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Abstract

Global positioning systems have been used increasingly in sports science due to their ability to quantify external loads of athletes during competitions and practices. Limited research has examined gender differences in external load throughout a collegiate soccer season. PURPOSE: The aim of this study was to compare game workloads across collegiate men (MSOC) and women (WSOC) soccer players. Division III MSOC and WSOC players wore GPS devices during games throughout a 15-week season. METHODS: Metrics analyzed from GPS data were: total distance (TD), sprint distance (SD), number of deceleration efforts (decel) (>-3 m/s²), number of acceleration efforts (accel) (>3 m/s²), sprint efforts, top speed (TS), player load per minute (PL/Min), and distances in five-speed zones (SZ1: 0-30%; SZ2: 30-50%; SZ3: 50-75%; SZ4: 75%-90%; SZ5: >90% of maximum speed). Independent groups factorial multivariate analysis of variance (MANOVA) was conducted to assess a 2 x 3 gender x position interaction effect, gender main effects, and position main effect on all 12 external load metrics. These effects were also examined as 12 separate univariate analyses of variance (ANOVAs). Bonferroni-adjusted pairwise comparisons were used to specify the nature of differences implied by significant effects (p < 0.05). RESULTS: Results of a 2 (gender) x 3 (position) independent samples MANOVA showed a significant multivariate interaction effect and significant multivariate main effects of gender and position (ps < 0.001). Significant univariate interaction effects were found for 11 out of 12 dependent variables (ps < 0.001). In addition, significant univariate main effects of gender were found for 11 out of 12 dependent variables (ps < 0.05). No significant gender difference was found in distance in SZ4 (p = 0.069). Significant univariate main effects of position were found for 11 out of 12 dependent variables (ps < 0.05) but no significant difference by position was found in SZ3 (p = 0.100). DISCUSSION: Notable gender differences were found between game external load metrics, gender, and position and within-gender position across external load metrics. Further, results can be used as a framework to develop gender-specific programs to prepare athletes for the demands of their competitive seasons.

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