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Why Even Tiger Has Off Days

Discover how regression to the mean explains the fall of top athletes after their peak performances, often linked to the Sports Illustrated jinx.

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Those who have risen to the top of their game have farther to fall—and statistically speaking, fall they will. In successive measurements, the best tend to get worse, and the worst tend to get better. "Once Tiger Woods has won all four majors, there's nowhere to go but down," says Trevor Price, a biologist at the University of Chicago.

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This tendency toward mediocrity—sometimes called the Sports Illustrated jinx because an athlete is likely to enter a career lull after appearing on the cover—is a variation on a mathematical principle known as regression to the mean. As long as there is any element of chance, competitors swap places in a hierarchy. "There are always random factors conspiring to make you better or worse than you inherently are," Price says. A morning cup of coffee could make the difference. "The most worst is not only inherently bad but feeling particularly grotty."

Price and his colleague Colleen Kelly, a statistician at Victoria University in Wellington, New Zealand, worry that sportscasters aren't the only ones who overlook regression to the mean. Biologists studying mate selection in the wild search for changes in appearance or behavior that cause unsuccessful individuals to do better in the next round of courtship. But if the ugly get lucky, the cause may just be the flip side of the jinx: Given a second chance, the rules of regression dictate that the losers shall rise.

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