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MLB True AVG Report – 8.28.2022

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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 8.28.2022
MLB True AVG model results for 8.28.2022

Recap from the previous slate's post: Solid outcomes across the board from the previous report. One of the most satisfying outcomes came from the Tigers up against Glenn Otto. He had the largest negative deviations and gave up four runs on five hits across five innings.

Passage from the MLB True AVG report from 8.26.2022
Passage from the MLB True AVG report from 8.26.2022

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 8.26.2022
Scoring Percentages from the MLB Models for Paydirt 8.26.2022
Stack priority matrix from the MLB models for Paydirt 8.26.2022
Stack priority matrix from the MLB models for Paydirt 8.26.2022
MLB Game Betting model results for Paydirt 8.26.2022
MLB Game Betting model results for Paydirt 8.26.2022

MLB True AVG notable results

Leading the way for the True AVG models is Aaron Sanchez. He's had back-to-back solid starts with twelve strikeouts in nine innings with four runs allowed and now gets an easy matchup with the Giants. Likewise, his BABIP is inflated and should come down, so we would expect a tad more luck as well. Speaking of the Giants, they have an 85 wRC+ and are a bit below league average in most areas. Granted, it's always possible that we see Sanchez turn into a pumpkin, considering he is a career long pumpkin, but this matchup is winnable. In sum, the True AVG and positive deviations mean we should give him a shot in GPPs.

On the other hand we look to Zach Davies with the worst True AVG available. Davies not only has the worst True AVG on the slate by a good margin, but he also has significant negative deviations of over -.100. His BABIP and LOB rates are both unsustainable and his xFIP is around 1.5 runs above his ERA. He has very poor strikeout stuff, so when the luck turns around there's nothing to mitigate his downside. His opponent, the White Sox, are a league average team. Overall we should be attacking Davies every start until he implodes.

Significant deviations to consider

  • The largest positive deviations go to Patrick Corbin up against the Reds. Moving forward, this report may actually be named “How is Patrick Corbin doing this week?” just to make it more apt. That said, he's doing better this week that before, but not quite to where we expect. Importantly, we expect him to be a 4.5-5.5 ERA pitcher, which is really bad, so even with good fortune that doesn't necessitate a priority. The Reds strikeout at the third highest rate in the league, but otherwise are a league average team with solid power. In conclusion, there's no reason to use Corbin, but fading the Reds (if highly owned) is valuable based on the deviations.
  • Lastly the largest negative deviations belong to Edward Cabrera facing the Dodgers. Pitchers like Cabrera are able to get away with being sloppy against medium to bad teams because they have such crazy stuff. However, they will typically falter against teams with good plate discipline like the Dodgers. Likewise, Cabrera is due for massive regression, considering his BABIP of .178, LOB rate of 100%, and home run rates of literally 0%. Unfortunately for Cabrera, this is a spot that can blow up in his face as the Dodgers are the third best team in the league against RHP. Stack the Dodgers at low ownership and profit.

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