The Relationship between CrossFit® Performance and Laboratory-Based Measurements of Fitness
| Autor: | Whitney D Leyva, Immanuel Y Terbio, Edward Jo, Elisabeth Zeitz, Lena F Cook, Joshua D. Dexheimer, Justin R. Tran, Srdjan Lemez |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
aerobic fitness
lcsh:Sports body composition 030209 endocrinology & metabolism Physical Therapy Sports Therapy and Rehabilitation Regression analysis Total body Squat 030229 sport sciences Predictive value high-intensity functional training lcsh:GV557-1198.995 03 medical and health sciences 0302 clinical medicine One-repetition maximum Statistics Aerobic exercise Orthopedics and Sports Medicine Multiple linear regression analysis Mathematics |
| Zdroj: | Sports, Vol 8, Iss 112, p 112 (2020) Sports Volume 8 Issue 8 |
| ISSN: | 2075-4663 |
| DOI: | 10.3390/sports8080112 |
| Popis: | To date, research has examined the physiological determinants of performance in standardized CrossFit® (CF) workouts but not without the influence of CF familiarity. Therefore, the purpose of this present study was to examine the predictive value of aerobic fitness, body composition, and total body strength on performance of two standardized CF workouts in CF-naï ve participants. Twenty-two recreationally trained individuals (males = 13, females = 9) underwent assessments of peak oxygen consumption (VO2 peak), ventilatory thresholds, body composition, and one repetition maximum tests for the back squat, deadlift, and overhead press in which the sum equaled the CF Total. Participants also performed two CF workouts: a scaled version of the CF Open workout 19.1 and a modified version of the CF Benchmark workout Fran to determine scores based on total repetitions completed and time-to-completion, respectively. Simple Pearson&rsquo s r correlations were used to determine the relationships between CF performance variables (19.1 and modified Fran) and the independent variables. A forward stepwise multiple linear regression analysis was performed and significant variables that survived the regression analysis were used to create a predictive model of CF performance. Absolute VO2 peak was a significant predictor of 19.1 performance, explaining 39% of its variance (adjusted R2 = 0.39, p = 0.002). For modified Fran, CF Total was a significant predictor and explained 33% of the variance in performance (adjusted R2 = 0.33, p = 0.005). These results suggest, without any influence of CF familiarity or experience, that performance in these two CF workouts could be predicted by distinct laboratory-based measurements of fitness. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|