首页> 美国卫生研究院文献>Journal of Human Kinetics >A new physical performance classification system for elite handball players: cluster analysis
【2h】

A new physical performance classification system for elite handball players: cluster analysis

机译:精英手球运动员新的身体表现分类系统:聚类分析

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

The aim of the present study was to identify different cluster groups of handball players according to their physical performance level assessed in a series of physical assessments, which could then be used to design a training program based on individual strengths and weaknesses, and to determine which of these variables best identified elite performance in a group of under-19 [U19] national level handball players. Players of the U19 National Handball team (n=16) performed a set of tests to determine: 10 m (ST10) and 20 m (ST20) sprint time, ball release velocity (BRv), countermovement jump (CMJ) height and squat jump (SJ) height. All players also performed an incremental-load bench press test to determine the 1 repetition maximum (1RMest), the load corresponding to maximum mean power (LoadMP), the mean propulsive phase power at LoadMP (PMPPMP) and the peak power at LoadMP (PPEAKMP). Cluster analyses of the test results generated four groupings of players. The variables best able to discriminate physical performance were BRv, ST20, 1RMest, PPEAKMP and PMPPMP. These variables could help coaches identify talent or monitor the physical performance of athletes in their team. Each cluster of players has a particular weakness related to physical performance and therefore, the cluster results can be applied to a specific training programmed based on individual needs.
机译:本研究的目的是根据在一系列身体评估中评估的身体表现水平来识别手球运动员的不同组群,然后将其用于基于个人的长处和短处设计训练计划,并确定哪些这些变量中最能确定一组19岁以下[U19]国家级手球运动员的精英水平的表现。 U19国家手球队(n = 16)的球员进行了一组测试,以确定:10 m(ST10)和20 m(ST20)的短跑时间,发球速度(BRv),反向运动跳跃(CMJ)高度和下蹲跳跃(SJ)高度。所有参与者还进行了增量负载卧推测试,以确定最大1次重复(1RMest),对应于最大平均功率(LoadMP)的负载,LoadMP处的平均推进相功率(PMPPMP)和LoadMP处的峰值功率(PPEAKMP) )。测试结果的聚类分析产生了四类参与者。最能区分物理性能的变量是BRv,ST20、1RMest,PPEAKMP和PMPPMP。这些变量可以帮助教练识别人才或监控运动员在团队中的身体表现。每个运动员群体都有一个与身体表现有关的特殊弱点,因此,可以将这些结果应用于基于个人需求进行的特定训练。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号