The attacking process in football: a taxonomy for classifying how teams create goal scoring opportunities

The majority of existing Performance Analysis (PA) research has adopted a reductionist approach which considers only selected events such as the number of shots, passes or pass success rates in isolation for analysis (Mackenzie & Cushion, 2013). James (2009) also suggested the obvious problem associated with previous types of research is that simply analysing outcome measures cannot provide meaningful information for improvement without an understanding of the processes undertaken to achieve these outcomes. Understanding the patterns of play exhibited within a game can help coaching be more specific and objective to facilitate the improvement for tactical performances of teams (Tenga et al., 2015). Previous football research has traditionally measured the number of passes (Reep and Benjamin, 1968; Bate, 1988; Hughes and Frank, 2005) or duration of team possessions (Jones et al., 2004; Bloomfield et al., 2005; Lago and Martin, 2007; Lago, 2009) to determine playing styles of team. Although these methods identified different team playing styles, based on overall match statistics, the authors have typically not distinguished the “how” different attacking procedures evolved e.g. how teams initiate or develop build-up play, progress attacks and create goal scoring opportunities. Therefore, this thesis aimed to identify the attacking process to provide practically useful and objective information for applied practice. Study 1 established operational definitions for unstable situations (potential goal scoring opportunities) in football to differentiate stable and unstable game states. Validity tests were conducted by four football coaches and two performance analysts from a professional football club in the English Premier League to create robust operational definitions. After the completion of this process, five specific situations were deemed as unstable situations, which arose due to pitch location, game situation or a specific action i.e. 1) Penalty Box Possession (PBP), 2) Count Attack (CA), 3) Ratio of Attacking to Defending players (RAD), 4) Successful Cross (SC) and 5) Successful Shot (SS). Study 2 produced a framework for the attacking process to describe how all unstable situations arose from the start of each possession. The attacking process was categorised into three independent situations, stable (no advantage), advantage, and unstable (potential goal scoring opportunity) situations. Possessions that did not results in advantage or unstable situations were not analysed. English Premier League football matches (n=38) played by Crystal Palace Football Club in the 2017/2018 season were analysed as an exemplar. Results showed that Crystal Palace FC created a median of 53.5 advantage situations and 23 unstable situations per match. They frequently utilised wide areas (advantage) to progress their attack, which resulted in 26.6% unstable situations i.e. penalty box possessions and successful crosses. However, this was the lowest success rate compared to the other advantage situations. This study provided a novel methodology for classifying the attacking process with a scientifically valid approach for use in the applied world. Study 3 analysed all possessions for Crystal Palace Football Club in the 2017/2018 season, irrespective of whether advantage or unstable situations arose. This enabled the analysis of the influence of situational variables i.e. match venue, opposition quality, match status, key player’s appearance on the attacking process. Appropriate categorisations for independent variables were presented with one problem associated with some previous papers i.e. only using the end of season ranking for team quality (Lago-Peñas & Lago-Ballesteros, 2011; Almeida et al., 2014; Liu et al., 2015; Aquino et al., 2016; Mendez-Dominguez et al., 2019) amended. Crystal Palace had, on average, 91.3 stable, 54 advantage and 26 unstable situations from 114.8 possessions per match which resulted in 12.5 shots. Poisson log-linear regression explained that Crystal Palace created more midfield line breaks; more zone 14, wide area and penalty box possessions and less counter attack chances for different levels of each independent variable e.g. when playing at home compared to away. This suggests that strategy changes depending on the situation would be advantageous. Overall, this thesis aimed to provide useful information for the applied world and close the purported gap between academic and applied areas. This methodology will help teams better analyse opponent’s patterns for creating advantage and unstable situations. Future research should consider using the duration of possessions and pitch area information to further develop the usefulness of the model