Bautista Iker J, Chirosa Ignacio J, Robinson Joseph E, van der Tillaar Roland, Chirosa Luis J, Martín Isidoro Martínez
FisioSalud Elite, Health, Training & Innovation University of Granada ( Spain ).
Department of Physical Education and Sport. University of Granada ( Spain ).
J Hum Kinet. 2016 Jul 2;51:131-142. doi: 10.1515/hukin-2015-0177. eCollection 2016 Jun 1.
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 (ST) and 20 m (ST) 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 (1RM), the load corresponding to maximum mean power (Load), the mean propulsive phase power at Load (PMP) and the peak power at Load (PMP). Cluster analyses of the test results generated four groupings of players. The variables best able to discriminate physical performance were BRv, ST, 1RM, PMP and PMP. 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.
本研究的目的是根据在一系列体能评估中所测定的身体表现水平,确定手球运动员的不同聚类组,进而据此设计基于个人优势和劣势的训练计划,并确定这些变量中哪些最能鉴别19岁以下(U19)国家级手球运动员的精英表现。U19国家手球队的运动员(n = 16)进行了一组测试,以测定:10米(ST)和20米(ST)短跑时间、掷球速度(BRv)、纵跳(CMJ)高度和蹲跳(SJ)高度。所有运动员还进行了递增负荷卧推测试,以确定1次重复最大值(1RM)、对应最大平均功率的负荷(Load)、负荷下的平均推进阶段功率(PMP)以及负荷下的峰值功率(PMP)。对测试结果进行聚类分析产生了四组运动员。最能区分身体表现的变量是BRv、ST、1RM、PMP和PMP。这些变量可以帮助教练识别天赋或监测其团队中运动员的身体表现。每组运动员在身体表现方面都有特定的弱点,因此,聚类结果可应用于基于个人需求的特定训练计划。