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 yesterday’s post: Although both Thompson’s had relatively uninspiring results, the negative regression candidates did see some corrections. Framber and Burnes both saw some corrections in terms of BABIP and LOB rates. However, their outcomes were still okay for DFS purposes.
MLB True AVG notable results
We lead off with Brandon Woodruff as the lowest True AVG on the day. Granted, his home run rates will be worse moving forward, but his True AVG of .134 is terrific. Both his BABIP and LOB rates could use some corrections in the recent sample and his strikeout rates are phenomenal. The matchup with the Giants is good, with them being below average with a 93 wRC+ in the recent sample. You won’t get an ownership discount, but Woodruff should be a priority in all formats.
Next up is a familiar face at the bottom of the True AVG table: Andre Pallante. This is a situation where we have a bad pitcher that hasn’t been hurt by bad luck in many ways, so we expect them to continue to struggle. Pallante is a pitch to contact guy that relies on a high groundball rate to find success. Unfortunately, the Reds suck, and are a bottom five offense in baseball against RHP. That said, they will come in with low ownership against a bad pitcher who gives up power. In sum you should take the unders on Pallante and utilize the Reds power bats in DFS.
Significant deviations to consider
- The largest positive deviations go to Patrick Sandoval facing the Dodgers. His recent sample shows a very high BABIP paired with lucky LOB rates, which is an interesting combination. In short, he has been unlucky in terms of baserunners but lucky in terms of allowing runs. Outside of that, his strikeout rates are fantastic and his ERA and xFIP are in agreement. He’s facing a Dodgers team that is one of the best in the league against RHP but struggles with LHP. Their wRC+ drops 15 points and their strikeout rate jumps 3%. You’ll want to consider Sandoval as a strong GPP play and hit his overs in the strikeout props.
- Finally the largest negative deviations go to Jose Urquidy. this is one of the largest deviations we have seen and it’s very apparent when you look at the baselines. In the recent sample his BABIP is just .100, he’s got a 97% LOB rate and a 10% home run rate. All three of these have greatly benefitted by luck, and so it’s no surprise that his xFIP is almost three runs worse than his ERA. Especially considering a lower groundball rate and less strikeout potential, we should expect Urquidy to crash down to earth soon. The matchup today with the Athletics doesn’t scream leverage, but they have more power than people realize. Look to take unders on Urquidy in the bettering markets and stack up OAK in large field GPPs for massive leverage and upside.