Aggregating expert ratings using preferennce-neutral weights: The case of the college football polls

Aggregating expert ratings using preferennce-neutral weights: The case of the college football polls

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Article ID: iaor20052232
Country: United States
Volume: 34
Issue: 4
Start Page Number: 314
End Page Number: 320
Publication Date: Jul 2004
Journal: Interfaces
Authors:
Keywords: recreation & tourism, sports, programming: linear, programming: multiple criteria
Abstract:

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.

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