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 picture perfect outcome came from the True AVG Models yesterday. Yusei Kikuchi had the worst True AVG on the slate and gave up four hits, six runs, and a home run in just 3.1 innings pitched against the Orioles.
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
the best True AVG on the day goes to Justin Steele. The recent sample has been insane for Steele with a 30%+ strikeout rate and room for BABIP regression. Likewise, his xFIP is a clean 2.63 which is one of the best on the slate. With the best True AVG and positive deviations in his corner this is an obvious spot to start lineups. What's more is his opponent, the Nationals, has a top five strikeout rate against LHP and is just league average overall. Make sure to hit the overs for Steele in the prop markets and prioritize him in DFS.
Meanwhile, the worst True AVG belongs to Taijuan Walker. After a terrific start to the year things have gone south for Walker in a big way, with dramatic drops in strikeout rate and xFIP. His career numbers have not been great, so this downturn isn't a surprise. He has given up 16 runs in the last four games combined and models believe he should continue the trend. Unfortunately for him, he has a matchup with the Braves and their .207 ISO power against RHP. In sum, you should be stacking the Braves in all formats and taking the unders on Walker.
Significant deviations to consider
- The largest positive deviations go to our best friend in the whole world, Patrick Corbin. It is hard to describe how unlucky he has been, but an xFIP of 4.96 and ERA of 17.72 is a good start. Literally every stat is just screaming “regression” from BABIP to home run rates. Is it terrifying? Absolutely. But you have to consider Corbin as a prime positive regression candidate. He's got a matchup to find it as well, since the Cubs have just a 74 wRC+ and 26% strikeout rate against LHP. The hope here is that I don't have to have “Still waiting for Patrick Corbin's regression to hit” on my tombstone. Overall, take Corbin's overs and fade the Cubs in all formats.
- The largest negative deviations go to Edward Cabrera up against the Padres. Again, we are dealing with some super small samples for this dude, but the season long stat justify the pessimism. His BABIP is well under .200 and the LOB rates are way too high. Because of this, his xFIP is nearly twice as high as his ERA. Granted, the kid is a fuckin fireballer and has great stuff, but that doesn't mean we can expect him to cheat regression. Likewise, he faces the Padres today who are a top five team in the league against RHP. In conclusion, Look to avoid Cabrera and bet on a downturn.