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Comparing player rating systems as a metric for assessing individual performance in soccer
James Ball1, Minh Huynh1, Matthew C Varley1
1Sport, Performance, and Nutrition Research Group, School of Allied Health, Human Services and Sport, La Trobe University, Melbourne, Australia.
Soccer player ratings from WhoScored, FotMob, and Sofascore differ significantly. Offensive metrics most influence ratings, while defensive metrics play a smaller role, indicating systems are not interchangeable.
Area of Science:
- Sports Science
- Data Analytics
- Football Analytics
Background:
- Soccer player performance is often summarized by single-value ratings.
- Several prominent rating systems exist, including WhoScored, FotMob, and Sofascore.
- The comparability and underlying factors of these systems are not fully understood.
Purpose of the Study:
- To investigate the associations between soccer player performance metrics and ratings.
- To compare the influence of various metrics across three major rating systems: WhoScored, FotMob, and Sofascore.
- To assess the interchangeability and potential biases of these rating systems.
Main Methods:
- Utilized data from over 2,100 players across two seasons in top European leagues.
- Employed generalized linear mixed models to analyze the impact of 73 performance metrics on player ratings.
- Performed comparative analysis across WhoScored, FotMob, and Sofascore rating systems.
Main Results:
- Offensive metrics like shots on target, key passes, and successful take-ons significantly influenced all rating systems.
- Defensive metrics, such as clearances, had a smaller but consistent impact on ratings.
- Systematic differences were observed, with WhoScored ratings being significantly lower overall compared to FotMob and Sofascore.
Conclusions:
- Soccer rating systems capture distinct aspects of player performance and are not directly interchangeable.
- The findings highlight the need for careful consideration of rating system methodologies in scouting and player development.
- Further research is recommended to explore the utility of these systems in recruitment and talent identification, addressing transparency and potential biases.
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