From the pitch to the market: how game outcomes score on stock prices

Abstract

This study investigates how football match outcomes affect the stock prices of publicly traded European football clubs. Using panel data from Manchester United, Borussia Dortmund, Juventus, Lazio, and Lyon over the 2017–2024 seasons, I examine investor response to match performance. The dependent variable is the log return from the most recent available pre-match trading price (match day or day before) to the trading day after the match. Key explanatory variables include expected goals difference (xG – xGA), actual goal difference, match result dummies (loss and draw, with win as the reference), and a European competition indicator. Expected goals (xG) are statistical estimates based on the quality of a team's scoring chances, incorporating factors such as shot location, assist type, and goalkeeper position. An interaction term between the xG difference and European competition is also included. After addressing non-stationarity and applying fixed and random effects estimations, I find that expected goals difference significantly influences post-match stock returns, while match result and actual goal difference do not show consistent effects. These results suggest that investors are more responsive to underlying match performance than to final scorelines alone. This thesis contributes to the literature on sports, financial and behavioural economics/finance by showing that stock markets may be more sensitive to advanced performance metrics, like expected goals, than to basic match outcomes.