The main purpose of this study is to determine the order of swimmers in mixed relay teams to ensure optimal performance at the FINA World Championships in Kazan (Russia, 2015), Budapest (Hungary, 2017) and Gwangju (South). Korea, 2019). Data taken from the official 4 × 100 m freestyle and 4 × 100 m medley results database at Site 1, including 660 entries from 188 final events and 472 preliminary events. The results showed that the fastest swimmers (according to the best results of the season) took primarily first or second place in the freestyle relay. The most successful gender strategy in the 4x100m freestyle relays (57 of 82 observations) and 4x100m medley relays (29 of 83 observations) was male-male-female-female, although no statistics were available. found in the medley relay (p = 0.79). In the 4x100m freestyle, the second (p = 0.002; β = 1.62) and third (p = 0.003; β = 1.41) legs of the relay had a statistical impact on the total relay time, while in the 4x100m medley, all the four relay legs had a statistical effect on final performance (p < 0.001), and the weight of the four poles in the preliminary round was different from the weight in the final round. In addition, the later position of the first swimmer or the sequential position of two swimmers in a team order significantly affects the performance of the relay in a particular event. Mixed relays appear to present special strategies compared to traditional all-male or all-female relay squads.
Swimming’s international governing body (FINA) has added two new relay events to the 2015 World Championships: the 4x100m freestyle and the 4x100m medley. In these mixed competitions, each team consists of two men and two women, arranged in a free order. One of the new events, the 4x100m medley relay, will also be included in the Tokyo 2021 Olympic Games. Thus, relays account for almost a quarter of the total number of Olympic swimming events. World Championships or Olympic Games.
To date, swimming relay research has focused primarily on (1) the composition of men’s and women’s relay teams and (2) differences between individual and relay performance. Relay team order is the order in which swimmers are positioned on a relay team (McGibbon et al., 2018). International relay races use different strategies depending on the swimming ability of the team members and the performance level of the four swimmers (McGibbon et al., 2018; Fischer et al., 2019). Teams typically place the two fastest swimmers on the first and fourth legs of the relay and the two slowest swimmers on the second and third legs, although there are men’s and women’s relay medalists, as well as medalists and non-medalists (McGibbon et al., 2017). , 2018). For example, teams that are successful in the 4x200m freestyle relay at the FINA World Aquatics Championships typically leave their best swimmer for the fourth leg of the relay. The order in which a relay team is formed also affects a swimmer’s pacing strategy during the relay leg. For example, swimmers in the second to fourth legs of a relay event tend to use fast starting laps and a positive pace more often than lead swimmers in the 4 × 200 m freestyle final (McGibbon et al., 2020).
Team swim relay results do not appear to show significant improvement in timing compared to individual swim times. Skoski et al. (2016), when comparing individual and relay results in the same race, found that relay swimmers did not swim faster than the individual race results in the first leg of the race. Due to different starting rules in relays, only swimmers placed second through fourth in the relay appeared to benefit from a shorter start. However, this may depend on the current state of the competition, and the likelihood of team success may increase the swimmer’s motivation to achieve a team result. In fact, Hüffmeier et al. (2012) observed that relay performance improved when a swimmer made a significant contribution to the team’s performance (i.e., was positioned later in the relay) or when the team had a good chance of winning a medal. These strategies, based on an individual swimmer’s ability and expected race position, can have practical implications in relay races and make the difference between winning and losing (Ward-Smith and Radford, 2020).
With the inclusion of mixed relays in competitive swimming, tactical options for team strategies have become more extensive, as coaches must consider not only individual swimming abilities, but also other psychological (Diener et al., 2015), morphological (Zamparo, 2006) Barbosa et al. , 2010) or biomechanical (Pelayo et al., 1996) characteristics of female and male athletes. Although the average gap between men’s and women’s swimming world records is about 8%, female swimmers tend to have smaller tempo changes (Veiga et al., 2019) or rely more on stroke tempo to swim faster (Pelayo et al. ., 1996). ) (Thibault et al., 2010; Millard-Stafford et al., 2018). This means that in mixed relays the gap in the middle can be larger than in either men’s or women’s only events, depending on the gender of the swimmers in each relay lineup. Thus, a mixed relay team’s strategy will be influenced not only by expected individual swimming ability, but also by expected performance in individual races.
Despite these complex race strategies, no previous research has described or examined how mixed relay teams are structured or how they should be structured to achieve greater success. Additionally, the lack of scientific research examining relay events has been highlighted (Fischer et al., 2019). Therefore, the main purpose of this manuscript is to describe the composition of the relay team in the mixed relay at the World Championships in order to determine the optimal composition for the final performance. It is expected that the final relay time will be influenced by the position of the female athletes, with the final time of a relay team consisting of male athletes being faster in the first leg.
To evaluate the association between relay team composition and gender, previous ranking, and stroke, we conducted an observational retrospective study in accordance with the Declaration of Helsinki. Therefore, we obtain historical data from a database website to obtain official results (www.swimrankings.net). The local university ethics committee approved the study on November 30, 2016, and informed consent was not required because the data were based on publicly available sources. Data taken from the 4x100m freestyle relay and 4x100m medley relay at the FINA World Swimming Championships in Kazan (Russia 2015), Budapest (Hungary 2017) and Gwangju (South Korea 2019). The database contains 660 records, including records for 188 final and 472 preliminary records. Each entry contains the following variables: total relay time, round (final or preliminary), order of relay teams (first to fourth), gender, 4x100m relay (medley or freestyle), swimmer’s best time of the season in the 100m, and every entry. Swimmer’s 100m relay race.
Statistical analysis was performed using R software (v.3.6.1 for Windows). Descriptive statistics (means and coefficients of variance) were calculated for all variables included in this study. The first analysis was conducted to determine the relationship between relay team order (first to fourth relay legs) and swimmers’ best performance in the season. To do this, we calculated Cramer’s V coefficient using a comprehensive table. Next, to determine the most successful strategy in terms of relay team composition, a one-way ANOVA was conducted by gender in the 4x100m freestyle and medley relays. Confidence intervals for the mean time for each type of team composition were also calculated and graphically presented.
Subsequently, several general linear models were built for each event. In each model, the goal is to explain the target variable (total relay time) from a set of independent variables, including the time of each leg of the relay, the position of the first swimmer (first F), and continuous variables. This is a dichotomous variable that takes the value 1 when the positions of two women in a relay race are consecutive, and the value 0 when the positions of two women in a relay race are discontinuous. Relative to the variable first F, which represents the position of the first swimmer on the team (value 1, 2 or 3). Both variables are used to determine the team relay order for two consecutive women [woman (F); man (M); female-female-male-male (FFMM), male-female-female-male (MFFM)). or Male-Male-Female-Female (MMFF)] or how the position of the first female swimmer can affect the outcome of the entire relay. R2 coefficients were calculated along with global significance tests to evaluate these models. This is done to determine whether the variables included in the model have a significant effect on each target variable. The beta coefficient (β) measures how much the outcome variable changes for every unit change in the predictor variable. If the beta coefficient is positive, the interpretation is that for every unit increase in the predictor variable, the outcome variable increases by the value of the beta coefficient. If the beta coefficient is negative, the interpretation is that for every unit increase in the predictor variable, the outcome variable decreases by the value of the beta coefficient. The independent variables are assessed one by one and are generally considered significant when the p-value is less than 5% in a linear regression model. Model assumptions of normality and homoscedasticity were tested using the Kolmogorov-Smirnov test and residual plots, respectively. All the remains showed a satisfactory picture.
Judging by the composition of the mixed 4x100m freestyle relay teams at the European Championships and the 2015 World Swimming Championships, a swimmer’s best individual season result is closely related to his position in the relay leg. As shown in Figure 1, the fastest swimmers were predominantly (96%) in the first or second leg of the relay, while the slowest swimmers were predominantly (89%) in the third or fourth leg of the relay. This happened in all rounds (Total V Cramer: 0.50, Preliminary V Cramer: 0.46), but especially in the final (V Cramer: 0.59).
Figure 1. Team composition in the mixed 4x100m freestyle relay at the 50m World Swimming Championships in 2015, 2017 and 2019. according to the best results of the individual season (1-4, from fast to slow) and the order of stages (from first to fourth)). M: man, F: woman.
According to one-way ANOVA, the most common gender strategy in the 4x100m freestyle relay and medley relay was male-male-female-female (57 of 82 in the freestyle and 29 of 83 in the medley relay, respectively). This male-male-female relay combination produced the best overall relay time in the 4x100m freestyle medley relay (p < 0.001), while no statistical difference was found in the 4x100m freestyle medley relay (p = 0.79 ) (Fig. 2). In the latter case, according to the final time, the best relay combination is female-male-female-male, corresponding to the sequence of backstroke-breaststroke-butterfly-freestyle (237.47±16.14 s). The coefficient of variation (CV) of the relay results showed that not only were the female swimmers’ performances better than the male swimmers, but that they were also higher in the preliminaries compared to the finals (CV 6.17% vs. 1.39% for men, CV is 8.38% for men, CV for men is 1.39%). In the finals and preliminary matches, 1.46% were female players respectively).
Figure 2. Times of teams of different genders in the 4 × 100 m freestyle (top) and 4 × 100 m medley relays (bottom) in 2015, 2017 and 2019. (mean ± 95% confidence interval) Previous World 50m Swimming Championships. M: man, F: woman.
Regression analysis showed that in the mixed 4×100 m freestyle competition (Table 1), the second and third stages of the relay had a statistical effect on the total relay time, and the influence of the second stage was stronger than the third stage (first: p < 0.001, second: p <0.05). Additionally, the position of the first swimmer had a statistical effect on team order (p < 0.001), indicating that overall relay times were better when women swam in delayed order. Quasi-collinearity problems prevented the efficient estimation of regression model parameters for the mixed 4 × 100 m freestyle preliminary or final competition.
Table 1. Linear regression model for the mixed 4 × 100 m freestyle relay at the 50 m World Aquatics Championships in 2015, 2017 and 2019.
In the 4×100 m medley race, all four stages of the relay had a statistical impact on the total relay time (Table 2). However, the freestyle had the biggest impact on the overall relay time in the heats, and the breaststroke had the biggest impact on the finals. In this event, the position of the first athlete and the successive positions of the two athletes in the relay order have a greater influence on the final, but have little influence on the preliminary competition.
Table 2 Linear regression model for the 4x100m mixed medley relay at the 50m World Aquatics Championships in 2015, 2017 and 2019.
The purpose of this study was to determine the most successful order of team members in a mixed relay based on their best swimming performance and gender. Previous studies have examined differences in performance and pacing between individual and relay swimming events, but no available work provides insight into how teams should be composed for mixed relay teams, although these are new to the Olympic, World and European Championship design.
After comparing full FINA 50m pool mixed relay events (since 2015), the main findings of this study show that there are no significant differences between gender strategic positions in the medley relay, but there are significant differences in the mixed relay. differences between the sexes. For the freestyle relay, the most suitable combination among the teams analyzed was male-male-female-female. Traditionally, teams tend to place their fastest swimmers on the first and last legs of the relay (McGibbon et al., 2018), and in mixed freestyle relays this will be the male swimmers on the first and fourth legs of the relay. However, our data shows that the gender variable appears to change team sequencing strategy (at least in freestyle) as it appears to give the team more leverage when the two fastest (male) swimmers have an advantage in the first two stages of the relay. In fact, we found a strong relationship between individual swimming ability (season best) and relay order, with half of the participating teams ranking their swimmers from fastest to slowest (Figure 1). Previous data from the 4x100m track and field relay also showed that the best overall time was achieved by the team that placed the fastest athlete in the first leg and the two slowest athletes in the last two legs of the relay (Ward-Smith and Radford, 2020)). Likewise, the Australian swimming team recorded the fastest time in the world in 2019 in the 4×100 freestyle coed (see footnote 1). This strategy allows the team to secure a lead large enough in the early stages of the race to allow the slowest athlete to maintain the lead (McGibbon et al., 2018). However, little evidence has been found in the literature regarding relay team sequencing, and decisions may be based on coach experience and swimmer performance. For example, in 2017, the United States set a world record for the mixed 4x100m freestyle in the order men-women-men-women. In the medley relay, although there was no statistical difference, teams that relayed in the following order: women’s (backstroke), men’s (breaststroke), women’s (butterfly) and men’s (freestyle) had the fastest times. This will provide the team with male breaststroke swimmers and, according to World Swimming Records (Thibault et al., 2010), not only will the gender gap be larger (11.31%) but also the percentage of time contributed in the individual medley events (Saavedra et al., 2012). Of course, judging by the overall results, the spread of relay times in the preliminary competitions was greater than in the finals. It is clear that the teams are selecting their fastest lineups for the finals and may have retained some of their fastest swimmers for the heats. Within a race, the typical improvement for the same swimmer from prelims to finals can be about 1.2% (Pyne et al., 2004), which is much less than the variance in relay times found in the current study. Additionally, in relays the differences were greater for women compared to men, which may indicate that the reserve teams were more female-dominated in the races, or even that there was a greater range of performance among the women’s teams.
Regression analysis in this study showed that in the freestyle medley relay, performance in the second and third legs of the relay (theoretically the slowest) has a statistical impact on the final relay performance. Each additional second on the second or third leg of the relay reduces the total relay time by 1.62 or 1.42 seconds, respectively. This is a valuable finding because the fastest swimmers tend to be on the first leg of the relay, and it suggests that the range of performance within relay teams should be narrower (McGibbon et al., 2018). Additionally, the position of the first swimmer greatly influences the overall relay time: relay times are better for teams that place their swimmer on the last leg of the relay. This may be explained by the fact that female athletes are more likely to be ambitious than male athletes during competition (Diener et al., 2015), suggesting that female athletes are in a position of delayed race (i.e., if they are placed for the first stage of the relay). poor male swimmer) compared to a female swimmer occupying a leading position (i.e. when entering the third or fourth leg of the relay after a male swimmer). In addition, previous research has pointed out the importance of current race position (and thus the chance of winning the relay) on the additional effort a swimmer expends to swim faster (Hüffmeier et al., 2012). As noted in previous studies of relay team strategies, strategies that place female swimmers in the final segment of the freestyle medley relay can provide significant time gains (Ward-Smith and Radford, 2020).
In the medley relay, all four relay legs (backstroke, breaststroke, butterfly and freestyle) had a statistical impact on the overall relay time. However, controversies arose depending on the preliminary or finals. In the race, the floor leg had the greatest impact on the relay time (each additional second of the floor leg increased the total relay time by 1.05 seconds), while the influence of the women’s position on the team order was not detected. However, in the final, the breaststroke had the biggest impact on the relay time, and the women’s first place finish also contributed to the overall result. Each additional second of breaststroke increases the overall race time by 1.23 seconds, and conversely, each time the first athlete is delayed by one position, the race time decreases by 0.73 seconds. Changes in performance from preliminary to final performance in a given competition do not appear to be affected by changes in fitness or technique and can therefore be explained by tempo or tactical decisions (Pyne et al., 2004). In heats, relay teams compete for the last place (not for the last time) as their goal is to reach the final round (eight fastest teams, regardless of finishing time), so in the final leg of the relay (freestyle) it is important to touch the finish wall before your opponent. This is similar to the importance of the last race in mass start rules, where athletes compete for the final position rather than time (Rodriguez and Veiga, 2018; Menting et al., 2019). However, in the final, in addition to competing for the best place, teams may also compete for the best time (Abbiss and Laursen, 2008), so the slowest leg (breaststroke) is critical to relay performance. At the same time, swimmers who entered the final stage of the relay can demonstrate a decisive advantage in the last seconds (Table 2). Previous data from individual medley swimming (Saavedra et al., 2012) showed that men spend less time swimming breaststroke than women, so this may explain why the relay leg is critical to individual medley relay performance.
In addition to the order of the relay team, the sequential (or inconsistent) position of the swimmers on the relay team also has a statistical impact on the final laps of the medley relay (Table 2). This sequential ranking can have a significant impact on changeover timing as it is an important factor in relay team performance (Skorski et al., 2016). Transition time includes the period from the moment the new swimmer touches the wall until the next swimmer leaves the starting area. In a mixed relay race, male swimmers approach much faster than female swimmers and vice versa (Ribeiro et al., 2019). When the women’s and men’s positions are not sequential in the relay order, it may be more difficult for the outgoing swimmer to time his start. In fact, the timing of the starting movement depends on the gender of the incoming swimmer. This is especially important for mixed relays, as transition time is more important to the final performance in women’s relays than in men’s relays (Saavedra et al., 2014). However, further research is needed to confirm this hypothesis.
This study analyzed a limited number of events. This is due to FINA’s recent inclusion of these competitions in various competitions. The upcoming Olympics in Japan will increase the amount of data available on world-class mixed relays.
Based on results observed at the European and World Aquatics Championships, freestyle and mixed medley relays appear to require distinct strategies compared to traditional men’s or women’s relays. Successful teams often place their fastest swimmers on the first leg of the relay, especially in freestyle relays where the male swimmers are ahead of the female swimmers in the relay line-up. This strategy allows swimmers to lead the race, which has a significant impact on the overall outcome of the relay. Moreover, the overall success of a medley relay team appears to be more dependent on the slowest leg (i.e. the breaststroke leg of the medley relay), particularly in the finals, suggesting that the range of performance within a relay team should be the narrowest. . It is only in races, when teams are trying to determine their place in the final, that the ability of the last team member (in the freestyle relay stage) to touch the finish wall before his opponents is critical to the performance of the relay.
During the FINA World Championships, teams competing in the mixed freestyle relays are usually ranked from fastest (first leg of the relay) to slowest (fourth leg of the relay) swimmers. This suggests that the most common gender strategy is the male-male-female relay, which appears to provide a statistical advantage in terms of overall performance. The second and third legs of the freestyle relay had a statistical impact on the final performance time, and the swimmer’s later position also provided a significant time gain. In the mixed medley relay, there was no advantage in the final time based on typical lineups, but a statistical effect was recorded in the women’s first place, indicating a later placing compared to the men. Additionally, performance in the freestyle relay during the prelims and performance in the breaststroke during the finals had a statistical impact on the relay results. These results provide coaches with key information specific to mixed relay strategies that can make the difference between winning and losing.
This study analyzed publicly available datasets. This data can be found at: https://www.swimrankings.net.
The studies involving human participants were reviewed and approved by the Ethics Committee of the University of Castilla La Mancha. In accordance with national legislation and institutional requirements, written informed consent was not required for this study.
LR and SV contributed to the conception and design of the study. AT and JS organize the database. JC, JG-R, and SV performed the statistical analyses. SV and JG-R wrote the first draft of the manuscript. All authors contributed to the revision of the manuscript and read and approved the submitted version.
This work was funded by a group grant from the University of Castilla-La Mancha and co-funded by the European Union through the European Regional Development Fund (project number: 2020-GRIN-28718). Research group: Grupo de Investigación Rendimiento Deportivo (GIRD).
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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