This page provides a reference list of academic papers on rating sports teams or predicting game outcomes.  An archive of all the publicly-available papers themselves may be downloaded here.

[Annis 2005] David H. Annis, Bruce A. Craig, "Hybrid Paired Comparison Analysis, with Applications to the Ranking of College Football Teams," Journal of Quantitative Analysis in Sports, Volume 1, Issue 1, 2005.
[Ashburn  2007] James R. Ashburn, Paul M. Colvert, "A Bayesian Mean-Value Approach
with a Self-Consistently Determined Prior Distribution for the Ranking of College Football Teams." 
[Balreira 2014] Eduardo Cabral Balreira, Brian K. Miceli and Thomas Tegtmeyer, "An Oracle method to predict NFL games", Journal of Quantitative Analysis in Sports. Volume 10, Issue 2, Pages 183–196, ISSN (Online) 1559-0410, ISSN (Print) 2194-6388,DOI: 10.1515/jqas-2013-0063, March 2014 
[Barrow 2013] D. Barrow, I. Drayer, P. Elliott, G. Gaut, and B. Osting, "Ranking rankings: an empirical comparison of the predictive power of sports ranking methods," 2013.
[Bashuk 2012] Mark Bashuk, "Using Cumulative Win Probabilities to Predict NCAA Basketball Performance," MIT Sloan Sports Analytics Conference 2012.
[Bassett 1996] Gilbert W. Bassett, "Predicting the Final Score."
[Bassett 1997] Gilbert W. Bassett, "Robust Sports Ratings Based on Least Absolute Error,"  American Statistician, May 1997, Vol. 51, No. 2.
[Beckler 2009] "NBA Oracle," CMU Classwork.
[Berri 1999] David J. Berri, "Who is ‘Most Valuable’? Measuring the Player’s Production of Wins in the National Basketball Association," Nanage. Decis. Econ. 20: 411–427 (1999).
[Bethel 2005] Roy Bethel, "A Solution To The Unequal Strength Of Schedule Problem."
[Brent 2010] Richard P. Brent, "Note on Computing Ratings from Eigenvectors," [math.NZ].
[Callaghan, et al, 2004] Thomas Callaghan, Peter J. Mucha, and Mason A. Porter, "The Bowl Championship Series: A Mathematical Review," Notices of the AMS, September 2004, pp 887-893.
[Callaghan, et al, 2006] Thomas Callaghan, Peter J. Mucha, and Mason A. Porter, "Random Walker Ranking for NCAA Division I-A Football," arXiv:physics/0310148v4.
[Carlin 1994] Bradley P. Carlin, "Improved NCAA Basketball Tournament Modeling via Point Spread and Team Strength Information"
[Carlin 2005] Jarad B. Niemi, Bradley P. Carlin, and Jonathan M. Alexander, "Identifying and Evaluating Contrarian Strategies for NCAA Tournament Pools."
[Caruana 2004] Rich Caruana, et al, "Ensemble Selection from Libraries of Models," Proceedings of the 21rd International Conference on Machine Learning, Banff, Canada, 2004.
[Caruana 2006] Rich Caruana, and Alexandru Niculescu-Mizil, "An Empirical Comparison of Supervised Learning Algorithms," Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, PA, 2006.
[Caudill 2010] Steven B. Caudill and Franklin G. Mixon, Jr., "Legends of the Fall: A Historical Ranking System Using a  Logistic Transformation of Pairwise Comparisons," International Journal of Applied Economics, 7(1), September 2010, pp. 21-27.
[Chen 2011]  Leland Chen, Joseph Huang, and Ryan Thompson, "Bayesian Skill Ranking," 2011.
[Clay 2014] Clay, Daniel, "Player Rotation, On-court Performance and Game Outcomes in NCAA Men's Basketball", International Journal of Performance Analysis in Sport · August 2014
[Clay 2015] Clay, Daniel, "Geospatial Determinants of Game Outcomes in NCAA Men’s Basketball," International journal of sport and society 02/2015; 4(4):71-81.
[Colley 2002] Wesley N. Colley, "Colley’s Bias Free College Football Ranking Method: The Colley Matrix Explained,"
[Coulom 2008] Rémi Coulom, "Whole-History Rating: A Bayesian Rating System for Players of Time-Varying Strength," Computers and Games, Lecture Notes in Computer Science, 2008, Volume 5131/2008, 113-124.
[Dani 2006] Varsha Dani, et al, "An Empirical Comparison of Algorithms for Aggregating Expert Predictions," 2006.
[Dietterich 1999] Thomas G. Dietterich, "An Experimental Comparison of Three Methods for Constructing Ensembles of Decision Trees: Bagging, Boosting, and Randomization," Machine Learning, 1-22, 1999.
[Di Fatta  2009] Giuseppe Di Fatta, Guy McC. Haworth and Kenneth W. Regan, "Skill Rating by Bayesian Inference," 2009.
[Dubbs 2015]  Dubbs, Alexander, "Statistics-Free Sports Prediction",
[Gill 2008] "Assessing Methods for College Football Rankings," JQAS 2008.
[Gleich 2014] Gleich, David. "PageRank Beyond the Web,"
[Govan 2006] Anjela Y. Govan and Carl D. Meyer, "Ranking National Football League Teams Using Google’s PageRank.
[Govan 2008] Anjela Y. Govan, et al, "Generalizing Google’s PageRank to Rank National Football League Teams,"  SAS Global Forum 2008.
[Govan 2009] Anjela Y. Govan, et al, "Offense-Defense Approach to Ranking Team Sports," Journal of Quantitative Analysis in Sports, 2009.
[Hoegh 2015]  Andrew Hoegh, Marcos Carzolio, Ian Crandell, Xinran Hu, Lucas Roberts, Yuhyun Song and Scotland C. Leman, "Nearest-neighbor matchup effects: accounting for team matchups for predicting March Madness," Journal of Quantitative Analysis in Sports, 2015.
[Hvattum 2010] Lars Magnus Hvattum, , Halvard Arntzen, "Using ELO ratings for match result prediction in association football," International Journal of Forecasting 26 (2010) 460–470.
[Hunter 2004] David R. Hunter, "MM ALGORITHMS FOR GENERALIZED BRADLEY–TERRY MODELS," The Annals of Statistics 2004, Vol. 32, No. 1, 384–406.
[Jacobson 2009] Sheldon H. Jacobson, et al, "Seeding in the NCAA Men’s Basketball Tournament: When Is A Higher Seed Better?", The Journal of Gambling Business and Economics (2009), Vol. 3, No. 2, pp. 63-87.
[Kain 2011] Kyle J. Kain and Trevon D. Logan, "Are Sports Betting Markets Prediction Markets?  Evidence from a New Test," January 2011.
[Keener 1993] James P. Keener, "The Perron-Frobenius Theorem and the Ranking of Football Teams," SIAM Review, Vol. 35, No. 1. (Mar., 1993), pp. 80-93.
[Knorr-Held 1999] Leonhard Knorr-Held, "Dynamic Rating of Sports Teams."
[Kubatko 2007] Justin Kubatko, et al, "A Starting Point for Analyzing Basketball Statistics,"  Journal of Quantitative Analysis in Sports, 2007.
[Loeffelholz 2009] "Predicting NBA Games Using Neural Networks," JQAS 2009.
[Lopez 2015]  Michael J. Lopez  and Gregory J. Matthews, "Building an NCAA men's basketball predictive model and quantifying its success," JQAS 2015.
[Massey 1997] Massey, Kenneth. "Statistical models applied to the rating of sports teams." Bluefield College (1997).
[Mease 2003] David Mease, “A Penalized Maximum Likelihood Approach for the Ranking of College Football Teams Independent of Victory Margins,” The American  Statistician 57, 241-248.
[Melo 2012] Pedro O. S. Vaz De Melo, Virgilio A. F. Almeida, Antonio A. F. Loureiro, and Christos Faloutsos, "Forecasting in the NBA and Other Team Sports: Network Effects in Action," ACM Transactions on Knowledge Discovery from Data, Vol. 6, No. 3, Article 13, October 2012.
[Menke 2006] Joshua E. Menke and Tony R. Martinez, "A Bradley-Terry Artificial Neural Network Model for Individual Ratings in Group Competitions," 2006.
[Minton 1992] Minton, R. "A mathematical rating system." UMAP Journal 13.4 (1992): 313-334.
[Orendorff 2007] "First-Order Probabilistic Models for Predicting the Winners of Professional Basketball Games," JQAS 2007.
[Padgett 2004]  Joshua L. Padgett, "Strength Of Victory Based Ranking System," course paper.
[Page 2007] Garritt L. Page, Gilbert W. Fellingham, C. Shane Reese, "Using Box-Scores to Determine a Position’s Contribution to Winning Basketball Games," Journal of Quantitative Analysis in Sports, Volume 3, Issue 4 2007 Article 1.
[Park 2005] Juyong Park and M. E. J. Newman, "A network-based ranking system for US college football," Department of Physics and Center for the Study of Complex Systems, University of Michigan, Ann Arbor, MI, 2005.
[Parker 2010]  Ryan J. Parker, "Modeling Basketball's Points per Possession With Application to Predicting the Outcome of College Basketball Games," College of Charleston.
[Pugh 2010] Steven Pugh, "Compughter Ratings Theory," 
[Redmond 2003] Redmond, Charles. "A natural generalization of the win-loss rating system." Mathematics magazine (2003): 119-126.
[Schwertman 1996] Neil C. Schwertman; Kathryn L. Schenk; Brett C. Holbrook, "More Probability Models for the NCAA Regional Basketball Tournaments," The American Statistician, Vol. 50, No. 1. (Feb., 1996), pp. 34-38.
[Sokol 2006]  Paul Kvam and Joel S. Sokol, "A Logistic Regression/Markov Chain Model For NCAA Basketball," Naval Research Logistics 53 (2006).
[Sokol 2010] Mark Brown and Joel Sokol, "An Improved LRMC Method for NCAA Basketball Prediction," (in revision).
[Sokol 2012]  Mark Brown, Paul Kvam, George Nemhauser, Joel Sokol, "Insights from the LRMC Method for NCAA Tournament Prediction", MIT Sloan Sports Analytics Conference 2012.
[Stanke 2012]  Luke Stanke, "Can Statistical Models Out-predict Human Judgment?: Comparing Statistical Models to the NCAA Selection Committee," MIT Sloan Sports Analytics Conference 2012.
[Strumbelj 2012] Erik Štrumbelj, Petar Vračar, "Simulating a basketball match with a homogeneous Markov model and forecasting the outcome," International Journal of Forecasting 28 (2012) 532–542. 
[Trono 2007] Trono, John A., "An Effective Nonlinear Rewards-Based Ranking System," Journal of Quantitative Analysis in Sports, Volume 3, Issue 2, 2007.
[Trono 2010] "Rating/Rankings Systems, Post-Season Bowl Games, and 'The Spread'", JQAS 2010
[Warner 2010]  Jim Warner, "Predicting Margin of Victory in NFL Games: Machine Learning vs. the Las Vegas Line."
[West  2006] Brady T. West, "A Simple and Flexible Rating Method for Predicting Success in the NCAA Basketball Tournament," Journal of Quantitative Analysis in Sports, 2006.
[West 2008] Brady T. West, Madhur Lamsal, "A New Application of Linear Modeling in the Prediction of College Football Bowl Outcomes and the Development of Team Ratings," Journal of Quantitative Analysis in Sports, 2008.
[Wigness 2010]  "A New Iterative Method for Ranking College Football Teams," JQAS 2010.
[Yuan 2015] "A mixture-of-modelers approach to forecasting NCAA tournament outcomes," Journal of Quantitative Analysis in Sports, 2015.