaptive profiles of its stakeholders. &lt;br /&gt;
This article explains how the Behavioral Intelligence Quotient, or B-IQ, is calculated using measures of adaptive profiles and combining strategic and social performance indicators with other, more traditional economic indicators at the organizational level.&lt;br /&gt;
&lt;br /&gt;
=Construction of Performance Indicators=&lt;br /&gt;
&lt;br /&gt;
The unique properties of the adaptive profiles enable a precise understanding of people’s performance in context. Two key properties of their metrics are incorporated into the construction of performance indicators that can then be used at a group level. In summary, they are the following:&lt;br /&gt;
* &#039;&#039;&#039;Property 1&#039;&#039;&#039;: Adaptive profiles effectively indicate the level of individuals&#039; involvement, engagement, and effectiveness within their environment. Low adaptation combined with high engagement suggests that people are in roles that align with their values, expectations, interests, and social behavior preferences. Conversely, high adaptation and low engagement indicate disengagement, demotivation, and negative emotions among individuals in their roles. These levels of adaptation and engagement reflect either a mismatch between a person’s social behavior values and their position, or ineffective personal development.&lt;br /&gt;
* &#039;&#039;&#039;Property 2&#039;&#039;&#039;: Adaptive profiles, including their factors, scales, indicators, and profiles, offer a detailed view of people’s performance, encompassing social behaviors, values, preferences, styles, interests, and more. This view is based on both how people behave and how they think and feel about those social behaviors. Our best estimate at GRI is that the profiles capture up to 90% of people’s social behaviors across the short, medium, and long term. The intensity of these behaviors is influenced by Property 1 above. As a result, we not only gain a better understanding of how people function but also when their social behaviors are likely to be expressed.&lt;br /&gt;
&lt;br /&gt;
=Strategic Performance Indicators=&lt;br /&gt;
In fact, people consistently exhibit measurable social behaviors, preferences, and values. On the other hand, positions also have behavioral requirements that reflect the choices of the organization and its stakeholders. If the organization, its management, shareholders, pressure groups, etc., want efforts to be focused in a particular direction and in a relatively consistent and uniform manner, then this should occur. Conversely, if this is not the case, it suggests that management and recruitment efforts are not meeting their goals: behaviors are out of alignment with the objectives.&lt;br /&gt;
&lt;br /&gt;
By comparing actual behaviors of individuals with desired behaviors at the position level, the organization can assess and manage the relationship between actors&#039; behaviors and the organization’s needs, using the same behavioral dimensions. In practice, the difference can be measured between the behaviors described by the PBI (Position Behavior Indicator) profiles of positions and the actual behaviors of people, as shown in the Effective graph of the GRI adaptive profile. The gap between these indicates which actions should be taken to maximize the effectiveness of social behavior at each position. &lt;br /&gt;
&lt;br /&gt;
This performance is called strategic because understanding how to do things across all positions at every level is crucial when setting goals, planning, and controlling. The ways of selecting personnel, implementing processes, innovating, managing change, taking risks, defending, and gaining market share—highlighted by the adaptive profiles—shape how the organization functions. They involve decisions that are hard to reverse at the highest levels of hierarchy. The measurement of strategic performance is operationalized as the variable &#039;iopstra&#039; (the Objective Indicator of Strategic Performance).&lt;br /&gt;
&lt;br /&gt;
=Social Performance Indicators=&lt;br /&gt;
The measures of adaptation and engagement enable us to evaluate the gap between what might be deemed satisfactory from an organizational perspective, whether agreed upon by stakeholders or not, and what manifests at the individual level in terms of personal effectiveness. The organization may desire certain behaviors, but these behaviors may require efforts that create tension and reduce commitment, as noted in property 1 above. &lt;br /&gt;
&lt;br /&gt;
This performance is referred to as social performance. It reflects consideration of people&#039;s expectations and values, a good fit between job and personal profiles, a positive understanding of individual differences by management, employees&#039; self-awareness of their capacities and talents, and the proper adjustment of compensation and reward systems. The measure of social performance is represented by the variable &#039;iopsoc&#039; (the Objective Indicator of Social Performance).&lt;br /&gt;
&lt;br /&gt;
=Economic Performance Indicators=&lt;br /&gt;
Performance beyond the strategic and social performance outlined earlier is classified as economic performance. This includes aspects related to finance, production, marketing, sales, and customer relations. It covers the three dimensions of Kaplan and Norton&#039;s balanced scorecard&amp;lt;ref&amp;gt;Kaplan, R. S., Norton, D. P. (1998) The Balanced Scorecard. Organization Editions. Translation of the original 1996 edition: The balanced Scorecard: Translating strategy into action.&amp;lt;/ref&amp;gt;: financial, customer, internal processes, and innovation, along with part of the fourth dimension, learning and growth. As long as the indicators are outside the performance measures listed in the strategic and social indicators above, they fall within the scope of economic performance. Absenteeism and staff turnover rates, which can be translated into costs, are also included among economic performance criteria.&lt;br /&gt;
&lt;br /&gt;
Economic performance indicators should be broken down into as many indicators as needed, depending on the context. The measurement of economic performance is represented by the variable &#039;iopecon&#039; (the Objective Indicator of Economic Performance).&lt;br /&gt;
&lt;br /&gt;
=Types of performance=&lt;br /&gt;
&lt;br /&gt;
The strategic performance (&#039;iopstra&#039;) and social performance (&#039;iopsoc&#039;) indicators are calculated from individual adaptive profiles and expectations in positions (PBI) and expectations in teams (TBI).&lt;br /&gt;
&lt;br /&gt;
Once the individual profiles are available and the position and team expectations are set, the differences are calculated between the various Natural profiles and the position or team profiles on one hand, and between the Natural and Role profiles on the other hand.&lt;br /&gt;
&lt;br /&gt;
Calculations of deviations for different people within the same teams, departments, or company are integrated into strategic and social performance indicators and combined to form the Behavioral Intelligence Quotient, or B-IQ.&lt;br /&gt;
&lt;br /&gt;
Depending on how the economic, social, and strategic performance indicators change during the analysis period, we can draw the following conclusions about the B-IQ and performance. Different combinations of variables tracked over time lead to four possible outcomes: (1) optimal and pending, (2) lagging, (3) under pressure, or (4) lack of performance.&lt;br /&gt;
&lt;br /&gt;
===Optimal Performance===&lt;br /&gt;
If the three indicators of social (&#039;iopsoc&#039;), strategic (&#039;iopstra&#039;), and economic (&#039;iopecon&#039;) performance all improve positively over the period considered, we can refer to this as &#039;optimal performance&#039;. This indicates that people are more satisfied and engaged, that roles in the organization are aligned with the strategy in the short and medium/long term, and that economic goals are met.&lt;br /&gt;
&lt;br /&gt;
&#039;iopsoc&#039; is rising and &#039;iopstra&#039; is rising, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Lagging Performance===&lt;br /&gt;
If only economic and social performance improve, one might conclude there is a &#039;lagging performance.&#039; This indicates that people are more engaged and satisfied, economic goals are met, but job roles are not filled as originally planned. &lt;br /&gt;
&lt;br /&gt;
It is very likely that there is a selection issue. &#039;iopsoc&#039; is rising, &#039;iopstra&#039; is falling, &#039;iopecon&#039; is reached.&lt;br /&gt;
&lt;br /&gt;
===Performance Under Pressure===&lt;br /&gt;
If only strategic and economic performance show positive changes, we can conclude that overall performance is under pressure. This indicates that economic performance has improved, aligning people&#039;s adaptive profiles more closely with job profiles, but at the same time, people are experiencing more stress, lower motivation, and less engagement. It is likely there are issues with people management. &lt;br /&gt;
&lt;br /&gt;
The indicator &#039;iopsoc&#039; is decreasing, &#039;iopstra&#039; is increasing, and &#039;iopecon&#039; has been reached.&lt;br /&gt;
&lt;br /&gt;
===Pending Performance===&lt;br /&gt;
If only the social and strategic performances improve positively, we can classify this as a &#039;pending performance.&#039; This indicates that people are more engaged and satisfied, with social behavior more aligned with the strategy, but the economic objectives have not yet been achieved.&lt;br /&gt;
 &lt;br /&gt;
This scenario is categorized under the first &#039;optimal performance&#039; as a special case. The organization is awaiting economic outcomes while avoiding adverse effects on stakeholders. The economic objectives might not have been realistic, yet the organization remains committed. &#039;iopsoc&#039; is up, &#039;iopstra&#039; is up, &#039;iopecon&#039; is not achieved.&lt;br /&gt;
&lt;br /&gt;
===Lack of performance===&lt;br /&gt;
If the economic, social, and strategic performances all declined, we can conclude that there is a lack of performance. People are less involved; the adaptive profiles are less aligned with the strategy; the economic results are also lacking. &#039;iopecon&#039; is not reached, &#039;iopsoc&#039; is down, &#039;iopstra&#039; is down.&lt;br /&gt;
&lt;br /&gt;
The following table summarizes the four possible results for performance values:&lt;br /&gt;
&lt;br /&gt;
{| class=&amp;quot;wikitable&amp;quot; style=&amp;quot;margin: auto;&amp;quot;&lt;br /&gt;
|-&lt;br /&gt;
! !! Optimal Performance&amp;lt;br/&amp;gt;(and pending) !! Lagging&amp;lt;br/&amp;gt;Performance !! Performance&amp;lt;br/&amp;gt;Under Pressure !! Lack of&amp;lt;br/&amp;gt;Performance&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Strategic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopstra&#039;&#039; || Increase ↗ || Decrease ↘ || Increase ↗ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Social performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopsoc&#039;&#039; || Increase ↗ || Increase ↗ || Decrease ↘ || Decrease ↘&lt;br /&gt;
|-&lt;br /&gt;
| &#039;&#039;&#039;Economic performance&#039;&#039;&#039;&amp;lt;br/&amp;gt;&#039;&#039;iopecon&#039;&#039; || Achieved&amp;lt;br/&amp;gt;(or to be achieved) || Achieved || Achieved || Not Achieved&lt;br /&gt;
|}&lt;br /&gt;
&lt;br /&gt;
=Deployment of the Measures=&lt;br /&gt;
&lt;br /&gt;
The adaptive profiles show how people perform best and how they adjust to their environment. The development of the two indicators &#039;iopstra&#039; and &#039;iopsoc&#039; reflects the organization&#039;s overall performance at the strategic and social levels.&lt;br /&gt;
&lt;br /&gt;
* The indicator  &#039;iopsoc&#039; measures how stakeholders’ satisfaction and involvement evolve over time.&lt;br /&gt;
* The indicator &#039;iopstra&#039; measures how the strategy is reached as set with the TBI indicators for the teams, departments, and the organization.&lt;br /&gt;
&lt;br /&gt;
The profiles enable performance measurement that closely tracks the development of the two indicators &#039;iopsta&#039; and &#039;iopsoc&#039; over time, aligning as closely as possible with where the measures are applied: at the individual level with the adaptive profile and at the management level responsible for executing the strategy.&lt;br /&gt;
 &lt;br /&gt;
Given the rapid pace of change and organizational complexity, it is essential to reduce non-performance, as indicated by the indicators &#039;iopstra&#039; and &#039;iopsoc&#039;. It’s unrealistic to expect that all stakeholders&#039; adaptive profiles will perfectly align with the expectations of their roles, as reflected in the strategic performance indicator ‘iopstra’, or that all social performance indicators will reach their maximum levels, as shown by the social performance indicator ‘iopsoc’.&lt;br /&gt;
&lt;br /&gt;
Excessive adaptation and disengagement, which come with negative emotions, are undesirable. As management research shows, providing feedback to team members and training for managers helps both parties take ownership of the measures.&lt;br /&gt;
&lt;br /&gt;
Decentralizing adaptive profiles to operations enables strategy implementation as close as possible to where decisions are made and actions are taken, ensuring that measures and information best serve the organization and its members at various levels. When incorporated into performance reviews, these measures motivate teams and facilitate organizational change. Ultimately, individual and unit-level measures can be integrated into a management control system to ensure that performance targets are met.&lt;br /&gt;
&lt;br /&gt;
=Notes=&lt;br /&gt;
&lt;br /&gt;
[[Category:Articles]]&lt;br /&gt;
[[Category:Performance]]&lt;br /&gt;
[[Category:General Framework]]&lt;/div&gt;</summary>
		<author><name>Flc</name></author>
	</entry>
</feed>