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.
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.
Model Results
Recap from yesterday's post: The worst True AVG and one of the higher negative deviations was Matt Swarmer. He faced the Yankees and gave up seven hits and six home runs. From the article:
MLB True AVG notable results
To start, the largest True AVG on the day goes to Julio Urias. Surprisingly, Urias has been pretty bad this year after a promising start to his career. He's had walk rate issues in the recent sample and has been lucky with both BABIP and LOB rates and definitely has corrections coming. Therefore it's easy to see him falling apart against a quality opponent like the Giants. They are top 10 in the league against LHP and have a good chance to punish a shaky pitcher like Urias. That said, using the Giants in the later slates for DFS is a solid spot for leverage.
Next, the lowest True AVG belongs to Kyle Nelson, but he's an opener and his innings are uncertain. Instead let's look at Jose Quintana, who has the second lowest mark. Quintana's True AVG is at .218, which is .081 points better than his current actual. He's had a surprisingly strong year and has been very unlucky in the recent sample. Granted, he's facing the Braves, and that's always terrifying. This is a spot that will be a lot of leverage gained in DFS and looks to be a very strong spot for the overs on Quintana's strikeout props. However, it certainly comes with downside, so be aware!
Significant deviations to consider
- The largest positive deviation is for Kyle Nelson, but again, he's an opener. Subsequently, the next highest is for Cole Sands. Sands is a high strikeout rookie with some walk rate issues (as expected) but has been very unlucky in his time in the majors. His ERA is 8.49 and his xFIP is just 4.82, so there are multiple indications that corrections are coming. The Rays hold just an 86 wRC+ against RHP and a top 10 strikeout rate. This is a great spot to bet on regression for Sands in all formats.
- Meanwhile, we have Edward Cabrera with the highest negative deviations. In his short time as a starter, he has given up just three hits against 13 strikeouts. That sounds great, until you see a .080 BABIP, 100% LOB rate, and an xFIP of 4.68 against an ERA under 1.00. He faces the Astros, a top 10 team in the league, and is prime to get rocked. Using the Astros power hitters in stacks and taking the unders on Cabrera make a lot of sense.