Ohio State's Sports and Society Initiative is committed to advancing research at all levels of the university, especially among our undergraduate and graduate students.
2020 OSU Sports and Society Initiative Undergraduate Research Fair participants
- DeCort, Callie. "How Cost of Attendance Stipends are Creating New Precedents in NCAA Athletics."
- Feldman, Zach. "NFL Expected Completion Probability: Modeling passes in the NFL with publicly available data and reproducible research."
- Patel, Nayan. “A Model for Predicting D1 NCAA Hockey Games.”
- Sichel, Adam. "The Economic and Social Effects of Legalized Sports Gambling."
- Taylor, Corey. "Regression Discontinuities in the NFL Draft."
- Toorchen, Jasmine. "Study of Track Surface Type on Injury and Death in New York Horse Racing."
- Williams, Brooke. “Predicting Free Throws in the NBA.”
- Williams, Alexander, Clarke, Ben, and Seth Brugler. "MAYFIELD: Machine Learning Algorithm for Yearly Forecasting Indicators and Estimation of Long-run Player Development."
2019 Presentations and Submissions from SSI-funded Students
- Davis, Evan, and Chris Knoester. 2019. "Analyzing the Great Sport Myth: Evidence from the NSASS." Presented at the 2019 North American Society for the Sociology of Sports meetings in Virginia Beach, VA.
- Rockhill, Carter, Knoester, Chris, and Brian Turner. 2019. "Sports and Non-sports based Racial-Ethnic Prejudice."
- Presented at the 2019 North American Society for the Sociology of Sports meetings in Virginia Beach, VA.
- Tompsett, James, and Chris Knoester. 2019. "The Making of a College Athlete: High school experiences, socioeconomic advantages, and the likelihood of playing college sports." Presented at the 2019 North American Society for the Sociology of Sports meetings in Virginia Beach, VA.
- Tompsett, James, and Chris Knoester. "Family Socioeconomic Status and College Attendance: A consideration of individual-level and school-level effects" (under review)
- Ungureanu, Tiberiu. 2019. “Complementarity and Competency-Destroying Events: A comparative study of the American League and National League, before and after the introduction of the designated hitter.” Abstract submitted for the 2020 MIT Sloan Sports Analytic Conference Research Paper Competition.
- Williams, Alexander, Brugler, Seth, and Benjamin Clarke. 2019. "A Fast Approximate K-Nearest Neighbor Machine Learning Algorithm for NFL Career-Arc Regression.” Abstract submitted for the 2020 MIT Sloan Sports Analytic Conference Research Paper Competition. Full paper invited for review.
- Williams, Alexander. 2019. “Rationality and Efficiency in NFL Gambling Markets.” (under review)