Andrew's Musings

MLB: What to watch on August 17, 2025

Here are today's MLB games, ordered by watchability, based on how interesting the teams and starting pitchers look. Higher is better. For more information, read this post.

Notes:

Detail

Miami Marlins @ Boston Red Sox, 10:35a

Summary

This is mostly worth watching because Garrett Crochet is the kind of pitcher who makes every inning feel consequential; Miami’s Janson Junk provides enough unpredictability that the game rarely feels dull. The very high gNERD (15.69) comes almost entirely from Crochet’s pNERD (11.88) and Boston’s stronger team profile, so expect a pitcher-driven game that tilts toward strikeout-heavy swings and defensive plays.

Crochet pairs top-end velocity and swing-and-miss stuff with an outstanding underlying profile (elite xFIP and a season full of strikeouts), which explains why he’s the main attraction and why his starts tend to be watchable. Junk’s profile is the opposite: a journeyman lefty recently worked into Miami’s rotation after a minor-league deal and call-up, offering decent control but far less swing-and-miss upside, so his starts invite either length or a quick bullpen parade. Boston’s team metrics (better barreling, fielding and bullpen components) amplify the mismatch and the chances this turns into a one-sided outing — or, if Junk tangles a few hitters early, a tense bullpen chess match. Overall: prioritize this for Crochet’s strikeout theater and the tactical late-innings possibilities; don’t expect a high-offense slugfest.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

Miami Marlins

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -17.6 8.0% -2.0 5.3 16.1 $67.3M 26.8 6.0
Z-score -0.31 -0.45 -0.38 0.28 -0.52 -1.42 -1.96 0.28
tNERD -0.31 -0.45 -0.38 0.28 -0.52 1.42 1.96 0.28 4.00 6.26

Boston Red Sox

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 24.5 9.8% 5.0 18.8 45.4 $191.8M 28.7 -13.0
Z-score 0.48 1.02 0.79 0.98 1.16 0.25 -0.02 -0.62
tNERD 0.48 1.02 0.79 0.98 1.16 0.00 0.02 0.00 4.00 8.46

Janson Junk, Miami Marlins

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 97 9.0% 68.4% 93.7 mph 29 18.6s -2 0.0%
Z-score -0.23 -0.74 1.82 -0.06 0.07 0.05
pNERD 0.47 -0.37 0.91 0.00 0.00 -0.03 0.00 0.00 3.80 4.78

Garrett Crochet, Boston Red Sox

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 64 13.6% 67.0% 96.2 mph 26 17.2s -5 0.0%
Z-score -2.21 1.49 1.22 1.06 -0.70 -1.08
pNERD 4.41 0.75 0.61 1.06 0.70 0.54 0.00 0.00 3.80 11.88

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Seattle Mariners @ New York Mets, 4:10p

Summary

Quality matchup on paper: George Kirby’s high-end stuff (pNERD 8.68) vs. a Mets lineup and roster that scream watchability (tNERD 8.98), which pushes this game into the upper tail of interest (gNERD 13.01). The headline is simple — Kirby is the reason to tune in: his underlying profile (excellent xFIP-, elite command history and mid-90s velo) is what drives that pNERD and makes every inning matter.

Clay Holmes is a less compelling counter: a converted reliever with an average xFIP- and a low SwStr/zone footprint in this matchup (pNERD 3.03), and recent starts have shown both workload questions and some command wobble as he settles into a starter’s role.

Beyond the arms, the Mets supply big offensive perks — above-average barrel rate, baserunning, and a bullpen that boosts their team NERD — while Seattle’s offense has pop but shakier defense, which sets up a decent clash of tidy starting pitching against an eventful lineup.

If you prize pitcher-driven chess and a chance to see an elite young arm test a hitter-friendly club, this one’s worth prioritizing; if you want raw back-and-forth offense regardless of pitching, lower your expectations.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4, 5.)

Seattle Mariners

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 57.7 9.3% -1.5 -16.5 14.5 $152.8M 28.2 12.0
Z-score 1.11 0.61 -0.30 -0.85 -0.62 -0.27 -0.53 0.56
tNERD 1.11 0.61 -0.30 -0.85 -0.62 0.27 0.53 0.56 4.00 5.32

New York Mets

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 41.1 10.3% 6.2 3.6 37.9 $332.0M 29.7 18.0
Z-score 0.79 1.43 1.00 0.19 0.73 2.14 1.00 0.84
tNERD 0.79 1.43 1.00 0.19 0.73 0.00 0.00 0.84 4.00 8.98

George Kirby, Seattle Mariners

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 76 11.9% 66.5% 96.1 mph 27 19.7s 22 0.0%
Z-score -1.49 0.67 1.04 1.02 -0.45 0.94
pNERD 2.98 0.33 0.52 1.02 0.45 -0.47 0.05 0.00 3.80 8.68

Clay Holmes, New York Mets

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 100 9.0% 62.7% 93.7 mph 32 19.1s -8 0.0%
Z-score -0.06 -0.74 -0.57 -0.06 0.84 0.46
pNERD 0.11 -0.37 -0.28 0.00 0.00 -0.23 0.00 0.00 3.80 3.03

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Tampa Bay Rays @ San Francisco Giants, 1:05p

Summary

If you like watching an ace try to shut everything down, this one’s worth a seat: Logan Webb’s profile makes the game a pitching event, and the numbers say he’s the reason to tune in. Webb’s pNERD (9.39) is the standout here — his scant xFIP- and leap in strikeouts make him both high-floor and high-drama on the mound, and he’s been the Giants’ clear staff ace this season. Ryan Pepiot (pNERD 5.85) is no slouch: above-average velocity and a decent K profile mean he can keep this competitive, but he’s a notch below Webb’s dominance. Team-wise, the Rays (tNERD 6.39) bring youthful athleticism and excellent baserunning that can manufacture action despite mediocre power and shaky defense, while the Giants’ weak offense and recent home struggles — compounded by Matt Chapman landing on the IL — mute spectacle at the plate. The gNERD (11.80) sits above today’s average, so expect a mostly cerebral, pitcher-driven contest: pick it if you prefer quality starts and strategic at-bats, skip it if you need fireworks.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

Tampa Bay Rays

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -2.5 7.6% 8.9 -29.1 39.0 $89.9M 27.4 -18.0
Z-score -0.03 -0.78 1.45 -1.51 0.79 -1.12 -1.35 -0.86
tNERD -0.03 -0.78 1.45 -1.51 0.79 1.12 1.35 0.00 4.00 6.39

San Francisco Giants

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -29.0 7.4% -7.8 10.1 30.0 $195.3M 29.3 -8.0
Z-score -0.53 -0.94 -1.36 0.53 0.27 0.30 0.59 -0.39
tNERD -0.53 -0.94 -1.36 0.53 0.27 0.00 0.00 0.00 4.00 1.97

Ryan Pepiot, Tampa Bay Rays

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 97 11.3% 65.0% 95.1 mph 27 18.1s -2 0.0%
Z-score -0.23 0.38 0.41 0.57 -0.45 -0.35
pNERD 0.47 0.19 0.20 0.57 0.45 0.18 0.00 0.00 3.80 5.85

Logan Webb, San Francisco Giants

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 67 10.6% 66.0% 92.7 mph 28 16.4s 15 0.0%
Z-score -2.03 0.04 0.83 -0.52 -0.19 -1.72
pNERD 4.06 0.02 0.41 0.00 0.19 0.86 0.05 0.00 3.80 9.39

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Texas Rangers @ Toronto Blue Jays, 10:37a

Summary

This one’s worth tuning into because you’ve got a genuine top-end arm against a quietly menacing lineup—Eovaldi’s the story, Berríos the counter—and the Jays’ offense just showed it can blow a game open. Nathan Eovaldi’s high pNERD (7.88) reflects an excellent xFIP- (72) and strong strike/whiff profile, so when he’s on he forces contact into low-value places and piles up Ks; that makes every early-inning at-bat feel consequential. José Berríos (pNERD 2.30) grades much lower: his xFIP- sits above average (106) and his swing‑and‑miss/strike rates are underwhelming, so this has the shape of a pitcher’s duel tilted toward Texas rather than a bullpen arms race. Toronto’s tNERD (6.81) is buoyed by huge batting runs and good defense, and they just thumped Texas 14–2 yesterday — George Springer was activated and bolsters that offense — so expect a lineup that can punish any mistake. The Rangers’ tNERD (5.77) leans on baserunning and fielding despite a thin bat. Overall gNERD 11.38 is a hair above today’s mean, signaling an above-average watchability mostly because of Eovaldi vs. a hot, deep Blue Jays offense.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3.)

Texas Rangers

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -60.4 8.7% 8.6 17.6 33.1 $219.7M 30.4 -30.0
Z-score -1.12 0.12 1.40 0.92 0.45 0.63 1.71 -1.43
tNERD -1.12 0.12 1.40 0.92 0.45 0.00 0.00 0.00 4.00 5.77

Toronto Blue Jays

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 74.0 8.2% -5.6 24.7 27.3 $248.4M 29.6 27.0
Z-score 1.41 -0.29 -0.99 1.29 0.12 1.01 0.89 1.27
tNERD 1.41 -0.29 -0.99 1.29 0.12 0.00 0.00 1.27 4.00 6.81

Nathan Eovaldi, Texas Rangers

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 72 12.7% 66.8% 94.0 mph 35 19.9s -29 0.0%
Z-score -1.73 1.05 1.14 0.07 1.61 1.10
pNERD 3.46 0.53 0.57 0.07 0.00 -0.55 0.00 0.00 3.80 7.88

José Berríos, Toronto Blue Jays

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 106 9.4% 63.8% 92.5 mph 31 19.9s -13 0.0%
Z-score 0.30 -0.55 -0.13 -0.61 0.58 1.10
pNERD -0.61 -0.27 -0.07 0.00 0.00 -0.55 0.00 0.00 3.80 2.30

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Pittsburgh Pirates @ Chicago Cubs, 11:20a

Summary

Watch this if you like offense and texture: the Cubs bring the pop and polished defense, while the Pirates send a high-velocity swingman who’s better at inducing contact than strikeouts. The gNERD (10.99) sits a touch above today's game average, driven mostly by Chicago's strong tNERD (8.34) and a playable pNERD for Carmen Mlodzinski (5.62) versus an unknown work profile for Javier Assad (pNERD 0.00). Mlodzinski profiles as a 95–96 mph righty with legit starter stuff but a very low whiff rate, so expect fewer strikeouts and more balls in play that test Wrigley’s defense — a recipe for action rather than dominance. Assad has been coming off the injured list after an oblique issue and rehab innings, so his role and effectiveness carry uncertainty; that lack of pitcher data explains his blank pNERD. The Cubs’ team metrics — barrels, baserunning, and fielding — are what elevate the matchup and make this worth prioritizing even if the pitching matchup promises contact-heavy innings.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

Pittsburgh Pirates

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -103.5 8.0% -7.4 10.8 33.7 $88.9M 28.4 4.0
Z-score -1.93 -0.45 -1.29 0.56 0.49 -1.13 -0.33 0.18
tNERD -1.93 -0.45 -1.29 0.56 0.49 1.13 0.33 0.18 4.00 3.02

Chicago Cubs

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 61.3 9.9% 8.4 25.7 14.0 $197.7M 30.6 -14.0
Z-score 1.17 1.11 1.37 1.34 -0.64 0.33 1.91 -0.67
tNERD 1.17 1.11 1.37 1.34 -0.64 0.00 0.00 0.00 4.00 8.34

Carmen Mlodzinski, Pittsburgh Pirates

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 96 9.0% 63.8% 95.9 mph 26 18.6s 2 0.0%
Z-score -0.29 -0.74 -0.12 0.93 -0.70 0.05
pNERD 0.59 -0.37 -0.06 0.93 0.70 -0.03 0.05 0.00 3.80 5.62

Javier Assad, Chicago Cubs

No detailed stats available

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New York Yankees @ St. Louis Cardinals, 11:15a

Summary

Tune in for a clear stylistic showdown: the Yankees bring big-barrel offense and run creation, while St. Louis counters with elite defense and a veteran who lives off contact. The gNERD (10.56) sits a hair above today’s slate, driven mostly by a Yankees tNERD (7.74) that glues together strong batting runs and an above-average barrel rate, while the Cardinals’ middling tNERD (5.45) gets its pop from top-tier fielding that will keep balls in play. Will Warren’s pNERD (5.44) grades better than Mikolas’s (2.50): Warren has been eating innings and missing enough bats to make the Yankees’ lineup pay if he’s on, per recent start logs. Mikolas, a crafty veteran, has shown a couple of clean, longer outings recently and benefits from the Cardinals’ rotation spacing, but his strike‑missing profile is thin — which plays into New York’s power advantage. The real narrative: expect an offense‑versus‑defense game where a shaky Yankees ‘pen and Mikolas’s ability to induce weak contact will decide whether this one is watchable or merely watchable-ish.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

New York Yankees

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 80.2 11.4% -2.7 6.6 16.8 $290.9M 29.1 11.0
Z-score 1.53 2.34 -0.50 0.35 -0.48 1.58 0.38 0.51
tNERD 1.53 2.34 -0.50 0.35 -0.48 0.00 0.00 0.51 4.00 7.74

St. Louis Cardinals

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -3.9 7.8% -3.8 26.4 39.2 $135.7M 28.6 -4.0
Z-score -0.06 -0.61 -0.69 1.37 0.80 -0.50 -0.13 -0.20
tNERD -0.06 -0.61 -0.69 1.37 0.80 0.50 0.13 0.00 4.00 5.45

Will Warren, New York Yankees

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 86 9.8% 61.7% 93.2 mph 26 19.1s 22 0.0%
Z-score -0.89 -0.35 -0.99 -0.29 -0.70 0.46
pNERD 1.78 -0.18 -0.50 0.00 0.70 -0.23 0.05 0.00 3.80 5.44

Miles Mikolas, St. Louis Cardinals

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 113 7.3% 66.4% 92.5 mph 36 17.6s 8 0.0%
Z-score 0.72 -1.56 1.00 -0.61 1.86 -0.75
pNERD -1.44 -0.78 0.50 0.00 0.00 0.38 0.05 0.00 3.80 2.50

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San Diego Padres @ Los Angeles Dodgers, 1:10p

Summary

Worth your time if you like veteran horsepower versus a shiny bullpen; less so if you need crisp, predictable pitching. Yu Darvish’s return-from-injury timeline and shaky season make him a gamble while Tyler Glasnow’s better stuff and healthier finish to recent outings tilt the edge to the Dodgers. Darvish has been eased back into the rotation and showed a quiet, effective outing against the Giants in his last turn, but durability and pitch-count management remain real factors. Glasnow’s profile — lower xFIP-, plus above-average velocity and a stronger pNERD here — suggests more swing-and-miss upside, though his injury history is the caveat teams still whisper about. Team-wise, this is a matchup of a Dodger lineup that carries clear offensive heft against a Padres club whose bullpen is a genuine asset and a big reason the game’s tNERD is respectable. The gNERD near 10.4 is essentially average—expect a contest driven by bullpen leverage and Glasnow’s ability to miss bats more than by long, clean outings from Darvish.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4, 5, 6.)

San Diego Padres

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 5.5 7.0% -1.0 -1.9 63.3 $209.3M 30.0 13.0
Z-score 0.12 -1.27 -0.22 -0.10 2.19 0.49 1.30 0.61
tNERD 0.12 -1.27 -0.22 -0.10 2.19 0.00 0.00 0.61 4.00 5.33

Los Angeles Dodgers

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 79.7 9.8% 0.2 -7.8 44.0 $341.0M 29.6 -2.0
Z-score 1.52 1.02 -0.01 -0.40 1.08 2.26 0.89 -0.10
tNERD 1.52 1.02 -0.01 -0.40 1.08 0.00 0.00 0.00 4.00 7.21

Yu Darvish, San Diego Padres

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 105 11.2% 64.1% 93.6 mph 38 20.6s 34 0.0%
Z-score 0.24 0.33 0.01 -0.11 2.38 1.66
pNERD -0.49 0.16 0.00 0.00 0.00 -0.83 0.05 0.00 3.80 2.70

Tyler Glasnow, Los Angeles Dodgers

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 87 11.2% 59.4% 96.1 mph 31 18.6s -14 0.0%
Z-score -0.83 0.33 -1.95 1.02 0.58 0.05
pNERD 1.66 0.16 -0.97 1.02 0.00 -0.03 0.00 0.00 3.80 5.65

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Detroit Tigers @ Minnesota Twins, 11:10a

Summary

Mildly watchable: the Tigers' tidy blend of young boppers and aggressive baserunning promises action, but an unremarkable Chris Paddack start and an opponent listed as “TBD” keep this from being a priority pick. The gNERD of 9.57 sits just under today’s mean (9.85) and slightly below the historical mean (10.11), which fits the profile — offense-leaning team context with modest starting-pitch intrigue. Detroit’s strong tNERD (7.08) comes from above-average barrel rate, baserunning, and fielding, so expect quality contact and corner-case run value when they’re swinging. Minnesota’s lower tNERD (4.19) plus a bullpen runs component that reads poorly suggests late-inning scoring volatility and potential rallies if Detroit gets to the pen. Chris Paddack’s pNERD (2.87) masks a mid-rotation profile: modest xFIP- (~109) and a low whiff profile, so he’s more hittable than headline-grabbing. The unknown opponent starter (pNERD 0.00) further reduces pitching drama. In short: tune in if you want offense and bullpen theater; skip if you need high-end pitching matchups.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3.)

Detroit Tigers

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 24.8 9.7% 4.8 10.4 5.6 $148.2M 27.6 -25.0
Z-score 0.49 0.94 0.76 0.54 -1.13 -0.33 -1.14 -1.19
tNERD 0.49 0.94 0.76 0.54 -1.13 0.33 1.14 0.00 4.00 7.08

Minnesota Twins

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -20.3 8.8% -7.6 -10.2 48.1 $145.1M 28.8 11.0
Z-score -0.36 0.20 -1.33 -0.53 1.31 -0.37 0.08 0.51
tNERD -0.36 0.20 -1.33 -0.53 1.31 0.37 0.00 0.51 4.00 4.19

Chris Paddack, Detroit Tigers

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 109 9.1% 65.6% 93.8 mph 29 18.5s 8 0.0%
Z-score 0.48 -0.69 0.64 -0.02 0.07 -0.03
pNERD -0.97 -0.35 0.32 0.00 0.00 0.01 0.05 0.00 3.80 2.87

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Los Angeles Angels @ Athletics, 1:05p

Summary

Soriano’s juice makes this worth a look; he’s the real show — A’s offense and a big luck bump keep things interesting even if the rest of the Angels aren’t helping. José Soriano’s high-velocity arsenal and solid peripherals (he’s averaging mid-to-high 90s and has been one of the Angels’ better starters this year) drive his strong pNERD and the main appeal here.

The matchup’s watchability splits: the Angels bring a low tNERD thanks to poor defense and a shaky pen, though their barrel rate suggests one big swing could flip a quiet game; the A’s have a much higher tNERD largely from an unusual luck spike and roster upgrades that add offensive fun. Soriano (pNERD 8.22) projects to rack whiffs and weak contact, while Jeffrey Springs (pNERD 2.38) profiles as the more hittable arm — lower velocity, worse xFIP relative to Soriano, and fewer missing‑pitches — which ups the chance of a run trade.

All told, gNERD 9.50 is close to today’s average: pitchability and a potential A’s offensive uplift make this a middling-but-watchable game for fans who prefer good stuff over tense bullpen chess.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3.)

Los Angeles Angels

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -17.1 10.7% -1.7 -41.2 -5.9 $203.8M 29.2 -14.0
Z-score -0.30 1.76 -0.33 -2.14 -1.79 0.41 0.49 -0.67
tNERD -0.30 1.76 -0.33 -2.14 -1.79 0.00 0.00 0.00 4.00 1.20

Athletics

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 31.0 8.3% 0.0 -17.4 13.2 $77.1M 27.6 44.0
Z-score 0.60 -0.20 -0.05 -0.90 -0.69 -1.29 -1.14 2.07
tNERD 0.60 -0.20 -0.05 -0.90 -0.69 1.29 1.14 2.00 4.00 7.19

José Soriano, Los Angeles Angels

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 83 11.4% 61.9% 97.3 mph 26 18.0s 11 0.0%
Z-score -1.07 0.42 -0.93 1.56 -0.70 -0.43
pNERD 2.14 0.21 -0.46 1.56 0.70 0.22 0.05 0.00 3.80 8.22

Jeffrey Springs, Athletics

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 110 10.9% 63.3% 90.7 mph 32 19.2s -13 0.0%
Z-score 0.54 0.18 -0.31 -1.42 0.84 0.54
pNERD -1.09 0.09 -0.15 0.00 0.00 -0.27 0.00 0.00 3.80 2.38

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Milwaukee Brewers @ Cincinnati Reds, 10:40a

Summary

Good eyeballs: Milwaukee’s team profile makes this the more entertaining game — they bring high defensive and baserunning juice — but the arms on the bump turn it from must-watch to “interesting if you like subtlety.” The gNERD (8.93) sits a hair below today’s average, but the split in tNERD is what matters: Brewers 9.43 vs Reds 3.44, so expect a Brewers-favored script where exciting small-ball (excellent baserunning and plus fielding) and roster depth drive action rather than a fireworks pitching duel. Quintana’s pNERD is near zero: low swing-and-miss and velocity, more innings-eater than strikeout artist; he’s coming off a six-inning, one-run tune-up. Abbott’s higher pNERD reflects better strike% and younger profile — he’s been a reliable, tidy innings eater (7.2 IP, 3 ER in his recent outing). The Brewers’ bullpen footprint just shifted with DL Hall to the IL, a move that could nudge late-inning intrigue. If you prioritize team-driven, tactical baseball with occasional bullpen theater, this is worth a look; if you want a high-K, ace-on-ace showcase, skip it.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4, 5.)

Milwaukee Brewers

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 50.2 6.4% 14.9 25.1 34.0 $112.2M 27.6 -44.0
Z-score 0.96 -1.76 2.46 1.31 0.50 -0.82 -1.14 -2.09
tNERD 0.96 -1.76 2.46 1.31 0.50 0.82 1.14 0.00 4.00 9.43

Cincinnati Reds

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -34.1 7.0% 5.6 -1.2 20.1 $115.7M 28.7 -29.0
Z-score -0.62 -1.27 0.89 -0.06 -0.29 -0.77 -0.02 -1.38
tNERD -0.62 -1.27 0.89 -0.06 -0.29 0.77 0.02 0.00 4.00 3.44

Jose Quintana, Milwaukee Brewers

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 113 6.7% 61.2% 90.5 mph 36 19.6s -30 0.0%
Z-score 0.72 -1.86 -1.21 -1.51 1.86 0.86
pNERD -1.44 -0.93 -0.60 0.00 0.00 -0.43 0.00 0.00 3.80 0.39

Andrew Abbott, Cincinnati Reds

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 107 11.0% 66.0% 92.7 mph 26 17.8s -52 0.0%
Z-score 0.36 0.23 0.80 -0.52 -0.70 -0.59
pNERD -0.73 0.11 0.40 0.00 0.70 0.30 0.00 0.00 3.80 4.59

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Baltimore Orioles @ Houston Astros, 11:10a

Summary

Don’t expect a fireworks show—this is a pitcher’s duel with a modest gNERD, but it’s worth watching if you like length and texture rather than blowouts. Dean Kremer is the headline: a reliable innings-eater with a midrange pNERD who’s been giving the O’s length and steady strikeout ability of late, making this attractive if you want multi-inning starting pitching and fewer bullpen quirks. The Astros’ lineup and bullpen raise the entertaining ceiling—Houston’s tNERD gets a boost from a hot relief corps and some positive “luck” in recent results—so a late-inning decision is plausible if the pen gets involved. Cristian Javier shows a pNERD of 0 here only because the scoring set lacked his data, but he’s just back from Tommy John and struck out five in a five-inning season return, which makes him an interesting wild card: quality stuff but command and workload are questions. Overall, an 8.03 gNERD is below today’s average and the historic median, so this is more of a quietly watchable pitching matchup than must-see TV—best for viewers who prefer process over fireworks.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3.)

Baltimore Orioles

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -16.1 9.1% -4.0 -17.6 12.9 $167.6M 29.2 -13.0
Z-score -0.29 0.45 -0.72 -0.91 -0.71 -0.07 0.49 -0.62
tNERD -0.29 0.45 -0.72 -0.91 -0.71 0.07 0.00 0.00 4.00 1.90

Houston Astros

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 15.7 7.7% -4.0 2.4 43.5 $221.9M 29.0 27.0
Z-score 0.31 -0.70 -0.72 0.13 1.05 0.66 0.28 1.27
tNERD 0.31 -0.70 -0.72 0.13 1.05 0.00 0.00 1.27 4.00 5.34

Dean Kremer, Baltimore Orioles

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 100 9.8% 66.1% 93.2 mph 29 19.5s 3 0.0%
Z-score -0.06 -0.35 0.85 -0.29 0.07 0.78
pNERD 0.11 -0.18 0.42 0.00 0.00 -0.39 0.05 0.00 3.80 3.82

Cristian Javier, Houston Astros

No detailed stats available

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Arizona Diamondbacks @ Colorado Rockies, 12:10p

Summary

Low-stakes drama: this rates as a low-to-middling watch — Arizona’s offense and baserunning give the game some spark, but blank pNERD lines for both starters and Arizona’s bullpen baggage make it hard to promise consistent excitement.

The gNERD of 7.76 sits below today’s game average and the historical mean, so this isn’t a “must-watch” on paper; it’s watchable because Arizona’s team profile (tNERD 5.80) shows real batting, barrel, and baserunning value that can produce runs, while Colorado’s team profile drags the overall score down with a brutal negative batting and defensive footprint. The D-backs’ bullpen has been a recurring problem in recent games, which raises the odds of late-inning chaos. Colorado appears to be trotting out a veteran with a spotty season and recent time off, which makes the pitching matchup more uncertain than intriguing. Both starters show pNERD = 0, meaning we don’t have pitcher-level data to lean on, and Crismatt is essentially an unknown in this role. If you like Coors-field run-fests or bullpen volatility, tune in; otherwise, put this lower on the priority list.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

Arizona Diamondbacks

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 60.2 9.2% 4.5 7.2 -3.2 $189.5M 29.5 14.0
Z-score 1.15 0.53 0.71 0.38 -1.63 0.22 0.79 0.65
tNERD 1.15 0.53 0.71 0.38 -1.63 0.00 0.00 0.65 4.00 5.80

Colorado Rockies

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -116.1 8.2% -8.3 -28.6 -2.4 $125.9M 27.9 26.0
Z-score -2.17 -0.29 -1.44 -1.48 -1.59 -0.63 -0.84 1.22
tNERD -2.17 -0.29 -1.44 -1.48 -1.59 0.63 0.84 1.22 4.00 -0.27

Nabil Crismatt, Arizona Diamondbacks

No detailed stats available

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Atlanta Braves @ Cleveland Guardians, 10:40a

Summary

Low gNERD (6.84) means this isn’t a headline pitching duel—expect a middling game rather than a spectacle. Still, Logan Allen’s uptempo lefty profile and Atlanta’s offensive lift with Ronald Acuña Jr. returning give the game enough texture to keep it interesting for fans who like action over artistry.

The numbers say why: team NERDs are middling (5.04 Braves, 5.96 Guardians), so neither club offers consistently elite offense or chaos, and the matchup’s average pitcher NERD is a snooze-inducing 1.34. Logan Allen is the more watchable hurler here — his pNERD (3.29) buys you a brisk pace and a reliable length, even if his strike/wiff rates aren’t electric; he’s been eating innings lately while issuing the odd walk. Erick Fedde’s pNERD (-0.60) and poor xFIP and whiff metrics suggest he’s hittable and unlikely to pile up K’s, so expect contact and a chance for a higher-scoring, less-rosy game if Atlanta’s lineup — now bolstered by Acuña’s activation — wakes up. In short: not a can’t-miss, but worth tuning in if you prefer brisk innings, a lefty starter, and a lineup with renewed bite.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

Atlanta Braves

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -5.9 9.2% -3.1 13.5 16.9 $216.2M 29.4 20.0
Z-score -0.09 0.53 -0.57 0.70 -0.48 0.58 0.69 0.94
tNERD -0.09 0.53 -0.57 0.70 -0.48 0.00 0.00 0.94 4.00 5.04

Cleveland Guardians

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -60.0 6.7% 4.3 15.0 41.5 $102.3M 27.5 -25.0
Z-score -1.11 -1.52 0.68 0.78 0.93 -0.95 -1.25 -1.19
tNERD -1.11 -1.52 0.68 0.78 0.93 0.95 1.25 0.00 4.00 5.96

Erick Fedde, Atlanta Braves

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 129 7.1% 60.2% 93.2 mph 32 17.2s 2 0.0%
Z-score 1.68 -1.66 -1.61 -0.29 0.84 -1.08
pNERD -3.36 -0.83 -0.80 0.00 0.00 0.54 0.05 0.00 3.80 -0.60

Logan Allen, Cleveland Guardians

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 113 7.8% 61.7% 90.5 mph 26 15.1s -15 0.0%
Z-score 0.72 -1.32 -0.99 -1.51 -0.70 -2.77
pNERD -1.44 -0.66 -0.49 0.00 0.70 1.38 0.00 0.00 3.80 3.29

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Chicago White Sox @ Kansas City Royals, 11:10a

Summary

Low-energy afternoon: a gNERD of 6.67 puts this game at the bottom of today’s watchability list — think steady yawns, not instant classics. The numbers explain why: both clubs rank poorly for offense and batted-ball explosiveness (Chicago and Kansas City sit deep in negative batting-run and barrel-rate territory), so big, fun innings are unlikely. Pitching is similarly uninspiring on paper: Davis Martin and Ryan Bergert both post pNERDs near 3, which shows modest strikeout upside, middling xFIP marks, and low swinging-strike rates — the kind of matchup that tends to produce length but not fireworks. There is a wrinkle: Bergert is a young arm who’s looked effective since joining Kansas City and offers a deceptive changeup, while Martin has bounced back from injury with some usable outings; both narratives add mild intrigue but not enough to bump the game into “tune in” territory. The Royals’ recent home comfort and roster moves (a reinsertion of Michael Lorenzen and steady offense) make them the safer bet, but that’s more context than pure entertainment.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

Chicago White Sox

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -76.8 8.1% -4.0 -26.1 30.6 $79.0M 27.5 -9.0
Z-score -1.43 -0.37 -0.72 -1.35 0.31 -1.26 -1.25 -0.43
tNERD -1.43 -0.37 -0.72 -1.35 0.31 1.26 1.25 0.00 4.00 2.95

Kansas City Royals

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -62.4 7.5% -2.6 7.3 28.1 $130.0M 28.8 28.0
Z-score -1.16 -0.86 -0.48 0.38 0.16 -0.58 0.08 1.32
tNERD -1.16 -0.86 -0.48 0.38 0.16 0.58 0.00 1.32 4.00 3.94

Davis Martin, Chicago White Sox

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 107 9.5% 62.7% 93.6 mph 28 17.2s -5 0.0%
Z-score 0.36 -0.50 -0.56 -0.11 -0.19 -1.08
pNERD -0.73 -0.25 -0.28 0.00 0.19 0.54 0.00 0.00 3.80 3.27

Ryan Bergert, Kansas City Royals

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 111 8.7% 63.4% 93.5 mph 25 18.0s -41 0.0%
Z-score 0.60 -0.89 -0.29 -0.15 -0.96 -0.43
pNERD -1.20 -0.44 -0.15 0.00 0.96 0.22 0.00 0.00 3.80 3.18

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Philadelphia Phillies @ Washington Nationals, 8:35a

Summary

If you want a clear narrative, tune in for Aaron Nola's return from the injured list; if you want edge-of-your-seat back-and-forth, the Game NERD of 6.60 says look elsewhere. The numbers make the choice easy: Philadelphia's tNERD (6.46) and Nola's middling-but-interesting pNERD (4.72) are the only real draws, while Washington's club tNERD (0.59) and Mitchell Parker's weak pNERD (1.43) point toward a low-drama matchup. Nola's underlying stuff (xFIP- ~89) and strong Triple-A rehab outings — including an 11‑K performance — suggest he's worth watching to see if he reclaims form after injuries and a brief IL stay. Parker's 124 xFIP‑equivalent profile and below‑average whiff rates make him hittable rather than dominant, which combined with Washington's -38 defensive runs and a shaky bullpen lowers the game's unpredictability. Nola's deliberate pace also trims excitement, so this is best for viewers who value storyline and pitcher rehab arcs more than fireworks.

(A model from OpenAI generated this text using instructions, the NERD scores, and these sources: 1, 2, 3, 4.)

Philadelphia Phillies

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat 22.0 8.9% 6.9 3.4 24.9 $279.5M 29.5 10.0
Z-score 0.43 0.29 1.11 0.18 -0.02 1.43 0.79 0.47
tNERD 0.43 0.29 1.11 0.18 -0.02 0.00 0.00 0.47 4.00 6.46

Washington Nationals

Batting runs Barrel % Baserunning runs Fielding runs Bullpen runs Payroll Age Luck Constant Total
Raw stat -30.8 7.8% -2.8 -38.1 -5.4 $115.9M 27.5 -18.0
Z-score -0.56 -0.61 -0.52 -1.98 -1.76 -0.77 -1.25 -0.86
tNERD -0.56 -0.61 -0.52 -1.98 -1.76 0.77 1.25 0.00 4.00 0.59

Aaron Nola, Philadelphia Phillies

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 89 11.2% 65.6% 91.0 mph 32 21.1s 55 0.0%
Z-score -0.71 0.33 0.64 -1.28 0.84 2.07
pNERD 1.43 0.16 0.32 0.00 0.00 -1.03 0.05 0.00 3.80 4.72

Mitchell Parker, Washington Nationals

xFIP- SwStr% Strike % Velocity Age Pace Luck KN% Constant Total
Raw stat 124 9.2% 65.8% 92.9 mph 25 20.2s 8 0.0%
Z-score 1.38 -0.64 0.74 -0.43 -0.96 1.34
pNERD -2.76 -0.32 0.37 0.00 0.96 -0.67 0.05 0.00 3.80 1.43

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