Modelling of performance prediction by analysis of elite swimmers’ anthropometry, peak performance age and age-related performance progression

In this study, anthropometry, age-related performance progression and peak performance age (PPA) in elite swimmers were analysed to develop a model to predict peak performance. The best seasonal performances of the world's all-time top 20 male and female swimmers in 5 strokes/styles (FS: freestyle; BK: backstroke; BT: breaststroke; BF: butterfly; and MD: medley) and 17 individual events were considered. An event- and sex-specific model using dynamic panel data methods was used to calculate and present 95% confidence bands to formulate performance trends. We also analysed the historical changes in PPA, height and body mass by dividing these 20 top swimmers into two groups based on their YOB: former (n = 10) and recent (n = 10) swimmers. The height of male FS swimmers was significantly greater than that of BF and MD swimmers, and BK swimmers was greater than that of MD swimmers, and among females, height of MD swimmers was significantly smaller than that of FS, BK and BF swimmers. The PPA of BT swimmers was significantly higher than that of FS, BK and BF swimmers in males, and BF swimmers was significantly higher than that of MD swimmers in females. Both male and female more recent swimmers were shorter, lighter and, in particular, younger than their former counterparts in most events. Performance over the preceding 1 year in all events and 2 years in men's 50m BT and women's 100m BK, 100m BT, 200m BT and 200m BF, and weight in 100m BK were important for predicting future performance. Our models provide coaches with a practical tool for predicting PPA, performance records and appropriate benchmarks at different ages, which can be useful for talent identification, goal setting and evaluation of performance progression.

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Publication Details

Journal
PLoS ONE
Published
2025-09-17
DOI
https://doi.org/10.1371/journal.pone.0332306
Citations
1
Primary Topic
Sports Performance and Training
Type
article
Field-Weighted Citation Impact
1.72
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article

Modelling of performance prediction by analysis of elite swimmers’ anthropometry, peak performance age and age-related performance progression

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PLoS ONE
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article

Modelling of performance prediction by analysis of elite swimmers’ anthropometry, peak performance age and age-related performance progression

Mina Khantan, Tommy R. Lundberg, Omid Khademnoe, Ali Gorzi, Amir Nazari Mehrabi, Hamoon Imani
article en
1 citations

Abstract

In this study, anthropometry, age-related performance progression and peak performance age (PPA) in elite swimmers were analysed to develop a model to predict peak performance. The best seasonal performances of the world's all-time top 20 male and female swimmers in 5 strokes/styles (FS: freestyle; BK: backstroke; BT: breaststroke; BF: butterfly; and MD: medley) and 17 individual events were considered. An event- and sex-specific model using dynamic panel data methods was used to calculate and present 95% confidence bands to formulate performance trends. We also analysed the historical changes in PPA, height and body mass by dividing these 20 top swimmers into two groups based on their YOB: former (n = 10) and recent (n = 10) swimmers. The height of male FS swimmers was significantly greater than that of BF and MD swimmers, and BK swimmers was greater than that of MD swimmers, and among females, height of MD swimmers was significantly smaller than that of FS, BK and BF swimmers. The PPA of BT swimmers was significantly higher than that of FS, BK and BF swimmers in males, and BF swimmers was significantly higher than that of MD swimmers in females. Both male and female more recent swimmers were shorter, lighter and, in particular, younger than their former counterparts in most events. Performance over the preceding 1 year in all events and 2 years in men's 50m BT and women's 100m BK, 100m BT, 200m BT and 200m BF, and weight in 100m BK were important for predicting future performance. Our models provide coaches with a practical tool for predicting PPA, performance records and appropriate benchmarks at different ages, which can be useful for talent identification, goal setting and evaluation of performance progression.

PLoS ONEVol. 20(9)
Karolinska University Hospital (SE), Karolinska Institutet (SE), Shahid Beheshti University (IR), University of Zanjan (IR)
Openalex Percentile: Top 14%
Sports Performance and Training
1.72
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