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.
Recap from yesterday's post: We had an awesome result against the largest negative deviation on the slate. Jared Koenig went up against the Astros, and gave up six hits, five runs, and a home run in seven innings pitched.
MLB True AVG notable results
Getting started we look to Spencer Strider with the lowest True AVG on the day! With a matchup against the Nationals and their 95 wRC+ he has one of the best floors available. Likewise, Strider is one of the highest strikeout pitchers in the league, with an insane 39% strikeout rate on the season. Granted, the Nationals are a low strikeout rate team at just 18%, but those kind of things matter a lot more when the pitcher isn't elite. Considering strong marks across the board and no large deviations on luck stats, you'll want to utilize Strider in all formats.
Moving along it is Chris Archer with the highest True AVG, but we will chat about him later. Instead we will focus on Austin Gomber with the next highest mark. He's got a matchup with the Pirates who have one of the highest strikeout rates in the recent sample against LHP. Likewise, their wRC+ is just 84 so when they don't strikeout they aren't doing much damage. With a low strikeout rate and moderate groundball rate, we mostly expect Gomber's outcomes to be tied to strength of opponent. In sum, Gomber is bad but the Pirates might be worse. You will want to avoid this spot and look for better upside.
Significant deviations to consider
- The largest positive deviations belong to Jose Berrios who is facing the Royals. Berrios might be one of the most frustrating pitchers to project in the league. His range of outcomes is exceptionally wide and it seems like the good games are more random than most. Regardless, he is in a spot to benefit from positive regression in the near future and we should leverage that. The recent sample shows an xFIP of 3.79 and an ERA of 7.61 with bad luck in BABIP and home runs rates. The matchup with the Royals today should help in correcting those things.
- The largest negative deviations go to our boy Chris Archer up against the White Sox. Archer has not only been super lucky in the season long sample but it's been even more so in the recent one. To clarify, his season long ERA of 3.08 is almost two runs below his xFIP. In the recent sample his BABIP is a hilariously low .094 and his LOB rate is 98%. He's basically taunting the luck gods with those numbers. His opponent, the White Sox, are a middle of the road team but they will look like the Yankees today. Stack against Archer in all formats and hit his unders in the betting markets.