Back to Search Start Over

What Is the Best Discipline to Predict Overall Triathlon Performance? An Analysis of Sprint, Olympic, Ironman® 70.3, and Ironman® 140.6

Authors :
Thomas Rosemann
Caio Victor Sousa
Beat Knechtle
Pantelis T. Nikolaidis
Elias Villiger
Samuel da Silva Aguiar
Rafael Cunha
Rafael Reis Olher
University of Zurich
Source :
Frontiers in Physiology, Vol 12 (2021)
Publication Year :
2021
Publisher :
Frontiers Research Foundation, 2021.

Abstract

Objective: To analyze the proportion of dedication in each triathlon discipline (swimming, cycling, and running) and the importance of each separate discipline to predict overall performance of elite triathletes across different triathlon distances.Methods: Data from 2015 to 2020 (n = 16,667) from official races and athletes in Sprint, Olympic distance, IM 70.3 (Half-Ironman distance), and IM 140.6 (Full-Ironman distance) competitions were included. The proportion of each discipline was calculated individually and compared using general linear models by event distance, sex, and performance level. Automatic linear regression models were applied for each distance considering overall performance as the dependent variable.Results: A within-distance analysis showed that the best predictor for Sprint is cycling, for Olympic is swimming, for IM 70.3 is cycling, and for IM 140.6 is running. A between-distance analysis revealed that swimming is a better predictor in Olympic distance than in other triathlon distances. Cycling is a poor predictor for overall performance in IM 140.6, and the importance of running to predict overall performance is the highest in IM 140.6 and diminishes with decreasing race distance.Conclusion: Each discipline represents a different relative portion and importance to predict overall performance depending on the triathlon distance. Swimming is the most important predictor discipline in Sprint- and Olympic-distance triathlon, cycling in IM 70.3, and running in IM 140.6.

Details

Database :
OpenAIRE
Journal :
Frontiers in Physiology, Vol 12 (2021)
Accession number :
edsair.doi.dedup.....8ee95fd37f252c708a0c805321b76ebd
Full Text :
https://doi.org/10.5167/uzh-209734