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.
Model Results
Recap from the previous slate's post: Another strong day from the model with a priority on Blake Snell and a warning about Yusei Kikuchi. Snell ended up with six hits but just one run allowed and eight strikeouts. Meanwhile, Kikuchi got slapped for six hits, five runs, three home runs and just four strikeouts.
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
Opening up for the day we have Shohei Ohtani with both the best True AVG and largest positive deviations available. This shouldn't come as a surprise if you utilize the Season Long True AVG Tables (found here). While it is certainly fair to say that Ohtani can have some warts, he has been stellar in the recent sample. A 36% strikeout rate and walk rate below 5% lead to an xFIP of just 1.43. However, his ERA sits at 4.13 mostly because of high BABIP and home run rates. We should expect those to regress and get an insane ceiling from Ohtani. Matchups don't matter here, so feel free to roll him out with confidence in all formats.
Next up we move along to the worst True AVG on the day going to Tyler Alexander. Considering a low strikeout rate and issues getting through the order multiple times, his xFIP is nearly 5.00 and over 1.5 runs above his ERA in the recent sample. Likewise, the bullpen behind him in worth attacking as well. This matchup with the Guardians is nothing special as they are league average across the board. However, they have enough event upside with stolen bases and home runs that they are worth stacking in DFS. In sum, make sure you stay far away from Alexander and give the Cleveland upside bats a look.
Significant deviations to consider
- As noted above, the largest positive deviations go to Ohtani, but there are a couple other guys to look at as well. Both Ryan Feltner and Joe Musgrove look to be positive regression candidates but profile very differently. Feltner technically has the best positive deviations behind Ohtani, but he also mostly sucks. His True AVG is still much too high to consider backing. Especially at Coors against a surging Cardinals team (132 wRC+ recent sample) he is an avoid and attack. Meanwhile, Musgrove Has a respectable True AVG and his xFIP is 3.64 with an ERA of 7.29, all of which signal positive outcomes. His matchup with the Giants is positive as well. Overall, Look to prioritize Musgrove and steer clear of Feltner.
- We have a handful of large negative deviations to consider here: Martin Perez, Luis Castillo, Zack Wheeler, and Shane Bieber. Martin Perez has an xFIP nearly two runs above his ERA and wildly unsustainable LOB rates and a low BABIP. He faces an above average Astros squad who have plenty of power. Meanwhile, Luis Castillo has been slightly better about LOB rates but is equally as bad in terms of luck from BABIP. Likewise, he's got a spot against the Yankees and their 124 wRC+ against RHP. Wheeler has similar baselines to Castillo, but has a considerably easy matchup against the hapless Marlins. Finally, Bieber has lower strikeout rates but a strong xFIP at 2.78 and the easiest opponent, the Tigers. In conclusion, All four of these pitchers are likely an avoid on a slate as large as today.