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Physiological Performance Measures as Indicators of CrossFit® Performance

机译:生理表现指标作为CrossFit®表现指标

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摘要

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.
机译:CrossFit ®最初是另一个运动计划,旨在提高身体健康水平,并迅速发展为“健身运动”。但是,对于决定CrossFit ®运动表现的生理指标知之甚少。这项研究的目的是确定哪种生理机能指标是CrossFit ®锻炼机能的最大指标。男性(n = 12)和女性(n = 5)参与者成功完成了跑步机分级运动测试,以测量最大摄氧量(VO2max),进行了3​​分钟的全面跑步测试(3MT),以确定临界速度(CS)和超过CS(D')的行驶速度的有限能力,用于评估无氧峰值和平均功率的Wingate厌氧测试(WAnT),用于测量总体力量的CrossFit ®总数以及CrossFit ®基准锻炼:Fran,Grace和Nancy。假设CS和总体力量将是CrossFit ®性能的最大指标。皮尔逊的r相关性用于确定基准性能数据与生理性能指标之间的关系。对于每个与基准相关的变量,使用重要的相关数据创建了逐步线性回归。对于锻炼Fran,后蹲力量解释了42%的差异。 VO2max解释了锻炼Nancy的68%方差。最后,无氧峰值功率解释了CrossFit ®总性能的57%差异。总之,结果表明选择的生理机能变量可用于预测CrossFit ®锻炼机能。

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