Most of the time, you can determine if pitchers were unlucky over the course of a season by looking at few factors like LOB%, BABIP or HR/FB%. Today, I am going to look a little further to find pitchers who may have been even more lucky or unlucky on batted balls by looking at their wBABIP.
I noticed when writing about Jake Peavy that he had large number of extra base hits given up in 2011. In 2012, that number came down. At the same time, the White Sox outfield improved via substraction by moving Carlos Quentin. Could Peavy’s improvement have been because his outfield gave up more extra base hits in 2011 compared to 2012?
The idea behind using wBABIP is to see if a pitcher gave up an abnormally high number of extra base hits. The the cause of the extra base hits could have been from the pitcher throwing meatballs or slow footed outfielders. The goal is to see if the damage done from batted balls was evenly distributed or were there some extreme cases.
The get wBABIP, I took the pitchers’ run values for singles, doubles and triples for each season. With the weighted values, wBABIP was then calculated. The average wBABIP was about 20 points lower than the average BABIP. To deal with this difference, I adjusted wBABIP value so it would be at the some scale as BABIP.
Note: The standard reporting of stats, by anybody, does not included doubles and triples allowed for pitchers. To get the numbers, I had to use retrosheet data and create all the values from the play-by-play data. My BABIP values are just a bit off and I am not able to find the exact problem The values are the hits in play divided by hits in play plus outs in play.
Here are some of the starters from 2012 who had the largest differences in their wBABIP and BABIP (full list from 2010, 2011, 2012)
The biggest surprise from looking at all the numbers is the lack of difference between the two values. The worst case among starters is only around +/- 20 percentage points.
A little larger difference can be seen among relievers since they throw fewer pitches over the course of a season. For example, Jonny Venters had a .360 BABIP and only a .332 wBABIP. The lower wBABIP helped keep his LOB% high (83%).
Looking back at Jake Peavy, he did not have much of difference in his BABIP and wBABIP from one season to the next.
Season: BABIP, wBABIP
2011: .316, .312
2012: .270, .272
As a whole, I didn’t find the enhancement on BABIP was really needed. Not enough extra information can be extracted from wBABIP to use it in addition to BABIP. Initially, I though I would find a little extra information on some pitchers. In the end, I found wBABIP was just overkill.