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Effects of game location and final outcome on game-related statistics in each zone of the pitch in professional football
Abstract:Abstract

The aim of this large-scale study of elite professional football teams was to identify the independent and interactive effects of game location and final outcome on football game-related statistics according to the zone of the pitch in which they occurred. The sample consisted of 1900 games played over five seasons (from 2003–2004 to 2007–2008) of the Spanish Professional Football League. Factor analysis with principal components was applied to the game-related statistics recorded from the games, which limited the analysis to four factors (Factor 1: Turnovers in zone 5.2 and Crosses in zone 4; Factor 2: Goals and shots in zone 5.1, Turnovers in zone 4, and Ball recover in zone 2; Factor 3: Goals and shots in zone 5.2; and Factor 4: Turnovers in zone 5.1). Zone 2 was between the defensive semi-circle area and midfield circle, Zone 4 was between the midfield circle and offensive semi-circle area, Zone 5.1 was the offensive goal area, and Zone 5.2 was the offensive small area). A mixed linear model was applied to identify the effects of game location and final outcome on the previously identified factors. Game location and final outcome main effects were identified for all factors, with home and winning teams having better values. The interaction Location×Outcome was only significant for Factor 4 (Turnovers in zone 5.1). When playing at home, teams had higher frequencies for all analysed variables, probably resulting from home advantage factors such as facility familiarity and/or crowd. Additionally, winning teams’ exhibited different and consistent profiles from drawing and losing teams, mainly discriminated by their ability to recover the ball in Zone 2 and to organize the offence using penetrative passes to Zones 5.2 and 5.1 to increase the number of shots and consequently goals. The trends identified may provide important information for modelling high-level performances.
Keywords:Football  notational analysis  principal components analysis  mixed linear models
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