Distinguishing Between Roles of Football Players in Play-by-play Match Event Data

TL;DR

This paper proposes a method to automatically identify player roles in football using play-by-play event data, aiding teams in assessing player fit beyond traditional statistics.

Contribution

It introduces a set of 21 player roles and a novel method for role identification from match event data, enhancing player analysis capabilities.

Findings

Effective role classification from event data

Improved understanding of player functions in matches

Potential to inform recruitment and team strategy

Abstract

Over the last few decades, the player recruitment process in professional football has evolved into a multi-billion industry and has thus become of vital importance. To gain insights into the general level of their candidate reinforcements, many professional football clubs have access to extensive video footage and advanced statistics. However, the question whether a given player would fit the team's playing style often still remains unanswered. In this paper, we aim to bridge that gap by proposing a set of 21 player roles and introducing a method for automatically identifying the most applicable roles for each player from play-by-play event data collected during matches.