Faculty Advisor

Jayson D Wilbur

Abstract

Each year millions of dollars are wagered on the NFL during the season. A few people make some money, but most often the only real winner is the sports book. In this project, the effect of data transformation on the paired comparison model of Glickman and Stern (1998) is explored. Usual transformations such as logarithm and square-root are used as well as a transformation involving a threshold. The motivation for each of the transformations if to reduce the influence of blowouts on future predictions. Data from the 2003 and 2004 NFL seasons are examined to see if these transformations aid in improving model fit and prediction rate against a point spread. Strategies for model-based wagering are also explored.

Publisher

Worcester Polytechnic Institute

Degree Name

MS

Department

Mathematical Sciences

Project Type

Thesis

Date Accepted

2005-05-05

Accessibility

Unrestricted

Subjects

Bayesian, NFL, Bradley-Terry, Sports betting, Mathematical models, Bayesian statistical decision theory, Football

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