Actions Speak Louder Than Goals: Valuing Player Actions in Soccer

Assessing the impact of the individual actions performed by soccer players during games is a crucial aspect of the player recruitment process. Unfortunately, most traditional metrics fall short in addressing this task as they either focus on rare actions like shots and goals alone or fail to account for the context in which the actions occurred. This paper introduces (1) a new language for describing individual player actions on the pitch and (2) a framework for valuing any type of player action based on its impact on the game outcome while accounting for the context in which the action happened. By aggregating soccer players' action values, their total offensive and defensive contributions to their team can be quantified. We show how our approach considers relevant contextual information that traditional player evaluation metrics ignore and present a number of use cases related to scouting and playing style characterization in the 2016/2017 and 2017/2018 seasons in Europe's top competitions.Comment: Significant update of the paper. The same core idea, but with a clearer methodology, applied on a different data set, and more extensive experiments. 9 pages + 2 pages appendix. To be published at SIGKDD 201

The role of motion analysis in elite soccer

The optimal physical preparation of elite soccer (association football) players has become an indispensable part of the professional game especially due to the increased physical demands of match-play. The monitoring of players’ work-rate profiles during competition is now feasible through computer-aided motion analysis. Traditional methods of motion analysis were extremely labour intensive and were largely restricted to university- based research projects. Recent technological developments have meant that sophisticated systems, capable of quickly recording and processing the data of all players’ physical contributions throughout an entire match, are now being used in elite club environments. In recognition of the important role motion analysis now plays as a tool for measuring the physical performance of soccer players, this review critically appraises various motion analysis methods currently employed in elite soccer and explores research conducted using these methods. This review therefore aims to increase the awareness of both practitioners and researchers of the various motion analysis systems available, identify practical implications of the established body of knowledge, while highlighting areas that require further exploration

Using network science to analyze football passing networks: dynamics, space, time and the multilayer nature of the game

From the diversity of applications of Network Science, in this Opinion Paper we are concerned about its potential to analyze one of the most extended group sports: Football (soccer in U.S. terminology). As we will see, Network Science allows addressing different aspects of the team organization and performance not captured by classical analyses based on the performance of individual players. The reason behind relies on the complex nature of the game, which, paraphrasing the foundational paradigm of complexity sciences "can not be analyzed by looking at its components (i.e., players) individually but, on the contrary, considering the system as a whole" or, in the classical words of after-match interviews "it's not just me, it's the team".Comment: 7 pages, 1 figur

Squad management, injury and match performance in a professional soccer team over a Championship-winning season

Squad management, injury and physical, tactical and technical match performance were investigated in a professional soccer team across five consecutive league seasons (2008–2013, 190 league games) with specific focus on a championship-winning season (2010/11). For each player, match participation and time-loss injuries were recorded, the latter prospectively diagnosed by the team's physician. Defending and attacking tactical and technical performance indicators investigated included ball possession and possession in opponents' half, passes, forward passes, completed passes and forward passes, crosses and completed crosses, goal attempts and goal attempts on target, successful final third entries, free-kicks and 50/50 duels won/lost. Physical performance measures included total distance and distance covered at high-speeds (≥19.1 km/h). Results showed that during the 2010/11 season, squad utilisation was lowest potentially owing to the observed lower match injury occurrence and working days lost to injury thereby increasing player availability. In 2010/11, the team won both its highest number of points and conceded its lowest number of goals especially over the second half of this season. The team also won its highest number of games directly via a goal from a substitute and scored and conceded a goal first on the highest and lowest number of occasions, respectively. While multivariate analysis of variance (MANOVA) detected a significant difference in some attacking and defensive performance indicators across the five seasons, these were generally not distinguishing factors in 2010/11. Similarly, univariate ANOVAs showed a significant difference in running distances covered across seasons, but the trend was for less activity in 2010/11