Generic temporal features of performance rankings in sports and games

José A. Morales, Sergio Sánchez, Jorge Flores, Carlos Pineda*, Carlos Gershenson, Germinal Cocho, Jerónimo Zizumbo, Rosalío F. Rodríguez, Gerardo Iniguez

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

13 Citations (Scopus)
175 Downloads (Pure)

Abstract

Many complex phenomena, from trait selection in biological systems to hierarchy formation in social and economic entities, show signs of competition and heterogeneous performance in the temporal evolution of their components, which may eventually lead to stratified structures such as the worldwide wealth distribution. However, it is still unclear whether the road to hierarchical complexity is determined by the particularities of each phenomena, or if there are generic mechanisms of stratification common to many systems. Human sports and games, with their (varied but simple) rules of competition and measures of performance, serve as an ideal test-bed to look for universal features of hierarchy formation. With this goal in mind, we analyse here the behaviour of performance rankings over time of players and teams for several sports and games, and find statistical regularities in the dynamics of ranks. Specifically the rank diversity, a measure of the number of elements occupying a given rank over a length of time, has the same functional form in sports and games as in languages, another system where competition is determined by the use or disuse of grammatical structures. We use a Gaussian random walk model to reproduce the rank diversity of the studied sports and games. We also discuss the relation between rank diversity and the cumulative rank distribution. Our results support the notion that hierarchical phenomena may be driven by the same underlying mechanisms of rank formation, regardless of the nature of their components. Moreover, such regularities can in principle be used to predict lifetimes of rank occupancy, thus increasing our ability to forecast stratification in the presence of competition.

Original languageEnglish
Article number33
Pages (from-to)1-16
JournalEPJ Data Science
Volume5
Issue number1
DOIs
Publication statusPublished - 1 Dec 2016
MoE publication typeA1 Journal article-refereed

Keywords

  • complex systems
  • data analysis
  • rank distribution
  • rank diversity
  • sports

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