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MLB True AVG Report – 9.01.2022

PayDirt MLB Image

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

MLB True AVG model results for 9.01.2022
MLB True AVG model results for 9.01.2022

Recap from the previous slate's post: Two underwhelming but predictable outcomes came from the regression candidates yesterday. Bubic was slated to benefit from BABIP regression, and he did with a .176 BABIP, but it was assumed he would still be subpar and he was. Meanwhile, Peralta finished with two hits and just three strikeouts. Considering he was an avoid due to low upside, this played out perfectly.

Passage from the MLB True AVG report from 8.31.2022
Passage from the MLB True AVG report from 8.31.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.31.2022
Scoring Percentages from the MLB Models for Paydirt 8.31.2022
Stack priority matrix from the MLB models for Paydirt 8.31.2022
Stack priority matrix from the MLB models for Paydirt 8.31.2022
MLB Game Betting model results for Paydirt 8.31.2022
MLB Game Betting model results for Paydirt 8.31.2022

MLB True AVG notable results

Leading off with the best True AVG we have Spencer Strider. Not only does Strider have the best True AVG today, but if you look at the season long models (found here) you'll see him at the top of the list there as well! The mustachioed madman has one of the best strikeout rates in the league at 36.10% and his luck rates are all leveled out. Likewise, he doesn't have the same walk rate issues most fireballers do. Meanwhile, he's got a matchup with the Rockies and they are fucking terrible. Look to utilize Strider in all formats.

Next up is the pitcher with the worst True AVG, as well as the largest negative deviations, Glenn Otto. With a walk rate of 13.3% and a strikeout rate of 14.2%, he is a mere couple of centimeters away from hitting the chode zone. Likewise, his BABIP is drastically low and his xFIP of 5.49 is almost twice as high as his recent sample ERA. Overall, these things bode pretty badly for Mr. Otto. His matchup with the Red Sox is league average though they do have above average power. In sum, you'll want to have some Red Sox power hitters in your exposures and avoid Glenn Otto in all formats.

Significant deviations to consider

  • This is a pretty small slate of pitchers, so there aren't really any significant deviations. Therefore, I will leave you with a quirky fact: It is impossible to hum while holding your nose. Go ahead and try it out. Feels weird as shit.

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MLB True AVG Report – 8.31.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.31.2022
MLB True AVG model results for 8.31.2022

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.

Passage from the MLB True AVG report from 8.29.2022
Passage from the MLB True AVG report from 8.29.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.30.2022
Stack priority matrix from the MLB models for Paydirt 8.30.2022
Stack priority matrix from the MLB models for Paydirt 8.30.2022
MLB Game Betting model results for Paydirt 8.30.2022
MLB Game Betting model results for Paydirt 8.30.2022

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.

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MLB True AVG Report – 8.29.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.29.2022
MLB True AVG model results for 8.29.2022

Recap from the previous slate's post: Both large deviations from the models last night had drastic outcomes. Patrick Corbin ended up giving up just four hits (.188 BABIP) with five strikeouts and one earned run. On the other hand, Cabrera gave up six runs on five hits with just five strikeouts.

Passage from the MLB True AVG report from 8.28.2022
Passage from the MLB True AVG report from 8.28.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.26.2022
Stack priority matrix from the MLB models for Paydirt 8.28.2022
Stack priority matrix from the MLB models for Paydirt 8.28.2022
MLB Game Betting model results for Paydirt 8.28.2022
MLB Game Betting model results for Paydirt 8.28.2022

MLB True AVG notable results

The best True AVG belongs to Brayan Bello. After being removed from the rotation for a couple weeks he came back against the Blue Jays and spun a gem. However, he still had a BABIP far too high in that start, and he has more positive regression coming. With terrific strikeout rates and a good pedigree, we should expect his xFIP of 3.77 to give some very strong performances moving forward. He faces the Twins today who are league average in all forms. In sum, look to use Bello in GPPs and prioritize his ceiling.

Moving along, the worst True AVG goes to Miles Mikolas. Granted, his True AVG of .288 is not terrible and is more along the lines of below average. Mikolas is a contact oriented pitcher that looks to mitigate damage rather than avoid it. Because of this, he rarely gets blown up and is hard to stack against. Likewise, he is facing the Reds who are a bad team with low power outputs. Overall this is just an avoid on all sides.

Significant deviations to consider

  • The largest positive deviations technically go to Brayan Bello, but we already noted him as a priority. Instead we will look to Robert Stephenson up against the Brewers. Stephenson is a bullpen arm being stretched out right now. He went just two innings in his last start and should be expected a bit farther here. He's been very unlucky in terms of both BABIP and LOB rate and his xFIP is less than half of his current ERA. The Brewers are considerably better against RHP but are just above league average in wRC+ at 108. In conclusion, this is a volatile spot to target but there is upside if in that risk.
  • Lastly the largest negative deviations go to Dylan Bundy facing the Red Sox. Over the recent sample he has just a .178 BABIP along with unsustainably low home run rates. Meanwhile, his xFIP is above 5.00 and his ERA is below 3.00 for a difference of over two runs. The Red Sox are a league average matchup but they do have above average power. Overall, Bundy isn't the kind of pitcher that can mitigate downside when things go wrong. This makes the Red Sox a strong stack in all formats and the unders for Bundy attractive.

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MLB True AVG Report – 8.28.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.28.2022
MLB True AVG model results for 8.28.2022

Recap from the previous slate's post: Solid outcomes across the board from the previous report. One of the most satisfying outcomes came from the Tigers up against Glenn Otto. He had the largest negative deviations and gave up four runs on five hits across five innings.

Passage from the MLB True AVG report from 8.26.2022
Passage from the MLB True AVG report from 8.26.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.26.2022
Scoring Percentages from the MLB Models for Paydirt 8.26.2022
Stack priority matrix from the MLB models for Paydirt 8.26.2022
Stack priority matrix from the MLB models for Paydirt 8.26.2022
MLB Game Betting model results for Paydirt 8.26.2022
MLB Game Betting model results for Paydirt 8.26.2022

MLB True AVG notable results

Leading the way for the True AVG models is Aaron Sanchez. He's had back-to-back solid starts with twelve strikeouts in nine innings with four runs allowed and now gets an easy matchup with the Giants. Likewise, his BABIP is inflated and should come down, so we would expect a tad more luck as well. Speaking of the Giants, they have an 85 wRC+ and are a bit below league average in most areas. Granted, it's always possible that we see Sanchez turn into a pumpkin, considering he is a career long pumpkin, but this matchup is winnable. In sum, the True AVG and positive deviations mean we should give him a shot in GPPs.

On the other hand we look to Zach Davies with the worst True AVG available. Davies not only has the worst True AVG on the slate by a good margin, but he also has significant negative deviations of over -.100. His BABIP and LOB rates are both unsustainable and his xFIP is around 1.5 runs above his ERA. He has very poor strikeout stuff, so when the luck turns around there's nothing to mitigate his downside. His opponent, the White Sox, are a league average team. Overall we should be attacking Davies every start until he implodes.

Significant deviations to consider

  • The largest positive deviations go to Patrick Corbin up against the Reds. Moving forward, this report may actually be named “How is Patrick Corbin doing this week?” just to make it more apt. That said, he's doing better this week that before, but not quite to where we expect. Importantly, we expect him to be a 4.5-5.5 ERA pitcher, which is really bad, so even with good fortune that doesn't necessitate a priority. The Reds strikeout at the third highest rate in the league, but otherwise are a league average team with solid power. In conclusion, there's no reason to use Corbin, but fading the Reds (if highly owned) is valuable based on the deviations.
  • Lastly the largest negative deviations belong to Edward Cabrera facing the Dodgers. Pitchers like Cabrera are able to get away with being sloppy against medium to bad teams because they have such crazy stuff. However, they will typically falter against teams with good plate discipline like the Dodgers. Likewise, Cabrera is due for massive regression, considering his BABIP of .178, LOB rate of 100%, and home run rates of literally 0%. Unfortunately for Cabrera, this is a spot that can blow up in his face as the Dodgers are the third best team in the league against RHP. Stack the Dodgers at low ownership and profit.

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MLB True AVG Report – 8.26.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.26.2022
MLB True AVG model results for 8.26.2022

Recap from the previous slate's post: It was admittedly a tame day for the models predictions as well as the outcomes. Jordan Lyles had an okay, but not great, results as the largest positive deviation. He went seven innings with just one earned run but only one strikeout.

Passage from the MLB True AVG report from 8.25.2022
Passage from the MLB True AVG report from 8.25.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.25.2022
Scoring Percentages from the MLB Models for Paydirt 8.25.2022
Stack priority matrix from the MLB models for Paydirt 8.25.2022
Stack priority matrix from the MLB models for Paydirt 8.25.2022
MLB Game Betting model results for Paydirt 8.25.2022
MLB Game Betting model results for Paydirt 8.25.2022

MLB True AVG notable results

The models have three pitchers with True AVGs well above the field: Justin Steele, Spender Strider, and Reid Detmers. All three of these guys are priorities, but we will focus on Steele here. He's been downright phenomenal in the recent sample, with a strikeout rate above 30% and an xFIP of just 1.85. And if you are a Paydirt subscriber, the projections models have been telling you to play him every start to great results. He is facing the Brewers, who he faced in his last start as well, who are just tragically bad against LHP and hold a 31% strikeout rate in split. This is one of the best spots and while Steele may carry heavy ownership he is worthwhile.

Similarly to the best True AVGs, the models find two pitchers well below the rest in the metric: Bryse Wilson and Chad Kuhl. Both pitchers are bad and have bad matchups, with Wilson facing the Phillies (111 wRC+) and Kuhl facing the Mets (137 wRC+). While Wilson is technically the “better pitcher” by xFIP, his BABIP and LOB rates are pointing to some drastic regression coming soon. On the other hand, Chad Kuhl is a thick chode, with both his strikeout and walk rate sitting at 14.3% in the recent sample. Overall we want to look to the Mets and Phillies as top stacking options on the slate.

Significant deviations to consider

  • The largest positive deviations belong to our friend Reid Detmers who is up against the Blue Jays. Since returning from his stint in the minors he's found a much better strikeout rate which has boosted his ceiling. Likewise, his BABIP has been unsustainably high so we should expect even better outcomes ahead. His matchup with the Blue Jays is rough, but not impossible. Their wRC+ of 112 against LHP is great but not enough to outright avoid a pitcher. In sum, we likely get an ownership discount on Demters today and we should leverage it. Look to hit the over on his strikeouts and utilize him in GPPs.
  • Finally we have the largest negative deviations going to Glenn Otto up against the Tigers. We can just get it out of the way now: The Tigers are fucking bad. They have just a 70 wRC+ and an ISO under .100. However, Otto's regression situation might be worse, with BABIP and LOB rates both way off base. His ERA is almost 3 runs below his xFIP as well. This matchup is like an island game between the Texans and the Jets but neither side has any cornerbacks. Do you want to play it? Absolutely not. But we should. Take the over on the Tigers and unders on Otto.

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MLB True AVG Report – 8.25.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.25.2022
MLB True AVG model results for 8.25.2022

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.

Passage from the MLB True AVG report from 8.24.2022
Passage from the MLB True AVG report from 8.24.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.24.2022
Scoring Percentages from the MLB Models for Paydirt 8.24.2022
Stack priority matrix from the MLB models for Paydirt 8.24.2022
Stack priority matrix from the MLB models for Paydirt 8.24.2022
MLB Game Betting model results for Paydirt 8.24.2022
MLB Game Betting model results for Paydirt 8.24.2022

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.

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MLB True AVG Report – 8.24.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.24.2022
MLB True AVG model results for 8.24.2022

Recap from the previous slate's post: While the prediction for Robbie Ray was an easy one to make, he still came through. He went 6.2 innings with just two hits, one run, and seven strikeouts.

Passage from the MLB True AVG report from 8.23.2022
Passage from the MLB True AVG report from 8.23.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.23.2022
Scoring Percentages from the MLB Models for Paydirt 8.23.2022
Stack priority matrix from the MLB models for Paydirt 8.23.2022
Stack priority matrix from the MLB models for Paydirt 8.23.2022
MLB Game Betting model results for Paydirt 8.23.2022
MLB Game Betting model results for Paydirt 8.23.2022

MLB True AVG notable results

There are two pitchers at the top of the True AVG models today: Blake Snell and George Kirby. Both of these guys have been covered in multiple starts and it's no different today. Snell continues to benefit from a drastically reduced walk rate while maintaining a fantastic strikeout rate. Meanwhile, Kirby has similar baselines but has benefited from a home run rate that is much too low. Neither of these pitchers have great matchups, as both the Guardians (against Snell) and the Nationals (Against Kirby) are both around league average in their respective splits. Overall both of these pitchers are strong options in all formats and betting props.

Next up with the worst True AVG we find Jose Urena. He's just so fucking bad. And has been for, like, multiple years now. How does this guy keep getting work? Anyway, the Rangers are a strong stack in GPPs but will be popular. Make sure if you utilize them that you build in leverage in other parts of your lineups.

Significant deviations to consider

  • The largest positive deviations today belong to Brayan Bello who faces the Blue Jays. Granted, this is a really tough spot overall, but Bello has a lot of regression in his favor. His BABIP is far too high at above .450 and his strikeout rates have been awesome. The big issue here is a walk rate north of 10%. All of that said, he's a very volatile play in DFS but that is what we look for in GPPs. Hit his overs in strikeouts and take a shot on him in GPPs if you need the salary relief.
  • Finally there are two pitchers with large negative deviations: Shane McClanahan and Cal Quantrill. McClanahan has a prime matchup with the Angels and their 73 wRC+ against LHP, but his BABIP has been too low and his strikeout rates are down. On the other hand, Quantrill has a spot against the Padres who are a top five team against RHP and has both BABIP and home run rate regression acting against him. Overall, the much better play is stacking up the Padres than the Angels. In sum, you'll want to avoid Quantrill at all costs and be careful with McClanahan.

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MLB True AVG Report – 8.23.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.23.2022
MLB True AVG model results for 8.23.2022

Recap from the previous slate's post: We had a fantastic outcome for Syndergaard with the largest positive deviations on the day. He faced the Reds and gave up just one run on three hits over seven innings.

Passage from the MLB True AVG report from 8.22.2022
Passage from the MLB True AVG report from 8.22.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.22.2022
Scoring Percentages from the MLB Models for Paydirt 8.22.2022
Stack priority matrix from the MLB models for Paydirt 8.22.2022
Stack priority matrix from the MLB models for Paydirt 8.22.2022
MLB Game Betting model results for Paydirt 8.22.2022
MLB Game Betting model results for Paydirt 8.22.2022

MLB True AVG notable results

Getting started with the best True AVG is Aaron Sanchez. Granted, we have been here before with Sanchez and have been let down time and time again. However, in his last start his strikeout rates were fantastic and his other baselines were promising. He's got a matchup with the Astros and their 99 wRC+ to RHP. While that isn't a daunting task in itself, it is a much harder spot than his last opponent. Sanchez is likely not valuable in DFS but his overs on strikeout props look good.

Next up with the worst True AVG is Jonathan Heasley. Over the course of the full season there is very little to be optimistic about with Heasley and the recent sample is more of the same. He's got mediocre strikeout stuff and a bad walk rate to go with middling groundball rates. Basically he is unable to mitigate any damage should things go sideways. His opponent, the Diamondbacks, are league average but with a very low strikeout rate. It's very easy to hit the unders for Heasley overall and grab the Diamondbacks as a secondary stack in GPPs.

Significant deviations to consider

  • Although there are a handful of guys with strong marks, the largest positive deviations belong to Robbie Ray against the Nationals. He's been able to maintain great strikeout rates while getting super unlucky with BABIP in the recent sample. Likewise his home run rates should come down as well. His xFIP is two runs below his ERA and it speaks well to his ceiling. The Nationals are mostly a league average team but they are strikeout prone with a 25% strikeout rate which is what we love to see. Overall, Robbie Ray is an easy plug and play in all formats.
  • Finally there are two pitchers with large negative deviations: Tony Gonsolin and Ranger Suarez. Gonsolin is facing the Brewers and has been getting really lucky with both BABIP and home run rates. Likewise, Suarez has nearly identical baselines and luck benefit and faces the Reds. Gonsolin would be the one to attack between these two simply because the Brewers are so strong against RHP. In sum, go ahead and take a shot on the Brewers in GPPs but regardless of that make sure you avoid both of these pitchers.

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MLB True AVG Report – 8.22.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.22.2022
MLB True AVG model results for 8.22.2022

Recap from the previous slate's post: It was a clean sweep in the deviations for the Models last night. Patrick Corbin finished with just two earned runs in 5.1 innings pitched against the Padres. Likewise, Arihara went six innings pitched with just four hits allowed and three strikeouts.

Passage from the MLB True AVG report from 8.21.2022
Passage from the MLB True AVG report from 8.21.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.21.2022
Scoring Percentages from the MLB Models for Paydirt 8.21.2022
Stack priority matrix from the MLB models for Paydirt 8.21.2022
Stack priority matrix from the MLB models for Paydirt 8.21.2022
MLB Game Betting model results for Paydirt 8.21.2022
MLB Game Betting model results for Paydirt 8.21.2022

MLB True AVG notable results

Leading off with the best True AVG we have Max Scherzer. This season has, in nearly all regards, been more of the same for Scherzer. Granted, his home run rates are too low on the season long side, but outside of that he's been the ace we all expected. While we should expect more home runs in the near future his upside mitigates that damage. He's got a matchup with the Yankees and will likely strikeout 12 hitters and give up a home run to Aaron Judge. Overall you'll certainly want to prioritize him in all formats.

Moving along to the Worst True AVG there are a couple worth considering but we will look at Cole Ragans. This is one of those situations where we are looking at a bad pitcher but in this instance we expect him to get notably worse. Ragans is a chode with a walk rate higher than his strikeout rate and a low groundball rate as well. All of that combined with a BABIP too low and you've got a powder keg. He's facing the Twins who are a tad below league average against LHP but with above average power. In sum, the Twins make for a great focus in DFS and you'll want to avoid Ragans in all formats.

Significant deviations to consider

  • By far the largest positive deviations go to Noah Syndergaard up against the Reds. While the ceiling no longer remains for Thor after his surgery, he's still a serviceable back of the order arm. That said, his BABIP is far too high in the recent sample and we should expect some better results. His matchup with the Reds is advantageous as well, but nothing insane as their wRC+ is an 86 and their strikeout rates are average. In conclusion this is a good spot for Syndergaard to find some positive regression so look to leverage the overs in his props.
  • Lastly on the report is the largest negative deviations which belong to Luis Cessa facing the Phillies. Cessa is converting from the bullpen into a spot starter and it's going to be rough. His BABIP, LOB rates, and home run rates are all due to large corrections. Likewise, he hasn't given up a run in the recent sample and his xFIP is close to 4.00. Facing the Phillies is a neutral proposition in terms of wRC+9 but they do have strong power upside. The best plan here is to grab the power bats from the Phillies and take the unders on Cessa.

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MLB True AVG Report – 8.21.2022

PayDirt MLB Image

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

MLB True AVG model results for 8.21.2022
MLB True AVG model results for 8.21.2022

Recap from the previous slate's post: The models were strong in the previous report (from two days ago). Kevin Gausman was the best True AVG and largest positive deviations and went seven innings against the Yankees. He gave up just four hits and one walk with seven strikeouts. On the other hand, McCullers ran into trouble against the Braves. He gave up seven hits and three runs with a home run.

Passage from the MLB True AVG report from 8.19.2022
Passage from the MLB True AVG report from 8.19.2022

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!).

Scoring Percentages from the MLB Models for Paydirt 8.20.2022
Scoring Percentages from the MLB Models for Paydirt 8.20.2022
Stack priority matrix from the MLB models for Paydirt 8.20.2022
Stack priority matrix from the MLB models for Paydirt 8.20.2022
MLB Game Betting model results for Paydirt 8.20.2022
MLB Game Betting model results for Paydirt 8.20.2022

MLB True AVG notable results

Leading off with the best True AVG is Shohei Ohtani. The guy just fucks. He's the MLB version of the Karma Sutra.

Next up with the worst True AVG is Kyle Gibson. Granted, he had the best game of his life in his last start, but we shouldn't expect that to continue. Gibson has maintained low strikeout rates and a middling xFIP all year and True AVG sees him as a well below average pitcher. He's got a matchup with the Mets who are the third best team in the league against RHP and have low strikeout rates as well so that makes things even worse. Overall Gibson is an easy avoid in all formats and the Mets overs are attractive.

Significant deviations to consider

  • We have a couple large positive deviations to consider today: Patrick Corbin and Kohei Arihara. There have been plenty of pieces on Corbin in this report and he should continue to trend up. He faces the Padres who are good against RHP but have just a 71 wRC+ against LHP. Meanwhile Arihara is up against the Twins and was very unlucky in his first start. That said he did have improved strikeout rates on his career sample and might be somebody to monitor moving forward. In sum, it's likely best to just avoid stacking against these pitchers and take a shot on Arihara in large field GPPs.
  • Lastly on the report is the largest negative deviations going to Jose Urquidy against the Braves. This report has covered Urquidy quite a few times and he has continued to skirt by thanks to a lot of luck. His BABIP, LOB rates, and home run rates have all been out of whack and in need for regression. Likewise, his xFIP is nearly two runs over his ERA in this span so that's more justification of regression. Meanwhile, without a good strikeout rate to mitigate downside he's an easy spot to avoid. This kind of baseline might hold up against a bad opponent, but he faces the Braves today who are a top five team in power against RHP. Overall you should be attacking Urquidy in DFS and taking his unders in the betting markets.

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