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Prediction of Rowing Ergometer Performance from Functional Anaerobic Power Strength and Anthropometric Components

机译:从功能性无氧能力力量和人体测量学预测赛艇测功机的性能

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摘要

The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years) participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE). Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s). Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s). As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.
机译:这项研究的目的是开发不同的回归模型,以使用人体测量,厌氧和强度变量来预测2000 m划船测功机的性能,并确定当在同一方程式中一起进行时,由不同变量构成的预测模型如何精确地预测性能或单独。 38位男性大学赛艇运动员(20.17±1.22岁)参加了这项研究。进行了人体测量,强度测试,2000 m最大划船测功仪和划船厌氧能力测试。在SPSS 16中采用了多个线性回归程序,以使用一组不同的变量来构成五个不同的回归公式。回归模型的可靠性由R2和估计标准误(SEE)表示。通过皮尔逊相关系数研究了所有参数与性能的关系。发现结合厌氧,强度和人体测量变量的预测模型是预测2000 m划船测功机性能的最可靠方程(R2 = 0.92,SEE = 3.11 s)。此外,使用划船厌氧和强度测试结果的方程式也提供了可靠的预测(R2 = 0.85,SEE = 4.27 s)。总之,似乎很明显,受厌氧能量途径影响的生理决定因素也应参与划船中的性能预测和才能识别所使用的过程和模型。

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