Literature DB >> 12904633

Prediction of drafted-triathlon race time from submaximal laboratory testing in elite triathletes.

Olivier Hue1.   

Abstract

PURPOSE AND METHODS: To determine which physiological variables accurately predict the race time of an Olympic-distance International Triathlon undertaken in drafted conditions, 8 elite triathletes underwent both maximal and submaximal laboratory and field physiological testing: a 400-m maximal swim test; an incremental treadmill test; an incremental cycling test; 30 min of cycling followed by 20 min of running (C-R); and 20 min of control running (R) at the exact same speed variations as in running in C-R. Blood samples were drawn to measure venous lactate concentration after the 400-m swim and the cycle and run segments of C-R. During the maximal cycling and running exercises, data were collected using an automated breath-by-breath system.
RESULTS: The only parameters correlated with the overall drafted-triathlon time were lactate concentration noted at the end of the cycle segment (r = 0.83, p < 0. 05) and the distance covered during the running part of the submaximal C-R test (r = 0.92, p < 0. 01). Stepwise multiple regression analysis revealed a highly significant (r = 0.96, p < 0.02) relationship between predicted race time (from laboratory measures) and actual race time, using the following calculation: Predicted Triathlon Time (s) = 1.128 (distance covered during R of C-R [m]) + 38.8 ([lactate] at the end of C in C-R) + 13,338. The high R2 value of 0.93 indicated that, taken together, these two laboratory measures could account for 93% of the variance in race times during a drafted triathlon.
CONCLUSION: Complementing previous studies, this study demonstrates that different parameters seem to be reliable for predicting performance in drafted vs. nondrafted Olympic-triathlon races. It also demonstrates that, for elite triathletes competing in a drafted Olympic-distance triathlon, performance is accurately predicted from the results of submaximal laboratory measures.

Entities:  

Mesh:

Substances:

Year:  2003        PMID: 12904633     DOI: 10.1139/h03-042

Source DB:  PubMed          Journal:  Can J Appl Physiol        ISSN: 1066-7814


  6 in total

1.  Reliability and validity of physiological data obtained within a cycle-run transition test in age-group triathletes.

Authors:  Veronica Vleck; Gregoire P Millet; Francisco Bessone Alves; David J Bentley
Journal:  J Sports Sci Med       Date:  2012-12-01       Impact factor: 2.988

2.  Endurance sport and "cardiac injury": a prospective study of recreational ironman athletes.

Authors:  Roman Leischik; Norman Spelsberg
Journal:  Int J Environ Res Public Health       Date:  2014-09-03       Impact factor: 3.390

Review 3.  The impact of triathlon training and racing on athletes' general health.

Authors:  Veronica Vleck; Gregoire P Millet; Francisco Bessone Alves
Journal:  Sports Med       Date:  2014-12       Impact factor: 11.136

Review 4.  Variables that influence Ironman triathlon performance - what changed in the last 35 years?

Authors:  Beat Knechtle; Raphael Knechtle; Michael Stiefel; Matthias Alexander Zingg; Thomas Rosemann; Christoph Alexander Rüst
Journal:  Open Access J Sports Med       Date:  2015-08-25

5.  Swim Positioning and its Influence on Triathlon Outcome.

Authors:  Grant J Landers; Brian A Blanksby; Timothy R Ackland; Ronald Monson
Journal:  Int J Exerc Sci       Date:  2008-07-15

Review 6.  Elite Triathlete Profiles in Draft-Legal Triathlons as a Basis for Talent Identification.

Authors:  Alba Cuba-Dorado; Tania Álvarez-Yates; Oscar García-García
Journal:  Int J Environ Res Public Health       Date:  2022-01-13       Impact factor: 3.390

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.