This study investigates the existence and market response to the “hot hand” effect among Major League Baseball starting pitchers. Using a novel methodology that classifies pitchers as hot, cold, or neutral based on context-adjusted recent performance, we find strong evidence that short-term streaks predict daily fantasy sports (DFS) outcomes. However, these trends are not fully priced into DraftKings salaries—hot pitchers are underpriced and cold pitchers are overpriced—indicating pricing inefficiencies. In contrast, sportsbook betting lines tend to overreact, particularly for visiting hot and cold home starters. However, simulated betting strategies exploiting these trends do not yield statistically significant positive profits, suggesting that sportsbooks adjust prices to capitalize on user biases. By comparing DFS and betting markets, this paper demonstrates how institutional structures and incentives shape responses to performance signals. The findings offer new insight into pricing dynamics, market efficiency, and behavioral responses in modern sports analytics.
Baris et al. (2026) studied this question.