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.
CamererC. F. (1989). Does the basketball market believe in the ‘hot hand’?The American Economic Review, 79(5), 1257–1261. http://www.jstor.org/stable/1831452
2.
FamaE. F. (1970). Efficient capital markets: A review of theory and empirical work. The Journal of Finance, 25(2), 383–417. https://doi.org/10.2307/2325486
GilovichT.ValloneR.TverskyA. (1985). The hot hand in basketball: On the misperception of random sequences. Cognitive Psychology, 17(3), 295–314. https://doi.org/10.1016/0010-0285(85)90010-6
5.
GreenB.ZwiebelJ. (2018). The hot-hand fallacy: Cognitive mistakes or equilibrium adjustments? Evidence from major league baseball. Management Science, 64(11), 5315–5348. https://doi.org/10.1287/mnsc.2017.2804
6.
KahnemanD. (2011). Thinking, fast and slow. Macmillan.
7.
KotrbaV.StrnadováM.MartinezL. F.BrincaB. (2024). The most likeable soccer players and the least likeable hockey players are in greater demand. The Journal of Economic Inequality, 23, 529–548. https://doi.org/10.1007/s10888-024-09650-9
LosakJ. M. (2021). Player pricing mechanisms and the daily fantasy sport chance versus skill debate. International Journal of Sport Finance, 16(4), 206–222. https://doi.org/10.32731/ijsf/164.112021.04
10.
LosakJ. M.WeinbachA. P.PaulR. J. (2023). Behavioral biases in daily fantasy baseball: The case of the hot hand. Journal of Sports Economics, 24(3), 374–401. https://doi.org/10.1177/15270025221128955
11.
LosakJ. M.WeinbachA. P.PaulR. J. (2024). Does smart money believe in the hot hand? Evidence from daily fantasy baseball. American Behavioral Scientist, 70, 93–110. https://doi.org/10.1177/00027642241235828
12.
MillerJ. B.SanjurjoA. (2018). Surprised by the hot hand fallacy? A truth in the law of small numbers. Econometrica, 86(6), 2019–2047. https://doi.org/10.3982/ECTA14943
13.
ÖttingM.LangrockR.DeutscherC.Leos-BarajasV. (2020). The hot hand in professional darts. Journal of the Royal Statistical Society: Series A (Statistics in Society), 183(2), 565–580. https://doi.org/10.1111/rssa.12527
14.
PaulR. J.WeinbachA. P. (2005). Bettor misperceptions in the NBA: The overbetting of large favorites and the “hot hand”. Journal of Sports Economics, 6(4), 390–400. https://doi.org/10.1177/1527002504266861
15.
PaulR. J.WeinbachA. P. (2008). Price setting in the NBA gambling market: Tests of the Levitt model of sportsbook behavior. International Journal of Sport Finance, 3(3), 137–145. https://doi.org/10.1177/155862350800300302
16.
PaulR. J.WeinbachA. P. (2011). NFL bettor biases and price setting: Further tests of the Levitt hypothesis of sportsbook behavior. Applied Economics Letters, 18(2), 193–197. https://doi.org/10.1080/13504850903508242
17.
PaulR. J.WeinbachA. P.HumphreysB. (2011). Revisiting the “hot hand” hypothesis in the NBA betting market using actual sportsbook betting percentages on favorites and underdogs. The Journal of Gambling Business and Economics, 5(2), 42–56. https://doi.org/10.5750/jgbe.v5i2.569
18.
PaulR. J.WeinbachA. P.HumphreysB. (2014). Bettor belief in the “hot hand”: Evidence from detailed betting data on the NFL. Journal of Sports Economics, 15(6), 636–649. https://doi.org/10.1177/1527002512465414
19.
PaulR. J.WeinbachA. P.LosakJ. M. (2020). Market efficiency and the setting of salaries for NBA daily fantasy on FanDuel and draft kings. The Journal of Prediction Markets, 14(2), 45–60. https://doi.org/10.5750/jpm.v14i2.1813
20.
SauerR. D. (2005). The state of research on markets for sports betting and suggested future directions. Journal of Economics and Finance, 29, 416–426. https://doi.org/10.1007/BF02761586
21.
StinsJ. F.YaariG.WijmerK.BurgerJ. F.BeekP. J. (2018). Evidence for sequential performance effects in professional darts. Frontiers in Psychology, 9, https://doi.org/10.3389/fpsyg.2018.00591
WoodlandB. M.WoodlandL. M. (2000). Testing contrarian strategies in the National Football League. Journal of Sports Economics, 1(2), 187–193. https://doi.org/10.1177/152700250000100206
WoodlandL. M.WoodlandB. M. (2001). Market efficiency and profitable wagering in the National Hockey League: Can bettors’ score on longshots?Southern Economic Journal, 67(4), 983–995. https://doi.org/10.1002/j.2325-8012.2001.tb00385.x
26.
WoodlandL. M.WoodlandB. M. (2003). The reverse favourite-longshot bias and market efficiency in Major League Baseball: An update. Bulletin of Economic Research, 55, 113–123. https://doi.org/10.1111/1467-8586.00165
