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Regression to the Mean

‘Sports Illustrated Jinx’ is an urban legend that states that an athlete whose picture appears on the cover of Sports Illustrated magazine is doomed to perform poorly the following season. Overconfidence and the pressure of meeting high expectations are often offered as explanations. But as Daniel Kahneman explained in his book "Thinking, Fast and Slow", "There is a simpler account of the jinx: an athlete who gets to be on the cover of Sports Illustrated must have performed exceptionally well in the preceding season, probably with the assistance of a nudge from luck, and luck is fickle.”

Often times, when something extreme happens and the extremity recedes in subsequent events, we look for a cause, but what really happens is a simple rule of statistics, and that is regression to the mean.

Let’s say you work in sales. You performed exceptionally well this year, hitting record sales. Your skill had a lot to do with your performance, but luck also played a big part with favorable market conditions and simple random events that worked in your favor. 

While skill is an obvious element of success, luck is not. Luck is random. When the luck component goes away from your performance, your sales also regress to your average performance, which matches your current skill or capacity. There doesn’t need to be any causal explanation for your performance to drop from an exceptional level. This is how regression to the mean works. 




Imagine getting a new job. You negotiate your way to a very high-salary job compared to your peers with the same skill and capacity. In most cases, you will soon find yourself stuck there because you are already overpaid, and no new opportunities for further jumps in salary growth will come your way while your peers start catching up. Regression to the mean will balance it out.

Even in markets where assets become overvalued due to whatever reasons, regression to the mean works its magic to pull the prices down and vice versa. In cases like this, we often look for causal explanations because our mind is strongly biased towards them and does not deal well with mere statistics.

Someone with no knowledge of regression to the mean would say that his performance improved this year from a very bad performance last year because of x, y, and z. But I would correct him by saying that he improved his performance because he simply had a very bad year last year, and good or bad luck doesn’t sustain for long.

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