Tournaments are widely used in the economy to organize production and innovation. We study individual data on 2,775 contestants in 755 software algorithm development contests with random assignment. The performance response to added contestants varies non-monotonically across contestants of different abilities, precisely conforming to theoretical predictions. Most participants respond negatively, while the highest-skilled contestants respond positively. In counterfactual simulations, we interpret a number of tournament design policies (number of competitors, prize allocation and structure, number of divisions, open entry) and assess their effectiveness in shaping optimal tournament outcomes for a designer.
Individual contestant performance.
Increased competition reduces the likelihood of winning a prize, which reduces strategic incentives to exert high effort. The least-skilled contestants are negligibly affected by rising competition, the response becomes progressively more negative with higher levels of ability until, toward the range of the highest-skilled contestants the relationship becomes more positive.