This story is part of Peak, The Athletic’s desk covering the mental side of sports. Sign up for Peak’s newsletter here.
Dr. Jennifer Lerner is a professor of public policy, decision science and management at Harvard. She served as the first chief decision scientist for the U.S. Navy. Dr. Brian Gill is a senior researcher at GiveWell and a senior fellow at Mathematica, whose work seeks to navigate uncertainty to support better decision-making. Both are Boston Celtics fans.
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Last week, a curious event happened in the NBA. Kevin Pritchard, the president of basketball operations of the Indiana Pacers, apologized to fans after the NBA Draft Lottery did not go Indiana’s way.
The debate over the trade at its center is already well aired. However, the story is worth briefly recounting because it offers an unusually clear window into how we humans think about decisions, luck and blame.
A few months earlier, Pritchard had executed a trade with the LA Clippers for center Ivica Zubac. One of the key pieces in the trade involved Indiana’s first-round draft pick this year. Because the Pacers had one of the league’s worst records, the pick was almost certain to land in the lottery and had a meaningful chance of becoming one of the top selections in a draft loaded with talented prospects.
As is common in NBA trades, Indiana “protected” the pick by setting conditions on it: If the lottery balls landed such that the pick was in the top four, the Pacers would keep it and send another first-round pick in the future. If it fell outside the top four, the pick would go to the Clippers.
Both teams were making a calculated gamble.
When the season ended, Indiana had roughly a 52 percent chance of landing in the top four and keeping the pick. But the pick landed at No. 5 and went to the Clippers. Pacers fans understandably felt disappointed. But did the result warrant an apology from the team’s top basketball decision-maker?
As researchers who study judgment, uncertainty and risk, we spend a great deal of time thinking about how people evaluate decisions whose outcomes are partly shaped by luck. One of the most robust findings in decision science is known as outcome bias: the tendency to judge a decision by how it turned out rather than by the quality of the reasoning at the time it was made.
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In a classic 1988 study, decision scientists Jonathan Baron and John Hershey presented people with scenarios in which physicians made the same medically reasonable decision based on the same information. When the patient recovered, research participants rated the doctor’s decision highly. When the patient died from a rare complication, they judged the same decision much more harshly.
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Poker players have long had their own term for this mistake: “resulting.” The acclaimed poker player and author Annie Duke helped bring the concept to broader audiences.
In poker, a player can make a statistically sound move — for example, going all in with a 90 percent chance of winning — and still lose because of one unlucky card. Skilled players understand that a bad outcome does not necessarily mean the underlying decision was poor.
Pritchard could not control how the lottery balls fell. If Indiana truly had about a 52 percent chance of keeping the pick, then there was also nearly an equal chance of losing it. The fact that the worst outcome occurred does not, by itself, prove the trade was a mistake.
However, Pritchard’s comments after the lottery revealed a second cognitive trap that might be even more interesting.
“Surprised it came up 5th this year,” he wrote on social media. “I thought we were due some luck.”
Pacers fans likely understood the emotional logic behind the statement immediately. The team’s star point guard, Tyrese Haliburton, had missed the whole 2025-26 season after he tore his Achilles tendon during the final game of last year’s NBA Finals. His absence largely explains why the Pacers struggled badly enough to enter this year’s lottery in the first place.
But lottery balls do not compensate a team for prior suffering.
Decision scientists call this intuition the gambler’s fallacy, the mistaken belief that after a streak of bad luck, good luck somehow becomes more likely.
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More than 200 years ago, statistician Pierre-Simon Laplace observed that people routinely expect randomness to “correct itself” in the short run. Still, truly random sequences produce painful streaks, clusters and lopsided outcomes uncomfortably often. The gambler’s fallacy is so intuitively compelling that even today, many people mistakenly believe that, after a flipped coin comes up heads several consecutive times, the next flip is more likely to be tails (it isn’t).
Similarly, the Pacers were not more likely to win the lottery because they had suffered injuries the season before. Their odds remained the same regardless of the prior heartbreak. And yet, the belief felt entirely natural because these intuitions run deep in all of us.
We human beings crave narratives of control. Randomness threatens our sense of order. We want to believe the world is fair, that disciplined organizations will eventually be rewarded and suffering will somehow balance out.
Sports may offer one of the clearest windows into these tendencies because fans, executives and media members simultaneously embrace sophisticated analytics while also falling prey to ancient intuitions about luck, streaks, fate and cosmic balance — intuitions that have persisted for centuries precisely because they feel so true.
When assessing an important prior decision — whether in sports, business, medicine or our lives — it helps to ask:
- What information was available at the time?
- What outcomes were reasonably foreseeable, and how likely did they appear to be?
- Compared with the available alternatives, did the decision offer the best chance of achieving the desired goal?
- Was the reasoning disciplined, clear and evidence-based, or overly influenced by salient cues and transient emotion?
- Am I judging the quality of the decision itself, or merely reacting to the outcome?
Whether Pritchard’s trade was a good one depends on the probabilities attached to the possible outcomes at the time the trade was made, and on whether any realistic alternative trade would likely have produced a better chance at a championship. Pritchard runs a franchise that has already reached the NBA Finals, so the relevant question was how to maximize the Pacers’ odds of winning a title.
We are not in a position to conduct a full front-office analysis, but suppose Pritchard’s staff concluded, based on advanced analytics and scouting, that acquiring Zubac plus a top-four-protected 2026 pick would give Indiana a better chance of winning a title than any other deal realistically available.
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Suppose, too, that the Clippers would not agree to broader protections such as top-five or top-six. If so, then the trade may well have been the best available gamble, even if the lottery balls later bounced the wrong way.
In a world governed partly by chance, even excellent decisions sometimes produce painful results. However, the pull of false intuitions runs deep.
Even people (like us) who spend their careers analyzing probabilities might still wear their favorite team’s T-shirt while watching games on TV, aware that a small part of them believes the shirts matter.