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 and True AVG tables. 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.
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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.
Model Results
Recap from the previous slate's post: The models were strong in the previous report (from two days ago). Kevin Gausman was the best True AVG and largest positive deviations and went seven innings against the Yankees. He gave up just four hits and one walk with seven strikeouts. On the other hand, McCullers ran into trouble against the Braves. He gave up seven hits and three runs with a home run.
Below you'll find a recap of the DFS and Betting models. These models are powered by True AVG and other powerful metrics! so, If you are enjoying the True AVG report, you should try out a subscription to the site for access (Find an option here!).
MLB True AVG notable results
Leading off with the best True AVG is Shohei Ohtani. The guy just fucks. He's the MLB version of the Karma Sutra.
Next up with the worst True AVG is Kyle Gibson. Granted, he had the best game of his life in his last start, but we shouldn't expect that to continue. Gibson has maintained low strikeout rates and a middling xFIP all year and True AVG sees him as a well below average pitcher. He's got a matchup with the Mets who are the third best team in the league against RHP and have low strikeout rates as well so that makes things even worse. Overall Gibson is an easy avoid in all formats and the Mets overs are attractive.
Significant deviations to consider
- We have a couple large positive deviations to consider today: Patrick Corbin and Kohei Arihara. There have been plenty of pieces on Corbin in this report and he should continue to trend up. He faces the Padres who are good against RHP but have just a 71 wRC+ against LHP. Meanwhile Arihara is up against the Twins and was very unlucky in his first start. That said he did have improved strikeout rates on his career sample and might be somebody to monitor moving forward. In sum, it's likely best to just avoid stacking against these pitchers and take a shot on Arihara in large field GPPs.
- Lastly on the report is the largest negative deviations going to Jose Urquidy against the Braves. This report has covered Urquidy quite a few times and he has continued to skirt by thanks to a lot of luck. His BABIP, LOB rates, and home run rates have all been out of whack and in need for regression. Likewise, his xFIP is nearly two runs over his ERA in this span so that's more justification of regression. Meanwhile, without a good strikeout rate to mitigate downside he's an easy spot to avoid. This kind of baseline might hold up against a bad opponent, but he faces the Braves today who are a top five team in power against RHP. Overall you should be attacking Urquidy in DFS and taking his unders in the betting markets.