目的:在本研究中,我们比较了速度负荷跳跃测试过程中运动特异性的影响,以预测优秀速滑运动员的冰上加速表现。
方法:精英长跑速滑运动员(N=27)在单侧水平跳跃过程中使用3个外部载荷进行了速度载荷测试,侧跳,和双侧垂直逆动跳跃。对于单边测试,外部载荷条件设置为10N,相对于体重的外部负荷的7.5%和15%。对于反运动跳跃,负荷条件为体重和相对于体重的30%和60%的外部负荷。从站立开始的最大50米加速度期间获得了冰上性能测量值,包括最大滑冰速度,最大加速能力,和最大水平功率。还获得了500米比赛的100米分割时间。使用正则化回归模型来确定冰上加速性能的最重要预测因子。除了正则化的回归系数,计算模型保留的所有变量的皮尔逊相关系数(r),以评估单个预测因子与冰上绩效指标之间的相互关系。
结果:30%体重的反运动跳跃显示出与最大滑冰速度的最强关联,最大水平功率,和100-m时间(正则化回归系数=.16-.49,r=.84-.97,P<.001)。15%体重的水平跳跃是最大加速能力表现的最强预测指标(正则化回归系数=.08,r=.83,P<.001)。
结论:这项研究的结果表明,机械特异性而不是运动特异性与预测冰上加速性能更相关。
OBJECTIVE: In this study, we compared the influence of movement specificity during velocity-load jump testing to predict on-ice acceleration performance in elite speed skaters.
METHODS: Elite long-track speed skaters (N = 27) performed velocity-load testing with 3 external loads during unilateral horizontal jumping, lateral jumping, and bilateral vertical countermovement jumping. For the unilateral tests, external load conditions were set to 10 N, 7.5% and 15% of external load relative to body weight. For the countermovement jumping, load conditions were body weight and 30% and 60% of external load relative to body weight. On-ice performance measures were obtained during maximal 50-m accelerations from a standing start, including maximal skating speed, maximal acceleration capacity, and maximum horizontal power. The 100-m split time from a 500-m race was also obtained. Regularized regression models were used to identify the most important predictors of on-ice acceleration performance. In addition to regularized regression coefficients, Pearson correlation coefficients (r) were calculated for all variables retained by the model to assess interrelationships between single predictors and on-ice performance measures.
RESULTS: The countermovement jump with 30% of body mass demonstrated the strongest association with maximal skating speed, maximum horizontal power, and 100-m time (regularized regression coefficient = .16-.49, r = .84-.97, P < .001). Horizontal jump with 15% of body mass was the strongest predictor of maximal acceleration capacity performance (regularized regression coefficient = .08, r = .83, P < .001).
CONCLUSIONS: The findings of this study suggest that mechanical specificity rather than movement specificity was more relevant for predicting on-ice acceleration performance.