In the first part of this piece, I established a framework for evaluating streakiness, using David Wright’s consistent performance in 2007 and his streaky performance in 2010 as examples. Now that we have a methodology for assessing the streakiness of players, we can extend it to all players. I repeated the same process I applied to Wright for all 1,545 players with 500 or more PA in every year dating back to 2001. To save computer processing time, I only ran 1,000 simulations for all players, rather than the 10,000 I ran for Wright in the first part of this piece (this is the difference between the calculations taking days and their taking weeks). While this reduces our precision slightly, the distributions are nearly identical:

So, let’s just get right to the red meat. Here are the five most and five least streaky players in every year from 2001 to 2010:

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We are happy to present a two-part guest post by Seth Samuels, who takes an in-depth look at a topic that is often a source of disagreement. Part two will run tomorrow.

Last summer, I was catching up with Fangraphs founder (and my elementary school classmate) David Appelman when he mentioned an interest in being able to identify streakiness in baseball players. Baseball announcers and writers are often criticized for psychoanalyzing a player’s current hot or cold streak, even though those streaks may often be a function of small sample sizes. A full season, however, is a much larger sample than five games. So it certainly seems reasonable that some players might tend to be streakier than others over the course of a full year.

As both a Mets fan and an occasional fantasy player, I’ve repeatedly seen my teams — both real and imaginary — bolstered by surges and short-circuited by cold spells. So being able to identify which players are most or least likely to go on streaks would be a useful tool.

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