Physiological Performance Measures as Indicators of CrossFit® Performance
1
Department of Exercise Science, Concordia University Chicago, Riverforest, IL 60305, USA
2
Department of Kinesiology, Azusa Pacific University, Azusa, CA 91702, USA
3
Division of Biokinesiology & Physical Therapy, University of Southern California, Los Angeles, CA 90033, USA
4
Department of Kinesiology, Point Loma Nazarene University, San Diego, CA 92106, USA
5
Office of Research and Sponsored Projects, Rocky Mountain University of Health Professions, Provo, UT 84606, USA
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Sports 2019, 7(4), 93; https://doi.org/10.3390/sports7040093
Received: 15 February 2019 / Revised: 16 April 2019 / Accepted: 17 April 2019 / Published: 22 April 2019
(This article belongs to the Special Issue Research on High Intensity Functional Training)
Abstract
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 (n = 12) and female (n = 5) participants successfully completed a treadmill graded exercise test to measure maximal oxygen uptake (VO2max), 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. VO2max 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. View Full-TextKeywords:
CrossFit® sport performance; physiological indicators; benchmark performance; VO2max; critical speed; D′; strength
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MDPI and ACS Style
Dexheimer, J.D.; Schroeder, E.T.; Sawyer, B.J.; Pettitt, R.W.; Aguinaldo, A.L.; Torrence, W.A. Physiological Performance Measures as Indicators of CrossFit® Performance. Sports 2019, 7, 93.
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