Cargando…

Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon

Cut-off points and performance-related tools are needed for the development of the Olympic distance triathlon. The purposes of the present study were (i) to determine cut-off values to reach the top three positions in an Olympic distance triathlon; (ii) to identify which discipline present the highe...

Descripción completa

Detalles Bibliográficos
Autores principales: Gadelha, André Bonadias, Sousa, Caio Victor, Sales, Marcelo Magalhaes, dos Santos Rosa, Thiago, Flothmann, Marti, Barbosa, Lucas Pinheiro, da Silva Aguiar, Samuel, Olher, Rafael Reis, Villiger, Elias, Nikolaidis, Pantelis Theodoros, Rosemann, Thomas, Hill, Lee, Knechtle, Beat
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766989/
https://www.ncbi.nlm.nih.gov/pubmed/33352924
http://dx.doi.org/10.3390/ijerph17249491
_version_ 1783628850765234176
author Gadelha, André Bonadias
Sousa, Caio Victor
Sales, Marcelo Magalhaes
dos Santos Rosa, Thiago
Flothmann, Marti
Barbosa, Lucas Pinheiro
da Silva Aguiar, Samuel
Olher, Rafael Reis
Villiger, Elias
Nikolaidis, Pantelis Theodoros
Rosemann, Thomas
Hill, Lee
Knechtle, Beat
author_facet Gadelha, André Bonadias
Sousa, Caio Victor
Sales, Marcelo Magalhaes
dos Santos Rosa, Thiago
Flothmann, Marti
Barbosa, Lucas Pinheiro
da Silva Aguiar, Samuel
Olher, Rafael Reis
Villiger, Elias
Nikolaidis, Pantelis Theodoros
Rosemann, Thomas
Hill, Lee
Knechtle, Beat
author_sort Gadelha, André Bonadias
collection PubMed
description Cut-off points and performance-related tools are needed for the development of the Olympic distance triathlon. The purposes of the present study were (i) to determine cut-off values to reach the top three positions in an Olympic distance triathlon; (ii) to identify which discipline present the highest influence on overall race performance and if it has changed over the decades. Data from 1989 to 2019 (n = 52,027) from all who have competed in an official Olympic distance triathlon events (World Triathlon Series and Olympics) were included. The cut-off value to achieve a top three position was calculated. Linear regressions were applied for performance trends overall and for the top three positions of each race. Men had cut-off values of: swimming = 19.5 min; cycling = 60.7 min; running = 34.1 min. Women’s cut-off values were: swimming = 20.7 min; cycling = 71.6 min; running = 38.1 min. The running split seemed to be the most influential in overall race time regardless of rank position or sex. In conclusion, cut-offs were established, which can increase the chances of achieving a successful rank position in an Olympic triathlon. Cycling is the discipline with the least influence on overall performance for both men and women in the Olympic distance triathlon. This influence pattern has not changed in the last three decades.
format Online
Article
Text
id pubmed-7766989
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-77669892020-12-28 Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon Gadelha, André Bonadias Sousa, Caio Victor Sales, Marcelo Magalhaes dos Santos Rosa, Thiago Flothmann, Marti Barbosa, Lucas Pinheiro da Silva Aguiar, Samuel Olher, Rafael Reis Villiger, Elias Nikolaidis, Pantelis Theodoros Rosemann, Thomas Hill, Lee Knechtle, Beat Int J Environ Res Public Health Article Cut-off points and performance-related tools are needed for the development of the Olympic distance triathlon. The purposes of the present study were (i) to determine cut-off values to reach the top three positions in an Olympic distance triathlon; (ii) to identify which discipline present the highest influence on overall race performance and if it has changed over the decades. Data from 1989 to 2019 (n = 52,027) from all who have competed in an official Olympic distance triathlon events (World Triathlon Series and Olympics) were included. The cut-off value to achieve a top three position was calculated. Linear regressions were applied for performance trends overall and for the top three positions of each race. Men had cut-off values of: swimming = 19.5 min; cycling = 60.7 min; running = 34.1 min. Women’s cut-off values were: swimming = 20.7 min; cycling = 71.6 min; running = 38.1 min. The running split seemed to be the most influential in overall race time regardless of rank position or sex. In conclusion, cut-offs were established, which can increase the chances of achieving a successful rank position in an Olympic triathlon. Cycling is the discipline with the least influence on overall performance for both men and women in the Olympic distance triathlon. This influence pattern has not changed in the last three decades. MDPI 2020-12-18 2020-12 /pmc/articles/PMC7766989/ /pubmed/33352924 http://dx.doi.org/10.3390/ijerph17249491 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Gadelha, André Bonadias
Sousa, Caio Victor
Sales, Marcelo Magalhaes
dos Santos Rosa, Thiago
Flothmann, Marti
Barbosa, Lucas Pinheiro
da Silva Aguiar, Samuel
Olher, Rafael Reis
Villiger, Elias
Nikolaidis, Pantelis Theodoros
Rosemann, Thomas
Hill, Lee
Knechtle, Beat
Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon
title Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon
title_full Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon
title_fullStr Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon
title_full_unstemmed Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon
title_short Cut-Off Values in the Prediction of Success in Olympic Distance Triathlon
title_sort cut-off values in the prediction of success in olympic distance triathlon
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766989/
https://www.ncbi.nlm.nih.gov/pubmed/33352924
http://dx.doi.org/10.3390/ijerph17249491
work_keys_str_mv AT gadelhaandrebonadias cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT sousacaiovictor cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT salesmarcelomagalhaes cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT dossantosrosathiago cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT flothmannmarti cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT barbosalucaspinheiro cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT dasilvaaguiarsamuel cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT olherrafaelreis cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT villigerelias cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT nikolaidispantelistheodoros cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT rosemannthomas cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT hilllee cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon
AT knechtlebeat cutoffvaluesinthepredictionofsuccessinolympicdistancetriathlon