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Generic temporal features of performance rankings in sports and games.

Authors :
Morales, José
Sánchez, Sergio
Flores, Jorge
Pineda, Carlos
Gershenson, Carlos
Cocho, Germinal
Zizumbo, Jerónimo
Rodríguez, Rosalío
Iñiguez, Gerardo
Source :
EPJ Data Science; 11/25/2016, Vol. 5 Issue 1, p1-16, 16p
Publication Year :
2016

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21931127
Volume :
5
Issue :
1
Database :
Complementary Index
Journal :
EPJ Data Science
Publication Type :
Academic Journal
Accession number :
119755176
Full Text :
https://doi.org/10.1140/epjds/s13688-016-0096-y