Name
Abstract | ||
|---|---|---|
In most professional sports, playing field structure is kept neutral so that scoring imbalances may be attributed to differences in team skill. It thus remains unknown what impact environmental heterogeneities can have on scoring dynamics or competitive advantages. Applying a novel generative model of scoring dynamics to roughly 10 million team competitions drawn from an online game, we quantify the relationship between the structure within a competition and its scoring dynamics, while controlling the impact of chance. Despite wide structural variations, we observe a common three-phase pattern in the tempo of events. Tempo and balance are highly predictable from a competition's structural features alone and teams exploit environmental heterogeneities for sustained competitive advantage. Surprisingly, the most balanced competitions are associated with specific environmental heterogeneities, not from equally skilled teams. These results shed new light on the design principles of balanced competition, and illustrate the potential of online game data for investigating social dynamics and competition. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1038/srep03067 | SCIENTIFIC REPORTS |
Field | DocType | Volume |
Data science,Computer science,Competitive advantage,Exploit,Social dynamics,Artificial intelligence,Generative model | Journal | 3 |
Issue | ISSN | Citations |
1 | 2045-2322 | 4 |
PageRank | References | Authors |
0.54 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sears Merritt | 1 | 21 | 2.16 |
| Aaron Clauset | 2 | 2033 | 146.18 |