Undergraduate Research Paper
The history of wagering predictions and their impact on wide reaching disciplines such as statistics and economics dates to at least the 1700’s, if not before. Predicting the outcomes of sports is a multibillion-dollar business that capitalizes on these tools but is in constant development with the addition of big data analytics methods. Sportsline.com, a popular website for fantasy sports leagues, provides odds predictions in multiple sports, produces proprietary computer models of both winning and losing teams, and provides specific point estimates. To test likely candidates for inclusion in these prediction algorithms, the authors developed a computer model, and test its accuracy compared to the professional black box model. The result, named the Turnover Model, has consistent performance with Sportsline.com in two cases, the moneyline and over/under wagers, and a superior performance in the against the spread wager. Logistic regression analysis was then employed to determine what factors contributed to this superior performance. Further work will refine this model to incorporate additional variables.
University of Washington Tacoma
TBUS 469 Undergraduate Research
Teeter, Anthony and Bergman, Margo
"Applying the Data: Predictive Analytics in Sport,"
Access*: Interdisciplinary Journal of Student Research and Scholarship: Vol. 4:
1, Article 4.
Available at: https://digitalcommons.tacoma.uw.edu/access/vol4/iss1/4
Applied Statistics Commons, Business Analytics Commons, Business Intelligence Commons, Categorical Data Analysis Commons, Data Science Commons, Number Theory Commons, Numerical Analysis and Computation Commons, Other Applied Mathematics Commons, Other Statistics and Probability Commons, Probability Commons, Social Statistics Commons, Special Functions Commons, Sports Management Commons, Sports Studies Commons, Statistical Models Commons, Statistical Theory Commons