Literature DB >> 30500263

Repeated anaerobic tests predict performance among a group of advanced CrossFit-trained athletes.

Yuri Feito1, Michael J Giardina1,2, Scotty Butcher3, Gerald T Mangine1.   

Abstract

High-intensity functional training (HIFT) (i.e., CrossFit (CF) training) uses a combination of movements and self-selected time periods of work and rest. However, little is known about the physiological responses to an acute bout of HIFT exercise or about the physical parameters that distinguish performance. The purpose of this study was to examine the physiological responses in advanced CF athletes to consecutive Wingate trials with short, active recovery periods. Twenty-nine advanced-level CF-trained athletes volunteered for this study. The participants were required to complete 4 consecutive Wingate anaerobic tests (WAnTs) and a 15-min CF-style workout. Across the 4 WAnT trials, significant (p < 0.001) changes were observed in oxygen consumption, respiratory exchange ratio, and heart rate. Significant (p ≤ 0.001) differences among WAnT trials were observed in all anaerobic performance measures. Compared with all other trials, greater peak power (p < 0.04), relative peak power (p < 0.02), average power (p < 0.001), relative average power (p < 0.001), and total work (p < 0.001), together with a lower fatigue index (p < 0.01), were observed during WAnT 1. Overall, the 4 consecutive WAnT trials resulted in a significant (F = 177.0, p < 0.001) increase in blood lactate response. Stepwise regression revealed that the ability to predict total repetitions completed during the 15-min trial to complete as many repetitions as possible improved as the participants progressed from the first to the third WAnT trial. Our data suggest that, combined with the ability to better maintain performance across high-intensity exercise bouts, the ability to quickly recover between bouts is the most important factor in CF performance.

Entities:  

Keywords:  HIFT; Wingate; athlete; athlète; competition; compétition; condition physique; fitness; performance

Mesh:

Substances:

Year:  2018        PMID: 30500263     DOI: 10.1139/apnm-2018-0509

Source DB:  PubMed          Journal:  Appl Physiol Nutr Metab        ISSN: 1715-5312            Impact factor:   2.665


  9 in total

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Authors:  Gerald T Mangine; Jacob M McDougle; Yuri Feito
Journal:  Front Physiol       Date:  2022-05-27       Impact factor: 4.755

3.  Physiological differences between advanced CrossFit athletes, recreational CrossFit participants, and physically-active adults.

Authors:  Gerald T Mangine; Matthew T Stratton; Christian G Almeda; Michael D Roberts; Tiffany A Esmat; Trisha A VanDusseldorp; Yuri Feito
Journal:  PLoS One       Date:  2020-04-07       Impact factor: 3.240

4.  Physiological Predictors of Competition Performance in CrossFit Athletes.

Authors:  Rafael Martínez-Gómez; Pedro L Valenzuela; Lidia B Alejo; Jaime Gil-Cabrera; Almudena Montalvo-Pérez; Eduardo Talavera; Alejandro Lucia; Susana Moral-González; David Barranco-Gil
Journal:  Int J Environ Res Public Health       Date:  2020-05-24       Impact factor: 3.390

5.  Physiological Predictors of Performance on the CrossFit "Murph" Challenge.

Authors:  Ja'Deon D Carreker; Gregory J Grosicki
Journal:  Sports (Basel)       Date:  2020-06-28

6.  Evaluation of the repeatability and reliability of the cross-training specific Fight Gone Bad workout and its relation to aerobic fitness.

Authors:  Krzysztof Durkalec-Michalski; Emilia E Zawieja; Bogna E Zawieja; Tomasz Podgórski
Journal:  Sci Rep       Date:  2021-03-31       Impact factor: 4.379

7.  Physical and Physiological Predictors of FRAN CrossFit® WOD Athlete's Performance.

Authors:  Luis Leitão; Marcelo Dias; Yuri Campos; João Guilherme Vieira; Leandro Sant'Ana; Luiz Guilherme Telles; Carlos Tavares; Mauro Mazini; Jefferson Novaes; Jeferson Vianna
Journal:  Int J Environ Res Public Health       Date:  2021-04-12       Impact factor: 3.390

8.  Predicting the Unknown and the Unknowable. Are Anthropometric Measures and Fitness Profile Associated with the Outcome of a Simulated CrossFit® Competition?

Authors:  Javier Peña; Daniel Moreno-Doutres; Iván Peña; Iván Chulvi-Medrano; Alberto Ortegón; Joan Aguilera-Castells; Bernat Buscà
Journal:  Int J Environ Res Public Health       Date:  2021-04-01       Impact factor: 3.390

9.  CrossFit® open performance is affected by the nature of past competition experiences.

Authors:  Gerald T Mangine; Jacob M McDougle
Journal:  BMC Sports Sci Med Rehabil       Date:  2022-03-24
  9 in total

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