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Physiological Performance Measures as Indicators of CrossFit ? Performance

机译:生理表现指标可作为CrossFit的指标?性能

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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 (VO 2max ), 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 2max 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?这项运动是另一项运动计划,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?的生理指标了解甚少。运动表现。这项研究的目的是确定哪种生理机能指标是CrossFit的最大指标?锻炼表现。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(VO 2max),进行了3​​分钟的全面跑步测试(3MT),以确定临界速度(CS)以及超过CS的行驶速度的有限能力(D'),一种用于评估无氧峰值和平均功率的Wingate厌氧测试(WAnT), total可以测量整体力量,以及CrossFit?基准锻炼:Fran,Grace和Nancy。据推测,CS和全身力量将是CrossFit的最大指标?性能。皮尔森的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。对于每个基于基准的变量,使用重要的相关数据创建逐步线性回归。对于锻炼Fran,后蹲力量解释了42%的差异。 VO 2max解释了锻炼Nancy的68%方差。最后,无氧峰值功率解释了CrossFit?的性能差异的57%。总。总之,结果表明选择的生理性能变量可用于预测CrossFit?锻炼表现。

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