Investigating the efficiency of the Asian handicap football betting market with ratings and Bayesian networks

Author:

Constantinou Anthony C.12

Affiliation:

1. Bayesian Artificial Intelligence Research lab, School of Electronic Engineering and Computer Science, Queen Mary University of London (QMUL), London, E1 4NS, UK

2. The Alan Turing Institute, UK

Abstract

Despite the massive popularity of the Asian Handicap (AH) football (soccer) betting market, its efficiency has not been adequately studied by the relevant literature. This paper combines rating systems with Bayesian networks and presents the first published model specifically developed for prediction and assessment of the efficiency of the AH betting market. The results are based on 13 English Premier League seasons and are compared to the traditional market, where the bets are for win, lose or draw. Different betting situations have been examined including a) both average and maximum (best available) market odds, b) all possible betting decision thresholds between predicted and published odds, c) optimisations for both return-on-investment and profit, and d) simple stake adjustments to investigate how the variance of returns changes when targeting equivalent profit in both traditional and AH markets. While the AH market is found to share the inefficiencies of the traditional market, the findings reveal both interesting differences as well as similarities between the two.

Publisher

IOS Press

Reference24 articles.

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