Literature DB >> 31291652

Full-Squat as a Determinant of Performance in CrossFit.

Rafael Martínez-Gómez1, Pedro L Valenzuela2,3, David Barranco-Gil1, Susana Moral-González1, Adela García-González4, Alejandro Lucia1,5.   

Abstract

This study analyzed the relationship between CrossFit performance and power and strength variables measured in the full-squat exercise. Twenty male trained subjects (33±7 years) performed an incremental load full-squat test for assessment of the 1-repetition maximum (1RM) and the mean (Pmean) and peak (Ppeak) power. Performance in 5 different Workouts of the Day (WODs) was measured on different days, and overall CrossFit performance was determined as the sum of the scores obtained in these WODs. Athletes were then assigned to a high (HP) or low (LP) performance group based on the median score for overall performance. Correlation analysis between squat variables and performance was performed and between-group differences were assessed. Moderate to strong (r=0.47-0.69, p<0.05) positive correlations were found between squat variables and performance in the different WODs. Overall CrossFit performance was strongly and positively associated with absolute (r=0.62, p=0.01) and relative 1RM (r=0.65, p=0.07), and relative Pmean (r=0.56, p=0.02) and Ppeak (r=0.53, p=0.03). Large differences (effect sizes ranging 1.1-1.7, all p<0.05) were observed between HP and LP for absolute and relative 1RM, relative Pmean, and absolute and relative Ppeak. In summary, strength and power indexes measured in a squat test are positively associated with CrossFit performance. © Georg Thieme Verlag KG Stuttgart · New York.

Entities:  

Mesh:

Year:  2019        PMID: 31291652     DOI: 10.1055/a-0960-9717

Source DB:  PubMed          Journal:  Int J Sports Med        ISSN: 0172-4622            Impact factor:   3.118


  6 in total

1.  CrossFit® Training Strategies from the Perspective of Concurrent Training: A Systematic Review.

Authors:  Petr Schlegel
Journal:  J Sports Sci Med       Date:  2020-11-19       Impact factor: 2.988

2.  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

3.  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

4.  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

5.  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

6.  Determination of a CrossFit® Benchmark Performance Profile.

Authors:  Nicole Meier; Stefan Rabel; Annette Schmidt
Journal:  Sports (Basel)       Date:  2021-06-02
  6 in total

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