International matches elicit stable mechanical workload in high-level female ice hockey

Abstract

This study aimed to quantify in- and between-match characteristics and mechanical workload variations elicited by a congested schedule in high-level female ice hockey. Six players were monitored during four international pre-season exhibition matches against the same opponent. Two different methods (Player Load and Accel'Rate) were used to assess specific mechanical workload. Number of shifts and effective playing time per shift were significantly higher for period 2 (p = 0.03 for both). Mechanical workload intensity (i.e., relative and peak workload) showed a significant (p ≤ 0.05) decrease from period 1 to period 2 and period 3 (moderate-to-large Cohen's d). All workload variables remained stable between matches (p > 0.25). Team variability showed good-to-moderate CVs (< 10%) for all variables for in- and between-match variability. Accumulated workload computed with the Player Load method was threefold higher compared to the Accel'Rate method (+ 87.8% mean difference; large Cohen's d). These findings demonstrate that high-level female ice hockey-specific mechanical workload declines with reduced high-intensity output across periods, while it remains stable between matches against standardized opposition. This study strongly suggests that the present workload metrics could be used to determine the mechanical demand elicited by matches played against various opponents in real game conditions.

Keywords: Accelerometry; Congested fixture period; Mechanical demand; Skating; Workload monitoring.

FIG. 1

Effective playing time per shift excluding on-ice stoppage (panel A), accumulated workload Player Load (panel B) and Accel’Rate (panel C) by period. P1: period 1; P2: period 2; P3: period 3. ## (p ≤ 0.01) and ### (p ≤ 0.001) significantly different from P2.

FIG. 2

Relative mean difference between matches compared to Match 1 for accumulated mechanical workload Accel’Rate (AR; panel A), relative value of Accel’Rate (AR · min^-1; panel B) and peak workload using a rolling average of 9 s (peak AR; panel C). Absolute values of each measure are displayed as mean ± standard deviation. Coefficient of variation (CV) represents the between-match variability of each measure and the grey areas, called the smallest worthwhile change (SWC), represent trivial change.