Competitive intensity and quality maximizing seedings in knock-out tournaments

Dmitry Dagaev and Alex Suzdaltsev ()
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Alex Suzdaltsev: Stanford Graduate School of Business

Journal of Combinatorial Optimization, 2018, vol. 35, issue 1, No 14, 170-188

Abstract: Abstract Before a knock-out tournament starts, the participants are assigned to positions in the tournament bracket through a process known as seeding. There are many ways to seed a tournament. In this paper, we solve a discrete optimization problem of finding a seeding that maximizes spectator interest in a tournament when spectators are interested in matches with high competitive intensity (i.e., matches that involve teams comparable in strength) and high quality (i.e., matches that involve strong teams). We find a solution to the problem under two assumptions: the objective function is linear in quality and competitive intensity and a stronger team beats a weaker one with sufficiently high probability. Depending on parameters, only two special classes of seedings can be optimal. While one of the classes includes a seeding that is often used in practice, the seedings in the other class are very different. When we relax the assumption of linearity, we find that these classes of seedings are in fact optimal in a sizable number of cases. In contrast to existing literature on optimal seedings, our results are valid for an arbitrarily large number of participants in a tournament.

Keywords: Knock-out tournament; Seeding; Combinatorial optimization; Operations research in sports (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s10878-017-0164-7

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