Processes of commercialisation and globalisation have changed professional football and the composition of football teams fundamentally. Against the background of these shifting conditions we investigate to what extent the success of football teams in their national leagues is determined by: (a) the monetary value of the team expressed in its market value, (b) the inequality within the team, (c) the cultural diversity of the team, and (d) the degree of fluctuation among the team members. The empirical analysis refers to five football seasons, spanning from 2011/2012 until 2015/2016, and includes the twelve most important European football leagues. The findings demonstrate that success in national football championships is highly predictable. The market value of a team is by far the most important single predictor, whereas different features of a team’s composition – inequality, cultural diversity, and fluctuation – are less decisive. However, the market value of a team does not play the same role in all of the leagues. The lower the degree of financial inequality in a league, the lower the impact of the market value on teams’ performance.
Table 1: Correlations between team performance, market value, inequality, diversity and fluctuation (1) (2) Pearson Correlations (3) (4) (1) Team Performance -(2) Market Value of Players .76** -(3) Inequality in the Team (4) Cultural Diversity .23** .18** .25** .20** -.14** --
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(5) Team Fluctuation .28** .28** .08* .09** Notes: N = 1,074. Significance: +p<.10; *p<.05; **p<.01. To test our hypotheses more systematically we employ multiple regression analyses (Table 2). The dependent variable consists of the number of points earned by the end of a season. This score not only varies across teams in the same league, but to a lesser degree also across different leagues. This variation is essentially due to the different numbers of teams and thus different number of fixtures. The more teams there are in a league, the higher the average score of the teams at the end of the season. Therefore, fixed effects for all leagues are included in the models that account for these differences in average scores. However, as our research question focuses on the prediction of success within leagues, these effects are irrelevant and will not be discussed any further. The independent variables are gradually
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As we have assumed non-linear effects for some of the variables, squared terms are included in addition to the main explanatory variables. 11 (5) -(a) The models reveal a strong dependency of success on the mean market value of players before the season has started. The more valuable a squad is at the beginning of the season, the higher their points score at the end. By increasing the team market value by one standard deviation, a club can expect almost an additional 12.7 points at the end of the season (model I). How much money a club would have to actually invest in order to improve the squad by one standard deviation is dependent on the absolute level of dispersion within the league. In the Greek league the one with the lowest market value in our analysis the average market value per player would have to be raised by 588,000. For a squad with 25 players, 14.7 million would be needed. In the English league the most expensive one with regards
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4 million per player to increase the team market value by one standard deviation. This amounts to more than 134 million for a club with 25 players. Despite such different sums, they would provide the clubs with the same competitive advantage in their respective national leagues, i.e. about an additional 12.7 points. Of course, this advantage will only be realised if the other clubs in the same league do not invest in their squads as well. The relationship between the players market values and performance is not strictly linear though and can be better described as a non-linear relationship, as demonstrated by the significant squared term in model II. Through investments in a squad, a below-average performing team can easily turn into a good one, while it is harder to increase the quality of an already high-performing team by buying more
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