Modelling the Progression of Male Swimmers' Performances through Adolescence

Insufficient data on adolescent athletes is contributing to the challenges facing youth athletic development and accurate talent identification. The purpose of this study was to model the progression of male sub-elite swimmers' performances during adolescence. The performances of 446 males (12-...

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Bibliographic Details
Main Authors: Shilo J. Dormehl (Author), Samuel J. Robertson (Author), Craig A. Williams (Author)
Format: Book
Published: MDPI AG, 2016-01-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Shilo J. Dormehl  |e author 
700 1 0 |a Samuel J. Robertson  |e author 
700 1 0 |a Craig A. Williams  |e author 
245 0 0 |a Modelling the Progression of Male Swimmers' Performances through Adolescence 
260 |b MDPI AG,   |c 2016-01-01T00:00:00Z. 
500 |a 2075-4663 
500 |a 10.3390/sports4010002 
520 |a Insufficient data on adolescent athletes is contributing to the challenges facing youth athletic development and accurate talent identification. The purpose of this study was to model the progression of male sub-elite swimmers' performances during adolescence. The performances of 446 males (12-19 year olds) competing in seven individual events (50, 100, 200 m freestyle, 100 m backstroke, breaststroke, butterfly, 200 m individual medley) over an eight-year period at an annual international schools swimming championship, run under FINA regulations were collected. Quadratic functions for each event were determined using mixed linear models. Thresholds of peak performance were achieved between the ages of 18.5 ± 0.1 (50 m freestyle and 200 m individual medley) and 19.8 ± 0.1 (100 m butterfly) years. The slowest rate of improvement was observed in the 200 m individual medley (20.7%) and the highest in the 100 m butterfly (26.2%). Butterfly does however appear to be one of the last strokes in which males specialise. The models may be useful as talent identification tools, as they predict the age at which an average sub-elite swimmer could potentially peak. The expected rate of improvement could serve as a tool in which to monitor and evaluate benchmarks. 
546 |a EN 
690 |a adolescent 
690 |a specialisation 
690 |a quadratic functions 
690 |a talent-identification 
690 |a sub-elite 
690 |a Sports 
690 |a GV557-1198.995 
655 7 |a article  |2 local 
786 0 |n Sports, Vol 4, Iss 1, p 2 (2016) 
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787 0 |n https://doaj.org/toc/2075-4663 
856 4 1 |u https://doaj.org/article/f39b7d9b5f174b32a6fa01d45b85956c  |z Connect to this object online.