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MLB True AVG Report – 8.17.2022

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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 8.17.2022

Recap from the previous slate’s post: For the most part we got a strong outcome from the models last night. Justin Steele went six innings allowing just one unearned run while striking out five.

Passage from the MLB True AVG report from 8.16.2022

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 8.16.2022
Stack priority matrix from the MLB models for Paydirt 8.16.2022
MLB Game Betting model results for Paydirt 8.16.2022

MLB True AVG notable results

Leading off with the best True AVG is George Kirby, his second straight start at the top. there’s very little to dislike about Kirby in the recent sample as his strikeout rates have popped and his walk rates are miniscule. Granted, his home run rates will need to regress as he hasn’t given any up, but that’s the only wart. He faces the Angels and while they are looking better lately they are still a well below average team with high strikeout rates. This spot is cut and dry, so prioritize Kirby in all formats and consider the overs on his strikeouts and outs.

Meanwhile, we have two pitchers at the bottom of the models for True AVG: Rich Hill and Zach Davies. Rich Hill faces the Pirates and while that is a great matchup it’s hard to be optimistic. His strikeout rates have been abysmal and he’s old as dust. Meanwhile Zach Davies is up against the Giants. While the Giants are a below average team with a 92 wRC+ against RHP, They have low strikeout rates and decent power numbers. Davies is a bad combination of things: He’s a pitching chode (equal or worse walk rate against strikeout rate) as well as having large negative deviations. In conclusion, you’ll want to avoid these pitchers and consider their opponents in large field GPPs.

Significant deviations to consider

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