The predictive power of ranking systems in association football

We provide an overview and comparison of predictive capabilities of several methods for ranking association football teams. The main benchmark used is the official FIFA ranking for national teams. The ranking points of teams are turned into predictions that are next evaluated based on their accuracy. This enables us to determine which ranking method is more accurate. The best performing algorithm is a version of the famous Elo rating system that originates from chess player ratings, but several other methods (and method versions) provide better predictive performance than the official ranking method. Being able to predict match outcomes better than the official method might have implications for, e.g., a team’s strategy to schedule friendly games.

[1]  M. Glickman Parameter Estimation in Large Dynamic Paired Comparison Experiments , 1999 .

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

[3]  Tom Minka,et al.  TrueSkillTM: A Bayesian Skill Rating System , 2006, NIPS.

[4]  M. Newman,et al.  A network-based ranking system for US college football , 2005, physics/0505169.

[5]  Ian G. McHale,et al.  Statistical analysis of the effectiveness of the FIFA World Rankings , 2007 .

[6]  Thomas G. Dietterich Multiple Classifier Systems , 2000, Lecture Notes in Computer Science.

[7]  Kurt Hornik,et al.  Forecasting sports tournaments by ratings of (prob)abilities: A comparison for the EURO 2008 , 2010 .

[8]  P. V. Rao,et al.  Ties in Paired-Comparison Experiments: A Generalization of the Bradley-Terry Model , 1967 .

[9]  Richard Pollard,et al.  Home Advantage in Football: A Current Review of an Unsolved Puzzle , 2008 .

[10]  R. Davidson On Extending the Bradley-Terry Model to Accommodate Ties in Paired Comparison Experiments , 1970 .

[11]  Leo Katz,et al.  A new status index derived from sociometric analysis , 1953 .

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

[13]  Yannis Sismanis,et al.  How I won the "Chess Ratings - Elo vs the Rest of the World" Competition , 2010, ArXiv.

[14]  Mason A. Porter,et al.  Random Walker Ranking for NCAA Division I-A Football , 2007, Am. Math. Mon..

[15]  R. Pollard,et al.  Home advantage in football in Brazil: differences between teams and the effects of distance traveled , 2008 .

[16]  Stefan Luckner,et al.  On the Forecast Accuracy of Sports Prediction Markets , 2006, Negotiation, Auctions, and Market Engineering.

[17]  Aylin Seçkin,et al.  Home Advantage in Turkish Professional Soccer , 2008, Perceptual and motor skills.

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

[19]  R. Bruce Mattingly,et al.  A Markov Method for Ranking College Football Conferences , 2010 .