Teamwork and performance in professional women's football: A network-based analysis

Analysis of the underlying tactics and teamwork in women's football is rare and it is unknown how professional women's teams cooperate to be successful. The aim of this study was to investigate teamwork using network analysis while comparing match-outcome, match-type, ladder halves and tournament phases, to determine whether teamwork is related to success. Ball transfer data in 694 matches from the 2015, 2016 and 2017/18 Football Association Women's Super League (FA WSL) seasons; 2016-2018 National Women's Football League (NWSL) seasons; 2013 and 2017 European Cups; and 2011 and 2013 World Cups were analysed. The network metrics: edge density, transitivity, mean distance, out degree centrality, closeness centrality, betweenness centrality and eigenvector centrality were calculated. Success was categorised in match outcomes, ladder halves, tournament phases and ladder positions. It was found that successful professional women's football teams are highly connected (p = 0.006), and the distribution of ball possession is centralised (p = 0.001). There is a tendency for key players to send out a high number of passes, but there is no dependency on these key players for the total ball flow within a team, which is a characteristic that may be unique to women's football. Differences in teamwork exist between single matches and full seasons or tournaments, with successful teams having more effective ball movement and successful passes over the course of a season or tournament (p < 0.001). Moreover, successful league teams have more players with connecting roles than tournament teams and match tactics should be adapted to this.
© Copyright 2023 International Journal of Sports Science & Coaching. SAGE Publications. Kaikki oikeudet pidätetään.

Aiheet: jalkapallo naispuolinen huippu-urheilu analyysi joukkue kilpailu käyttäytyminen peliteko suhde menestyminen Euroopan mestaruus maailmanmestaruuskilpailut suoritusstatistiikka
Aihealueet: urheilukilpailut yhteiskuntatieteet järjestöt ja tapahtumat
Tagging: Netzwerkanalyse Big Data Liga
DOI: 10.1177/17479541221092355
Julkaisussa: International Journal of Sports Science & Coaching
Julkaistu: 2023
Vuosikerta: 18
Numero: 3
Sivuja: 848-857
Julkaisutyypit: artikkeli
Kieli: englanti (kieli)
Taso: kehittynyt