Physiological Performance Measures as Indicators of CrossFit ® Performance

CrossFit 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 sport performance. The purpose of this study was to determine which physiologic...

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Bibliographic Details
Published in:Sports (Basel) 2019-04, Vol.7 (4), p.93
Main Authors: Dexheimer, Joshua D, Schroeder, E Todd, Sawyer, Brandon J, Pettitt, Robert W, Aguinaldo, Arnel L, Torrence, William A
Format: Article
Language:English
Subjects:
Anaerobic threshold
Athletes
benchmark performance
Body composition
critical speed
CrossFit® sport performance
Data collection
Exercise
Fitness equipment
Heart rate
Metabolism
Physical fitness
Physical training
physiological indicators
Physiology
Recreation
strength
Variables
VO2max
Warm up (exercise)
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Summary:CrossFit 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 sport performance. The purpose of this study was to determine which physiological performance measure was the greatest indicator of CrossFit workout performance. Male ( = 12) and female ( = 5) participants successfully completed a treadmill graded exercise test to measure maximal oxygen uptake (VO ), 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 total to measure total body strength, as well as the CrossFit benchmark workouts: Fran, Grace, and Nancy. It was hypothesized that CS and total body strength would be the greatest indicators of CrossFit 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 explained 68% of the variance for the workout Nancy. Lastly, anaerobic peak power explained 57% of the variance for performance on the CrossFit total. In conclusion, results demonstrated select physiological performance variables may be used to predict CrossFit workout performance.
ISSN:2075-4663
2075-4663
DOI:10.3390/sports7040093