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

86.4
Whiff54.0%
Chase40.8%
Usage51.1%
Average velocity88.0 mph
Offspeed identity

Fernando Cruz

New York Yankees | RHP | Splitter

83.9
Whiff49.6%
Chase37.5%
Usage53.2%
Average velocity80.0 mph
Breaking identity

Scott Barlow

Athletics | RHP | Curveball

83.5
Whiff43.3%
Chase44.3%
Usage49.1%
Average velocity76.2 mph
Offspeed identity

Shota Imanaga

Chicago Cubs | LHP | Splitter

83.2
Whiff39.8%
Chase45.8%
Usage35.9%
Average velocity82.8 mph
Offspeed identity

Kevin Gausman

Chicago Cubs | RHP | Splitter

83.0
Whiff39.6%
Chase40.5%
Usage40.0%
Average velocity84.1 mph
Offspeed identity

Cristopher Sánchez

Philadelphia Phillies | LHP | Changeup

82.8
Whiff43.3%
Chase43.0%
Usage36.9%
Average velocity87.0 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 182 15.0% 90.3 58.0% 32.0% 77.7%
Aaron Ashby Milwaukee Brewers Slider 186 12.4% 85.1 56.1% 41.2% 73.7%
Adrian Morejon San Diego Padres Changeup 296 23.1% 92.1 55.4% 52.8% 55.3%
Seranthony Domínguez Seattle Mariners Splitter 126 11.9% 85.9 55.0% 32.2% 70.0%
Mason Miller San Diego Padres Slider 545 51.1% 88.0 54.0% 40.8% 45.4%
Erik Miller Boston Red Sox Slider 388 45.8% 85.6 52.3% 39.2% 58.8%
Jordan Hicks Chicago White Sox Sweeper 257 31.3% 86.5 51.5% 27.3% 60.1%
Luis Medina Athletics Curveball 158 13.0% 81.2 50.9% 26.0% 78.2%
Riley Cornelio Washington Nationals Slider 304 56.8% 84.9 50.4% 35.8% 41.9%
Tyler Glasnow Los Angeles Dodgers Knuckle Curve 219 21.8% 80.6 50.0% 33.8% 80.2%
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

Noah Schultz

Chicago White Sox · throws L

Cutter
Usage change+10.3 ptsWhiff change+15.4%Recent pitch sample64Earlier pitch sample196Shape2.2 HB / 9.0 IVB
  1. Sinker26.1%8.8% whiff
  2. Four-Seam Fastball22.9%19.5% whiff
  3. Cutter22.2%21.6% whiff
  4. Sweeper18.5%30.1% whiff
  5. Changeup10.3%26.6% whiff
Emerging weapon #2

Jeff Hoffman

Minnesota Twins · throws R

Slider
Usage change+8.3 ptsWhiff change+22.7%Recent pitch sample36Earlier pitch sample491Shape-3.2 HB / -1.1 IVB
  1. Slider46.3%47.5% whiff
  2. Four-Seam Fastball32.6%22.3% whiff
  3. Splitter21.1%29.9% whiff
Emerging weapon #3

Dylan Dodd

Atlanta Braves · throws L

Cutter
Usage change+11.2 ptsWhiff change+20.5%Recent pitch sample26Earlier pitch sample227Shape-1.9 HB / 6.1 IVB
  1. Sinker63.6%22.0% whiff
  2. Cutter36.4%32.4% whiff
Emerging weapon #4

Paxton Schultz

Washington Nationals · throws R

Cutter
Usage change+14.4 ptsWhiff change+6.3%Recent pitch sample59Earlier pitch sample214Shape-2.3 HB / 9.0 IVB
  1. Cutter56.9%19.5% whiff
  2. Four-Seam Fastball43.1%14.1% 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+14.4 pts

Paxton Schultz

Washington Nationals · Cutter

34.0 vs same-pitch peers59 recent pitches
usage up+14.6 pts

Matthew Liberatore

St. Louis Cardinals · Slider

34.6 vs same-pitch peers163 recent pitches
usage down-9.6 pts

Germán Márquez

San Diego Padres · Knuckle Curve

63.1 vs same-pitch peers71 recent pitches
usage up+27.6 pts

Kodai Senga

New York Mets · Forkball

60.6 vs same-pitch peers52 recent pitches
usage down-16.3 pts

Luis Mey

Cincinnati Reds · Sinker

59.8 vs same-pitch peers51 recent pitches
usage up+23.1 pts

Craig Yoho

Cleveland Guardians · Changeup

46.8 vs same-pitch peers63 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 Paxton Schultz Washington Nationals Cutter 214 59 42.3% 56.7% +14.4 pts 34.0 +0.4 -0.1 -0.5 +6.3%
2 Aaron Civale Chicago Cubs Cutter 615 78 36.7% 51.0% +14.3 pts 34.0 +1.7 +0.0 +0.6 -6.6%
3 Eric Lauer Los Angeles Dodgers Cutter 280 136 19.9% 33.3% +13.4 pts 34.0 +1.0 -1.0 +0.9 +1.8%
4 Ryan Johnson Los Angeles Angels Cutter 408 214 34.8% 46.4% +11.7 pts 34.0 +0.3 -0.1 +0.4 +2.0%
5 Matthew Liberatore St. Louis Cardinals Slider 511 163 24.2% 38.8% +14.6 pts 34.6 -0.9 -0.6 -1.1 +3.4%
6 Jordan Romano Colorado Rockies Slider 286 55 54.9% 67.9% +13.0 pts 34.6 +0.1 -0.1 +0.2 +7.1%
7 Patrick Sandoval Boston Red Sox Slider 180 63 26.8% 14.4% -12.4 pts 34.6 -0.6 +0.1 +0.4 -2.7%
8 Jeffrey Springs Athletics Slider 480 53 24.5% 12.6% -11.9 pts 34.6 +1.1 -1.0 +3.0 -12.0%
9 Germán Márquez San Diego Padres Knuckle Curve 224 71 35.1% 25.4% -9.6 pts 63.1 +0.8 +0.4 +0.5 -2.1%
10 Robbie Ray San Diego Padres Knuckle Curve 256 72 11.0% 16.3% +5.3 pts 63.1 +0.3 +0.8 -0.5 +9.6%
11 Gerrit Cole New York Yankees Knuckle Curve 180 72 12.9% 17.1% +4.3 pts 63.1 +0.6 +0.5 0.0 -5.9%
12 Kyle Freeland Colorado Rockies Knuckle Curve 339 107 20.8% 25.1% +4.2 pts 63.1 +0.0 -0.3 +1.7 +4.1%
13 Kodai Senga New York Mets Forkball 245 52 24.4% 52.0% +27.6 pts 60.6 -0.1 +1.9 -1.5 +16.0%
14 Luis Mey Cincinnati Reds Sinker 306 51 61.1% 44.7% -16.3 pts 59.8 -0.9 -1.1 -0.1 -3.8%
15 J.T. Ginn Athletics Sinker 576 226 33.4% 49.5% +16.1 pts 59.8 -0.5 -1.2 -0.6 -5.3%
16 Ryan Thompson Arizona Diamondbacks Sinker 358 51 65.1% 49.0% -16.1 pts 59.8 0.0 -1.0 -0.2 -2.4%
17 Brennan Bernardino Colorado Rockies Sinker 361 51 40.2% 56.0% +15.8 pts 59.8 +0.9 -0.4 -0.5 -0.6%
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 Craig Yoho Cleveland Guardians Changeup 264 63 50.2% 73.3% +23.1 pts 46.8 -0.3 -1.3 -3.4 +1.4%
20 Bryce Elder Atlanta Braves Changeup 160 114 8.9% 25.6% +16.7 pts 46.8 +0.1 +0.8 -0.8 +2.9%
21 Joey Cantillo Cleveland Guardians Changeup 579 68 25.6% 16.9% -8.7 pts 46.8 +0.8 +0.2 -1.3 -19.2%
22 Logan Henderson Milwaukee Brewers Changeup 307 195 32.6% 41.1% +8.5 pts 46.8 +0.8 -0.6 -0.8 -2.7%
23 Yohan Ramírez Pittsburgh Pirates Sweeper 532 50 41.1% 66.7% +25.6 pts 48.1 +0.8 +0.1 +0.8 -17.1%
24 Blade Tidwell San Francisco Giants Sweeper 198 105 37.1% 24.9% -12.2 pts 48.1 -0.3 +1.3 +0.8 -14.0%
25 Ryan Johnson Los Angeles Angels Sweeper 233 145 19.8% 31.5% +11.6 pts 48.1 +1.3 +1.6 +1.6 -7.1%
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 2,513 36.1% 6.6% 20.0% 96.8% 99.0
2 Mookie Betts Los Angeles Dodgers 1,833 41.2% 11.4% 20.0% 95.1% 98.3
3 Turner Hill San Francisco Giants 442 39.1% 12.7% 19.8% 93.1% 97.1
4 Geraldo Perdomo Arizona Diamondbacks 2,768 39.0% 10.5% 21.2% 93.4% 96.6
5 Chase DeLauter Cleveland Guardians 2,061 42.4% 13.6% 21.3% 92.5% 94.5
6 José Fermín St. Louis Cardinals 1,484 40.0% 10.6% 22.2% 92.1% 94.2
7 Mickey Gasper Boston Red Sox 819 38.7% 16.7% 21.2% 95.1% 94.2
8 Sal Frelick Milwaukee Brewers 1,412 42.9% 8.6% 24.3% 95.9% 94.2
9 Sam Antonacci Chicago White Sox 2,102 42.4% 12.7% 21.8% 91.8% 93.8
10 Maikel Garcia Kansas City Royals 1,234 39.7% 13.7% 23.6% 93.1% 92.8
11 Kevin McGonigle Detroit Tigers 2,744 42.7% 13.9% 19.2% 90.8% 92.8
12 Myles Straw Toronto Blue Jays 1,219 40.8% 11.5% 23.1% 91.9% 92.5
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