Physiological Performance Measures as Indicators of CrossFit<sup>®</sup> Performance

CrossFit<sup>®</sup> began as another exercise program to improve physical fitness and has rapidly grown into the “sport of fitness„. However, little is understood as to the physiological indicators that determine CrossFit<sup>®</sup> sport performance. The purpose of this st...

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Bibliographic Details
Main Authors: Joshua D. Dexheimer (Author), E. Todd Schroeder (Author), Brandon J. Sawyer (Author), Robert W. Pettitt (Author), Arnel L. Aguinaldo (Author), William A. Torrence (Author)
Format: Book
Published: MDPI AG, 2019-04-01T00:00:00Z.
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Summary:CrossFit<sup>®</sup> began as another exercise program to improve physical fitness and has rapidly grown into the “sport of fitness„. However, little is understood as to the physiological indicators that determine CrossFit<sup>®</sup> sport performance. The purpose of this study was to determine which physiological performance measure was the greatest indicator of CrossFit<sup>®</sup> workout performance. Male (<i>n</i> = 12) and female (<i>n</i> = 5) participants successfully completed a treadmill graded exercise test to measure maximal oxygen uptake (VO<sub>2max</sub>), a 3-minute all-out running test (3MT) to determine critical speed (CS) and the finite capacity for running speeds above CS (D′), a Wingate anaerobic test (WAnT) to assess anaerobic peak and mean power, the CrossFit<sup>®</sup> total to measure total body strength, as well as the CrossFit<sup>®</sup> benchmark workouts: Fran, Grace, and Nancy. It was hypothesized that CS and total body strength would be the greatest indicators of CrossFit<sup>®</sup> performance. Pearson’s r correlations were used to determine the relationship of benchmark performance data and the physiological performance measures. For each benchmark-dependent variable, a stepwise linear regression was created using significant correlative data. For the workout Fran, back squat strength explained 42% of the variance. VO<sub>2max</sub> explained 68% of the variance for the workout Nancy. Lastly, anaerobic peak power explained 57% of the variance for performance on the CrossFit<sup>®</sup> total. In conclusion, results demonstrated select physiological performance variables may be used to predict CrossFit<sup>®</sup> workout performance.
Item Description:2075-4663
10.3390/sports7040093