The intention of this paper is to provide new academic insights regarding an economically explainable valuation of transfer prices for European football players based on mathematical modeling. Football is the most popular sport in the world followed by approximately 3.5 billion people. The increasing commercialization and professionalization of the industry implies that every area of a football club is constantly put to the test for improvements. Especially after suffering financially under the consequences of the worldwide pandemic, clubs focus not only on sporting success but also on financial survival. Only financially stable clubs have the resources to be more successful. An expensive team does not have to be successful in terms of sports performance. However, a successful team in sports is expensive in the long run. Increasing digitalization offers new revenue potentials for football clubs that focus on selling merchandise in addition to gameday revenues and its media exploitation rights. However, player transfers have become increasingly important because these costs and revenues increased substantially in the relevance of a club’s financial situation. Regarding transfer costs, the question arises as to how transfer fees are determined and which factors have a major influence here. Clubs try to find new ways of evaluating the potential profit of player transfers to lower the risk of failed player investments. The aim of this article is to quantify the popularity of a football player in terms of his merchandising potential to amortize his transfer price. The mathematically formulated relationship calculates a reference value for a player, taking performance, age, number of customers purchasing merchandise, and player position into account. The information gained can be used by managers of European football clubs as a guide in transfer negotiations. For 6907 players of the European top leagues, we analyzed data in the period from 2003 to 2019. For 409 players in the season of 2018/2019 complete data sets were available, so that a model for calculating a theoretical transfer fee for a player during that season could be determined. The results of the study and the developed model suggest that, based on the available data, a football club should offer either one-year or three-year contracts to a transferred player, depending on the anticipated profit margin of merchandise sales and the quota of potential buyers of the products representing a percentage of the number of customers purchasing merchandise. This information gives football club’s management the chance to make better transfer decisions for the individual situation of the player and the club itself. Due to the increased importance of transfers on a football club’s financial performance, better transfer decision making leads to an improved financial stability of the respective clubs and eventually to sporting success.

No abstract

Research background: Professional football is becoming more and more commercialized. The most recent attempt to establish a “Super League” failed, but the big football clubs are nevertheless trying to generate success in sports through increasingly high player transfers. Purpose of the article: The aim of this paper is to empirically test the above statements and assumptions. On the one hand, the question arises whether the placement in a ranking table of a competition depends on the investment volume. At the same time, it is analyzed whether this relationship exhibits stability over time. Table placement was chosen because it has a direct influence on the distribution of funds in a competition. In addition, individual matches are analyzed to determine whether the investment volume has a statistically significant influence on winning a match. Methods: The years 2014 to 2020 of the competitions of one of the top five European leagues, the German Bundesliga, are prepared in a database. In addition to the player results and table positions, the market values of the players in the season are used. All data is taken from the website Transfermarkt.de. In the context of the table rankings, a regression analysis is performed to explain the place in the table by the market value of the team. When analyzing individual matches, the team value on the field in each case is determined and the differences between the values of the teams playing are established. These differences are explained as a dependent variable in a regression line with three dummy variables: won, lost, and draw. Findings & Value added: The results enable the management of football clubs to make an investment decision for a successful future. They show, on the one hand, whether the team value has an influence on the league position and, on the other hand, on the match result.