Statement of Originality This document is written by student Mats Mackaij who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents. Abstract In this thesis I try to find evidence for the Efficient Market Hypothesis in the men’s football betting market. The main research question this paper tries to answer is: Are popular markets more efficient than less popular markets? I use a large dataset of 102,888 football events, combining the betting odds of a betting exchange and eight bookmakers, to see if the odds of events with a high betting volume are better predictors of the actual outcome than odds of events with a lower betting volume. Intuition obtained from previous studies form the basis of my main hypothesis: more popular matches, i.e. matches with a higher betting volume, will have odds that are more precise estimators of the actual probability of the outcomes than less popular matches. I use a simple probit model on the result of the bet and the implied probability of the odds as the only independent variable. By dividing the dataset into 5 bins according to betting volume, the effect of betting volume on the predictive power of the odds can be evaluated. The result of the analysis shows that the betting volume in football matches has a clear positive relation on the predictive power of the odds. Furthermore it is found that the betting exchange is more efficient than all bookmakers. A simple betting strategy is proposed based on the findings of this paper, yielding substantial ex ante returns. Table of contents Abstract ........................................................................................................................................................................................... 0 1. Introduction ........................................................................................................................................................................ 2 2. Sports betting ..................................................................................................................................................................... 4 2.1 Efficient Market Hypothesis .................................................................................................................................... 4 2.2 Pari-mutuel ....................................................................................................................................................................... 5 2.3 Bookmaker ........................................................................................................................................................................ 7 2.4 Betting exchange............................................................................................................................................................ 8 2.5 Volume ................................................................................................................................................................................ 9 3. Hypothesis ........................................................................................................................................................................ 11 4. Data and Descriptive Statistics............................................................................................................................... 12 5. Empirical Research ...................................................................................................................................................... 15 5.1 Models .............................................................................................................................................................................. 15 5.2 Assessment of the models ...................................................................................................................................... 16 6. Results ................................................................................................................................................................................. 21 6.1 Regression results model 1 ................................................................................................................................... 21 6.2 Second hypothesis ..................................................................................................................................................... 26 6.3 Results regression model 2 ................................................................................................................................... 27 6.4 Simple Betting Strategy ........................................................................................................................................... 28 7. Conclusion and Discussion ....................................................................................................................................... 31 8. Appendix ............................................................................................................................................................................ 33 9. References......................................................................................................................................................................... 37 1 1. Introduction Sports betting is of all times and all cultures. Evidence of early times sports betting is found in North America, where the native population of America bet on foot races and ball games (Stewart Culin, 1921 in Sauer, 1998). In ancient Rome, sports betting was common practice. The famous racetrack Circus Maximus attracted an estimated 260.000 people, many of which had placed bets on the races (Humphrey, 1986). In the United States the first gaming laws were introduced after World War II; which made almost all types of sports betting illegal. Nevada and Maryland were the only two states which had any form of legalized gambling, most of which were slot machines. It was not until 1970 that sports betting became legal in some states (“US Gambling Laws”, 2016). In 1992 sports betting was outlawed in almost all states by the Professional and Amateur Sports Protection Act, leaving only Nevada with all types of legal sports betting. It is however estimated that Americans placed $149 billion in illegal sports bets in 2015 (American Gaming Association, 2016). In Europe, laws about sports betting differ from country to country. In the United Kingdom, bookmaking has been legal by law since the 1960 Act. Sports betting became legal in Spain in the 1980s. In Germany a bookmaker can apply for a license since 2012, which means that the sports betting market is regulated. Other countries with regulated sports betting markets are the Netherlands, France and Australia. ‘In-game’ bets are illegal in Australia, where only pre match bets are allowed. When bookmakers noticed the possibilities of the internet just after the turn of the millennium, online bookmakers started websites to attract more customers. In 2012 the size of the regulated global betting market was $58 billion, which accounted to 14% of total global gambling, according to a report from the European Gambling and Betting Association. The report also states that the unregulated market is many times larger. Estimations say that the total sports betting market, including illegal betting, surpass the trillion US dollars (Daily Mail, 2015). According to Statista, the size of online global gambling in 2015 was $41.36 billion. Along with the online bookmakers came a renewed interest for empirical research in the field of sports betting. One important focus of these papers is the efficiency of these markets as described in the efficient market hypothesis by Malkiel and Fama (1970). In this thesis I try to find evidence for the efficient market hypothesis in the men’s football betting market. My empirical research focuses on the effect of betting volume on the predictive power of odds. The main research question this paper tries to answer is: Are popular markets more efficient than less popular markets? I use a large dataset of 102,888 events, combining the betting odds of a betting exchange and eight bookmakers, to see if the odds of events with a high betting volume are better predictors of the actual outcome than odds of events with a lower betting volume. Insights obtained from previous studies form the basis of 2 my main hypothesis: more popular matches, i.e. matches with a higher betting volume, will have odds that are more precise estimators of the actual probability of the outcomes than less popular matches. I use a simple probit model with the result of the bet as dependent variable and the implied probability of the odds as the only independent variable. By dividing the dataset into 5 bins according to betting volume, the effect of betting volume on the predictive power of the odds can be evaluated. The models are evaluated based on two types of goodness-of-fit tests, often used in previous literature: Pseudo-R2’s and ROC-based statistics. In addition a new goodness-of-fit test is included in the analyses, called the heat map statistic. The result of the analysis shows that the betting volume has a clear positive relation