This study examines inefficiencies in football betting markets by analyzing the gap between bookmaker odds and empirically estimated probabilities. Using English Premier League data and a combination of Markov processes and ordered logit model, the paper constructs a betting strategy that does not rely on superior predictive power but exploits market mispricing. The strategy consistently yields abnormal returns, particularly for draws and away teams, challenging the Efficient Market Hypothesis (EMH). The analysis reveals potential behavioral biases, like emotions, and reliance on heuristics, which distort market prices. Robustness checks with data from other major European leagues support these findings. The results have broader implications for financial markets, as they highlight how behavioral patterns can create exploitable inefficiencies. We conclude that sports betting thus serves as a simplified, data-rich setting to test theories of market behavior, offering insights into how information, psychology, and pricing may interact in both betting and financial domains.
Bruce Lezana (Mon,) studied this question.