Key performance indicators at FIFA Women's World Cup in different playing surfaces

PLoS One. 2020 Oct 23;15(10):e0241385. doi: 10.1371/journal.pone.0241385. eCollection 2020.

Abstract

The aim of this study was to examine the key performance indicators of female professional soccer players during the 2011 and 2015 FIFA Women's World Cup, played on different surfaces (natural and artificial turf respectively). A total of 438 women from 24 national teams who participated at Canada 2015 (artificial turf) and 283 players from 16 national teams who played in Germany 2011 (natural grass) were selected for this study. The collected data were provided by OPTA Sports. Twenty-nine key performance indicators were included for analysis. The variables were calculated for the total sample and independently by positions (defense, midfielders and forwards) for matches on natural grass (2011) and artificial turf (2015). A Mann-Whitney U test was used out to identify differences between the sport surfaces. Moreover, a discriminant analysis was performed with the forced entry method to find the variables that better differentiated between the FIFA Women's World Cup 2011 (natural grass) and FIFA Women's World Cup 2015 (artificial turf). Key performance aspects were very similar between the two tournaments, but on natural grass, we observed a significantly higher number of total passes, successful dribbles, total tackles, successful tackles and interceptions. However, on artificial turf there were significantly higher percentages of success in total passes, and a higher number of fouls. This is an important factor for the choice of an elite competition surface because technical actions are crucial to the quality of the game and can influence the future behavior of spectators and fans.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Athletic Performance*
  • Female
  • Humans
  • Internationality
  • Soccer / physiology*

Grants and funding

This work was supported by the European University of Madrid, under Grant 2015/UEM08. SM-C received a funding of his Ph.D from University of Castilla-La Mancha (2019/5964).