Pitch Lab

MLB pitch arsenals, movement, discipline, and sequencing.

Pitch design, translated

How an arsenal creates the result

Velocity and movement matter. So do location, the previous pitch, the hitter’s handedness, and the count.

Pitch identities

Six pitches with a visual fingerprint

Movement location, velocity, bat-missing, chase, and usage combine into a transparent pitch-quality board.

Breaking identity

Mason Miller

San Diego Padres | RHP | Slider

86.3
Whiff53.4%
Chase41.4%
Usage51.7%
Average velocity88.0 mph
Breaking identity

Erik Miller

Boston Red Sox | LHP | Slider

84.2
Whiff53.7%
Chase40.3%
Usage46.9%
Average velocity85.7 mph
Offspeed identity

Fernando Cruz

New York Yankees | RHP | Splitter

83.8
Whiff49.6%
Chase37.5%
Usage53.2%
Average velocity80.0 mph
Breaking identity

Scott Barlow

Athletics | RHP | Curveball

83.4
Whiff43.3%
Chase44.3%
Usage49.1%
Average velocity76.2 mph
Offspeed identity

Cristopher Sánchez

Philadelphia Phillies | LHP | Changeup

83.0
Whiff43.9%
Chase43.7%
Usage37.6%
Average velocity87.0 mph
Offspeed identity

Shota Imanaga

Chicago Cubs | LHP | Splitter

82.8
Whiff40.4%
Chase45.9%
Usage34.9%
Average velocity82.8 mph
Arsenal leaderboard

Highest whiff pitch types

At least 50 swings and 100 total pitches in the underlying product.

Pitcher Team Pitch Pitches Usage Velo Whiff Chase Changed from prior
Luis Medina Athletics Changeup 170 14.8% 90.2 56.1% 30.5% 77.9%
Aaron Ashby Milwaukee Brewers Slider 182 12.9% 85.1 55.6% 41.1% 74.0%
Adrian Morejon San Diego Padres Changeup 281 23.0% 92.1 54.8% 53.2% 54.8%
Erik Miller Boston Red Sox Slider 359 46.9% 85.7 53.7% 40.3% 58.4%
Mason Miller San Diego Padres Slider 505 51.7% 88.0 53.4% 41.4% 45.7%
Luis Medina Athletics Curveball 142 12.3% 81.1 52.0% 25.3% 79.7%
Seranthony Domínguez Seattle Mariners Splitter 112 11.8% 85.8 51.9% 31.2% 69.8%
Aaron Ashby Milwaukee Brewers Curveball 310 22.0% 83.7 50.6% 26.9% 77.4%
Erik Sabrowski Cleveland Guardians Slider 106 14.8% 86.6 50.0% 42.4% 58.8%
Fernando Cruz New York Yankees Splitter 484 53.2% 80.0 49.6% 37.5% 41.7%
Expanded arsenal spotlights

When a pitch earns a larger job and better results

An emerging weapon must gain at least three percentage points of usage, appear at least 20 times in the pitcher’s latest five games, and improve its whiff rate versus the non-overlapping earlier-season sample. The complete arsenal stays visible because a pitch succeeds in relation to everything thrown beside it.

Emerging weapon #1

Gordon Graceffo

St. Louis Cardinals · throws R

Slider
Usage change+11.2 ptsWhiff change+17.7%Recent pitch sample66Earlier pitch sample279Shape-1.0 HB / -0.3 IVB
  1. Four-Seam Fastball41.4%7.6% whiff
  2. Slider34.4%29.4% whiff
  3. Changeup13.9%19.6% whiff
  4. Curveball10.3%12.1% whiff
Emerging weapon #2

Jordan Romano

Colorado Rockies · throws R

Slider
Usage change+10.9 ptsWhiff change+19.7%Recent pitch sample39Earlier pitch sample255Shape-2.8 HB / -4.1 IVB
  1. Slider56.4%33.3% whiff
  2. Four-Seam Fastball43.6%19.6% whiff
Emerging weapon #3

Tommy Nance

Minnesota Twins · throws R

Slider
Usage change+21.6 ptsWhiff change+8.0%Recent pitch sample76Earlier pitch sample303Shape-0.4 HB / 2.4 IVB
  1. Slider43.9%30.9% whiff
  2. Curveball29.0%21.9% whiff
  3. Sinker27.1%10.0% whiff
Emerging weapon #4

Ian Seymour

Tampa Bay Rays · throws L

Slider
Usage change+10.9 ptsWhiff change+27.7%Recent pitch sample64Earlier pitch sample56Shape3.5 HB / 12.1 IVB
  1. Changeup29.7%35.5% whiff
  2. Four-Seam Fastball27.6%21.7% whiff
  3. Sweeper20.6%29.1% whiff
  4. Sinker15.7%7.9% whiff
  5. Slider6.4%29.4% whiff
Pitch movement maps for four pitchers whose featured offering gained usage and whiffs
Emerging-weapon map. Every panel uses the same axes centered at zero. Color identifies pitch type, point size identifies season usage, and the red outline identifies the offering gaining both trust and bat-missing success.
Arsenal change detector

The pitches whose jobs changed most

The final five appearances are compared with the non-overlapping earlier season. Percentage-point movement is paired with a reader-friendly Change Index, where 50 is ordinary movement among pitchers throwing the same pitch.

usage up+21.6 pts

Tommy Nance

Minnesota Twins · Slider

30.5 vs same-pitch peers76 recent pitches
usage up+20.3 pts

Ryan Johnson

Los Angeles Angels · Cutter

32.5 vs same-pitch peers220 recent pitches
usage down-9.6 pts

Germán Márquez

San Diego Padres · Knuckle Curve

62.4 vs same-pitch peers71 recent pitches
usage up+20.6 pts

Wandy Peralta

San Diego Padres · Sinker

60.4 vs same-pitch peers61 recent pitches
usage up+10.8 pts

Kodai Senga

New York Mets · Forkball

60.6 vs same-pitch peers25 recent pitches
usage down-8.2 pts

Sean Newcomb

Chicago White Sox · Slurve

54.3 vs same-pitch peers46 recent pitches
Full context board

Usage, velocity, and shape moved together

Large usage shifts lead the ranking; velocity, horizontal break, induced vertical break, and whiff changes show what else moved.

Rank Pitcher Team Pitch Earlier N Recent N Earlier use Recent use Delta Change Index Velo delta HB delta IVB delta Whiff delta
1 Tommy Nance Minnesota Twins Slider 303 76 40.7% 62.3% +21.6 pts 30.5 +0.4 +0.2 +3.6 +8.0%
2 Matthew Liberatore St. Louis Cardinals Slider 458 168 23.9% 36.4% +12.4 pts 30.5 -1.1 -0.3 -1.9 +3.4%
3 Gordon Graceffo St. Louis Cardinals Slider 279 66 30.0% 41.2% +11.2 pts 30.5 -2.0 +0.9 -3.2 +17.7%
4 Patrick Corbin Toronto Blue Jays Slider 284 103 25.3% 35.6% +10.4 pts 30.5 +0.9 -0.3 +0.9 +3.5%
5 Ryan Johnson Los Angeles Angels Cutter 279 220 30.4% 50.7% +20.3 pts 32.5 +0.1 -0.1 -0.2 -10.6%
6 Paxton Schultz Washington Nationals Cutter 214 59 42.3% 56.7% +14.4 pts 32.5 +0.4 -0.1 -0.5 +6.3%
7 Cal Quantrill Texas Rangers Cutter 301 58 26.8% 12.5% -14.3 pts 32.5 +0.2 +1.0 +0.4 -12.7%
8 Eric Lauer Los Angeles Dodgers Cutter 280 136 19.9% 33.3% +13.4 pts 32.5 +1.0 -1.0 +0.9 +1.8%
9 Germán Márquez San Diego Padres Knuckle Curve 224 71 35.1% 25.4% -9.6 pts 62.4 +0.8 +0.4 +0.5 -2.1%
10 George Kirby Seattle Mariners Knuckle Curve 187 75 9.3% 16.3% +7.0 pts 62.4 +0.6 +0.9 +0.7 -2.8%
11 Zac Gallen Arizona Diamondbacks Knuckle Curve 245 59 20.4% 13.5% -6.9 pts 62.4 -0.2 -2.2 +0.6 -6.1%
12 Robbie Ray San Diego Padres Knuckle Curve 238 66 11.1% 15.2% +4.1 pts 62.4 -0.1 +0.8 -0.7 +10.3%
13 Wandy Peralta San Diego Padres Sinker 394 61 39.8% 60.4% +20.6 pts 60.4 -0.2 +0.4 -0.7 +6.4%
14 Spencer Miles Toronto Blue Jays Sinker 528 66 42.4% 62.3% +19.8 pts 60.4 +0.7 -0.3 +0.2 -6.0%
15 Randy Vásquez San Diego Padres Sinker 239 99 13.8% 30.1% +16.2 pts 60.4 +0.3 -1.4 -0.3 -4.8%
16 J.T. Ginn Athletics Sinker 576 226 33.4% 49.5% +16.1 pts 60.4 -0.5 -1.2 -0.6 -5.3%
17 Kodai Senga New York Mets Forkball 236 25 24.4% 35.2% +10.8 pts 60.6 -0.4 +1.5 -2.3 +7.8%
18 Roki Sasaki Los Angeles Dodgers Forkball 144 16 8.9% 3.6% -5.3 pts 60.6 +2.7 +0.1 +2.3 +18.3%
19 Sean Newcomb Chicago White Sox Slurve 368 46 33.5% 25.3% -8.2 pts 54.3 +0.5 -0.7 -0.4 -1.1%
20 Kyle Harrison Milwaukee Brewers Slurve 471 161 30.9% 35.8% +4.9 pts 54.3 -0.8 -1.0 +0.9 -2.8%
21 Michael Soroka Arizona Diamondbacks Slurve 390 103 32.8% 30.0% -2.8 pts 54.3 0.0 -0.5 -0.1 +7.1%
22 Cionel Pérez New York Mets Slurve 181 42 30.0% 42.4% +12.4 pts 54.3 +0.4 +0.6 +0.3 +12.3%
23 Lake Bachar Pittsburgh Pirates Curveball 188 50 16.7% 33.6% +16.9 pts 53.7 -0.3 +0.8 +1.4 -9.8%
24 Joey Cantillo Cleveland Guardians Curveball 602 161 28.8% 36.4% +7.6 pts 53.7 -0.4 -0.4 +0.9 -14.0%
25 JR Ritchie Atlanta Braves Curveball 192 88 25.4% 33.0% +7.6 pts 53.7 +0.0 +0.3 -0.1 -17.1%
Hitter recognition layer

Chase and contact belong beside the arsenal

Pitch-level discipline separates hitters who avoid expanding the zone from hitters who make exceptional contact when they do swing.

Qualified hitters plotted by chase rate and zone contact rate
Low chase and high zone contact define the upper discipline frontier.
Rank Hitter Team Pitches Swing Whiff Chase Zone contact Score
1 Steven Kwan Cleveland Guardians 2,325 36.4% 6.7% 20.4% 96.9% 98.8
2 Mookie Betts Los Angeles Dodgers 1,652 41.7% 11.8% 20.4% 95.0% 97.9
3 Geraldo Perdomo Arizona Diamondbacks 2,593 39.1% 10.5% 21.4% 93.1% 96.3
4 Sal Frelick Milwaukee Brewers 1,343 42.5% 8.9% 23.7% 95.6% 95.0
5 Mickey Gasper Boston Red Sox 713 39.3% 16.8% 20.6% 95.0% 94.6
6 José Fermín St. Louis Cardinals 1,374 39.8% 10.6% 22.0% 92.2% 94.3
7 Chase DeLauter Cleveland Guardians 1,931 42.6% 14.0% 21.6% 92.4% 94.1
8 Myles Straw Toronto Blue Jays 1,118 41.0% 11.4% 22.8% 92.5% 93.3
9 Sam Antonacci Chicago White Sox 1,983 42.1% 12.9% 21.5% 91.6% 93.2
10 Maikel Garcia Kansas City Royals 1,175 39.4% 13.4% 23.0% 93.0% 93.1
11 Jakob Marsee Miami Marlins 2,155 39.9% 16.5% 21.5% 92.8% 92.5
12 Kevin McGonigle Detroit Tigers 2,520 43.4% 14.1% 19.6% 90.8% 92.3
Reporter’s rule: the board finds the largest changes; it does not assign a cause. Confirm role, health, opponent mix, and pitch-classification stability before turning a signal into a story.
Pitch context

Sequence change

Previous to current

Every pitch can be evaluated relative to the pitch before it.

Location

Separation

Feet at the plate

Measures how far consecutive pitches move across the hitting window.

Contact

Quality

EV + launch angle

Hard-hit and barrel-proxy fields remain explicitly labeled.

Explore handedness matchup edges