Offense-Defense Approach to Ranking Team Sports

The rank of an object is its relative importance to the other objects in the set. Often a rank is an integer assigned from the set 1,...,n. A ranking model is a method of determining a way in which the ranks are assigned. Usually a ranking model uses information available on the objects to determine their respective ratings. The most recognized application of ranking is the competitive sports. Numerous ranking models have been created over the years to compute the team ratings for various sports. In this paper we propose a flexible, easily coded, fast, iterative approach we call the Offense-Defense Model (ODM), to generating team ratings. The convergence of the ODM is grounded in the theory of matrix balancing.

[1]  L. Mirsky,et al.  The Distribution of Positive Elements in Doubly‐Stochastic Matrices , 1965 .

[2]  Richard Sinkhorn,et al.  Concerning nonnegative matrices and doubly stochastic matrices , 1967 .

[3]  Richard Sinkhorn Diagonal equivalence to matrices with prescribed row and column sums. II , 1967 .

[4]  S. Ross A First Course in Probability , 1977 .

[5]  Gabriel Pinski,et al.  Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics , 1976, Inf. Process. Manag..

[6]  Nancy L. Geller,et al.  On the citation influence methodology of Pinski and Narin , 1978, Inf. Process. Manag..

[7]  T. Saaty Rank According to Perron: A New Insight , 1987 .

[8]  J. Lorenz,et al.  On the scaling of multidimensional matrices , 1989 .

[9]  Stavros A. Zenios,et al.  A Comparative Study of Algorithms for Matrix Balancing , 1990, Oper. Res..

[10]  George W. Soules The rate of convergence of Sinkhorn balancing , 1991 .

[11]  Stephen R. Clarke,et al.  Predictions and home advantage for Australian rules football , 1992 .

[12]  Leonid Khachiyan,et al.  On the rate of convergence of deterministic and randomized RAS matrix scaling algorithms , 1993, Oper. Res. Lett..

[13]  James P. Keener,et al.  The Perron-Frobenius Theorem and the Ranking of Football Teams , 1993, SIAM Rev..

[14]  Michael H. Schneider,et al.  Scaling Matrices to Prescribed Row and Column Maxima , 1994, SIAM J. Matrix Anal. Appl..

[15]  L. Khachiyan,et al.  On the Complexity of Matrix Balancing , 1997 .

[16]  Alan M. Nevill,et al.  Modelling performance at international tennis and golf tournaments: is there a home advantage? , 1997 .

[17]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

[18]  Alberto Borobia,et al.  Matrix scaling: A geometric proof of Sinkhorn's theorem , 1998 .

[19]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[20]  Jon Kleinberg,et al.  Authoritative sources in a hyperlinked environment , 1999, SODA '98.

[21]  S. Clarke,et al.  Using official ratings to simulate major tennis tournaments , 2000 .

[22]  Carl D. Meyer,et al.  Matrix Analysis and Applied Linear Algebra , 2000 .

[23]  D. Ruiz A Scaling Algorithm to Equilibrate Both Rows and Columns Norms in Matrices 1 , 2001 .

[24]  Charles Redmond,et al.  A Natural Generalization of the Win-Loss Rating System , 2003 .

[25]  Warren D. Smith Sinkhorn ratings, and new strongly polynomial time algorithms for Sinkhorn balancing, Perron eigenvectors, and Markov chains , 2005 .

[26]  A. Starnes,et al.  Statistical Models Applied to the Rating of Sports Teams , 2005 .

[27]  Jianbo Shi,et al.  Balanced Graph Matching , 2006, NIPS.

[28]  Joel Sokol,et al.  A logistic regression/Markov chain model for NCAA basketball , 2006 .

[29]  Amy Nicole Langville,et al.  Google's PageRank and beyond - the science of search engine rankings , 2006 .

[30]  Daniel Ruiz,et al.  A Fast Algorithm for Matrix Balancing , 2013, Web Information Retrieval and Linear Algebra Algorithms.

[31]  Philip A. Knight,et al.  The Sinkhorn-Knopp Algorithm: Convergence and Applications , 2008, SIAM J. Matrix Anal. Appl..

[32]  C. D. Meyer,et al.  Generalizing Google ’ s PageRank to Rank National Football League Teams , 2008 .