Predicting Professional Football (Soccer) Player Salaries
Faculty Sponsor(s)
Eric Schuck
Subject Area
Economics
Description
This paper examines the relationship between financial power, player recruitment strategies, and wage determination in professional football clubs, focusing on the Premier League. Professional football is run like a business, and the players are the inputs. Relative to other sports, soccer isn’t paid based on position but rather the individual's qualities. Using a regression analysis based on data from Football Manager 2023, the study investigates the impact of variables such as age, club affiliation, playing position, and appearances on player wages. Surprisingly, age shows a negative correlation with wages, indicating a preference for younger talents. Club affiliation, particularly with top-tier teams like Chelsea and Manchester City, positively influences wage levels. Additionally, how often a player appears for their club and country strongly influences how much they are paid. Research suggests the more Club’s spend on players, the more likely they are to succeed and grow as a business. Other analysis has indicated there has lately been an overassessment of low-level players. These findings offer valuable insights for club managers and talent scouts regarding player recruitment and contract negotiations in the highly competitive football industry.
Recommended Citation
Anderson, Brady, "Predicting Professional Football (Soccer) Player Salaries" (2024). Linfield University Student Symposium: A Celebration of Scholarship and Creative Achievement. Event. Submission 4.
https://digitalcommons.linfield.edu/symposium/2024/all/4
Predicting Professional Football (Soccer) Player Salaries
This paper examines the relationship between financial power, player recruitment strategies, and wage determination in professional football clubs, focusing on the Premier League. Professional football is run like a business, and the players are the inputs. Relative to other sports, soccer isn’t paid based on position but rather the individual's qualities. Using a regression analysis based on data from Football Manager 2023, the study investigates the impact of variables such as age, club affiliation, playing position, and appearances on player wages. Surprisingly, age shows a negative correlation with wages, indicating a preference for younger talents. Club affiliation, particularly with top-tier teams like Chelsea and Manchester City, positively influences wage levels. Additionally, how often a player appears for their club and country strongly influences how much they are paid. Research suggests the more Club’s spend on players, the more likely they are to succeed and grow as a business. Other analysis has indicated there has lately been an overassessment of low-level players. These findings offer valuable insights for club managers and talent scouts regarding player recruitment and contract negotiations in the highly competitive football industry.
