Going Deep: Using Pitch Acceleration to Predict Batted Ball Quality

(Photo by Scott Winters/Icon Sportswire)

In the depths of Statcast are a handful of statistics that are tracked, but not displayed prominently. A few such are pitch acceleration metrics, measured at the point of release in three directions. These statistics measure how a pitch should move in the air due to the forces of drag, Magnus effect, and gravity.

A pitch with high acceleration in air intuitively should be harder to hit than one that is flat. To calculate the sum of acceleration of a pitch in three dimensions, it can be represented as the magnitude of a 3D vector (√ax2 + ay2 + az2). As results tend to cluster around the same baselines for average acceleration on each pitch type, scores for each pitch are represented by its percentile among other pitches of the same type. Pitchers are given an overall score of the average percentile of each pitch they throw.

Firstly, it is important to establish that acceleration percentiles (ACC%) are repeatable year to year to show that pitchers have influence over the effects of acceleration in air.  The samples used were pitchers who threw at least 50 innings between 2016-17 (227 pitchers) and 2017-18 (120), as Statcast data past 2015 is more reliable.

Yearr2 of ACC% with itself year+1

In the same sample, these correlations compare similarly to groundball rate allowed and better than strikeout and walk rates, all three well established repeatable skills. The 2017-18 r2 was likely higher because almost all pitchers to throw at least 50 innings in 2017 and 2018 so far were starting pitchers who had higher innings totals to stabilize. ACC% also shows some predictive value in pitcher performance on batted balls:

Statistic2016 r2 with wOBA allowed on batted balls year+12017 r2 with wOBA allowed on batted balls year+1 

In both time frames, ACC% performed slightly better than GB% in predicting pitcher wOBA on batted balls. Pitchers with high acceleration percentiles tended to allow weaker contact. While still not the strongest correlation, batted ball results are the most confounding element of pitching to project. ACC% should be used in conjunction with GB% in understanding how a pitcher may have the ability to suppress contact.

I tested other relationships between ACC% and several statistics such as K% and BABIP and found some other modest correlations, but the most unique value compared to existing statistics came in evaluating batted ball profiles. Another possible application could be noting that a sharp drop in ACC% may indicate a pitcher is injured or has a mechanical issue.

The following are the 2018 leaders among qualified SP and RP. Of course there are some good pitchers who succeed with low acceleration and some mediocre pitchers who remain middling despite high acceleration. ACC% still provides a unique insight to pitcher ability that appears to be at least equal to and possibly more than the value that GB% provides.

Chris Sale’s score of 0.96 means that his average pitch is in the 96th percentile of acceleration adjusted for type. While 0.5 is average, starting pitchers tend to score slightly lower than relief pitchers.

SP Leaders

1Chris Sale0.96
2Charlie Morton0.90
3Luis Castillo0.84
4Clayton Richard0.83
5Sean Manaea0.81
6Aaron Nola0.78
7Luis Severino0.75
8Trevor Bauer0.74
9Gerrit Cole0.73
10Ivan Nova0.72
11James Paxton0.71
12Max Scherzer0.70
13Justin Verlander0.69
14Nick Pivetta0.67
15Lance McCullers0.64
16Eduardo Rodriguez0.64
17Mike Leake0.62
18Jose Urena0.62
19Carlos Carrasco0.62
20Mike Foltynewicz0.62
21Kevin Gausman0.59
22Tyler Mahle0.58
23Jakob Junis0.56
24Michael Fulmer0.56
25David Price0.56
26Reynaldo Lopez0.55
27Mike Clevinger0.55
28Steven Matz0.55
29Jose Berrios0.55
30Jake Arrieta0.55
31Zack Wheeler0.55
32Miles Mikolas0.53
33Jacob deGrom0.53
34Jhoulys Chacin0.53
35Luke Weaver0.53
36Gio Gonzalez0.52
37Corey Kluber0.52
38Zack Godley0.50
39Jameson Taillon0.49
40Cole Hamels0.48
41Bartolo Colon0.48
42Vince Velasquez0.47
43Blake Snell0.47
44James Shields0.47
45Julio Teheran0.45
46Felix Hernandez0.45
47Rick Porcello0.45
48Daniel Mengden0.45
49Tyson Ross0.44
50Patrick Corbin0.44
51German Marquez0.43
52Lucas Giolito0.43
53Sal Romano0.43
54Junior Guerra0.42
55Dylan Bundy0.42
56Marco Gonzales0.42
57Dallas Keuchel0.41
58Tyler Skaggs0.41
59Kyle Freeland0.40
60Chase Anderson0.40
61Jason Hammel0.40
62Sean Newcomb0.39
63Kyle Gibson0.39
64J.A. Happ0.38
65Danny Duffy0.38
66CC Sabathia0.38
67Jon Gray0.37
68Ian Kennedy0.37
69Trevor Williams0.33
70Jon Lester0.33
71Andrew Cashner0.32
72Chad Bettis0.31
73Mike Fiers0.30
74Tanner Roark0.30
75Chris Stratton0.29
76Jose Quintana0.28
77Zack Greinke0.27
78Jake Odorizzi0.27
79Mike Minor0.25
80Andrew Heaney0.25
81Alex Wood0.23
82Matthew Boyd0.23
83Tyler Anderson0.14
84Marco Estrada0.09
85Kyle Hendricks0.08

RP Leaders

1Aaron Loup0.91
2Brad Hand0.90
3Jared Hughes0.87
4Joe Kelly0.86
5T.J. McFarland0.86
6Brandon Morrow0.85
7Jordan Hicks0.85
8Blake Treinen0.85
9Trevor Hildenberger0.84
10Brad Ziegler0.83
11Tayron Guerrero0.83
12Alex Claudio0.83
13Buck Farmer0.82
14Felipe Vazquez0.82
15Hector Rondon0.82
16Matt Barnes0.81
17Hector Neris0.80
18Joe Jimenez0.79
19Chaz Roe0.79
20Adam Cimber0.78
21Aroldis Chapman0.78
22Mychal Givens0.77
23Taylor Williams0.77
24Miguel Castro0.77
25Arodys Vizcaino0.77
26Justin Anderson0.76
27Craig Kimbrel0.76
28Steve Cishek0.76
29Kirby Yates0.76
30Adam Ottavino0.76
31Zach McAllister0.75
32Richard Rodriguez0.75
33Ryan Tepera0.75
34Lou Trivino0.75
35Seranthony Dominguez0.75
36Jacob Barnes0.75
37Jeurys Familia0.74
38Chris Devenski0.74
39Raisel Iglesias0.74
40Sam Dyson0.73
41Ken Giles0.73
42Collin McHugh0.72
43Austin Brice0.72
44Jorge De La Rosa0.71
45Ryan Madson0.71
46Danny Barnes0.71
47Will Harris0.71
48Jake Diekman0.70
49Hansel Robles0.69
50Scott Alexander0.69
51Amir Garrett0.69
52Bruce Rondon0.69
53Edwin Diaz0.68
54Steven Brault0.68
55Jace Fry0.68
56Mike Mayers0.67
57Kelvin Herrera0.67
58Jeremy Jeffress0.67
59Bryan Shaw0.66
60Paul Sewald0.66
61Edubray Ramos0.66
62Hunter Strickland0.66
63Matt Albers0.66
64Kyle Crick0.66
65Seth Lugo0.66
66Alex Colome0.66
67Cory Gearrin0.64
68Shane Greene0.64
69Robert Gsellman0.64
70Edgar Santana0.64
71Dan Otero0.64
72Zach Duke0.63
73Kevin McCarthy0.63
74Tyler Glasnow0.62
75Dan Jennings0.62
76Wandy Peralta0.62
77Warwick Saupold0.62
78Taylor Rogers0.62
79Brad Peacock0.62
80Brad Brach0.61
81Jesse Biddle0.60
82Tony Watson0.60
83Dylan Floro0.60
84Cam Bedrosian0.60
85Matt Andriese0.59
86Sam Tuivailala0.59
87Archie Bradley0.59
88Pierce Johnson0.59
89John Brebbia0.58
90Bud Norris0.58
91Ryan Pressly0.58
92Dellin Betances0.58
93Shane Carle0.57
94Jose Alvarado0.57
95Drew Steckenrider0.56
96Richard Bleier0.56
97David Robertson0.55
98Andrew Chafin0.55
99Kyle Barraclough0.55
100A.J. Minter0.55
101Chad Green0.54
102Tommy Hunter0.54
103John Axford0.54
104Santiago Casilla0.54
105Jake McGee0.53
106Chris Beck0.53
107Chasen Shreve0.52
108Reyes Moronta0.52
109Cody Allen0.52
110Jesse Chavez0.51
111Matt Magill0.51
112Heath Hembree0.51
113Josh Hader0.51
114Mike Wright0.51
115Pedro Strop0.49
116Craig Stammen0.48
117Chasen Bradford0.48
118Matt Grace0.48
119Burch Smith0.48
120Daniel Hudson0.47
121Chris Volstad0.46
122Sergio Romo0.46
123Hector Velazquez0.46
124Ryan Yarbrough0.46
125Chris Rusin0.45
126Austin Pruitt0.45
127Brandon Kintzler0.45
128Jonathan Holder0.45
129Jim Johnson0.44
130Seung Hwan Oh0.44
131Pedro Araujo0.44
132Josh Fields0.43
133Jose Leclerc0.43
134Yoshihisa Hirano0.43
135Jose Alvarez0.43
136Juan Nicasio0.43
137Blake Parker0.42
138Noe Ramirez0.40
139Fernando Rodney0.40
140Keone Kela0.39
141James Pazos0.39
142Joakim Soria0.39
143Brian Flynn0.37
144Sammy Solis0.37
145Erik Goeddel0.36
146Emilio Pagan0.36
147Justin Wilson0.36
148Dan Winkler0.36
149Brian Johnson0.35
150Wade Davis0.34
151Michael Feliz0.34
152Sam Freeman0.34
153Brad Boxberger0.32
154Victor Arano0.31
155David Hernandez0.30
156Robbie Erlin0.30
157Chris Hatcher0.29
158Michael Lorenzen0.28
159Kenley Jansen0.26
160Addison Reed0.25
161Pedro Baez0.25
162Tyler Clippard0.23
163Sean Doolittle0.20
164Alex Wilson0.17
165Hector Santiago0.16
166Fernando Salas0.14
167Yusmeiro Petit0.06
Alex Isherwood

Creator of @ProspectBot and former FantasyPros writer. Studying computer science and mathematics at William & Mary.


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