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Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study

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 recruit...

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Autores principales: Mangine, Gerald T., Feito, Yuri, Tankersley, Joy E., McDougle, Jacob M., Kliszczewicz, Brian M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Sciendo 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120962/
https://www.ncbi.nlm.nih.gov/pubmed/34025867
http://dx.doi.org/10.2478/hukin-2021-0043
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author Mangine, Gerald T.
Feito, Yuri
Tankersley, Joy E.
McDougle, Jacob M.
Kliszczewicz, Brian M.
author_facet Mangine, Gerald T.
Feito, Yuri
Tankersley, Joy E.
McDougle, Jacob M.
Kliszczewicz, Brian M.
author_sort Mangine, Gerald T.
collection PubMed
description 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 (R(2) = 0.89), second (R(2) = 0.99), and fifth (R(2) = 0.94) workouts, while the competitors’ rate on their slowest round best predicted workout three performance (R(2) = 0.94, p < 0.001). The wall ball completion rate (R(2) = 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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spelling pubmed-81209622021-05-20 Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study Mangine, Gerald T. Feito, Yuri Tankersley, Joy E. McDougle, Jacob M. Kliszczewicz, Brian M. J Hum Kinet Section II - Exercise Physiology & Sports Medicine 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 (R(2) = 0.89), second (R(2) = 0.99), and fifth (R(2) = 0.94) workouts, while the competitors’ rate on their slowest round best predicted workout three performance (R(2) = 0.94, p < 0.001). The wall ball completion rate (R(2) = 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. Sciendo 2021-03-31 /pmc/articles/PMC8120962/ /pubmed/34025867 http://dx.doi.org/10.2478/hukin-2021-0043 Text en © 2021 Gerald T. Mangine, Yuri Feito, Joy E. Tankersley, Jacob M. McDougle, Brian M. Kliszczewicz, published by Sciendo https://creativecommons.org/licenses/by-nc-nd/3.0/This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.
spellingShingle Section II - Exercise Physiology & Sports Medicine
Mangine, Gerald T.
Feito, Yuri
Tankersley, Joy E.
McDougle, Jacob M.
Kliszczewicz, Brian M.
Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study
title Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study
title_full Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study
title_fullStr Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study
title_full_unstemmed Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study
title_short Workout Pacing Predictors of Crossfit(®) Open Performance: A Pilot Study
title_sort workout pacing predictors of crossfit(®) open performance: a pilot study
topic Section II - Exercise Physiology & Sports Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8120962/
https://www.ncbi.nlm.nih.gov/pubmed/34025867
http://dx.doi.org/10.2478/hukin-2021-0043
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