PT  - JOURNAL ARTICLE
AU  - Robin Pla
AU  - Arthur Leroy
AU  - Romain Massal
AU  - Maxime Bellami
AU  - Fatima Kaillani
AU  - Philippe Hellard
AU  - Jean-François Toussaint
AU  - Adrien Sedeaud
TI  - Bayesian approach to quantify morphological impact on performance in international elite freestyle swimming
AID  - 10.1136/bmjsem-2019-000543
DP  - 2019 Oct 01
TA  - BMJ Open Sport & Exercise Medicine
PG  - e000543
VI  - 5
IP  - 1
4099  - http://bmjopensem.bmj.com/content/5/1/e000543.short
4100  - http://bmjopensem.bmj.com/content/5/1/e000543.full
SO  - BMJ OPEN SP EX MED2019 Oct 01; 5
AB  - 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.