NFL Betting Market: Using Adjusted Statistics to Test Market Efficiency and Build a Betting Model

• Main Author: Donnelly, James P
• Format: Others
• Published: Scholarship @ Claremont 2013
• Subjects: NFL; betting; adjusted statistics; Efficient Market Hypothesis; Applied Statistics; Economics; Statistical Models; Statistics and Probability
• Online Access: http://scholarship.claremont.edu/cmc_theses/721; http://scholarship.claremont.edu/cgi/viewcontent.cgi?article=1822&context=cmc_theses

The use of statistical analysis has been prevalent in the sports gambling industry for years. More recently, we have seen the emergence of "adjusted statistics", a more sophisticated way to examine each play and each result (further explanation below). And while adjusted statistics have become commonplace for professional and recreational bettors alike, little research has been done to justify their use. In this paper the effectiveness of this data is tested on the most heavily wagered sport in the world – the National Football League (NFL). The results are studied with two central questions in mind: Does the market account for the information provided by adjusted statistics? And, can this data be interpreted to create a profitable betting strategy? First, the Efficient Market Hypothesis is introduced and tested using these new variables. Then, a betting model is built and tested.