There is a term of art in both sports and statistics called “regression to the mean,” which describes what happens when a small sample size of data produces results that are unusually small or large compared to their expected value, only for the remaining data points to fall much closer to the population mean. To put that in sports terms, if a career .270 hitter starts the season batting .400, one can usually expect that player’s remaining at-bats to be more in line with their traditional performance than with their extreme outlier. While the word “regression” might imply that this phenomenon only applies to a comedown after early results are unsustainably high, regression to the mean also happens when a player or team starts the season performing abnormally poorly based on their past results, only to revert back to their statistical mean as the season progresses.
Jordan Bohannon is Back. The Big Ten Has Been Put on Notice.
