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Empirical Evaluation of Real World Tournaments

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arxiv 1608.01039 v1 pith:RRQKNH5F submitted 2016-08-03 cs.GT cs.AIcs.MA

classification cs.GTcs.AIcs.MA
keywords realtournamentsworlddatatournamentcomsocchoicedistribution
verification ladder T0 review T1 audit T2 compute T3 formal
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Computational Social Choice (ComSoc) is a rapidly developing field at the intersection of computer science, economics, social choice, and political science. The study of tournaments is fundamental to ComSoc and many results have been published about tournament solution sets and reasoning in tournaments. Theoretical results in ComSoc tend to be worst case and tell us little about performance in practice. To this end we detail some experiments on tournaments using real wold data from soccer and tennis. We make three main contributions to the understanding of tournaments using real world data from English Premier League, the German Bundesliga, and the ATP World Tour: (1) we find that the NP-hard question of finding a seeding for which a given team can win a tournament is easily solvable in real world instances, (2) using detailed and principled methodology from statistical physics we show that our real world data obeys a log-normal distribution; and (3) leveraging our log-normal distribution result and using robust statistical methods, we show that the popular Condorcet Random (CR) tournament model does not generate realistic tournament data.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Tournament Robustness via Redundancy

    cs.DM 2025-06 conditional novelty 7.0 of 10

    This paper constructs knockout tournament brackets that guarantee the strongest player wins even when up to one third of matches on each path are manipulated, with only a polynomial increase in bracket size.

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