MLB Advanced Analytics: wOBA-xwOBA For Pitchers
Mike Alexander breaks down wOBA vs. xwOBA for pitchers and how it can be used as a tool to predict regression to the mean.
We’ve been examining Weighted On-Base Average minus Expected Weighted On-Base Average (wOBA-xwOBA) for hitters up to this point. It works for pitchers as well once the sample has become large enough. A higher xwOBA than wOBA indicates someone’s been lucky with balls in play. A higher wOBA means they’ve had poor luck.
Here is the leaderboard of wOBA-xwOBA for a minimum of 500 pitches.
Many of these pitchers have fastball problems. Corbin Burnes is the poster boy for that. Great secondary stuff could be muddled by a fastball that hitters do what they want with.
A bunch of relievers show up here, likely due to a select number of poor innings in a smaller sample. Those blips will smooth if they continue to pitch well.
That won’t be the case for someone like José Leclerc if he continues to have control issues.
Chris Stratton is still not a major league pitcher, despite his luck.
Is Tyler Beede as bad as his wOBA? Maybe not. He’s...