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Diamond Data — 10 Stats to Know for MLB DFS Thursday (4/14)

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Data in baseball runs deeper and is more comprehensive than in any other sport. These are the 10 stats I find most relevant to Thursday’s DFS slate.

 

1. The Cubs and Rockies have a combined implied total over 11.5 runs

Despite this, only one hitter from this game, Frank Schwindel, is priced over $5k. Many strong bats are in the $3ks. Consequently, this game will be mega-chalk, but it may be worth trying to stack it in a contrarian way rather than fading it altogether.

2. Kyle Freeland uses five pitches, leading to just a 26% fastball rate (not including sinkers and cutters)

This presents an opportunity to find hitters who benefit from the multiple types of “fastballs.” Cubs who hit cutters and sinkers better than fastballs:

(Build your MLB DFS lineup with our Optimizer!)

3. Justin Steele throws a sinker or slider around 40% of the time, and both pitches in this game lost over a run and a half per 100 pitches (they’re terrible)

Rockies who stand to benefit:

If there’s a reason to fade Colorado bats, it’s that as a whole, they’re a poor fit for Steele’s pitch mix.

4. Casey Mize threw one sinker in his opening start, despite a 22% sinker usage a year ago

This is a drastic change, and it’s potentially a smart one. He lost a run per 100 sinkers, but his fastball was fairly neutral. The matchup with KC is an intriguing one — they have numerous players who struggle against fastballs, crush sinkers and struggle with sliders, Mize’s best pitch.

Mize could be a great option if using multiple chalk stacks.

5. Six pitchers project within 4 DK points of one another in the Strikeout Model

Table

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With such little separation in this grouping, the decisions could/should come down to price and ownership. I will, however, note that Kevin Gausman begins to separate from a ceiling perspective with his probabilities of scoring at least 25 and 30 DK points.

6. Shohei Ohtani’s slider is elite, gaining 2.35 runs per 100 pitches

This is noteworthy considering I suggested fading chalk Texas bats Tuesday due to their weakness against sliders (as seen below). While Ohtani doesn’t throw as many of them as Chad Kuhl, his is even better. 

Chart, table

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7. Kevin Gausman throws splitter around one-third of the time and gains over 2 runs per 100 splitters

The Yankees are a mixed bag against splitters. While the vast majority of their lineup crushes fastballs, only Aaron Hicks, DJ LeMahieu and Josh Donaldson have fared well against the split. Aaron Judge, Giancarlo Stanton and Gleyber Torres have struggled immensely with it.

The decision to use Gausman or not will likely come down to his ownership for me.

 

8. Luis Severino averaged 97.9 mph with his fastball in his opening start

CSW, or called strikes plus whiffs per pitch, is the best measure of command we have. Historically he has sat just under 30%, but in his opening start, he posted just 21.5%. The stuff however, can’t be questioned, as evidenced by the fastball velocity. 

Consider Severino as another viable option to provide enough differentiation alongside two chalk stacks.

(More: Check out Jake Kucheck’s look at the Thursday starting pitching slate in The Opener.)

9. Spencer Torkelson hit 25 home runs in 90 minor league games in 2021

As Zack Greinke’s skillset continues to deteriorate, we can begin to consciously attack him. In fact, the Tigers are third in Kyle Murray’s HR Rater. Torkelson has a .318 wOBA and .235 ISO to begin the season, suggesting he’ll have no trouble continuing his success at the plate despite the jump to the majors.

10. Walker Buehler is projected for just 14.7 pitches per inning

Pitch-per-inning efficiency is incredibly predictive of fantasy success for pitchers, as it has signal for all of command, power/run prevention, and strikeout potential. Buehler’s baseline pitches per inning of just 15.1 is already strong, but it should be magnified by this Cincinnati order. They have the 4th lowest walk rate and 4th lowest OBP so far this season, both of which line up with the historical performance of their individual players.

This projected pitch-per-inning efficiency is the reason Buehler’s projected DK points is first on the slate according to the Strikeout Model.

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