Dataset Information

Bayesian approach to quantify morphological impact on performance in international elite freestyle swimming.

ABSTRACT: Objectives:The purpose of this study was to quantify the impact of morphological characteristics on freestyle swimming performance by event and gender. Design:Height, mass, body mass index (BMI) and speed data were collected for the top 100 international male and female swimmers from 50 to 1500?m freestyle events for the 2000-2014 seasons. Methods:Several Bayesian hierarchical regressions were performed on race speed with height, mass and BMI as predictors. Posterior probability distributions were computed using Markov chain Monte Carlo algorithms. Results:Regression results exhibited relationships between morphology and performance for both genders and all race distances. Height was always positively correlated with speed with a 95% probability. Conversely, mass plays a different role according to the context. Heavier profiles seem favourable on sprint distances, whereas mass becomes a handicap as distance increases. Male and female swimmers present several differences on the influence of morphology on speed, particularly about the mass. Best morphological profiles are associated with a gain of speed of 0.7%-3.0% for men and 1%-6% for women, depending on race distance. BMI has been investigated as a predictor of race speed but appears as weakly informative in this context. Conclusion:Morphological indicators such as height and mass strongly contribute to swimming performance from sprint to distance events, and this contribution is quantified for each race distance. These profiles may help swimming federations to detect athletes and drive them to compete in specific distances according to their morphology.

SUBMITTER: Pla R

PROVIDER: S-EPMC6830458 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Bayesian approach to quantify morphological impact on performance in international elite freestyle swimming.

Pla Robin R Leroy Arthur A Massal Romain R Bellami Maxime M Kaillani Fatima F Hellard Philippe P Toussaint Jean-François JF Sedeaud Adrien A

BMJ open sport & exercise medicine 20191023 1

<h4>Objectives</h4>The purpose of this study was to quantify the impact of morphological characteristics on freestyle swimming performance by event and gender.<h4>Design</h4>Height, mass, body mass index (BMI) and speed data were collected for the top 100 international male and female swimmers from 50 to 1500 m freestyle events for the 2000-2014 seasons.<h4>Methods</h4>Several Bayesian hierarchical regressions were performed on race speed with height, mass and BMI as predictors. Posterior probab ...[more]

PMID: 31749980

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Project description:In this paper, we present the ON score for evaluating the performance of athletes and teams that includes a season-long evaluation system, a single-game evaluation, and an evaluation of an athlete's overall contribution to their team. The approach used to calculate the ON score is based on mixed-effects regression models that take into account the hierarchical structure of the data and a principal component analysis to calculate athlete rating. We apply our methodology to a large dataset of National Basketball Association (NBA) games spanning four seasons from 2015-2016 to 2018-2019. Our model is validated using two systematic approaches, and our results demonstrate the reliability of our approach to calculate an athlete's performance. This provides coaches, General Managers and player agents with a powerful tool to gain deeper insights into their players' performance, make more informed decisions and ultimately improve team performance. Our methodology has several key advantages. First, by incorporating the hierarchical structure of the data, we can obtain valuable information about an athlete's contribution within their team. Second, the use of principal component analysis allows us to calculate a single score, the ON score, that captures the overall performance of an athlete. Third, our approach is based on classical restricted likelihood methods, which makes the calculation faster than Bayesian methods typically requiring 1000 posterior samples. With our approach, coaches and managers can evaluate athletes' performance throughout the season, compare athletes and teams over a year, and assess an athlete's performance during a single game. Our methodology can also complement other ratings and box score metrics to provide a more comprehensive assessment of an athlete's performance as our method uses the hierarchical nature of performance data (i.e. player nested within team over season) which is typically ignored in player rating systems. In summary, our methodology represents a significant contribution to the field of sports analytics and provides the foundation for future developments.

Dataset Information

Bayesian approach to quantify morphological impact on performance in international elite freestyle swimming.

Publications

Bayesian approach to quantify morphological impact on performance in international elite freestyle swimming.

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