An Outcome Determinant Analysis of NCAA Rules Violations: An Application of Multivariate Statistics to the Committee on Infractions' Decisions on Major Cases. Issue 1 (2nd January 2017) - Smith, Joshua R.; Cho, Sungho
ABSTRACT: Since the National Collegiate Athletic Association ("NCAA" hereafter) began enforcing major rules infractions, there have been concerns over the causes and implications of the violations. The penalty structure that the NCAA recently promulgated would be one of the efforts to address such concerns. The project investigated the outcome of the violations with respect to all major infraction cases since 1994. A data set was constructed from all cases reported since 1994. Each case was coded in terms of charged violations, sanctions, level of competition, repeat violation, and whether the institution self-imposed their own penalties. Multiple regression analysis indicates that the aggregate score of violations statistically predicts the severity of sanctions imposed by the Committee. Logistic regression analysis revealed that the repeat violator status and self-imposed penalty would likely influence the severity of sanctions. In contrast, self-discovery or self-reporting does not affect the overall sanctions imposed by the NCAA.