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: The highest negative deviations from yesterday went to Robbie Ray who had a big correction. He gave up 10 hits, six runs, and two home runs. Likewise, the home runs went to Altuve and Pena, who both made sense as one-off options.
MLB True AVG notable results
Leading things off we have Nick Lodolo with the lowest True AVG. His recent sample mark is phenomenal at .121 thanks to an incredibly unlucky string of games. Likewise, his season long True AVG (which can be found here) is the best in the league. To sweeten the deal, He's facing the Marlins who are dead last in the league against LHP. they have an impressively low 47 wRC+ in the recent sample and somehow just a 2% walk rate. Sometimes making choices on pitching is complicated, but not today. Just start with Lodolo in DFS and hit the overs on his props and move along.
Next we will look into Kyle Freeland with the highest True AVG on the day. Considering a relatively low negative deviation, this is a case of a bad pitcher that we expect to stay bad. Granted, his rates have mostly been unlucky in terms of LOB and home run rates, but the BABIP is about where we would expect for his profile. His matchup today with the Brewers is league average, so we should expect them to play up. It's unlikely the Brewers go unnoticed in DFS today, but Freeland is someone worth attacking even with ownership.
Significant deviations to consider
- The largest positive deviations go to Nick Pivetta up against the Guardians. Pivetta certainly has upside but it comes at the expense of volatility. His recent sample has shown the downside, with 22 earned runs in 19 innings pitched. However, his BABIP and LOB rates have been drastically unlucky in this sample and his ERA is five runs above his xFIP. With a matchup against a league average team, this is a spot to cash in on positive regression on Pivetta. He offers solid leverage in DFS and has attractive strikeout props.
- Finally the largest negative deviations belong to Adam Oller facing the Astros. Granted, there are no truly large negative deviations to consider, as most of the high True AVGs belong to bad pitchers in general. Still, Oller is somebody to attack in all regards and the negative regression is just a cherry on top! He faced the Astros in his last start as well and gave up six hits and three earned runs. Considering his upside down ratio of walks and strikeouts and the Astros being a top five team, we can expect more damage this time around. Stack them up in all formats and take the unders on Oller in the markets.