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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Sciendo
2021
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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. |
format | Online Article Text |
id | pubmed-8120962 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Sciendo |
record_format | MEDLINE/PubMed |
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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