Abstract

Player pathways: Understanding career paths that deliver success for professional football players and clubs

In football, as in any profession, it is understood that careful career decisions could be critical in dictating one’s potential for professional success. Similarly, the well-considered formation of a cohesive, complimentary team is a critical ingredient in determining club performance. But what are the journeys that deliver such individual success, and how might one navigate the optimal path to maximise their career trajectory and achieve their desired outcomes? Moreover, is there a model combination of career histories and player backgrounds that can help distinguish between teams that have experienced different levels of success?

This data challenge considers whether it is possible to measure different definitions of success and identify key determinants for achieving each outcome. The study aims to derive preliminary insights for advising players and clubs in crucial decision making processes, primarily in relation to those made in the arena in which football players are available for transfer to clubs - the so called ‘transfer market’.

The challenge focuses on the career paths and other key attributes of players, and seeks to identify the journeys and characteristics which deliver most success to both individual players and clubs. This is of particular interest to PlayerLens, the challenge owner, who work closely with both players and teams at the point of considering transfer opportunities.

Methods for understanding indicators of performance outcome are presented. These could be used to gain insight into questions such as, ‘Is there an archetypal career path to the highest level of football?’, ‘Is there a recommended age at which players should change club?’, ‘Is it beneficial to experience lower league football?’ and ‘Is there an optimal composition of players that a club should aim for, with regards to player pathways?’.

Citation information

Data Study Group team. (2019, November 29). Data Study Group Final Report: PlayerLens. Zenodo. http://doi.org/10.5281/zenodo.3558253

Additional information

Aditi Shenvi, University of Warwick
Amanda Otley, University of Leeds
Basma Albanna, University of Manchester
Bhavan Chahal, University of Warwick
Daniel Justus, Digital Catapult
Haoyuan Zhang, Queen Mary University of London
Jacopo Diquigiovanni, University of Padua (Italy)
Naomi Muggleton, Warwick Business School

Turing affiliated authors