EPJ Data Sci. (2014) 3: 4
https://doi.org/10.1140/epjds29

Regular article

Scoring dynamics across professional team sports: tempo, balance and predictability

⁹ Department of Computer Science, University of Colorado, Boulder, CO, 80309, USA
¹⁰ BioFrontiers Institute, University of Colorado, Boulder, CO, 80303, USA
¹¹ Santa Fe Institute, 1399 Hyde Park Rd., Santa Fe, NM, 87501, USA

^* e-mail: aaron.clauset@colorado.edu

Received: 20 January 2014
Accepted: 5 February 2014
Published online: 28 February 2014

Abstract

Despite growing interest in quantifying and modeling the scoring dynamics within professional sports games, relative little is known about what patterns or principles, if any, cut across different sports. Using a comprehensive data set of scoring events in nearly a dozen consecutive seasons of college and professional (American) football, professional hockey, and professional basketball, we identify several common patterns in scoring dynamics. Across these sports, scoring tempo - when scoring events occur - closely follows a common Poisson process, with a sport-specific rate. Similarly, scoring balance - how often a team wins an event - follows a common Bernoulli process, with a parameter that effectively varies with the size of the lead. Combining these processes within a generative model of gameplay, we find they both reproduce the observed dynamics in all four sports and accurately predict game outcomes. These results demonstrate common dynamical patterns underlying within-game scoring dynamics across professional team sports, and suggest specific mechanisms for driving them. We close with a brief discussion of the implications of our results for several popular hypotheses about sports dynamics.

(See supplementary material 1)