Predicting the value of professional sport clubs. A study of European soccer, 2005–2018

This article aims to build a general valuation model that can be applied by investors and current shareholders of professional sport clubs from different countries and leagues. The study is based on panel data on the valuation of soccer clubs published annually by Forbes. Authors analyze all value-drivers that were used previously, expanding the time horizon (number of observations) and incorporating various models including linear and non-linear mixed effect regressions. The best performance is obtained using a mixed-effect model with treebased fi xed part. The following determinants were found signifi cant for the fi xed effect: revenue and number of Google search requests. Analysis of actual deals in 2015–2020 confi rms the model’s predictive ability. It is also shown that since Forbes overestimates the market value of soccer clubs, the proposed model predicts an upper bound on the real value. In this regard, transactions with real value exceeding the estimates are of particular interest. A deeper analysis of such transactions allows to identify additional “non-soccer” factors affecting the deal. Therefore, the proposed model can serve as a tool for the rapid assessment of a soccer club based on open data.