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He's on Fire? Strategic Decisions and Allocation Adjustments Under the Hot Hand Fallacy

Möllestam, William LU (2022) NEKN01 20212
Department of Economics
Abstract
This paper empirically explores 10 years of play-by-play data from the seasons 2011-2021 from National Basketball Association with a comprehensive dataset with 2.7 million shots to test for a hot hand, (i.e., predictability in future outcomes) using three separate models. I find proof for its existence in all short-term categories using panel data as well as when adjusting for shot difficulty using a linear regression prediction model. The measured values are significant where a hot hand equates to around a 0.70-0.77 standard deviation of player ability distribution. The findings are in contrast to most of the hot-hand research, which has typically reported either no hand or a very weak hand in sports when controlled shooting designs are... (More)
This paper empirically explores 10 years of play-by-play data from the seasons 2011-2021 from National Basketball Association with a comprehensive dataset with 2.7 million shots to test for a hot hand, (i.e., predictability in future outcomes) using three separate models. I find proof for its existence in all short-term categories using panel data as well as when adjusting for shot difficulty using a linear regression prediction model. The measured values are significant where a hot hand equates to around a 0.70-0.77 standard deviation of player ability distribution. The findings are in contrast to most of the hot-hand research, which has typically reported either no hand or a very weak hand in sports when controlled shooting designs are used. This difference, I argue, is due to the lack of large datasets and the absence of the athletes’ natural environment, both of which are necessary for creating a realistic setting for evaluating a hot hand. In my regression discontinuity design, I found that hot players remain rational by not taking more difficult shots. There does not seem to exist any endogenous defensive response, i.e., the closest defender distance remains unchanged, and the coach begins to modify strategy first after longer streaks (a sequence of seven hits or longer). (Less)
Please use this url to cite or link to this publication:
author
Möllestam, William LU
supervisor
organization
course
NEKN01 20212
year
type
H1 - Master's Degree (One Year)
subject
keywords
Hot hand fallacy, law of small numbers, sequential decision making, selection bias
language
English
id
9072275
date added to LUP
2022-02-22 11:20:26
date last changed
2022-02-22 11:20:26
@misc{9072275,
  abstract     = {{This paper empirically explores 10 years of play-by-play data from the seasons 2011-2021 from National Basketball Association with a comprehensive dataset with 2.7 million shots to test for a hot hand, (i.e., predictability in future outcomes) using three separate models. I find proof for its existence in all short-term categories using panel data as well as when adjusting for shot difficulty using a linear regression prediction model. The measured values are significant where a hot hand equates to around a 0.70-0.77 standard deviation of player ability distribution. The findings are in contrast to most of the hot-hand research, which has typically reported either no hand or a very weak hand in sports when controlled shooting designs are used. This difference, I argue, is due to the lack of large datasets and the absence of the athletes’ natural environment, both of which are necessary for creating a realistic setting for evaluating a hot hand. In my regression discontinuity design, I found that hot players remain rational by not taking more difficult shots. There does not seem to exist any endogenous defensive response, i.e., the closest defender distance remains unchanged, and the coach begins to modify strategy first after longer streaks (a sequence of seven hits or longer).}},
  author       = {{Möllestam, William}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{He's on Fire? Strategic Decisions and Allocation Adjustments Under the Hot Hand Fallacy}},
  year         = {{2022}},
}