Gib Bassett : Quantile Regression Modeling and Estimation for Paired Comparisons

Posted by Weiya Zhang , part of the Statistics and Data Science Seminar.

At

April 26, 2006, 3:30 p.m.

In

SEO 512

Abstract

After a brief introduction to quantile regression and modeling the talk will consider paired comparisons. The context is rating and ranking sports teams based on game outcomes. The quantile regression approach includes the standard model as a special case, while allowing for a richer set of possible relationships between teams and outcomes. Compared to models that focus on one part of a distribution, the quantile approach expresses relationships that depend on the different parts of a distribution. We can have "A better than B" based on the expected outcome, while at the same time B is more likely to win the game. The ratings are defined as handicaps that make handicap-adjusted outcomes of games evenly matched (where "equally matched" depends on which property of the outcome distribution is to be equalized). We consider connections to point spreads and odds wagering as well as the roundness of a round robin.

There is Tea from 3:15pm.