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Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers

The aim of this study was 1) to validate the 0.5 body-mass exponent for maximal. oxygen uptake [Formula: see text] as the optimal predictor of performance in a 15 km classical-technique skiing competition among elite male cross-country skiers and 2) to evaluate the influence of distance covered on t...

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Autores principales: Carlsson, Tomas, Carlsson, Magnus, Hammarström, Daniel, Rønnestad, Bent R, Malm, Christer B, Tonkonogi, Michail
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4689292/
https://www.ncbi.nlm.nih.gov/pubmed/26719730
http://dx.doi.org/10.2147/OAJSM.S93174
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author Carlsson, Tomas
Carlsson, Magnus
Hammarström, Daniel
Rønnestad, Bent R
Malm, Christer B
Tonkonogi, Michail
author_facet Carlsson, Tomas
Carlsson, Magnus
Hammarström, Daniel
Rønnestad, Bent R
Malm, Christer B
Tonkonogi, Michail
author_sort Carlsson, Tomas
collection PubMed
description The aim of this study was 1) to validate the 0.5 body-mass exponent for maximal. oxygen uptake [Formula: see text] as the optimal predictor of performance in a 15 km classical-technique skiing competition among elite male cross-country skiers and 2) to evaluate the influence of distance covered on the body-mass exponent for [Formula: see text] among elite male skiers. Twenty-four elite male skiers (age: 21.4±3.3 years [mean ± standard deviation]) completed an incremental treadmill roller-skiing test to determine their [Formula: see text]. Performance data were collected from a 15 km classical-technique cross-country skiing competition performed on a 5 km course. Power-function modeling (ie, an allometric scaling approach) was used to establish the optimal body-mass exponent for [Formula: see text] to predict the skiing performance. The optimal power-function models were found to be [Formula: see text] and [Formula: see text] , which explained 69% and 81% of the variance in skiing speed, respectively. All the variables contributed to the models. Based on the validation results, it may be recommended that [Formula: see text] divided by the square root of body mass (mL · min(−1) · kg(−0.5)) should be used when elite male skiers’ performance capability in 15 km classical-technique races is evaluated. Moreover, the body-mass exponent for [Formula: see text] was demonstrated to be influenced by the distance covered, indicating that heavier skiers have a more pronounced positive pacing profile (ie, race speed gradually decreasing throughout the race) compared to that of lighter skiers.
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spelling pubmed-46892922015-12-30 Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers Carlsson, Tomas Carlsson, Magnus Hammarström, Daniel Rønnestad, Bent R Malm, Christer B Tonkonogi, Michail Open Access J Sports Med Original Research The aim of this study was 1) to validate the 0.5 body-mass exponent for maximal. oxygen uptake [Formula: see text] as the optimal predictor of performance in a 15 km classical-technique skiing competition among elite male cross-country skiers and 2) to evaluate the influence of distance covered on the body-mass exponent for [Formula: see text] among elite male skiers. Twenty-four elite male skiers (age: 21.4±3.3 years [mean ± standard deviation]) completed an incremental treadmill roller-skiing test to determine their [Formula: see text]. Performance data were collected from a 15 km classical-technique cross-country skiing competition performed on a 5 km course. Power-function modeling (ie, an allometric scaling approach) was used to establish the optimal body-mass exponent for [Formula: see text] to predict the skiing performance. The optimal power-function models were found to be [Formula: see text] and [Formula: see text] , which explained 69% and 81% of the variance in skiing speed, respectively. All the variables contributed to the models. Based on the validation results, it may be recommended that [Formula: see text] divided by the square root of body mass (mL · min(−1) · kg(−0.5)) should be used when elite male skiers’ performance capability in 15 km classical-technique races is evaluated. Moreover, the body-mass exponent for [Formula: see text] was demonstrated to be influenced by the distance covered, indicating that heavier skiers have a more pronounced positive pacing profile (ie, race speed gradually decreasing throughout the race) compared to that of lighter skiers. Dove Medical Press 2015-12-16 /pmc/articles/PMC4689292/ /pubmed/26719730 http://dx.doi.org/10.2147/OAJSM.S93174 Text en © 2015 Carlsson et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Carlsson, Tomas
Carlsson, Magnus
Hammarström, Daniel
Rønnestad, Bent R
Malm, Christer B
Tonkonogi, Michail
Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers
title Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers
title_full Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers
title_fullStr Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers
title_full_unstemmed Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers
title_short Optimal [Formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers
title_sort optimal [formula: see text] ratio for predicting 15 km performance among elite male cross-country skiers
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4689292/
https://www.ncbi.nlm.nih.gov/pubmed/26719730
http://dx.doi.org/10.2147/OAJSM.S93174
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