Luck, skill, and depth of competition in games and social hierarchies
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Abstract (arXiv)
Patterns of wins and losses in pairwise contests, such as occur in sports and games, consumer research and paired comparison studies, and human and animal social hierarchies, are commonly analyzed using probabilistic models that allow one to quantify the strength of competitors or predict the outcome of future contests. Here we generalize this approach to incorporate two additional features: an element of randomness or luck that leads to upset wins, and a "depth of competition" variable that measures the complexity of a game or hierarchy. Fitting the resulting model to a large collection of data sets we estimate depth and luck in a range of games, sports, and social situations. In general, we find that social competition tends to be "deep," meaning it has a pronounced hierarchy with many distinct levels, but also that there is often a nonzero chance of an upset victory, meaning that dominance challenges can be won even by significant underdogs. Competition in sports and games, by contrast, tends to be shallow and in most cases there is little evidence of upset wins, beyond those already implied by the shallowness of the hierarchy.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 5 of its 44 references that are in the map. First posted on arXiv 7 Dec 2023.
Builds on
5 of 44 references.
References · 5
- 2017A Conceptual Introduction to Hamiltonian Monte Carlocited by 207
- 2022Efficient computation of rankings from pairwise comparisonscited by 31
- 2017A physical model for efficient ranking in networkscited by 10
- 2022Ranking with multiple types of pairwise comparisonscited by 4
- 2015Depth, balancing, and limits of the Elo modelcited by 1
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Citing papers per year: 2025: 2; 2026: 3.
5 papers.
- 2025Estimation of partial rankings from sparse, noisy comparisonscited by 3
- 2026RALS: Resources and Baselines for Romanian Automatic Lexical Simplificationcited by 1
- 2025Model inference for ranking from pairwise comparisonscited by 0
- 2026On rankings in multiplayer games with an application to the game of Whistcited by 0
- 2026Multiple latent orderings better predict language model preferencescited by 0
- 2026Multiple latent orderings better predict language model preferences26 Aug 2026
- 2026RALS: Resources and Baselines for Romanian Automatic Lexical Simplification22 Jul 2026
- 2026On rankings in multiplayer games with an application to the game of Whist1 Apr 2026
- 2025Model inference for ranking from pairwise comparisons17 Dec 2025
- 2025Estimation of partial rankings from sparse, noisy comparisons5 Jan 2025