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MLB True AVG Report – 8.19.2022

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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

MLB True AVG model results for 8.19.2022
MLB True AVG model results for 8.19.2022

Recap from the previous slate's post: The models hit on two of the three big positive regression candidates yesterday. Corey Kluber gave up two runs, but it came on just four hits while striking out eight over six IP. Likewise, Stripling went 6.1 innings with just one hit allowed and seven strikeouts.

Passage from the MLB True AVG report from 8.18.2022
Passage from the MLB True AVG report from 8.18.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.18.2022
Scoring Percentages from the MLB Models for Paydirt 8.18.2022
Stack priority matrix from the MLB models for Paydirt 8.18.2022
Stack priority matrix from the MLB models for Paydirt 8.18.2022
MLB Game Betting model results for Paydirt 8.18.2022
MLB Game Betting model results for Paydirt 8.18.2022

MLB True AVG notable results

Technically the lowest True AVG belongs to Kevin Gausman, but we will talk about him with the deviations. Instead, we will start the report with Blake Snell who is a very close second. To clarify, this is a really interesting situation because Snell has been unlucky with BABIP but very lucky with LOB rates and home run rates. The stat that has pushed him towards the top of the models is an exceptional walk rate, which is significantly better than his career averages. Likewise, the Nationals have a 27% strikeout rate to LHP. While there is likely some damage coming from other rates, the strikeout and walk rates should mitigate them. Make sure you focus on Snell in all formats.

Moving along with the worst True AVG we can take a look at Bryse Wilson. There is very little to like for Wilson, with low strikeout rates and a mediocre groundball rate. These things lead to a higher xFIP and allows for more damage when things go wrong. Pair that with a high True AVG and you can see how much danger surrounds pitchers with this archetype. Meanwhile, he's facing the Reds and their 90 wRC+ and middling power numbers. This is a bad pitcher facing a bad team, so you'll want to lean towards the side that demands less ownership. Overall, avoid Wilson unless he offers significant leverage.

Significant deviations to consider

  • As alluded above, Kevin Gausman has the largest positive deviations and is facing the Yankees. While the positive deviations are not exceptionally large, a difference of +.082 is strong and by far the most on the slate. Paired with the best True AVG, a strong strikeout rate, and a 2.77 xFIP in the recent sample, you've got an obvious priority pitcher. Likewise, he's facing the Yankees and their 97 wRC+. Gausman will surely have low ownership today and makes for a fantastic leverage play on the field. Take his overs for strikeouts and outs.
  • Finishing this up with the largest negative deviations is Lance McCullers against the Braves. Granted, this is a one game sample size, but there are some re flags in terms of coming regression. His velocity was down from his career averages and his strikeout rate suffered. Likewise, his walk rate was worse than before. tie all of this with a .167 BABIP, and his xFIP was 4.68 for the start where he allowed zero runs. While the xFIP can be negligible here, the baseline rates are scary. Especially considering a matchup with the Braves, McCullers is a very strong fade in all formats.

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