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MLB True AVG Report – 9.01.2022

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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 9.01.2022
MLB True AVG model results for 9.01.2022

Recap from the previous slate's post: Two underwhelming but predictable outcomes came from the regression candidates yesterday. Bubic was slated to benefit from BABIP regression, and he did with a .176 BABIP, but it was assumed he would still be subpar and he was. Meanwhile, Peralta finished with two hits and just three strikeouts. Considering he was an avoid due to low upside, this played out perfectly.

Passage from the MLB True AVG report from 8.31.2022
Passage from the MLB True AVG report from 8.31.2022

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 8.31.2022
Scoring Percentages from the MLB Models for Paydirt 8.31.2022
Stack priority matrix from the MLB models for Paydirt 8.31.2022
Stack priority matrix from the MLB models for Paydirt 8.31.2022
MLB Game Betting model results for Paydirt 8.31.2022
MLB Game Betting model results for Paydirt 8.31.2022

MLB True AVG notable results

Leading off with the best True AVG we have Spencer Strider. Not only does Strider have the best True AVG today, but if you look at the season long models (found here) you'll see him at the top of the list there as well! The mustachioed madman has one of the best strikeout rates in the league at 36.10% and his luck rates are all leveled out. Likewise, he doesn't have the same walk rate issues most fireballers do. Meanwhile, he's got a matchup with the Rockies and they are fucking terrible. Look to utilize Strider in all formats.

Next up is the pitcher with the worst True AVG, as well as the largest negative deviations, Glenn Otto. With a walk rate of 13.3% and a strikeout rate of 14.2%, he is a mere couple of centimeters away from hitting the chode zone. Likewise, his BABIP is drastically low and his xFIP of 5.49 is almost twice as high as his recent sample ERA. Overall, these things bode pretty badly for Mr. Otto. His matchup with the Red Sox is league average though they do have above average power. In sum, you'll want to have some Red Sox power hitters in your exposures and avoid Glenn Otto in all formats.

Significant deviations to consider

  • This is a pretty small slate of pitchers, so there aren't really any significant deviations. Therefore, I will leave you with a quirky fact: It is impossible to hum while holding your nose. Go ahead and try it out. Feels weird as shit.

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