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Machine-Learning-Based Statistical Arbitrage Football Betting

dc.contributor.authorKnoll, Julian
dc.contributor.authorStübinger, Johannes
dc.date.accessioned2021-04-23T09:30:27Z
dc.date.available2021-04-23T09:30:27Z
dc.date.issued2020
dc.description.abstractAcross countries and continents, football (soccer) has drawn increasingly more attention over the last decades and developed into a huge commercial complex. Consequently, the market of bookmakers providing the possibility to bet on the result of football matches grew rapidly, especially with the appearance of the internet. With a high number of games every week in multiple countries, football league matches hold enormous potential for generating profits over time with the use of advanced betting strategies. In this paper, we use machine learning for predicting the outcome of football league matches by exploiting data about match characteristics. Based on insights from the field of statistical arbitrage stock market trading, we show that one could generate meaningful profits over time by betting accordingly. A simulation study analyzing the matches of the five top European football leagues from season 2013/14 to 2017/18 presented economically and statistically significant returns achieved by exploiting large data sets with modern machine learning algorithms. In contrast to these modern algorithms, the break-even point could not be reached with an ordinary linear regression approach or simple betting strategies, e.g. always betting on the home team.de
dc.identifier.doi10.1007/s13218-019-00610-4
dc.identifier.pissn1610-1987
dc.identifier.urihttp://dx.doi.org/10.1007/s13218-019-00610-4
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/36268
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 34, No. 1
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectBetting strategy
dc.subjectFootball
dc.subjectMachine learning
dc.subjectSports forecasting
dc.subjectStatistical arbitrage
dc.titleMachine-Learning-Based Statistical Arbitrage Football Bettingde
dc.typeText/Journal Article
gi.citation.endPage80
gi.citation.startPage69

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