The match-to-match variation of match-running in elite female soccer


Objectives The purpose of this study was to examine the match-to-match variation of match-running in elite female soccer players utilising GPS, using full-match and rolling period analyses. Design Longitudinal study. Methods Elite female soccer players (n = 45) from the same national team were observed during 55 international fixtures across 5 years (2012-2016). Data was analysed using a custom built MS Excel spreadsheet as full-matches and using a rolling 5-min analysis period, for all players who played 90-min matches (files = 172). Variation was examined using co-efficient of variation and 90% confidence limits, calculated following log transformation. Results Total distance per minute exhibited the smallest variation when both the full-match and peak 5-min running periods were examined (CV = 6.8-10%). Sprint-efforts were the most variable during a full-match (CV = 53%), whilst high-speed running per minute exhibited the greatest variation in the post-peak 5-min period (CV = 143%). Peak running periods were observed as slightly more variable than full-match analyses, with the post-peak period very-highly variable. Variability of Accelerations (CV = 17%) and Player Load (CV = 14%) was lower than that of high-speed actions. Positional differences were also present, with centre backs exhibiting the greatest variation in high-speed movements (CV = 41-65%). Conclusions Practitioners and researchers should account for within player variability when examining match performances. Identification of peak running periods should be used to assist worst case scenarios. Whilst micro-sensor technology should be further examined as to its viable use within match-analyses.

Journal of Science and Medicine in Sport, 21(1)
Josh Trewin
Josh Trewin
Data Scientist

I’m a data scientist, learning my way through R / Python and applying to football data from StatsBomb, provided for free through GitHub. Follow my journey on here or Twitter to find out when I add new content.

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