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

J Sci Med Sport. 2018 Feb;21(2):196-201. doi: 10.1016/j.jsams.2017.05.009. Epub 2017 May 25.

Abstract

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=6.8-7.2%). 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.

Keywords: Accelerations; Accelerometer; GPS; High-speed running; Player Load.

MeSH terms

  • Acceleration
  • Athletic Performance / physiology
  • Athletic Performance / statistics & numerical data
  • Female
  • Geographic Information Systems
  • Humans
  • Longitudinal Studies
  • Running / physiology*
  • Running / statistics & numerical data
  • Soccer / physiology*
  • Soccer / statistics & numerical data
  • Task Performance and Analysis