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J Sports Sci. 2019 May;37(10):1162-1167. doi: 10.1080/02640414.2018.1546547. Epub 2018 Nov 15.

Key somatic variables in young backstroke swimmers.

Author information

1
a Research Unit (UR17JS01) Sport Performance, Health & Society», Higher Institute of Sport and Physical Education of Ksar Saîd , University of "La Manouba" , La Manouba , Tunisia.
2
b Higher Institute of Sports and Physical Education , Manouba University , La Manouba , Tunisia.
3
c Faculty of Education , Health, and Wellbeing, University of Wolverhampton , Wolverhampton WV1 1LY , UK.
4
d Division of Training and Movement Sciences , Research Focus Cognition Sciences, University of Potsdam , Potsdam , Germany.
5
e High Institute of Sports and Physical Education, Kef , University of Jendouba , Tunisia.

Abstract

The purpose of this study was to estimate the optimal body size, limb-segment length, girth or breadth ratios for 100-m backstroke mean speed performance in young swimmers. Sixty-three young swimmers (boys [n = 30; age: 13.98 ± 0.58 years]; girls [n = 33; age: 13.02 ± 1.20 years]) participated in this study. To identify the optimal body size and body composition components associated with 100-m backstroke speed performance, we adopted a multiplicative allometric log-linear regression model, which was refined using backward elimination. The multiplicative allometric model exploring the association between 100-m backstroke mean speed performance and the different somatic measurements estimated that biological age, sitting height, leg length for the lower-limbs, and two girths (forearm and arm relaxed girth) are the key predictors. Stature and body mass did not contribute to the model, suggesting that the advantage of longer levers was limb-specific rather than a general whole-body advantage. In fact, it is only by adopting multiplicative allometric models that the abovementioned ratios could have been derived. These findings highlighted the importance of considering somatic characteristics of young backstroke swimmers and can help swimming coaches to classify their swimmers and enable them to suggest what might be the swimmers' most appropriate stroke (talent identification).

KEYWORDS:

Allometric models; anthropometric measures; backstroke swimming; gender; talent identification

PMID:
30430909
DOI:
10.1080/02640414.2018.1546547
[Indexed for MEDLINE]

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