Superstar Salaries and Soccer Success

Abstract

This study estimates the relationship between production and salary structure in Major League Soccer (MLS), the highest level of professional soccer (association football) in North America. Soccer production, measured as league points per game, is modeled as a function of a team’s total wage bill, the distribution of the team’s wage bill, and goals per game. Both the Gini coefficient and the coefficient of variation are utilized to measure salary inequality. The results indicate that production in MLS is negatively responsive to increases in the salary inequality; the estimation model with the best fit uses the coefficient of variation to measure dispersion. Furthermore, MLS teams appear to be constrained in their choices of salary inequality by the salary cap and other regulations.

How to be Successful in Football: A Systematic Review

“…They revealed that salary inequality has a negative effect on success but the wage bill of a team has a positive relationship with success by a similar amount. This results support the cohesion theory [69]. Secondary data Three independent variables were significant factors on the final outcome: the quality of the opposition (p<0.001), the minute in which the first goal is scored (p<0.01) and the team scoring first (p<0.001); teams that scored first scored 1.88 goals more than the opponent…”

“…Passes and shot accuracy turned out to be better predictors for points. Coates, Frick and Jewell [69] investigated the relationship between salary structure and success. They revealed that salary inequality has a negative effect on success but the wage bill of a team has a positive relationship with success by a similar amount.…”

Does Experience Matter? Salary Dispersion, Coaching, and Team Performance

“…Studies of the role and influence of managers in business and managers or coaches in sports are common (Britton 2013;Hawkins 2011;Weinberg and Gould 2007). Similarly common are studies of the impact of salary distribution on production within a firm or sports team (Breunig et al 2014;Coates, Frick, and Jewell 2016;Katayama and Nuch 2011;Simmons and Berri 2011). This study is one of a very few that combine the influence of the coach and the influence of salary distribution into a single model (Berri and Jewell 2004) and the first to consider the possibility that coaches alter the manner in which salary distribution affects production.…”

“…The relationship between a team's salary distribution (as measured by the Gini coefficient, coefficient of variation, or the Herfindahl-Hirschman Index) and team performance has been an active area of research on professional team sports. A number of researchers have examined whether the salary structure of a team has an effect on its on-field success (Breunig et al 2014;Coates, Frick, and Jewell 2016;Debrock, Hendricks, and Koenker 2004;Simmons and Berri 2011). There are two competing hypotheses in the literature regarding the influence of a team's salary distribution on its performance: that wider dispersion raises performance and that wider dispersion harms performance.…”

“…However, Breunig et al (2014) found, for major league baseball (MLB), that greater salary inequality may lead to lower productivity, especially if cooperation between players (or workers) is an important feature of the production function (Levine, 1991;Kahn 2000). Moreover, Coates, Frick, and Jewell (2016) explored data from MLS clubs and found that the more equal the salary structure, the higher is the sporting performance. Therefore, there is no consensus on the effect of salary variation on performance.…”