Welcome to The Opener, where every weekday morning you’ll get a fresh, topical column to start your day from one of SI.com’s MLB writers.
There’s an oft-cited piece within baseball analytics circles written by Russell Carlton of Baseball Prospectus that discusses the concept of small sample sizes. Speaking in the broadest of terms, there comes a point in the season when a sample size of data is “big enough” to carry ample weight when doing retrospective analysis into player performances. If, say, Ronald Acuña Jr. goes 0-for-4 in back-to-back games, that’s probably not enough information to conclude that something was fundamentally wrong with his swing for those two games—sometimes, that’s just the way the cookie crumbles.