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. 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 yesterday's post: Triston McKenzie had the highest True AVG as well as the largest negative deviations. He faced the Twins and gave up nine hits, six runs, and three home runs. They scored a total of 10 runs!
MLB True AVG notable results
The highest overall True AVG today belongs to Devin Smeltzer who faces the Guardians. Smeltzer has been relatively bad in general with a 4.93 xFIP in the recent sample, but he's been lucky it's not been worse. The Guardians are worse against LHP, but still maintain league average baselines. This isn't a spot where we expect fireworks, but Smeltzer is in line for a lot of regression and should be avoided in all formats.
The lowest True AVG is tied between Joe Musgrove and Kyle Wright at .234, a notably high mark for a given slate. They both have league average matchups against the Phillies and Giants. The one thing to pay attention here is the large negative deviation for Joe Musgrove, signaling a worse set of outcomes. Likewise, the Giants strike out at a higher clip than the Phillies, so models and intuition lean in Wright's favor here. Both are viable in all formats based on price but Wright should be the priority.
Significant deviations to consider
- We are going back to the well with Jose Quintana having the largest positive deviation. He's going up against the Cubs, who have a league average baseline with a slightly higher strikeout rate against LHP. Quintana has a lot of room for regression here, with a 5.79 ERA and 3.75 xFIP in the recent sample. On that same note he has been unlucky in BABIP and home run rates, so we can expect some much better outcomes in the near future. Hit the overs on Quintana and use him for salary relief in DFS.
- Since it is Smeltzer with the highest negative deviation, we will look at Kyle Freeland here instead. He's mostly been bad this year with lot strikeout rates and a mediocre 4.79 xFIP. The recent sample sees those areas get worse, with his xFIP ballooning to 5.71. Granted, his matchup with the Marlins is relatively soft considering their 83 wRC+ against LHP and high strikeout rates. This is a spot where you would prefer to just avoid Freeland, but you can leverage the power bats for the Marlins as well.