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不同运动策略在 NBA 球员中反跳的表现。

Different Movement Strategies in the Countermovement Jump Amongst a Large Cohort of NBA Players.

机构信息

Peak Performance Project, Santa Barbara, CA 93101, USA.

Laboratory of Adaptations to Strength Training, Escola de Educação Física e Esporte, Universidade de Sao Paulo, São Paulo 05508-060, Brazil.

出版信息

Int J Environ Res Public Health. 2020 Sep 2;17(17):6394. doi: 10.3390/ijerph17176394.

Abstract

Previous research has demonstrated large amounts of inter-subject variability in downward (unweighting & braking) phase strategies in the countermovement jump (CMJ). The purpose of this study was to characterize downward phase strategies and associated temporal, kinematic and kinetic CMJ variables. One hundred and seventy-eight NBA (National Basketball Association) players (23.6 ± 3.7 years, 200.3 ± 8.0 cm; 99.4 ± 11.7 kg; CMJ height 68.7 ± 7.4 cm) performed three maximal CMJs. Force plate and 3D motion capture data were integrated to obtain kinematic and kinetic outputs. Afterwards, athletes were split into clusters based on downward phase characteristics (-means cluster analysis). Lower limb joint angular displacement (i.e., delta flexion) explained the highest portion of point variability (89.3%), and three clusters were recommended (Ball Hall Index). Delta flexion was significantly different between clusters and players were characterized as "stiff flexors", "hyper flexors", or "hip flexors". There were no significant differences in jump height between clusters ( > 0.05). Multiple regression analyses indicated that most of the jumping height variance was explained by the same four variables, (i.e., sum concentric relative force, knee extension velocity, knee extension acceleration, and height) regardless of the cluster ( < 0.05). However, each cluster had its own unique set of secondary predictor variables.

摘要

先前的研究表明,在反跳(减重和制动)阶段,受试者之间存在大量的策略变化。本研究的目的是描述反跳阶段的策略以及相关的时间、运动学和动力学变量。178 名 NBA(美国职业篮球联赛)球员(23.6 ± 3.7 岁,200.3 ± 8.0cm;99.4 ± 11.7kg;CMJ 高度 68.7 ± 7.4cm)进行了三次最大的 CMJ 测试。力板和 3D 运动捕捉数据被整合以获得运动学和动力学输出。之后,根据反跳阶段的特点(-均值聚类分析)将运动员分成了不同的小组。下肢关节角位移(即屈肌伸展度)解释了点变异性的最大部分(89.3%),并推荐了三个小组(球霍尔指数)。屈肌伸展度在组间存在显著差异,运动员被分为“僵硬屈肌”、“过度屈肌”或“髋关节屈肌”。各组之间的跳跃高度没有显著差异(>0.05)。多元回归分析表明,跳跃高度的大部分变化都可以用相同的四个变量来解释(即,总向心相对力、膝关节伸展速度、膝关节伸展加速度和高度),与组无关(<0.05)。然而,每个组都有其自己独特的一组次要预测变量。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1381/7504515/42b688fe9592/ijerph-17-06394-g001.jpg

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