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Workout Pacing Predictors of Crossfit® Open Performance: A Pilot Study.
Mangine, Gerald T; Feito, Yuri; Tankersley, Joy E; McDougle, Jacob M; Kliszczewicz, Brian M.
Afiliação
  • Mangine GT; Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA, USA.
  • Feito Y; Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA, USA.
  • Tankersley JE; Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA, USA.
  • McDougle JM; Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA, USA.
  • Kliszczewicz BM; Department of Exercise Science and Sport Management, Kennesaw State University, Kennesaw, GA, USA.
J Hum Kinet ; 78: 89-100, 2021 Mar.
Article em En | MEDLINE | ID: mdl-34025867
ABSTRACT
To observe workout repetition and rest interval pacing strategies and determine which best predicted performance during the 2016 CrossFit® Open, five male (34.4 ± 3.8 years, 176 ± 5 cm, 80.3 ± 9.7 kg) and six female (35.2 ± 6.3 years, 158 ± 7 cm, 75.9 ± 19.3 kg) recreational competitors were recruited for this observational, pilot study. Exercise, round, and rest time were quantified via a stopwatch for all competitors on their first attempt of each of the five workouts. Subsequently, pacing was calculated as a repetition rate (repetitions·s-1) to determine the fastest, slowest, and average rate for each exercise, round, and rest interval, as well as how these changed (i.e., slope, Δ rate / round) across each workout. Spearman's rank correlation coefficients indicated that several pacing variables were significantly (p < 0.05) related to performance on each workout. However, stepwise regression analysis indicated that the average round rate best predicted (p < 0.001) performance on the first (R2 = 0.89), second (R2 = 0.99), and fifth (R2 = 0.94) workouts, while the competitors' rate on their slowest round best predicted workout three performance (R2 = 0.94, p < 0.001). The wall ball completion rate (R2 = 0.89, p = 0.002) was the best predictor of workout four performance, which was improved by 9.8% with the inclusion of the deadlift completion rate. These data suggest that when CrossFit® Open workouts consist of multiple rounds, competitors should employ a fast and sustainable pace to improve performance. Otherwise, focusing on one or two key exercises may be the best approach.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article