Pitch actions that distinguish high scoring teams: Findings from five European football leagues in 2015-16

Abstract

Abstract. In order to find the determinants of non-penalty goals scored per match, in association football (soccer), this paper developed a regression model consisting of 8 explanatory variables, based on observations for 98 teams playing in the top tiers of club football in England, Spain, Germany, France and Italy. We started with a framework that considered twenty-one different pitch actions that included both technical and tactical variables. Using data for the 2015-16 football season we narrowed down to the 8 variable model. The paper used a log-linear regression model in order to remove heteroscedasticity. The model estimated the number of non-penalty goals per game with error of less than |0.33| for 93 teams out of 98. For 52 teams the margin of error was less than |0.1|. Shots from penalty box per game, share of shots from goal box in total shots and long pass accuracy were found to have statistically significant positive impact on non-penalty goals scored per game. Share of long passes in total passes and crosses per game have significant negative impact.

Player Valuation in European Football

“…Much work focuses on game play, including rating game actions [9,28], pass prediction [18,5,7,31,13], shot prediction [25], expectation for goals given a game state [8], or more general game strategies [24,3,15,11,12,4,14,1]. Other works try to predict the outcome of a game by estimating the probability of scoring for the individual goal scoring opportunities [10], by relating games to the players in the teams [26], or by using team rating systems [21].…”

Predicting Player Trajectories in Shot Situations in Soccer

“…In many sports (but for the sake of brevity we focus on soccer), work has started on game play. For instance, in soccer, there is work on rating actions [9,36], pass prediction [21,5,7,39,15], shot prediction [29], expectation for goals given a game state [8] or a possession [11], or more general game strategies [28,17,12,14,4,16,1]. Game play information can be used to predict the outcome of a game by estimating the probability of scoring for the individual goal scoring opportunities [10], by relating games to the players in the teams [30], or by using team rating systems [24].…”

Analysis of goal scoring patterns as a factor in understanding the evolution of international cerebral palsy football

“…For example, the scoring rate in the last FIFA World Cup (Russia 2018 FIFA World Cup) was 2.64 goals per match (Kubayi, 2020), and most of the goals came from open play (60.9%; out of which 82.5% were from organized attacks and 17.5% from counterattacks), while a 39.1% came from set pieces (mainly from penalties [34.9%], corner kicks [31.8%] and free kicks [30.3%]) (Kubayi, 2020). In addition, the higher possibilities to score a goal are when players shoot from the penalty and goal areas, rather than from long distances (outside the penalty area) (Sarkar & Chakraborty, 2018). Another highly studied factor is the impact of the first goal on the result, since previous research has observed that scoring the first goal is highly related to eventually winning the match (García-Rubio et al, 2017;Ramos-Pérez et al, 2021).…”