The genesis of data-driven decision-making in the world of soccer tactics : deciphering the potential of big data

Abstract

Arguably, soccer is a more fluid sport than other popular sports such as baseball, American football, and cricket, which explicitly require more discrete ‘plays.’ Moreover, with twenty-two players always committed, it has more moving elements than basketball or ice hockey. From a mathematical perspective, this signifies that soccer has more degrees of freedom than these other sports, making it difficult to evaluate the game using one or a small number of metrics. Over time, this challenge has been made exceedingly more difficult within the soccer community. The availability of data has increased much more rapidly than the scientific advancements required to valorize these data. In the aftermath, most recent research papers have elaborated on specific in-game data separately and how to approach them -not how soccer clubs can assemble and utilize them through big data analytics. In accordance, an exploratory case study conducted in collaboration with a major European soccer organization exhibited their state-of-the-art technology to mainly focus on player profiling supplementary to player recruitment -leaving the business in need of a more tactical advancement. To these ends, this dissertation approaches the socio-technical difficulties on how these player-centric metrics can be utilized to simplify tactical decision-making in soccer.