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
Recap from the previous slate's post: A rather interesting result from the last report for Miles Mikolas. He did, indeed, get blown up in this spot by the Reds which was a bit surprising even with the worst True AVG. He gave up four runs on six hits (three home runs) with just three strikeouts.
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!).
MLB True AVG notable results
The best True AVG for today goes to Joe Ryan. Ryan is coming off one of his best starts of the season, with eight strikeouts and just two hits allowed. Likewise, the recent sample has given him some strong baselines and most of his rates are normalized. His spot against the Red Sox is a positive one, as they are league average at best and struggling badly in the more recent sample. Overall, Joe Ryan is a great option in DFS and his overs are attractive in terms of strikeout props.
On the other hand, the worst True AVG belongs to Anibal Sanchez. There's not a lot of optimism when it comes to Sanchez as his xFIP is nearing 6.00 and he's dangerously close to the chode zone (walk rate at or above strikeout rate). with no upside in strikeout rate to mitigate his downside, he's a very risky option in all regards. Meanwhile, he's facing an Athletics squad that put up 10+ runs last night and should be able to run up the score again. In sum, utilize the Athletics in GPPs and take all the unders on Sanchez.
Significant deviations to consider
- The largest positive deviations are for Kris Bubic up against the White Sox. The recent sample has been unfair for Bubic and it's reflected in an ERA almost two runs higher than his xFIP. Likewise, his BABIP and LOB rates are very unlucky and should regress. Granted, the walk rate isn't awesome and we don't expect Bubic to be incredible even on regression, but he should be serviceable. His matchup with the White Sox isn't great, as they are a slightly above average team but with little power. You will want to utilize Bubic as salary relief in DFS if you need it, but he's not a priority.
- Finally the largest negative deviations go to Freddy Peralta facing the Pirates. With just a .145 BABIP to go with unsustainably strong LOB and home run rates, Peralta should have some bad outcomes coming. Likewise, his xFIP is over two runs higher than his ERA and the strikeout rates have been uninspiring. The issue here is a matchup with the Pirates and their 83 wRC+ which makes it hard to feel confident in regression coming this start. the most likely outcome is something like 7-9 hits, two earned runs, and 4-6 strikeouts. In conclusion, avoid the downside of Peralta but don't feel pressured to prioritize the Pirates.