The Hot Hand Illusion: Why Even Nobel Laureates Believe in Sports Myths

For decades, the fallacy of the hot hand has been cited to show that folktales of luck and streakiness are no match for cold, hard numbers. But the numbers do not prove the hot hand is a figment of imagination.

NBA superstar Stephen Curry is among the many athletes who insist that the "hot hand" effect is real. But a study from the 1980s claimed to show that the hot hand is a myth. Now, a new analysis of the data suggests that the original study may have been flawed.

The hot hand effect is the idea that players' successes come in streaks—dependent on some mysterious inner quality that ebbs and flows—and when a player’s hand is hottest and they’re “in the zone,” it can feel almost like they can’t miss.

Curry knows a thing or two about a hot hand. He holds the NBA record for making at least one three-pointer in 268 consecutive games. Following a practice one day, he sank 105 three-pointers in a row. In the Hot Ones interview, Curry said the authors of the study “don’t know what they’re talking about at all.” When Curry totaled 60 points in one game, he said, “It’s literally a tangible, physical sensation of all I need is to get this ball off my fingertips and it’s going to go in.”

The study, “The Hot Hand in Basketball: On the Misperception of Random Sequences,” was written in 1985 by eminent psychologists Thomas Gilovich, Robert Vallone, and Amos Tversky. They allegedly demonstrated through an analysis of basketball shooting data that the hot hand was a myth. Recently deceased Nobel laureate (and Tversky’s chief collaborator) Daniel Kahneman proclaimed, “The hot hand is a massive and widespread cognitive illusion.” In statistical circles, the hot hand study has taken on a metaphorical significance beyond basketball. For decades, the fallacy of the hot hand has been cited to show that folktales of luck and streakiness are no match for cold, hard numbers.

But the numbers do not prove the hot hand is a figment of imagination. Economists Joshua Miller of the University of Adelaide and Adam Sanjurjo at the University of Alicante in Spain, used data from multiple different sports, including the same basketball data used by Gilovich, Vallone, and Tversky, to provide robust support for a hot hand. The problem, say Miller and Sanjurjo, lies in the way the original authors analyzed their data and, in particular, a mistake they made about what random data should look like without the influence of a hot hand.

Imagine we’re looking at a chart of hits and misses over some number of shots and trying to find where a shooter might have had a hot hand. Suppose we look for hot-handedness by considering only those attempts that came after a sequence of hits, such as three baskets in a row. These sequences are candidates for being shot with a “hot hand.”

Shouldn’t years of testimony from athletes like Stephen Curry count for something?

However, if there’s no such thing as a hot hand, we might expect the player to have the same success rate in these attempts—the shots after three consecutive makes—as their overall average. Since our working theory is that the previous successes have no predictive power for the next shot, it would seem intuitive that our choice of shots based on what happened right before the hot streak shouldn’t matter at all.

But that’s wrong. By selecting attempts that come after a hot streak and computing a proportion over this subset, we have unwittingly introduced a negative bias into the estimate of the rate of success that could counteract a hot-hand-induced positive effect. In other words, the observed percentage of success-following-success being equal to the rate of success-following-anything, would be evidence for the hot hand instead of against it. The way we selected the data artificially penalized the shooter; their true success rate may have been a few percentage points higher than what we tabulated. So, if our observation matched their usual average, it must be that something else was at work to offset our bias—a hot hand.

If you find yourself doubting this bias exists, you’re in good company, including the esteemed professors who first “debunked” the hot hand. Like other famously counterintuitive examples in probability, such as the Monty Hall Problem—the puzzle of whether to switch doors when searching for a prize on the game show Let’s Make a Deal—the phenomenon acts almost like an optical illusion: Our natural senses tell us something that turns out to be contradicted when we try to confirm it with hard measurement.

I’ll freely admit that I didn’t believe it either, at first. I only became convinced after I ran 100,000 simulations of 100 random coin flips and tabulated the proportions of heads following streaks of three heads. I knew the coin flips were perfectly random 50/50 processes under any conditions (coins don’t get “hot”). So, if I