Sample Size in Baseball: How Much Data is Enough?
2025-04-04
A baseball season is a collection of countless small events, each pitch contributing to the final outcome. Evaluating player performance requires a substantial amount of data, but the key is understanding which data points are meaningful. This article explores the issue of sample size in baseball statistics, explaining why a single at-bat isn't enough to judge a player's skill and why more data is needed to cancel out randomness. It highlights that different statistics require different sample sizes to 'stabilize,' for example, strikeout rate needs a smaller sample than BABIP. The author stresses the importance of sample size to avoid jumping to conclusions based on limited data.
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