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February 24, 2014

Baseball Therapy

But…He Finished Strong Last Season!

by Russell A. Carleton


Over the past couple of weeks, I’ve introduced the idea of estimating a player’s talent level at specific points in time, at least retrospectively, by using a moving average. The idea is that instead of simply assuming that at every plate appearance, a batter could be described by his seasonal average, we might allow that his true talent level varied over the course of a season.

Hitters do grow and develop within a single season, because that’s what humans do. Sometimes it’s obvious that a hitter has figured something out mid-season and that he’s much better at swinging the stick in September than he was in April. Fans and front office types alike love it when that happens, and even if a team doesn’t end up making it to the playoffs, that late-season surge provides hope for the next season—hope that is currently fueling the fantasies of every fan in baseball. Ike Davis had a .326 OBP last year, but in his last 100 plate appearances, he posted a .460 OBP. Jason Castro had a perfectly glorious .350 OBP, but in his last 100 PA, he put up a nifty .450. Ben Revere’s overall OBP was .338, but .410 in his last century of times to the plate. It’s tempting to think that these players—these young players—are finally ready to step up from good, solid players to elite status. After all, the trend line is pointing up, right?

It’s so tempting to want to believe, but like everything else, we need to examine whether it’s a belief based on solid evidence. You want to believe that because he finished strong, he’ll start strong and he’ll stay strong, right? (And in a fantastic feat of cognitive dissonance, you will also assume that the guy who tailed off at the end of the year was just a small sample size fluke that doesn’t mean anything.)

Warning! Gory Mathematical Details Ahead!
Recently, I laid out the method for how we can retrospectively estimate a player’s true talent at a given point in a season. Basically, I calculated a series of moving averages (how the player has done in his last 50 chances, last 100 chances, last 150 chances, and so on) and also the player’s seasonal average. I allowed the computer to pick which of those best described the player during the course of a season, based on a logistic regression. Some hitters show evidence of this sort of variation in their talent level. For some, the seasonal average is all you need.

This time, I’m looking at OBP. For the years 2009-2013, I coded for each player (min 250 PA) whether a plate appearance ended in an on-base event. I then took moving averages for the last 50, 60, 70, etc. plate appearance up to 200 and determined what the best descriptor for his chances of an on-base event was. For example, if the regression said that he was best described by his previous 130 PA, I assigned his true talent level to be his OBP in his last 130 PA. For players who were best described by their seasonal average, I simply input his seasonal average.

I calculated several OBP estimates:

  • Overall seasonal OBP
  • Seasonal OBP regressed to the league mean (using KR-21 coefficients, described here)
  • What his true talent estimate was at his last PA of the season
  • His highest estimated true talent point during the season
  • His lowest estimated true talent point during the season
  • His OBP over the last 100 PA of the season, whether that was his best descriptor or not

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Premium Article Pebble Hunting: The Po... (02/24)
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