Welcome to the True AVG report! This will be a frequent post outlining the results of the True AVG models on the site which can be found in the MLB Range of Outcomes as well as the free Binomial Projections model. The goal of these posts is to look into the numbers and find large outliers between production and regression. We can use that to take advantage of them in sports betting markets and daily fantasy sports.
All underlined players have a link to their Fangraphs page for ease of research!
What is MLB True AVG?
True AVG is a regressed metric based on batting average allowed for MLB starting pitchers. You can use it for finding pitchers that have had their results affected either positively or negatively by factors of luck. Basically, we are trying to take luck out of the equation and find what pitchers “truly” deserve. Similar to the predictive xHR/9 stat which I developed to leverage luck in home run deviations, True AVG has been built to be an intuitive way to assess realistic outcomes for pitchers. For more info, check out this video.
Recap from yesterday's post: Paolo Espino and Ross Stripling had large negative deviations yesterday, and it was suggested to attack them. The Phillies against Espino scored eight runs and the Yankees against Stripling scored 10 runs.
MLB True AVG notable results
First off, the worst True AVG is Dylan Bundy facing the Diamondbacks. As you can see, his actual average allowed of .333 and his True AVG of .305 are both very high. In situations like this is always makes sense to attack with their opponent, no matter how bad they are. The Diamondbacks in this instance are a league average team against RHP (98 wRC+) though with some strikeout issues. Bundy is likely to be popular in DFS, so using a Diamondbacks stack is strong leverage.
Next we have Braxton Garrett with the lowest True AVG and facing the Mets. Granted, he has a small sample, but in that sample he has pitched well even with some bad batted ball luck. His strikeout rates have been high (10 K/9) against quality opponents and his xFIP is just 3.70. This will likely be his toughest matchup so far, as the Mets have the lowest strikeout rate in the league and a 120 wRC+ to LHP. In sum, expect Garrett to mitigate damage but his ceiling is likely a bit limited overall.
Significant deviations to consider
- The king of the positive deviations is Jose Quintana. His overall season numbers are looking about right, but his recent sample has been very unlucky. Over the last five starts his ERA is two runs higher than his xFIP! He faces the Giants today who have the third highest strikeout rate against LHP. Cash in on the correction here and prioritize him.
- Closing things out, We are looking at Kutter Crawford as the pitcher with the largest negative deviations. Unfortunately, he only has one full start, but we have data from his time in the bullpen. He profiles as a high strikeout, high walkrate guy with absolutely no groundball rate. In case you didn't know, that's a recipe for disaster. When guys like this have their luck run out it's usually catastrophic. He's facing the Cardinals today who are a top 10 team in the league against RHP, so avoid Crawford and get some exposure on the Cards.