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Aggregating Expert Ratings Using Preference-Neutral Weights: The Case of the College Football Polls

Decision and Information Sciences, Warrington College of Business Administration, University of Florida, Gainesville, Florida 32611-7169
ira.horowitz{at}cba.ufl.edu

I use two principal college football polls to illustrate a preference-neutral linear programming procedure for determining optimal weights for aggregating expert ratings. I compute the weights for 84 weekly polls released during the 1999 through 2003 college football seasons. The weights vary from week to week (sometimes considerably over a year), the range of weights over which the aggregate ranking holds also tends to vary and to be quite small (with a range of zero almost half the time), and nothing is systematic about the week-to-week changes in either the weights or their ranges. The results suggest that predisposition to a particular set of weights is a bad idea, not just for the purpose of aggregating the football polls, but in any situation in which one wants to aggregate ratings provided by multiple sources of complementary expertise.

Key Words: linear programming applications; multiple criteria; recreation and sports