Journal of Sports Science and Medicine
Journal of Sports Science and Medicine
ISSN: 1303 - 2968   
Ios-APP Journal of Sports Science and Medicine
Androit-APP Journal of Sports Science and Medicine
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©Journal of Sports Science and Medicine (2023) 22, 310 - 316   DOI: https://doi.org/10.52082/jssm.2023.310

Research article
Analysis of Motion Characteristics and Metabolic Power in Elite Male Handball Players
Manuel Bassek , Dominik Raabe, Daniel Memmert, Robert Rein
Author Information
Institute of Exercise Training and Sport Informatics, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany

Manuel Bassek
✉ Institute of Exercise Training and Sport Informatics, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany
Email: m.bassek@dshs-koeln.de
Publish Date
Received: 16-08-2022
Accepted: 16-05-2023
Published (online): 01-06-2023
 
 
ABSTRACT

While handball is characterized by repeated sprints and changes of direction, traditional player load models do not consider accelerations and decelerations. The aim of this study was to analyze the differences between metabolic power and speed zones for player load assessment with regard to the player role. Position data from 330 male individuals during 77 games from the 2019/20 German Men’s Handball-Bundesliga (HBL) were analyzed, resulting in 2233 individual observations. Players were categorized into wings, backs and pivots. Distance covered in different speed zones, metabolic power, metabolic work, equivalent distance (metabolic work divided by energy cost of running), time spend running, energy spend running, and time over 10 and 20 W were calculated. A 2-by-3 mixed ANOVA was calculated to investigate differences and interactions between groups and player load models. Results showed that total distance was longest in wings (3568 ± 1459 m in 42 ± 17 min), followed by backs (2462 ± 1145 m in 29 ± 14 min), and pivots (2445 ± 1052 m in 30 ± 13 min). Equivalent distance was greatest in wings (4072.50 ± 1644.83 m), followed by backs (2765.23 ± 1252.44 m), and pivots (2697.98 ± 1153.16 m). Distance covered and equivalent distance showed moderate to large interaction effects between wings and backs (p < .01, ES = 0.73) and between wings and pivots (p < .01, ES = 0.86) and a small interaction effect between backs and pivots (p < .01, ES = 0.22). The results underline the need for individualized management of training loads and the potential of using information about locomotive accelerations and decelerations to obtain more precise descriptions of player load during handball game performance at the highest level of competition. Future studies should investigate the influence of physical performance on smaller match sequences, like ball possession phases.

Key words: Position data, performance analysis, big data, LPS, player load


           Key Points
  • Player load variables should be comparable and interpretable for research and practice
  • Assessment of player load in multidirectional team sports, like handball, requires the incorporation of accelerations and decelerations, which is achieved in the Metabolic Power concept
  • Analyzing player load in handball with metabolic power shows that wing players' movement behavior is characterized by more frequent accelerations and decelerations than the movement of backcourts and pivots
 
 
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