Progression and variation of competitive 100 and 200m performance at the 2021 European Swimming Championships

Abstract

Progressions in competitive swimming are necessary to ensure that peak performance occurs when medals are decided. This study aimed to: i) study the coefficient of variation (CV) and performance changes (%∆) among swimmers who participated in different rounds (i.e., heats, semi-finals and finals); ii) study the CV changes as a function of FINA-points. A total of 1447 performances were analysed in the 100 and 200m-races during the Budapest 2021 European-Championships. Linear mixed-effects models were applied for total and split times to obtain intra-athlete CV and %∆. The FINA-points were studied with two-way ANOVA and Pearson's correlation assessed the relations with the CV. The CV in 100m-races was: 0.48±0.21% for males and 0.50±0.20% for females (∆=-0.66%); in 200m-races: 0.63±0.36% for males and 0.60±0.34% for females (∆=-0.82%). There were differences in FINA-points between strokes and distances (p<0.02) and this was associated with higher CV for the 200m-races (r=0.37; p=0.003), indicating that best swimmers changed their performance over the rounds. In conclusion, swimmers who qualified for the finals performed easier during the heats by going slower in the first 50m-lap; however, some of them would have little chance of qualifying for the finals during major championships because some events were below FINA-points world-standards.

Full text

Progression and variation of competitive 100 and 200m performance at the 2021
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European Swimming Championships
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Cuenca-Fernández, F1*; Ruiz-Navarro, JJ1*; González-Ponce, A1; López-Belmonte, O1;
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Gay, A1; Arellano, R1
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1.- Aquatics Lab. Department of Physical Education and Sports. Faculty of Sport
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Sciences. University of Granada (Granada) Spain
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*- These two authors contributed equally to this work.
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Word count: 4603 words (excluding references, tables and figure captions)
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Corresponding author:
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Raúl Arellano
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Aquatics Lab. Department of Physical Education and Sports. Faculty of Sport Sciences.
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Ctra. Alfacar SN (18071), Granada. University of Granada, Granada, Spain
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Phone: +34 626976150
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Email: r.arellano@ugr.es
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TWITTER:
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Francisco Cuenca-Fernández: @Cuenca_Fernandz
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Jesús Juan Ruiz-Navarro: @Ruiz_NavarroPhD
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Óscar López-Belmonte: @Oscarlobel95
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Ana Gay: @AnaGayP
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Raúl Arellano: @R_Arellano_C
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FUNDING INFORMATION:
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This study was supported by grants awarded by the Ministry of Science, Innovation and
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Universities (Spanish Agency of Research) and the European Regional Development
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Fund (ERDF); PGC2018-102116-B-I00 ‘SWIM II: Specific Water Innovative
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Measurements: Applied to the performance improvement’ and the Spanish Ministry of
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Education, Culture and Sport: FPU17/02761, FPU16/02629 and FPU19/02477 grants.
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Progression and variation of competitive performance in the 100m and 200m events
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at the 2021 European Swimming Championships
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ABSTRACT
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Progressions in competitive swimming are necessary to ensure that peak performance
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occurs when medals are decided. This study aimed to: i) study the coefficient of variation
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(CV) and performance changes (%∆) among swimmers who participated in different
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rounds (i.e., heats, semi-finals and finals); ii) study the CV changes as a function of FINA-
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points. A total of 1447 performances were analysed in the 100 and 200m-races during the
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Budapest 2021 European-Championships. Linear mixed-effects models were applied for
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total and split times to obtain intra-athlete CV and %∆. The FINA-points were studied
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with two-way ANOVA and Pearson's correlation assessed the relations with the CV. The
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CV in 100m-races was: 0.48±0.21% for males and 0.50±0.20% for females (∆=-0.66%);
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in 200m-races: 0.63±0.36% for males and 0.60±0.34% for females (∆=-0.82%). There
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were differences in FINA-points between strokes and distances (p<0.02) and this was
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associated with higher CV for the 200m-races (r=0.37; p=0.003), indicating that best
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swimmers changed their performance over the rounds. In conclusion, swimmers who
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qualified for the finals performed easier during the heats by going slower in the first 50m-
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lap; however, some of them would have little chance of qualifying for the finals during
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major championships because some events were below FINA-points world-standards.
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Keywords: Competition analysis; tactical and strategy; finalists and non-finalists;
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Budapest 2021
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INTRODUCTION
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Swimming is one of the few sports in which athletes repeatedly compete in the same event
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(distance and stroke), so the reliability of their performance may differ between races
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(Stewart & Hopkins, 2000). Progressions are often necessary to ensure the swimmer
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qualification for the semi-final and then the final in a given event, and that his or her peak
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performance occurs in the final, when medals are decided (Mujika et al., 2019; Pyne et
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al., 2004; Sánchez et al., 2021). According to Thompson et al. (2004), high-level
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competitors sometimes prefer to save their best performance for the final of a competition
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and try to conserve energy during heats (Skorski et al., 2014), especially if the event is at
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regional or national level. However, this may not be the case in major events such as the
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European Championships, where swimmers have to face the best competitors on the
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continent from the very beginning. Thus, they may only be able to reserve their peak
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performance to a certain extent during heats and semi-finals, otherwise, they have the risk
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of not qualifying for the final.
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The multifactorial nature of sport outcomes implies that intra-individual competitive
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performances often differ (Thompson et al., 2004). This is known as the coefficient of
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variation (CV) and is defined as the percentage of random variation in athlete
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performance (Hopkins et al., 1999). In the study of Fulton et al. (2009) with Paralympic
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swimmers, intra-swimmer variability from race to race, expressed as CV, ranged from
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1.2% to 3.7% over 15 events counted over a two-year period. In terms of intra-
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competition results, it has been reported that a strategy intended to significantly change
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performance in a closely matched competition (e.g., an Olympic final) must be equivalent
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to at least ~0.5% of that CV to be considered effective (Stewart & Hopkins, 2000). This
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could therefore be defined as the smallest worthwhile improvement in performance that
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will affect an athlete's chance of winning a medal or reaching a final.
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Previous studies reported similar performance improvements from heats to finals in elite
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and competitive junior swimmers (-1.2%) (Skorski et al., 2014; Skorski et al., 2013).
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Additionally, Pyne et al. (2004) described that to be in the running for a medal in the
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Olympic 50, 100 and 200m events, swimmers experienced a CV of 0.7 to 1.0% between
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heats for given distances and strokes, with a change in performance of -0.6 to -0.7%
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between heats and semi-finals, and -0.5 to -0.7% between semi-finals and finals.
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Therefore, tactical approaches to conserve energy may explain these differences. In this
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regard, research has shown that intra-swimmer CV in performance is more consistent
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between different distances of the same stroke than between the same distance in different
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strokes (Stewart & Hopkins, 2000). This suggests that, during a competition in which
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swimmers perform their preferred strokes, they may find it easier to voluntarily vary their
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pace to swim faster or slower in the different rounds (i.e., heats, semi-finals and finals).
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It has been estimated that to have a realistic opportunity of winning an international
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medal, swimmers need to have a top 10 ranking in that event, and make a -0.6%
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progression in their world-ranking time (Trewin et al., 2004); whereby, these swimmers
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could predict their actual probabilities of success by observing their own performance
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and that of their rivals in the months leading up to the event (Mujika et al., 2019). Within
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the swimmers who participated in the 2021 European Championships, there were
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different groups of swimmers with different standards: those who aspired to reach a semi-
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final or a final, and those who focused exclusively on winning a medal or setting a new
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World Record (WR). This differentiation is observed through International Swimming
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Federation (FINA) points (i.e., a value of the swimmer's best mark relative to the world
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best mark) (Morais et al., 2020), and could be crucial in distinguishing the CV between
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them. For example, previous studies (Mujika et al., 2019; Stewart & Hopkins, 2000;
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Trewin et al., 2004) claimed that faster swimmers (i.e., with higher FINA points) might
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be more consistent in their performance than slower swimmers (i.e., with lower FINA
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points). However, this claim seems to be supported by comparisons between Olympic-
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level and national-level swimmers, but not by comparisons between faster and slower
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contenders within the same competition. Therefore, it was our interest to study this issue
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among competitors at the 2021 European Swimming Championships.
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The purposes of this study were: i) to study the coefficient of variation (CV) and the actual
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changes in performance (%∆) among swimmers who participated in the different rounds
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(i.e., heats, semi-finals and finals), and; ii) to study the competitive level of performance
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and CV changes based on FINA points. It was hypothesised that if faster swimmers decide
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not to excel during heats, then performance changes would be detected during the
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following rounds, leading to a significant change in CV (at least ~0.5%). Subsequently,
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this CV might be more evident in swimmers that achieved higher FINA points.
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MATERIAL AND METHODS
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Subjects
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With the exception of disqualifications, individual performances in all 100 and 200m of
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the four swimming strokes (i.e., freestyle, breaststroke, backstroke and butterfly), counted
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during the Budapest 2021 European Championships, were evaluated. A total of 1447
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performances of 1009 different elite swimmers (548 males [age: 22.78 ± 3.79] and 461
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females [age: 21.92 ± 4.30]) were analysed, being 766 male-races (butterfly: 147,
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backstroke: 151, breaststroke: 161, and freestyle: 222) and 681 female-races (butterfly:
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130, backstroke: 131, breaststroke: 151, and freestyle: 183).
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Data collection
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All data were obtained from the official publicly available Budapest 2021 European
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Championships swimming website (www.len.eu). As this study was a retrospective
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analysis of publicly available data, there was no participant recruitment, treatment or
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experimental intervention. Therefore, informed consent and ethical approval from the
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local committee were not required.
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For each event, the results and changes in performance during the three rounds (i.e., heats,
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semi-finals, and final) and the split times were collected to analyse the process of sports
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performance. The official data was downloaded by implementing a Web Scraping routine
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in Python®. Once the automated process was completed, two independent researchers
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verified that no information was missing. The downloaded data consisted of "distance",
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"stroke", "round", "rank", "lane", "swimmer name", "reaction time", "split times", "race
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time" and the corresponding "FINA points". Therefore, using the final times, the
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following variables were calculated:
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- The intra-athlete CV, which represents the random variation in performance
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between rounds (Hopkins et al., 1999). Three different intra-athlete CVs were
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obtained: 1) between heats and semi-finals (H-SF); 2) between semi-finals and
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finals (SF-F), and; 3) between heats and finals (H-F), including all three rounds,
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total times, and split times. The CV was calculated using the following equation:
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𝐶𝑉 = 𝑆𝑡𝑎𝑛𝑑𝑎𝑟𝑑 𝑑𝑒𝑣𝑖𝑎𝑡𝑖𝑜𝑛 (𝑒. 𝑔., 𝑆𝐹 − 𝐹)
𝑀𝑒𝑎𝑛 (𝑒. 𝑔., 𝑆𝐹 − 𝐹) × 100
(1)
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- The inter-athlete CV, which represents the dispersion of ability among athletes in
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the different rounds. Three different inter-athlete CVs were obtained: 1) H,
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obtained from the performance of the participants in the heats; 2) SF, obtained
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from the semi-finalists; and 3) F, obtained from the finalists.
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- Relative change (%∆) in performance between rounds was calculated using the
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following equation:
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%∆ = 𝑅𝑜𝑢𝑛𝑑 2 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 − 𝑅𝑜𝑢𝑛𝑑 1 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒
𝑅𝑜𝑢𝑛𝑑 1 𝑝𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 × 100
(1)
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where, Round 2 performance refers to the race time achieved on the second round
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and Round 1 performance refers to the race time achieved on the previous round.
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The criterion for performance progression, no change, or regression was %∆ being
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lower, equal, or higher than 0, respectively (Mujika et al., 2019).
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- The FINA points were retrieved directly from the official results, being its
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calculation as follows: 1000 × (World Record time (s) / swim time (s))3).
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Statistical Analysis
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The normality of the distribution was confirmed with Shapiro-Wilk test and the
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homoscedasticity was confirmed with the Levene test. All analyses were conducted
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differentially by sex (Shapiro et al., 2021). Linear mixed-effects models were applied for
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all swimmers and performances both in the total and split times to estimate means (fixed
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effects) and within- and between-swimmer variations (random effects, modelled as
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variances), in accordance with equation (1), as explained in previous studies (Pyne et al.,
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2004; Stewart & Hopkins, 2000). The fixed main effects were event (100 and 200m), lap
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(e.g., from 0 to 50m) and rounds (e.g., heats, semi-finals, and final). Subsequently,
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analysis of variance (ANOVA) test was applied to explore differences in CV and %∆
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between distances. Pearson’s product correlation between performances (i.e., FINA
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points), CV and %∆ was conducted to assess whether the variability in performance was
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related to the swimmers’ level. In addition, the FINA points of the finalists were analysed
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with two-way ANOVA (factors: distance [100 and 200m] × stroke [freestyle,
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breaststroke, backstroke and butterfly]) with Bonferroni post hoc pairwise comparisons.
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Statistical procedures were carried out using SPSS 24.0 (IBM, Chicago, IL, USA) with
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significance level set at p< 0.05.
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RESULTS
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The results of the linear mixed-effects model analysis, intra-subject CVs and ∆%
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progression between the different rounds, distances, and strokes are presented for total
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performances in Table 1. This analysis revealed interactions in CV and ∆% for swimmers
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who qualified for finals compared to heats, with 60% of the swimmers achieving a CV
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greater than 0.5% and with 82.8% of swimmers achieving performance improvements.
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The average race times for each round, distance and race are presented in Figure 1, in
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addition, this information has also been collected for each event including the results
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obtained by the medallists (see supplementary material). The results of the linear mixed-
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effect model analysis for the split times in 100 and 200m races are shown in Tables 2
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(males) and 3 (females). Among the swimmers who progressed to the semi-finals and
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finals, the improvements in performance occurred predominantly in the first lap of the
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race (p < 0.05).
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(Table 1 near here)
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(Figure 1 near here)
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(Table 2 near here)
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(Table 3 near here)
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ANOVA testing revealed no differences in intra-subject CV and ∆% between the heats
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and semi-finals, but showed differences in CV between the semi-finals and finals (F =
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5.804; p = 0.017). Specifically, the 100m races showed a CV of 0.28-0.30%, while the
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200m races showed a CV of ~0.43%. These differences were obtained for the whole
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group, but not according to sex. The inter-subjects CVs for each round and stroke are
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presented in Table 4. The highest inter-subject variation was obtained during the heats,
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and the lowest during the Finals.
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(Table 4 near here)
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Correlation analysis revealed no associations for the 100m races between FINA points
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and CV when finals performance was compared to heats (p = 0.07). However, an
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association was found for the 200m races when finals performance was compared to heats
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(r = 0.37; p = 0.003), and this relationship was confirmed by the association between
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FINA points and ∆% (r = -0.50; p < 0.001).
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Two-way ANOVA showed a distance × stroke interaction on FINA points for both males
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(F = 5.472; p < 0.001) and females (F = 2.791; p = 0.016). Post hoc comparisons and
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FINA points achieved for each distance and stroke are presented in Table 5 and Figure 2.
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(Table 5 near here)
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(Figure 2 near here)
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DISCUSSION AND IMPLICATIONS
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The first objective of this study was to study the coefficient of variation (CV) and
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effective changes in performance (%∆) between swimmers participating in different
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rounds of the same championship. It was hypothesised that if faster swimmers performed
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the heats more slowly, a change in performance would be detected in the following rounds
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and therefore, a significant change in CV (~0.5%) would occur. Our results showed that
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swimmers had a mean CV of ~0.5% between performances achieved during finals
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compared to heats, with a mean range of performance improvement of ~0.7%. When
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these differences between distances or rounds were studied, different trends emerged
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(e.g., higher CV in the medium versus short events or little improvement from semi-finals
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to finals); nevertheless, the strategy of increasing pace in the first lap of the race appeared
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to be common among swimmers who progressed to the next rounds.
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It has been shown that distance swimmers achieve greater variation in performance from
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heats to finals than swimmers in shorter events (Pyne et al., 2004). In this study,
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combining males and females, the 200m races had the greatest variation and the 100m
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the least (Table 1). Specifically, in the progression from the semi-finals to the finals, in
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the 200m races, both males and females obtained a mean performance improvement value
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of -0.24% (Table 1), while in the 100m races, some female races obtained performance
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deteriorations, resulting in only -0.02% performance improvements for this distance (i.e.,
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the improvements observed in some swimmers were offset by performance deterioration
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in others). Thus, although CV represented changes in performance, these were not always
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positive for performance.
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Within the total sample of swimmers, at least 27.1% did not reach performance
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progression. This failure could be the result of ineffective planning or the swimmers'
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inability to perform at their best under the pressure of international competition (Mujika
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et al., 2019). Specifically, performance improvements for all finalists accounted for -
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0.7%, and this rose to -1.2% when only medallists were considered (See supplemental
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material). These results were lower than those obtained by Thompson (1998), who
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reported a -2.8% improvement in race time between heats and finals for national level
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swimmers. In contrast, our results appeared to be closer to that reported in the study of
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Trewin et al. (2004) with elite swimmers, as only gold medallists showed a progression
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as large as -0.9%. Hence, these results may be common to medal winners and/or finalists,
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and their particular ability to obtain variations in performance during the event.
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Sporting achievements are influenced by a number of post-training factors that increase
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with years of practice (Nowacka & Słomiński, 2018). Therefore, multiple tactics and
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pacing strategies are applied in competition to progress from one round to the next (Foster
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et al., 2009). According to Stewart and Hopkins (2000), a strategy aimed at changing an
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athlete's performance must account for at least ~0.5% of the CV to be considered
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effective. Therefore, top-level swimmers who are unable to make such performance
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improvements at major international meets will reduce their chances of winning a medal
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(Trewin et al., 2004). In this study, performance improvements from heats to finals were
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greater than this percentage, especially in the 200m events (Table 1), confirming that
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swimmers who entered in the top 8 positions managed to perform during heats at a lighter
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pace than their maximum. However, the H-SF and SF-F CVs were around 0.3-0.4%,
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meaning that this variation may or may not be effective depending on the cumulative
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change in performance in each case (Trewin et al., 2004), with some of the improvements
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referred to as trivial (Table 1). Specifically, in swimming, the race time is made up of the
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start, swim, turn, and finish times; therefore, if turns account for 20% of the total time, a
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2.5% gain in turn time would be needed to improve the total time by 0.5% (Sánchez et
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al., 2021). However, large changes in certain phases (e.g., the swim start) may be useless
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if performance in others (e.g., the swim phase) is not maintained. Therefore, future studies
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should explore whether there are specific factors that are modified more when swimmers
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want to achieve large improvements.
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In this study the split times were collected to analyse the process of sports performance.
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In the case of the 100m events, significant changes in performance were mostly a
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consequence of improved performance in the first lap of the event (i.e., from 0 to 50m),
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while the pace of the second lap (i.e., from 50 to 100m) was no different or slightly slower
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than the previous round (Tables 2 & 3). These trends were repeated in both the semi-
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finals and finals, although they appeared to be more common in males than females,
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which would suggest that males adopted a more aggressive strategy to try to get into a
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more advanced position from the beginning of the race, while females would have
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pursued the same purpose but more gradually. In the 200m events, the results of the first
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lap were quite similar to the 100m. In general, swimming the first or second laps faster
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and holding on for the rest of the race seemed to be the norm for those progressing to the
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semi-finals and finals; however, while in the semi-finals for some strokes there was also
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an improvement in the last split of the race (i.e., from 150m to 200m), during the finals
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there was a general deterioration of performance during the last 50m lap in all strokes
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(Tables 2 & 3).
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This deterioration could be a consequence of performance fatigue and/or lactate
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accumulation when trying to perform faster in the first part of the middle-distance races
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(Cuenca-Fernández et al., 2021), supporting the hypothesis that the best swimmers may
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have tried strategies to avoid this in the previous rounds. However, it is important to
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mention that visual feedback could also play a relevant role in this performance
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impairment (Szczepan et al., 2018). For instance, the swimmers during the finals may
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choose to let it go and slow down at the end of the race if they do not see themselves
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among the medal contenders. Conversely, swimmers know that it may not be enough to
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be among all contenders during the semi-finals, but that it would also be necessary to
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achieve the fastest possible time to beat the performance times achieved in the other semi-
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final, so they may have opted to attempt an extra effort at the end of the race. In either
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case, these group values could be largely influenced by significant performance
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improvements made by a single swimmer. For example, in the men's 200m butterfly, a
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significant time drop was observed in the last 50m lap between heats and semi-finals,
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attaining a CV = 1.24% and considerable changes in performance (-0.67%). However,
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this strategy was not representative of the whole group (p = 0.07), but these results were
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strongly influenced by the astonishing performance shown by one of the swimmers (T.K.,
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HUN), who completed the last lap of the semi-final race with a difference of ∆ = -8.37%
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compared to the heats (~2.2s). Therefore, although this study describes the strategies used
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by elite swimmers to progress between rounds, it is important to note that elite sport
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performances are often composed of "outliers" and therefore trends will always be
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somewhat influenced by this.
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The second purpose of this study was to explore the competitive level of performance and
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the CV changes achieved by the finalists as a function of FINA points. Although it has
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previously been reported that faster swimmers may vary their performance less between
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competitions than slower swimmers, control their paces better, or be more likely to sustain
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effort until the end of the race (Mujika et al., 2019; Stewart & Hopkins, 2000), it was
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hypothesised that a higher CV might be more evident in faster swimmers within
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competitions. In the present study, no higher or lower CVs were found for the fastest
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swimmers (i.e., those who scored the highest FINA points) when comparing performance
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in finals and heats for the 100m races; although associations were found between FINA
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points and CV for the 200m events (r = 0.37, p = 0.003), confirmed by the association
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between FINA points and ∆% (r = -0.50, p < 0.001). Therefore, this would indicate that
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the best 200m swimmers varied their performance more, as they did not swim at their
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maximum during the heats in the middle-distance races, thus saving energy to
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progressively improve their performance throughout the following rounds. This race
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strategy may be more relevant and frequent in 200m events than in shorter distance
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events.
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The two-way ANOVA revealed that there were differences for both males and females in
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the FINA points scored in the finals during the four strokes (Table 5). Specifically, only
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the finals were considered, as this is the time when swimmers try to perform at their best,
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regardless of the different tactics chosen during heats or semi-finals. For the 100m events,
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there were no differences between strokes in FINA points, especially in females, meaning
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that the level of competition in the finals was quite similar (Figure 2). This was possibly
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a consequence of the general deterioration in performance from the semi-finals to the
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finals in butterfly, backstroke, and breaststroke (Table 1), with swimmers more focused
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on winning the event than on achieving an improvement in performance. In males,
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although only freestyle and backstroke were observed to visually outperform butterfly
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and breaststroke (p = 0.5), these results were interesting. For example, in the 100m
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breaststroke final, the current WR holder (A.P., GBR) participated with a worse
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performance than his best, possibly conditioned by a periodisation of training aimed at
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reaching the 2021 Olympic Games (Mujika et al., 2019). Thus, this race accumulated
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fewer FINA points than expected. On the other hand, the swimmer who eventually
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achieved the fastest time of the Championships during the relays (K.K., RUS: 52.00s) did
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not participate in the 100m backstroke final. Therefore, these results may not only have
382
been very different, but suggest that sometimes the winner may not be the fastest (See
383
supplemental material).
384
385
In the case of the 200m races, other particular examples were observed. For instance, in
386
the men's 200m breaststroke, the FINA points were large and higher than for the other
387
strokes; however, the inter-athlete CV for this event was quite low (Table 4), indicating
388
that the competitive level of the final was high and similar (Chatard et al., 2001), with
389
some swimmers close to WR and others with good medal chances. In the case of the
390
women's butterfly and backstroke, the FINA points appeared to be quite low for success
391
in other major championships such as the Olympic Games. In particular, in the 200m
392
butterfly swimmers were far away from the WR; however, the inter-athlete CV was also
393
low (Table 4), indicating that, at least at present, these European swimmers presented a
394
similar performance, but it is unlikely that one of them could break the 200m butterfly
395

WR anytime soon. For the 200m backstroke, the FINA points were also low but the
396
differences between athletes were high (Table 4), possibly because as competitors cannot
397
see each other and control the race leaders, this leads to different strategies being chosen
398
among them (Girold et al., 2001), and this caused some swimmers to significantly worsen
399
their performance during the final due to the lack of visual references.
400
401
It is important to mention that during a championship, some swimmers have to face
402
several events in the same session (other strokes, distances or relay events).
403
Consequently, their progression between rounds may be compromised by having little
404
rest time between high-demanding events. Obviously, this human variability could have
405
had a direct effect on the results and the CV, as swimmers with serious medal chances
406
possibly performed better during heats, but could not achieve the expected improvements
407
during the following heats. This could be argued as one of the limitations of the results
408
reported in this study, as variations in performance may not be the consequence of a
409
previously deliberate strategy. In any case, all these aspects are part of the competition
410
and give it an unpredictable character that makes it more exciting and open to a wider
411
group of competitors. An interesting approach for future studies should be to observe
412
whether swimmers were slower in the heats by choice by comparing those times with the
413
start list times obtained before this competition.
414
415
CONCLUSION
416
417
In conclusion, swimmers qualified for the 100, and 200m finals showed performance
418
variations above the 0.5% reported in previous literature, indicating that the changes
419
obtained were possibly the consequence of a tactic chosen not to excel during the heats.
420

In any case, it is not excluded that reasons other than their own choice (e.g., improper
421
warm-up, waiting time, and/or lower competitive level of the other swimmers in the heat)
422
may have influenced these results. Specifically, there was a trend for the greatest
423
performance improvements during the semi-finals, although some swimmers also made
424
significant improvements during the finals, specifically the medallists. In particular, most
425
of the performance improvements were in the first 50m lap of the races, indicating that
426
increasing the pace at the beginning and trying to maintain it until the end may have been
427
the strategy chosen by the swimmers to qualify for the next rounds. In terms of the
428
competitive level of the Championships, there were some differences in FINA points
429
between strokes, which may suggest that some events could be significantly below world
430
standards. Therefore, even with significant changes in performance, these European
431
swimmers may have little chance of qualifying for the final rounds of major
432
championships, such as the Olympic Games.
433
434
DISCLOSURE STATEMENT:
435
436
The authors have no conflicts of interest to report.
437
438
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439
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441
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Sánchez, L., Arellano, R., & Cuenca-Fernández, F. (2021). Analysis and influence of the
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10.1123/ijspp.2013-0469
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502
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503
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10.1055/s-0032-1316357
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Stewart, A. M., & Hopkins, W. G. (2000). Consistency of swimming performance within and
507
between competitions. Medicine & Science in Sports & Exercise, 32(5), 997-1001. Doi:
508
10.1097/00005768-200005000-00018
509
510
Szczepan, S., Zaton, K., Cuenca-Fernandez, F., Gay, A., & Arellano, R. (2018). The effects of
511
concurrent visual versus verbal feedback on swimming strength task execution. Baltic
512

Journal of Health and Physical Activity. The Journal of Gdansk University of Physical
513
Education and Sport, 10(4).
514
Thompson, K. (1998). Differences in blood lactate concentrations in national breaststroke
515
swimmers after heats and finals. Journal of Sports Sciences, 16(1), 63-64. Doi:
516
10.1080/026404198366957a
517
518
Thompson, K. G., MacLaren, D. P., Lees, A., & Atkinson, G. (2004). The effects of changing
519
pace on metabolism and stroke characteristics during high-speed breaststroke swimming.
520
Journal of Sports Sciences, 22(2), 149-157. Doi: 10.1080/02640410310001641467
521
522
Trewin, C. B., Hopkins, W. G., & Pyne, D. B. (2004). Relationship between world-ranking and
523
Olympic performance of swimmers. Journal of Sports Sciences, 22(4), 339-345. Doi:
524
10.1080/02640410310001641610
525
526
Chatard, J., Caudal, N., Cossor, J., & Mason, B. (2001). Specific strategy for the medallists versus
527
finalists and semi-finalists in the men's 200m breaststroke at the Sidney Olympic Games.
528
ISBS-Conference Proceedings Archive,
529
530
Cuenca-Fernández, F., Boullosa, D., Ruiz-Navarro, J. J., Gay, A., Morales-Ortíz, E., López-
531
Contreras, G., & Arellano, R. (2021). Lower fatigue and faster recovery of ultra-short race
532
pace swimming training sessions. Research in Sports Medicine, 1-14.
533
534
Foster, C., Hendrickson, K. J., Peyer, K., Reiner, B., deKoning, J. J., Lucia, A., Battista, R. A.,
535
Hettinga, F. J., Porcari, J. P., & Wright, G. (2009). Pattern of developing the performance
536
template. British Journal of Sports Medicine, 43(10), 765-769.
537
538
Fulton, S. K., Pyne, D. B., Hopkins, W. G., & Burkett, B. (2009). Variability and progression in
539
competitive performance of Paralympic swimmers. Journal of Sports Sciences, 27(5),
540
535-539.
541
542
Girold, S., Chatard, J., Cossor, J., & Mason, B. (2001). Specific strategy for the medalists versus
543
finalists and semi-finalists in the men's 200 m backstroke at the Sydney Olympic games.
544
ISBS-Conference Proceedings Archive,
545
546
Hopkins, W. G., Hawley, J. A., & Burke, L. M. (1999). Design and analysis of research on sport
547
performance enhancement. Medicine and Science in Sports and Exercise, 31(3), 472-
548
485.
549
550

Morais, J. E., Forte, P., Nevill, A. M., Barbosa, T. M., & Marinho, D. A. (2020). Upper-limb
551
kinematics and kinetics imbalances in the determinants of front-crawl swimming at
552
maximal speed in young international level swimmers. Scientific Reports, 10(1), 1-8.
553
554
Mujika, I., Villanueva, L., Welvaert, M., & Pyne, D. B. (2019). Swimming fast when it counts: A 7-
555
year analysis of Olympic and world championships performance. International Journal
556
of Sports Physiology and Performance, 14(8), 1132-1139.
557
558
Nowacka, A., & Słomiński, P. (2018). Swimming–an analysis of age and somatic profile of finalists
559
and medalists in rio de Janeiro 2016. SWIMMING VII, 84.
560
561
Pyne, D. B., Trewin, C. B., & Hopkins, W. G. (2004). Progression and variability of competitive
562
performance of Olympic swimmers. Journal of Sports Sciences, 22(7), 613-620.
563
564
Sánchez, L., Arellano, R., & Cuenca-Fernández, F. (2021). Analysis and influence of the
565
underwater phase of breaststroke on short-course 50 and 100m performance.
566
International Journal of Performance Analysis in Sport, 1-17.
567
568
Shapiro, J. R., Klein, S. L., & Morgan, R. (2021). Stop ‘controlling’for sex and gender in global
569
health research. BMJ Global Health, 6(4), e005714.
570
571
Skorski, S., Faude, O., Abbiss, C. R., Caviezel, S., Wengert, N., & Meyer, T. (2014). Influence of
572
pacing manipulation on performance of juniors in simulated 400-m swim competition.
573
International Journal of Sports Physiology and Performance, 9(5), 817-824.
574
575
Skorski, S., Faude, O., Rausch, K., & Meyer, T. (2013). Reproducibility of Pacing Profiles in
576
Competitive Swimmers. International Journal of Sports Medicine, 34(2), 152-157.
577
578
Stewart, A. M., & Hopkins, W. G. (2000). Consistency of swimming performance within and
579
between competitions. Medicine & Science in Sports & Exercise, 32(5), 997-1001.
580
https://journals.lww.com/acsm-
581
msse/Fulltext/2000/05000/Consistency_of_swimming_performance_within_and.18.as
582
px
583
584
Szczepan, S., Zaton, K., Cuenca-Fernandez, F., Gay, A., & Arellano, R. (2018). The effects of
585
concurrent visual versus verbal feedback on swimming strength task execution. Baltic
586
Journal of Health and Physical Activity. The Journal of Gdansk University of Physical
587
Education and Sport, 10(4).
588
589
Thompson, K. (1998). Differences in blood lactate concentrations in national breaststroke
590
swimmers after heats and finals. Journal of Sports Sciences, 16(1), 63-64.
591
592

Thompson, K. G., MacLaren, D. P., Lees, A., & Atkinson, G. (2004). The effects of changing pace
593
on metabolism and stroke characteristics during high-speed breaststroke swimming.
594
Journal of Sports Sciences, 22(2), 149-157.
595
596
Trewin, C. B., Hopkins, W. G., & Pyne, D. B. (2004). Relationship between world-ranking and
597
Olympic performance of swimmers. Journal of Sports Sciences, 22(4), 339-345.
598
599
TABLES AND FIGURE CAPTIONS
600
601
Table 1. Males and females’ intra-athlete coefficient of variation (CV).
602
603
Table 2. Males’ differences in the coefficient of variation (CV) and relative change in
604
performance (%∆) between race splits in 100 and 200m races.
605
606
Table 3. Females’ differences in the coefficient of variation (CV) and relative change in
607
performance (%∆) between race splits in 100 and 200m races.
608
609
Table 4. Inter-athlete coefficient of variation (CV).
610
611
Table 5. Results comparison in the FINA points between strokes.
612
613
Figure 1. The mean race times achieved for each round, distance and stroke.
614
615
Figure 2. The mean FINA points achieved for each round, distance and stroke
616
617

Table 2. Males’ differences in the coefficient of variation (CV) and relative change in performance (%∆) between race splits in 100 and 200m races.
* Only the swimmers that progressed to the final
100m
EVENTS
Split
Heats
(n = 16)
Semi-finals
(n = 16)
H-SF
Semi-finals
(n = 8)*
Final
(n = 8)
SF-F
CV
p
%∆
CV
p
%∆
Freestyle
1st 50m
23.26 ± 0.29
23.25 ± 0.26
0.41 ± 0.29
0.508
-0.05 ± 0.72
23.18 ± 0.28
23.04 ± 0.35
0.56 ± 0.39
0.017
-0.65 ± 0.73
50 to 100m
25.19 ± 0.41
25.20 ± 0.46
0.42 ± 0.27
0.508
0.05 ± 0.72
24.84 ± 0.20
24.85 ± 0.22
0.17 ± 0.10
0.811
0.03 ± 0.29
Breaststroke
1st 50m
27.78 ± 0.43
27.63 ± 0.40
0.53 ± 0.36
0.003
-0.53 ± 0.74
27.36 ± 0.36
27.30 ± 0.49
0.51 ± 0.47
0.264
-0.21 ± 1.00
50 to 100m
31.72 ± 0.37
31.72 ± 0.44
0.63 ± 0.55
0.445
-0.01 ± 1.21
31.46 ± 0.35
31.48 ± 0.42
0.35 ± 0.31
0.950
0.07 ± 0.68
Backstroke
1st 50m
26.09 ± 0.27
26.05 ± 0.42
0.81 ± 0.79
0.162
-0.18 ± 1.74
25.76 ± 0.34
25.72 ± 0.28
0.31 ± 0.25
0.291
-0.14 ± 0.57
50 to 100m
27.66 ± 0.45
27.71 ± 0.43
0.77 ± 0.92
0.781
0.15 ± 1.56
27.35 ± 0.23
27.34 ± 0.27
0.60 ± 0.30
0.387
-0.02 ± 1.01
Butterfly
1st 50m
24.15 ± 0.28
24.02 ± 0.30
0.59 ± 0.44
0.018
-0.58 ± 0.89
24.04 ± 0.30
23.88 ± 0.26
0.48 ± 0.34
0.025
-0.59 ± 0.62
50 to 100m
27.67 ± 0.49
27.64 ± 0.51
0.62 ± 0.42
0.485
-0.10 ± 1.08
27.23 ± 0.31
27.28 ± 0.50
0.55 ± 0.45
0.378
0.19 ± 1.03
200m
EVENTS
Split
Heats
(n = 16)
Semi-finals
(n = 16)
H-SF
Semi-finals
(n = 8)*
Final
(n = 8)
SF-F
CV
p
%∆
CV
p
%∆
Freestyle
1st 50m
25.48 ± 0.30
25.02 ± 0.24
0.64 ± 0.59
0.197
-0.16 ± 1.24
24.94 ± 0.28
24.69 ± 0.35
1.28 ± 1.22
0.010
-1.05 ± 2.38
50 to 100m
27.16 ± 0.27
27.09 ± 0.16
0.61 ± 0.45
0.114
-0.25 ± 1.06
27.04 ± 0.17
27.01 ± 0.41
0.92 ± 0.48
0.490
-0.13 ± 1.54
100 to 150m
27.71 ± 0.18
27.58 ± 0.26
0.68 ± 0.52
0.035
-0.47 ± 1.14
27.53 ± 0.29
27.40 ± 0.28
0.51 ± 0.36
0.048
-0.49 ± 0.76
150 to 200m
27.52 ± 0.56
27.21 ± 0.55
1.35 ± 0.93
0.010
-1.15 ± 2.08
26.81 ± 0.40
26.88 ± 0.48
1.13 ± 0.99
0.286
0.21 ± 2.21
Breaststroke
1st 50m
29.62 ± 0.43
29.60 ± 0.35
0.55 ± 0.38
0.549
-0.06 ± 0.97
29.38 ± 0.33
29.32 ± 0.30
0.32 ± 0.24
0.173
-0.19 ± 0.54
50 to 100m
29.60 ± 0.45
33.26 ± 0.39
0.78 ± 0.39
0.534
0.34 ± 1.21
33.02 ± 0.34
32.68 ± 0.37
0.73 ± 0.60
0.002
-1.04 ± 0.85
100 to 150m
33.58 ± 0.39
33.57 ± 0.58
0.96 ± 0.79
0.649
-0.05 ± 1.80
33.23 ± 0.42
33.11 ± 0.47
0.52 ± 0.54
0.155
-0.36 ± 1.04
150 to 200m
33.91 ± 0.81
33.50 ± 0.62
1.06 ± 1.02
0.004
-1.24 ± 1.73
33.09 ± 0.56
33.41 ± 0.79
0.84 ± 0.79
0.139
0.94 ± 1.32
Backstroke
1st 50m
27.83 ± 0.41
27.67 ± 0.53
0.92 ± 0.85
0.031
-0.58 ± 1.70
27.64 ± 0.44
27.55 ± 0.72
0.95 ± 0.87
0.480
-0.35 ± 1.87
50 to 100m
29.96 ± 0.55
29.77 ± 0.60
0.69 ± 0.49
0.008
-0.65 ± 1.03
29.41 ± 0.54
29.33 ± 0.50
0.91 ± 0.80
0.213
-0.28 ± 1.77
100 to 150m
30.11 ± 0.52
30.17 ± 0.59
0.59 ± 0.45
0.979
0.20 ± 1.04
29.70 ± 0.13
29.75 ± 0.38
0.74 ± 0.50
0.541
0.14 ± 1.32
150 to 200m
29.78 ± 0.50
29.94 ± 0.98
1.07 ± 1.15
0.477
0.49 ± 2.14
29.46 ± 0.19
29.98 ± 0.72
1.58 ± 1.16
0.489
1.68 ± 2.22
Butterfly
1st 50m
25.90 ± 0.41
25.81 ± 0.32
0.55 ± 0.40
0.067
-0.37 ± 0.96
25.61 ± 0.33
25.37 ± 0.39
0.66 ± 0.51
0.002
-0.94 ± 0.72
50 to 100m
29.47 ± 0.53
29.55 ± 0.37
0.81 ± 0.40
0.806
0.26 ± 1.33
29.32 ± 0.31
28.99 ± 0.44
0.97 ± 0.99
0.007
-1.14 ± 1.67
100 to 150m
30.24 ± 0.48
30.29 ± 0.20
0.87 ± 0.40
0.769
0.16 ± 1.54
30.23 ± 0.23
29.87 ± 0.59
1.22 ± 1.28
0.016
-1.24 ± 2.27
150 to 200m
30.93 ± 0.63
30.37 ± 0.77
1.24 ± 0.40
0.072
-0.67 ± 2.70
30.28 ± 0.65
30.52 ± 0.65
1.01 ± 0.62
0.305
0.79 ± 1.52

Table 3. Females’ differences in the coefficient of variation (CV) and relative change in performance (%∆) between race splits in 100 and 200m races.
* Only the swimmers that progressed to the final
100m
EVENTS
Split
Heats
(n = 16)
Semi-finals
(n = 16)
H-SF
Semi-finals
(n = 8)*
Final
(n = 8)
SF-F
CV
p
%∆
CV
p
%∆
Freestyle
1st 50m
26.24 ± 0.26
26.06 ± 0.19
0.58 ± 0.44
0.001
-0.67 ± 0.78
25.92 ± 0.14
25.81 ± 0.18
0.40 ± 0.28
0.015
-0.42 ± 0.56
50 to 100m
28.16 ± 0.19
28.14 ± 0.45
0.69 ± 0.51
0.506
-0.09 ± 1.23
27.77 ± 0.24
27.73 ± 0.31
0.30 ± 0.30
0.270
-0.15 ± 0.60
Breaststroke
1st 50m
31.64 ± 0.31
31.44 ± 0.35
0.65 ± 0.39
0.002
-0.64 ± 0.87
31.31 ± 0.28
31.22 ± 0.24
0.47 ± 0.32
0.264
-0.28 ± 0.79
50 to 100m
35.30 ± 0.45
35.19 ± 0.43
0.64 ± 0.47
0.078
-0.30 ± 1.10
34.92 ± 0.28
35.09 ± 0.34
0.54 ± 0.49
0.950
0.47 ± 0.93
Backstroke
1st 50m
29.33 ± 0.17
29.15 ± 0.36
0.63 ± 0.57
0.012
-0.60 ± 1.06
29.00 ± 0.36
28.87 ± 0.27
0.56 ± 0.31
0.060
-0.45 ± 0.82
50 to 100m
30.96 ± 0.53
30.74 ± 0.49
0.56 ± 0.43
0.001
-0.70 ± 0.72
30.43 ± 0.38
30.71 ± 0.55
0.82 ± 0.43
0.045
0.90 ± 0.97
Butterfly
1st 50m
27.20 ± 0.36
27.11 ± 0.25
0.50 ± 0.50
0.097
-0.30 ± 0.96
26.94 ± 0.22
26.81 ± 0.18
0.39 ± 0.20
0.025
-0.47 ± 0.42
50 to 100m
31.39 ± 0.42
31.16 ± 0.64
0.88 ± 0.64
0.025
-0.65 ± 1.42
30.70 ± 0.28
31.02 ± 0.42
0.97 ± 0.56
0.378
0.99 ± 1.26
200m
EVENTS
Split
Heats
(n = 16)
Semi-finals
(n = 16)
H-SF
Semi-finals
(n = 8)*
Final
(n = 8)
SF-F
CV
p
%∆
CV
p
%∆
Freestyle
1st 50m
27.98 ± 0.53
27.74 ± 0.44
0.74 ± 0.46
0.001
-0.85 ± 0.90
27.40 ± 0.30
27.31 ± 0.48
0.45 ± 0.42
0.123
-0.34 ± 0.82
50 to 100m
30.13 ± 0.35
30.01 ± 0.30
0.56 ± 0.40
0.049
-0.39 ± 0.91
29.86 ± 0.31
29.54 ± 0.46
0.75 ± 0.64
0.002
-1.07 ± 0.92
100 to 150m
30.67 ± 0.21
30.69 ± 0.32
0.44 ± 0.37
0.892
0.07 ± 0.81
30.52 ± 0.28
30.35 ± 0.28
0.51 ± 0.42
0.026
-0.53 ± 0.79
150 to 200m
30.64 ± 0.44
30.60 ± 0.66
1.22 ± 0.88
0.383
-0.16 ± 2.18
30.19 ± 0.30
30.39 ± 0.71
1.34 ± 0.63
0.001
0.61 ± 2.11
Breaststroke
1st 50m
33.46 ± 0.40
33.20 ± 0.44
0.73 ± 0.32
0.549
-0.71 ± 0.89
33.07 ± 0.36
32.80 ± 0.31
0.64 ± 0.52
0.013
-0.80 ± 0.86
50 to 100m
36.95 ± 0.50
36.78 ± 0.50
1.06 ± 0.66
0.534
-0.47 ± 1.74
36.45 ± 0.45
36.29 ± 0.53
0.68 ± 0.72
0.080
-0.44 ± 1.38
100 to 150m
37.42 ± 0.42
37.02 ± 0.42
0.88 ± 0.71
0.649
-1.09 ± 1.21
36.73 ± 0.28
36.80 ± 0.51
0.61 ± 0.39
0.824
0.18 ± 1.04
150 to 200m
37.79 ± 0.80
37.58 ± 0.77
0.85 ± 0.65
0.004
-0.57 ± 1.44
37.08 ± 0.70
37.38 ± 0.78
0.89 ± 0.43
0.164
0.78 ± 1.19
Backstroke
1st 50m
31.16 ± 0.43
31.08 ± 0.44
0.67 ± 0.49
0.211
-0.25 ± 1.17
30.95 ± 0.50
30.67 ± 0.33
0.67 ± 0.78
0.014
-0.92 ± 1.15
50 to 100m
33.21 ± 0.53
33.21 ± 0.67
0.98 ± 0.81
0.472
-0.03 ± 1.82
32.78 ± 0.48
32.56 ± 0.72
0.80 ± 0.75
0.084
-0.67 ± 1.46
100 to 150m
33.81 ± 0.48
33.81 ± 0.76
0.95 ± 0.62
0.597
-0.01± 1.64
33.19 ± 0.45
33.10 ± 0.70
0.53 ± 0.19
0.228
-0.26 ± 0.80
150 to 200m
33.63 ± 0.90
33.53 ± 1.03
1.17 ± 0.85
0.202
-0.34 ± 2.06
32.67 ± 0.54
32.75 ± 0.64
1.01 ± 0.68
0.750
0.21 ± 1.78
Butterfly
1st 50m
29.54 ± 0.46
29.52 ± 0.46
0.34 ± 0.40
0.579
-0.07 ± 0.75
29.27 ± 0.22
29.30 ± 0.30
0.38 ± 0.29
0.897
0.10 ± 0.69
50 to 100m
33.24 ± 0.50
33.34 ± 0.40
0.42 ± 0.33
0.107
0.31 ± 0.68
33.07 ± 0.19
32.96 ± 0.38
0.46 ± 0.42
0.096
-0.36 ± 0.84
100 to 150m
33.77 ± 0.60
33.80 ± 0.74
0.75 ± 0.54
0.962
0.07 ± 1.33
33.31 ± 0.39
32.20 ± 0.45
0.63 ± 0.41
0.189
-0.35 ± 1.05
150 to 200m
34.58 ± 1.33
34.18 ± 1.34
1.02 ± 0.70
0.002
-1.17 ± 1.34
33.34 ± 0.43
33.35 ± 0.58
0.71 ± 0.46
0.859
0.02 ± 1.26

Table 4. Inter-athlete coefficient of variation (CV).
EVENT
100m Races
Males
Females
Heats
Semi-finals
Final
Heats
Semi-finals
Final
Freestyle
3.6%
1.1%
0.8%
4.3%
1.1%
0.6%
Breaststroke
2.9%
1.2%
1.1%
2.5%
0.8%
0.5%
Backstroke
3.2%
1.3%
0.4%
3.3%
1.1%
1.2%
Butterfly
3.5%
0.9%
1.0%
3.4%
1.4%
0.7%
MEAN
3.3%
1.1%
0.8%
3.4%
1.1%
0.7%
EVENT
200m Races
Males
Females
Heats
Semi-finals
Final
Heats
Semi-finals
Final
Freestyle
3.1%
0.7%
1.0%
3.8%
1.1%
1.1%
Breaststroke
3.7%
1.2%
0.9%
2.4%
1.1%
1.2%
Backstroke
2.3%
1.6%
1.3%
3.2%
1.8%
1.6%
Butterfly
2.9%
1.0%
1.5%
3.7%
1.9%
0.9%
MEAN
3.0%
1.1%
1.2%
3.3%
1.5%
1.2%

Table 5. Results comparison in the FINA points between strokes.
Males
Females
Distance
Stroke
Difference [95%CI]
p
Difference [95%CI]
p
100m
Freestyle
Butterfly
34 [−7, 76]
0.187
18 [−20, 56]
1
Backstroke
7 [−34, 49]
1
-1 [−40, 37]
1
Breaststroke
34 [−8, 76]
0.195
-3 [−42, 35]
1
Breaststroke
Butterfly
0 [−41, 42]
1
21 [−17, 60]
0.81
Backstroke
-26 [−68, 15]
0.572
2 [−36, 40]
1
Freestyle
-34 [−76, 8]
0.195
3 [−35, 42]
1
Backstroke
Butterfly
26 [−15, 68]
0.553
19 [−19, 58]
1
Breaststroke
26 [−15, 68]
0.572
-2 [−40, 36]
1
Freestyle
-7 [−49, 34]
1
1 [−37, 40]
1
Butterfly
Backstroke
-26 [−68, 15]
0.553
-19 [−58, 19]
1
Breaststroke
0 [−42, 41]
1
-21 [−60, 17]
0.81
Freestyle
-34 [−76, 7]
0.187
-18 [−56, 20]
1
200m
Freestyle
Butterfly
-7 [−49, 34]
1
41 [2, 80]
0.03
Backstroke
6 [−35, 48]
1
34 [−4, 73]
0.109
Breaststroke
-52 [−95, −10]
0.007
-28 [−67, 10]
0.294
Breaststroke
Butterfly
45 [3, 87]
0.027
70 [31, 108]
<0.001
Backstroke
59 [17, 101]
0.002
63 [24, 101]
<0.001
Freestyle
52 [10, 95]
0.007
28 [−10, 67]
0.294
Backstroke
Butterfly
-13 [−55, 28]
1
6 [−31, 45]
1
Breaststroke
-59 [−101, −17]
0.002
-63 [−101, −24]
<0.001
Freestyle
-6 [−48, 35]
1
-34 [−73, 4]
0.109
Butterfly
Backstroke
13 [−28, 55]
1
-6 [−45, 31]
1
Breaststroke
-45 [−87, −3]
0.027
-70 [−108, −31]
<0.001
Freestyle
7 [−34, 49]
1
-41 [−80, −2]
0.03

Table 1. Males and females’ intra-athlete coefficient of variation (CV).

MALES
EVENT
100m Races
H-SF-F
H-SF
SF-F
CV
p
%∆
CV
p
%∆
CV
p
%∆
Freestyle
0.39 ± 0.15
0.010
-0.60 ± 0.34
0.32 ± 0.16
0.821
0.01 ± 0.51
0.28 ± 0.19
0.029
-0.29 ± 0.38
Breaststroke
0.55 ± 0.27
0.045
-0.53 ± 0.83
0.39 ± 0.26
0.053
-0.25 ± 0.62
0.38 ± 0.28
0.436
-0.05 ± 0.67
Backstroke
0.45 ± 0.14
0.307
-0.78 ± 0.20
0.53 ± 0.80
0.479
0.01 ± 1.32
0.30 ± 0.16
0.357
-0.08 ± 0.48
Butterfly
0.53 ± 0.25
0.003
-0.81 ± 0.66
0.39 ± 0.35
0.018
-0.36 ± 0.08
0.25 ± 0.25
0.203
-0.14 ± 0.48
MEAN
0.48 ± 0.21
-0.68 ± 0.55
0.41 ± 0.46
-0.15 ± 0.83
0.30 ± 0.22
-0.14 ± 0.49
EVENT
200m Races
H-SF-F
H-SF
SF-F
CV
p
%∆
CV
p
%∆
CV
p
%∆
Freestyle
0.64 ± 0.22
0.001
-1.10 ± 0.71
0.46 ± 0.21
0.001
-0.51 ± 0.49
0.48 ± 0.19
0.001
-0.34 ± 0.67
Breaststroke
0.48 ± 0.33
0.040
-0.64 ± 0.84
0.41 ± 0.34
0.104
-0.25 ± 0.72
0.23 ± 0.17
0.186
-0.15 ± 0.42
Backstroke
0.61 ± 0.31
0.207
-0.39 ± 1.16
0.49 ± 0.49
0.105
-0.28 ± 0.95
0.41 ± 0.43
0.576
0.28 ± 0.81
Butterfly
0.78 ± 0.55
0.009
-1.31 ± 0.99
0.51 ± 0.40
0.300
-0.14 ± 0.92
0.58 ± 0.78
0.026
-0.78 ± 1.12
MEAN
0.63 ± 0.36
-0.86 ± 0.96
0.47 ± 0.36
-0.30 ± 0.78
0.43 ± 0.44
-0.25 ± 0.76
FEMALES
EVENT
100m Races
H-SF-F
H-SF
SF-F
CV
p
%∆
CV
p
%∆
CV
p
%∆
Freestyle
0.60 ± 0.15
0.001
-1.10 ± 0.31
0.39 ± 0.29
0.012
-0.37 ± 0.57
0.23 ± 0.24
0.027
-0.28 ± 0.36
Breaststroke
0.41 ± 0.19
0.004
-0.54 ± 0.42
0.65 ± 0.67
0.006
-0.46 ± 0.77
0.14 ± 0.11
0.236
0.12 ± 0.22
Backstroke
0.55 ± 0.24
0.001
-0.58 ± 0.72
0.48 ± 0.30
0.001
-0.66 ± 0.43
0.38 ± 0.36
0.696
0.24 ± 0.72
Butterfly
0.45 ± 0.20
0.026
-0.26 ± 0.76
0.56 ± 0.35
0.011
-0.48 ± 0.80
0.36 ± 0.31
0.358
0.32 ± 0.63
MEAN
0.50 ± 0.20
-0.62 ± 0.63
0.52 ± 0.43
-0.49 ± 0.66
0.28 ± 0.28
0.10 ± 0.55
EVENT
200m Races
H-SF-F
H-SF
SF-F
CV
p
%∆
CV
p
%∆
CV
p
%∆
Freestyle
0.64 ± 0.25
0.002
-1.08 ± 0.70
0.45 ± 0.27
0.050
-0.31 ± 0.68
0.48 ± 0.23
0.083
-0.31 ± 0.68
Breaststroke
0.70 ± 0.28
0.001
-0.93 ± 1.02
0.50 ± 0.36
0.001
-0.70 ± 0.54
0.49 ± 0.25
0.390
-0.04 ± 0.80
Backstroke
0.74 ± 0.48
0.034
-1.09 ± 1.27
0.53 ± 0.50
0.337
-0.15 ± 1.02
0.50 ± 0.33
0.079
-0.40 ± 0.74
Butterfly
0.31 ± 0.15
0.028
-0.45 ± 0.52
0.31 ± 0.21
0.072
-0.22 ± 0.48
0.21 ± 0.14
0.197
-0.14 ± 0.35
MEAN
0.60 ± 0.34
-0.89 ± 0.92
0.45 ± 0.35
-0.35 ± 0.73
0.42 ± 0.26
-0.22 ± 0.65

BREASTSTROKE BACKSTROKE BUTTERFLY FREESTYLE
700
725
750
775
800
825
850
875
900
925
950
Heats Semi-final Final
FINA points
100m Males
700
725
750
775
800
825
850
875
900
925
950
Heats Semi-final Final
FINA points
100m Females
700
725
750
775
800
825
850
875
900
925
950
Heats Semi-final Final
FINA points
200m Females
700
725
750
775
800
825
850
875
900
925
950
Heats Semi-final Final
FINA points
200m Males
s
s
ss

BREASTSTROKE BACKSTROKE BUTTERFLY FREESTYLE
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
Heats Semi-finals Final
Race time (s)
100m Males
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
Heats Semi-finals Final
Race time (s)
100m Females
104
106
108
110
112
114
116
118
120
122
124
126
128
130
132
134
136
138
Heats Semi-finals Final
Race time (s)
200m Males
116
118
120
122
124
126
128
130
132
134
136
138
140
142
144
146
148
150
152
Heats Semi-finals Final
Race time (s)
200m Females

Males Females
52.0
52.5
53.0
53.5
54.0
54.5
55.0
55.5
56.0
Heats Semi-finals Final
Race time (s)
100m Backstroke
58.0
58.5
59.0
59.5
60.0
60.5
61.0
61.5
62.0
Heats Semi-finals Final
Race time (s)
100m Backstroke
65.0
65.5
66.0
66.5
67.0
67.5
68.0
68.5
69.0
Heats Semi-finals Final
Race time (s)
100m Breaststroke
47.0
47.5
48.0
48.5
49.0
49.5
50.0
50.5
Heats Semi-finals Final
Race time (s)
100m Freestyle
53.0
53.5
54.0
54.5
55.0
55.5
56.0
56.5
Heats Semi-finals Final
Race time (s)
100m Freestyle
ALL PARTICIPANTS SEMI-FINALISTS FINALISTS MEDALLISTS
BRONZE SILVER GOLD
ALL PARTICIPANTS SEMI-FINALISTS FINALISTS MEDALLISTS
BRONZE SILVER GOLD
49.5
50.0
50.5
51.0
51.5
52.0
52.5
53.0
53.5
Heats Semi-finals Final
Race time (s)
100m Butterfly
56.5
57.0
57.5
58.0
58.5
59.0
59.5
60.0
60.5
Heats Semi-finals Final
Race time (s)
100m Butterfly
57.0
57.5
58.0
58.5
59.0
59.5
60.0
60.5
61.0
61.5
Heats Semi-finals Final
Race time (s)
100m Breaststroke

Males Females
126
127
128
129
130
131
132
133
134
135
Heats Semi-finals Final
Race time (s)
200m Backstroke
126
127
128
129
130
131
132
133
134
Heats Semi-finals Final
Race time (s)
200m Breaststroke
141
142
143
144
145
146
147
148
149
Heats Semi-finals Final
Race time (s)
200m Breaststroke
104
105
106
107
108
109
110
111
112
Heats Semi-finals Final
Race time (s)
200m Freestyle
116
117
118
119
120
121
122
123
124
Heats Semi-finals Final
Race time (s)
200m Freestyle
ALL PARTICIPANTS SEMI-FINALISTS FINALISTS MEDALLISTS
BRONZE SILVER GOLD
ALL PARTICIPANTS SEMI-FINALISTS FINALISTS MEDALLISTS
BRONZE SILVER GOLD
110
111
112
113
114
115
116
117
118
119
Heats Semi-finals Final
Race time (s)
200m Butterfly
125
126
127
128
129
130
131
132
133
134
Heats Semi-finals Final
Race time (s)
200m Butterfly
113
114
115
116
117
118
119
120
121
122
Heats Semi-finals Final
Race time (s)
200m Backstroke

CV p∆% CV p∆% CV p∆% CV p∆% CV p∆% CV p∆%
Freestyle 0.33 0.151 -0.46 0.33 0.966 -0.01 0.3 0.145 -0.44 0.67 0.002 -1.28 0.6 0.045 -0.79 0.33 0.085 -0.48
Breaststroke 0.8 0.001 -1.46 0.67 0.010 -0.96 0.37 0.151 -0.49 0.3 0.499 -0.27 0.4 0.448 -0.28 0.07 0.955 0.01
Backstroke 0.45 0.001 -0.76 0.48 0.021 -0.68 0.2 0.620 -0.08 0.70 0.002 -1.29 0.7 0.019 -0.97 0.27 0.284 -0.31
Butterfly 0.53 0.007 -0.97 0.40 0.100 -0.58 0.27 0.180 -0.38 0.6 0.435 -0.44 0.47 0.020 -0.62 0.53 0.748 0.18
MEAN 0.53 -0.91 0.47 -0.56 0.29 -0.35 0.57 -0.82 0.54 -0.67 0.30 -0.15
CV p∆% CV p∆% CV p∆% CV p∆% CV p∆% CV p∆%
Freestyle 0.83 0.001 -1.68 0.63 0.011 -0.85 0.57 0.001 -0.82 0.87 0.001 -1.79 0.57 0.001 -0.80 0.7 0.001 -1.97
Breaststroke 0.77 0.040 -1.20 0.80 0.104 -0.65 0.37 0.186 -0.55 0.97 0.001 -1.92 0.90 0.001 -1.28 0.43 0.390 -0.63
Backstroke 0.60 0.065 -1.04 0.63 0.131 -0.90 0.17 0.475 -0.14 1.13 0.004 -2.20 0.80 0.075 -1.10 0.80 0.002 -1.08
Butterfly 1.23 0.038 -2.16 0.73 0.255 -0.87 0.93 0.213 -1.28 0.33 0.012 -0.59 0.20 0.598 -0.09 0.33 0.001 -0.49
MEAN 0.86 -1.52 0.70 -0.82 0.51 -0.70 0.83 -1.63 0.62 -0.82 0.57 -1.04
Significant (p< 0.05) improvements in performance
Non-significant (p>0.05) improvements in performance
Deterioration in performance
EVENT
200m Races
200m Races
H - SF - F
H - SF
SF - F
H - SF - F
H - SF
SF - F
EVENT
100m Races
100m Races
H - SF - F
H - SF
SF - F
H - SF - F
H - SF
SF - F
MEDALLISTS ONLY