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: The best True AVG from yesterday went to Zack Wheeler. He pitched well, although he only had three strikeouts. Meanwhile the worst True AVG belonged to Matt Swarmer. Facing the Padres, he gave up four hits, four runs, and five walks with a home run. The Padres ended up scoring six total runs.
MLB True AVG notable results
First off, the worst True AVG on the day goes to Devin Smeltzer as he faces the Diamondbacks. There are a multitude of things working against Smeltzer in this spot. His True AVG is .317, which is .109 points worse than his actual for the sample. His LOB rate of 92.3% is way above league average and his xFIP is more than two runs worse than his ERA. For all intents and purposes this dude is a ticking time bomb. The Diamondbacks are not a consistently good team, but they do have a ceiling in the right spot, and this looks like a spot to take a shot.
Leading the way with the best True AVG is Carlos Carrasco. Carrasco has had a great year overall and is right in line with his estimators, but his recent sample has had some unlucky moments. Even through a “rough patch” he has maintained his strikeout rates and even increased them in his most recent starts. He faces the MArlins, who have been above league average in most ways, but this is a matchup that an ace can win. Look for his regression to help him out here and take him in DFS and hit the over on his strikeout props.
Significant deviations to consider
- The top of the models are littered with notable positive deviations, so we have a bunch of guys to look to for positive corrections. All of Charlie Morton, Carlos Carrasco, and Lucas Giolito have positive deviations above .080 points. All three have slightly below average matchups with Giolito being the one with the highest upside due to profile. If any are underowned in DFS they represent a lot of leverage on the field.
- Closing things out, there are two big negative deviations to focus on for Paolo Espino and Ross Stripling. Both have very tough matchups against the Phillies and Yankees respectively. The Yankees have a .193 ISO against RHP and Stripling has just a 7.1% HR/FB which speaks to home run corrections coming. In sum, Attack both of these pitchers in all formats.