by
Aaron Clauset
March 28, 2013
The outcomes of many team-based competitions are determined by the steady accumulation of minor interactions over time. Yet we lack a general understanding of their fundamental dynamics and how those dynamics are shaped by a competition's structure. We introduce a novel generative model that can directly quantify a competition's scoring tempo and balance. We then investigate the link between competition structure and dynamics by applying this framework to a novel data set of nearly 1 billion competitive interactions across more than 10 million diversely structured team competitions from a popular online game. Despite wide variations in competition geography, rules, resources, and team skill, we find a common three-phase pattern in the tempo of events, a pattern also observed in some professional sports, and that competition winners are often predictable after only a few moments of gameplay. Furthermore, tempo and balance dynamics are highly predictable from structural features alone. Much like competition between firms, teams in these games exploit heterogeneities in geographic structures and resource types for sustained competitive advantage. Counterintuitively, the most balanced outcomes arise from specific geographic heterogeneities, not from teams of equal skill competing in homogeneous environments. These results shed new light on the principles of balanced competition, and illustrate the rich potential of online game data for investigating social dynamics and competition.
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