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A new physical performance classification system for elite handball players: cluster analysis
Iker J Bautista1, Ignacio J Chirosa2, Joseph E Robinson2
1FisioSalud Elite, Health, Training & Innovation University of Granada ( Spain ).
Journal of Human Kinetics
|February 3, 2017
Summary
This study identified four distinct physical performance clusters in under-19 handball players. Key variables like ball release velocity and sprint time can guide individualized training programs and talent identification.
Area of Science:
- Sports Science
- Human Movement Analysis
- Talent Identification
Background:
- Optimizing training programs requires understanding athlete physical performance variations.
- Elite handball performance is influenced by a complex interplay of physical attributes.
Purpose of the Study:
- To classify under-19 national handball players into physical performance clusters.
- To identify key performance indicators for elite handball players.
- To inform individualized training program design based on player strengths and weaknesses.
Main Methods:
- Cluster analysis was performed on physical performance data from 16 under-19 national handball players.
- Tests included sprint times (10m, 20m), ball release velocity, jump heights (CMJ, SJ), and bench press performance (1RMest, LoadMP, PMPPMP, PEAKMP).
Main Results:
- Four distinct player clusters were identified based on physical performance.
- Ball release velocity, 20m sprint time, estimated 1 repetition maximum, peak power, and mean propulsive power were key discriminating variables.
- Each cluster exhibited unique physical performance weaknesses.
Conclusions:
- The identified clusters and discriminating variables can aid coaches in talent identification and athlete monitoring.
- Tailored training programs can be developed for each cluster to address specific physical limitations and enhance performance.
