Minimum Violations and Predictive Meta-Rankings for College Football

作     者：Coleman, B. Jay 

作者机构：Univ N Florida Dept Management Coggin Coll Business Jacksonville FL 32224 USA 

出 版 物：《NAVAL RESEARCH LOGISTICS》 (海军后勤学研究)

年 卷 期：2014年第61卷第1期

页      面：17-33页

核心收录：

学科分类：11[军事学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 

主　　题：sports minimum violations ranking integer programming applications forecasting 

摘      要：This article presents two meta-ranking models that minimize or nearly minimize violations of past game results while predicting future game winners as well as or better than leading current systemsa combination never before offered for college football. Key to both is the development and integration of a highly predictive ensemble probability model generated from the analysis of 36 existing college football ranking systems. This ensemble model is used to determine a target ranking that is used in two versions of a hierarchical multiobjective mixed binary integer linear program (MOMBILP). When compared to 75 other systems out-of-sample, one MOMBILP was the leading predictive system while getting within 0.64% of the retrodictive optimum;the other MOMBILP minimized violations while achieving a prediction total that was 2.55% lower than the best mark. For bowls, prediction sums were not statistically significantly different from the leading value, while achieving optimum or near-optimum violation counts. This performance points to these models as potential means of reconciling the contrasting perspectives of predictiveness versus the matching of past performance when it comes to ranking fairness in college football. (c) 2013 Wiley Periodicals, Inc. Naval Research Logistics 61: 17-33, 2014