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Statistical Modelling
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Articles

Quantile regression for rating teams

Gilbert W Bassett

Gilbert W Bassett Jr is Department of Finance, University of Illinois at Chicago, 601 South Morgan (MC168), Chicago, Illinois 60607–7121. E-mail: gib{at}uic.edu

Quantile regression is proposed for modeling game out comes and as the basis for rating teams. The model includes the standard location model for team strength as a special case, while allowing for a richer specification in which teams differ according to the quantiles of the out come distribution. Team ratings are defined as the handicap needed to equalize the out come of a contest. With teams differing by quantiles, this leads to a class of ratings that depend on where in the out come distribution the out come is equalized. Relation ships with betting games are discussed. The approach is illustrated by rating National Football League (NFL) teams based on game results for the 2005 season.

Key Words: handicaps • odds • pointspreads • quantile regression • sportsratings

Statistical Modelling, Vol. 7, No. 4, 301-313 (2007)
DOI: 10.1177/1471082X0700700402
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