Abstract #300434

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JSM 2003 Abstract #300434
Activity Number: 149
Type: Invited
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Sports
Abstract - #300434
Title: Adaptive Tournament Design: Separating the Best from the Rest
Author(s): Mark Glickman*+ and Shane T. Jensen
Companies: Boston University and Harvard University
Address: Edith Nourse Rogers Mem Hosp (152), 70, Bedford, MA, 01730,
Keywords: Bayesian optimal design ; Kullback-Leibler divergence ; Bradley-Terry model ; paired comparisons ; tournaments
Abstract:

Typical paired comparison experimental designs do not allow for the incorporation of prior information. This is particularly relevant for the design of tournament schedules for players of games and sports, which often use ad hoc algorithms. The problem of pairing players can be formalized as a Bayesian optimal design. Assuming a linear paired comparison model for outcomes, we develop a pairing method that maximizes the gain in Kullback-Leibler information from the prior to the posterior distribution. The optimal pairing is determined using a combinatorial optimization method commonly applied in graph-theoretic contexts. We discuss the properties of our optimal pairing criterion, and demonstrate our method as an adaptive procedure for pairing players round by round. We compare the performance of our method on simulated data against a variation of a system that is currently in use in tournament chess.


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