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: Another easy prediction with solid results from the models. Jose Urena was the worst True AVG on the slate and allowed nine runs on nine hits with just one strikeout in 1.1 innings.
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
Leading off is Jacob deGrom with the best True AVG on the day. It's hard to overstate what deGrom has been able to do in the last couple years. To clarify, he's currently got a 1.08 xFIP and a 45.7% strikeout rate, both numbers that are just insanity. This is a relatively easy matchup as well with the Rockies being a below average team with just an 88 wRC+. Overall there are no reasons to avoid deGrom and he should be where you start in all formats.
Next up we find the worst True AVG going to Justin Dunn. A walk rate well above 10% matched with lucky LOB rates is a recipe for disaster. Likewise, Dunn has a 6.06 xFIP and all his baselines point towards continued mediocrity. Meanwhile, he is facing the Phillies today and their 109 wRC+ and top 10 ISO numbers against RHP. In sum you'll definitely want to avoid Dunn today and hit his unders in the prop markets while stacking up the Phillies in DFS.
Significant deviations to consider
- The largest positive deviations today go to Jordan Lyles facing the White Sox. It's been a rough go for Lyles in the recent sample with back to back starts of four runs allowed. However, the strikeout rates have been solid and his BABIP is way too high. Granted, his home run rates are a tad low and will regress the other way as well. The White Sox are an above average team but with well below average power. Overall this is a spot that Lyles can hope to experience positive regression. Look to take his overs on strikeouts and outs recorded while using him in GPPs for DFS.
- Lastly, the largest negative deviations belong to Jameson Taillon up against the Athletics. This is an interesting spot because while Taillon has benefitted greatly from BABIP luck he's been notably unlucky with LOB rates and home run rates. Because of this, his xFIP is just 3.51 even though we should expect him to get hit more easily moving forward. The Athletics are league average in all facets, so the matchup doesn't have an affect here. In conclusion it's likely fine to attack Taillon in larger field GPPs but if you want to avoid the situation all together it would be a fine choice.