INTRODUCTION: In complex team sports like handball, analysis of player load (PL) during competition is a challenging task. However, correctly assessing load and physiological requirements underlying successful game performance is critical for efficient training regimes, optimizing performance, and preventing injuries. Recent work analyzed PL using position data of official team handball matches using time on court and distances covered in different velocity zones (1). However, these measures give little insight intro PL because of players frequent accelerations and decelerations. In contrast, estimating Metabolic Power (MP; 2) allows to capture the energy expenditure over time, including the cost of accelerations and decelerations. The present study therefore analyzed PL in elite male handball players using distance covered and MP. METHODS: Data from 290 male field players of 18 teams during 77 games of the 2019/20 German Men`s Handball Bundesliga were analyzed. Position data was collected using a local positioning system at 20 Hz. For every player, total distance, and equivalent distance were calculated. Differences between distance covered and equivalent distance was analyzed with a 2 (distance vs. equivalent distance) by 3 (wings vs. backs vs. pivots) mixed-effects ANOVA. Statistical significance was set at a = 0.05. RESULTS: Statistical analysis for distance covered and equivalent distance revealed statistically significant group by distance interaction effects (p < .01). Post-hoc analysis showed a significant group effect between wings vs. backs (p < .01; d = 0.92), wings vs. pivots (p < .01; d = .92), but no group effect between backs vs. pivots. Repeated measure effects between distance and equivalent distance were significant for wings (p < .01; d = 0.32), backs (p < .01; d = 0.25), and pivots (p < .01; d = 0.23). Interaction effect for groups and (equivalent) distance were significant for wings vs. backs (p < .01; d = 0.73), wings vs. pivots (p < .01; d = 0.86), and backs vs. pivots (p < .01; d = 0.22), meaning that differences between distance and equivalent distance were greater for wings than for backs and pivots. CONCLUSION: This is the first study that applied MP to handball. Our results indicate that distance covered underestimates player load of wings because their movement is characterized by frequent high intensity accelerations. Thus, standard approaches relying solely on distance covered are not sufficient to assess PL in handball. The MP concept seems to be a valuable approach to obtain more precise information about PL from position data in handball. Still, the effect of static efforts, e.g. from the pivot fighting for position, on internal PL remains unclear and warrants further investigation.
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