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Relative age effects in track-and-field: Identification and performance rebalancing

Introduction: Relative Age Effect (RAE) consists of a biased distribution of the dates of birth in a same-age group. Objectives: This study aimed to investigate Relative Age Effect among French athletes in different track-and-field events, and propose a corrective adjustment method to highlight the...

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Autores principales: Difernand, Audrey, De Larochelambert, Quentin, Homo, Sébastien, Rousseau, Florian, Antero, Juliana, Toussaint, Jean-François, Sedeaud, Adrien
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879012/
https://www.ncbi.nlm.nih.gov/pubmed/36714323
http://dx.doi.org/10.3389/fphys.2022.1082174
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author Difernand, Audrey
De Larochelambert, Quentin
Homo, Sébastien
Rousseau, Florian
Antero, Juliana
Toussaint, Jean-François
Sedeaud, Adrien
author_facet Difernand, Audrey
De Larochelambert, Quentin
Homo, Sébastien
Rousseau, Florian
Antero, Juliana
Toussaint, Jean-François
Sedeaud, Adrien
author_sort Difernand, Audrey
collection PubMed
description Introduction: Relative Age Effect (RAE) consists of a biased distribution of the dates of birth in a same-age group. Objectives: This study aimed to investigate Relative Age Effect among French athletes in different track-and-field events, and propose a corrective adjustment method to highlight the true potential of an athlete with respect to his/her relative age. Methods: 358,610 performances from 2009 to 2019 of female and male athletes between 12 and 21 years old were collected. Relative age distributions of performances were analyzed by level of competitiveness (“All,” “Top50%,” “Top10%” where “all” represents all athletes, top50% and top10% represent the best 50% and 10% of athletes per age category respectively) and age category, with chi-square and odd-ratio statistics. A linear relationship between distribution of performances and age leads to a calibration coefficient allowing to rebalance the performance by considering the effect of Relative Age Effect. Validation is obtained by Wilcoxon statistical test on actual athlete data. Results: Relative Age Effect is present in all types of events. It is larger when the level of competitiveness increases. In male 100 m sprint, 1 year difference between two athletes birth date represents an average gain of 931.01 ms (6.5%) in the U13 (Under 13 years old) and 229.65 ms (1.9%) in the U17 (Under 17 years old) categories. Our validated rebalancing methods allows to compensate for the biases induced by the relative age effect. By comparing the rebalanced performance and the realised performance of each athlete, we cannot say that they are significantly different. On average, there is no significant difference between these two performances. Conclusion: This study showed that there is a relative age effect among young French athletes, with an even greater effect as the level of competition increases. Thanks to the rebalancing method that has been validated, performances can now be better appreciated according to category and event.
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spelling pubmed-98790122023-01-27 Relative age effects in track-and-field: Identification and performance rebalancing Difernand, Audrey De Larochelambert, Quentin Homo, Sébastien Rousseau, Florian Antero, Juliana Toussaint, Jean-François Sedeaud, Adrien Front Physiol Physiology Introduction: Relative Age Effect (RAE) consists of a biased distribution of the dates of birth in a same-age group. Objectives: This study aimed to investigate Relative Age Effect among French athletes in different track-and-field events, and propose a corrective adjustment method to highlight the true potential of an athlete with respect to his/her relative age. Methods: 358,610 performances from 2009 to 2019 of female and male athletes between 12 and 21 years old were collected. Relative age distributions of performances were analyzed by level of competitiveness (“All,” “Top50%,” “Top10%” where “all” represents all athletes, top50% and top10% represent the best 50% and 10% of athletes per age category respectively) and age category, with chi-square and odd-ratio statistics. A linear relationship between distribution of performances and age leads to a calibration coefficient allowing to rebalance the performance by considering the effect of Relative Age Effect. Validation is obtained by Wilcoxon statistical test on actual athlete data. Results: Relative Age Effect is present in all types of events. It is larger when the level of competitiveness increases. In male 100 m sprint, 1 year difference between two athletes birth date represents an average gain of 931.01 ms (6.5%) in the U13 (Under 13 years old) and 229.65 ms (1.9%) in the U17 (Under 17 years old) categories. Our validated rebalancing methods allows to compensate for the biases induced by the relative age effect. By comparing the rebalanced performance and the realised performance of each athlete, we cannot say that they are significantly different. On average, there is no significant difference between these two performances. Conclusion: This study showed that there is a relative age effect among young French athletes, with an even greater effect as the level of competition increases. Thanks to the rebalancing method that has been validated, performances can now be better appreciated according to category and event. Frontiers Media S.A. 2023-01-12 /pmc/articles/PMC9879012/ /pubmed/36714323 http://dx.doi.org/10.3389/fphys.2022.1082174 Text en Copyright © 2023 Difernand, De Larochelambert, Homo, Rousseau, Antero, Toussaint and Sedeaud. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Physiology
Difernand, Audrey
De Larochelambert, Quentin
Homo, Sébastien
Rousseau, Florian
Antero, Juliana
Toussaint, Jean-François
Sedeaud, Adrien
Relative age effects in track-and-field: Identification and performance rebalancing
title Relative age effects in track-and-field: Identification and performance rebalancing
title_full Relative age effects in track-and-field: Identification and performance rebalancing
title_fullStr Relative age effects in track-and-field: Identification and performance rebalancing
title_full_unstemmed Relative age effects in track-and-field: Identification and performance rebalancing
title_short Relative age effects in track-and-field: Identification and performance rebalancing
title_sort relative age effects in track-and-field: identification and performance rebalancing
topic Physiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9879012/
https://www.ncbi.nlm.nih.gov/pubmed/36714323
http://dx.doi.org/10.3389/fphys.2022.1082174
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