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.
Underlined phrases and words have links for extra information! 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 the previous slate's post: A really strong results came for Patrick Sandoval as the best True AVG and largest positive deviation. He pitched 5.2 innings and allowed just three hits and struck out five.
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
Getting started with the best True AVG we have Nick Lodolo. Lodolo has maintained his spot at the top of the season long True AVG tables (Found here) and still has room to improve. Likewise, his strikeout rates continue to be terrific and his walk rate is fine. He is matched with the Brewers, who are good against RHP but suck against LHP with just a 65 wRC+ in the recent sample. In sum, Lodolo is a priority pitcher in all formats and a good bet to go over on his outs and strikeout props.
Next up we find the worst True AVG on the day going to Chris Flexen. The recent sample has been really bad, with well below average strikeout rates and a .206 BABIP. Tied with a 90%+ LOB rate, we see Flexen with a 2.57 ERA and a 5.64 xFIP, so we know there's a lot of regression coming. He faces the Angels on the second half of a double header, and while they are a league average team they have been trending up the last week. Because of the relatively weak opponent, this is a situation where we avoid Flexen but shouldn't necessarily feel pressured to roster the Angels.
Significant deviations to consider
- The largest positive deviation belong to Patrick Corbin who is facing the Phillies. While it's easy to say “Corbin sucks” because of recent outcomes, there's some context that is needed. His recent sample is about as bad of luck as you can find, with BABIP, LOB rates, and home run rates all out of favor. To clarify that, Corbin's xFIP is just 3.55 in the recent sample while his ERA is over 10. At this point, the opponent hardly matters. You'll want to leverage the field with some exposure to Corbin in GPPs and bank on regression.
- The largest negative deviation goes to Shane McClanahan up against the Tigers. The usual caveat of an Ace being on this list applies, as we shouldn't expect an implosion even when regression comes forth. However, McLanahan has been skating by with some benefit to luck in terms of BABIP. While the Tigers are not a scary opponent, they are league average and can present issues for LHP. Considering the projected ownerships here, it's likely best to fade McLanahan and look for an ace with more upside. In conclusion, hit McLanahan's unders and go under the field in DFS/