2022 season · rankings

2022 MLB Pitching Leaders

45 players qualified at 162 innings pitched, ranked by dbWAR. Every column sorts across the full qualified set — not just the rows shown — and the whole table downloads as Parquet. Filter by position, cohort, league or country of birth, several countries at a time.

TableBatting Pitching

RoleLeaguePool

Who

Born in

45 of 45 qualifiedDownload Parquet

#
1	Aaron Nola	United States	29	32	32	205.0	11	13	235	3.25	2.58	0.96	10.3	27.9%	13.8%	3.6%	25.5%	65	6.0
2	Carlos Rodón	United States	30	31	31	178.0	14	8	237	2.88	2.25	1.03	12.0	31.2%	15.5%	7.3%	26.1%	57	5.8
3	Sandy Alcantara	Dominican Republic	27	32	32	228.2	14	9	207	2.28	2.99	0.98	8.1	25.4%	13.6%	5.6%	17.7%	75	5.5
4	Kevin Gausman	United States	31	31	31	174.2	12	10	205	3.35	2.38	1.24	10.6	29.4%	16.4%	3.9%	24.4%	60	5.4
5	Shohei Ohtani two-way	Japan	28	28	28	166.0	15	9	219	2.33	2.40	1.01	11.9	33.1%	16.2%	6.7%	26.5%	61	5.2
6	Justin Verlander	United States	39	28	28	175.0	18	4	185	1.75	2.49	0.83	9.5	24.2%	13.0%	4.4%	23.4%	63	5.2
7	Max Fried	United States	28	30	30	185.1	14	7	170	2.48	2.70	1.01	8.3	26.1%	13.0%	4.4%	18.8%	68	5.0
8	Shane Bieber	United States	27	31	31	200.0	13	8	198	2.88	2.87	1.04	8.9	29.7%	14.8%	4.6%	20.5%	72	5.0
9	Framber Valdez	Dominican Republic	29	31	31	201.1	17	6	194	2.82	3.06	1.16	8.7	25.8%	12.1%	8.1%	15.4%	77	4.6
10	Logan Webb	United States	26	32	32	192.1	15	9	163	2.90	3.03	1.16	7.6	24.1%	11.4%	6.2%	14.5%	76	4.4
11	Corbin Burnes	United States	28	33	33	202.0	12	8	243	2.94	3.14	0.97	10.8	35.2%	16.3%	6.4%	24.1%	79	4.4
12	Dylan Cease	United States	27	32	32	184.0	14	8	227	2.20	3.10	1.11	11.1	33.3%	15.8%	10.4%	19.9%	78	4.3
13	Zac Gallen	United States	27	31	31	184.0	12	4	192	2.54	3.05	0.91	9.4	23.0%	10.9%	6.6%	20.3%	77	4.2
14	Martín Pérez	Venezuela	31	32	32	196.1	12	8	169	2.89	3.27	1.26	7.7	21.0%	9.3%	8.4%	12.2%	82	4.1
15	Jose Quintana	Colombia	33	32	32	165.2	6	7	137	2.93	2.99	1.21	7.4	24.0%	11.5%	6.9%	13.3%	75	4.0
16	Shane McClanahan	United States	25	29	28	166.1	12	8	194	2.54	3.00	0.93	10.5	34.3%	17.0%	5.9%	24.3%	76	3.8
17	Alek Manoah	United States	24	31	31	196.2	16	7	180	2.24	3.35	0.99	8.2	24.9%	12.3%	6.5%	16.4%	84	3.8
18	Gerrit Cole	United States	32	33	33	200.2	13	8	257	3.50	3.47	1.02	11.5	34.1%	16.4%	6.3%	26.1%	87	3.6
19	Yu Darvish	Japan	36	30	30	194.2	16	8	197	3.10	3.31	0.95	9.1	25.1%	12.5%	4.8%	20.8%	83	3.6
20	Tyler Anderson	United States	33	30	28	178.2	15	5	138	2.57	3.31	1.00	7.0	24.3%	12.8%	4.8%	14.7%	83	3.6
21	Logan Gilbert	United States	25	32	32	185.2	13	6	174	3.20	3.46	1.18	8.4	24.2%	12.2%	6.4%	16.3%	87	3.3
22	Merrill Kelly	United States	34	33	33	200.1	13	8	177	3.37	3.65	1.14	8.0	23.6%	11.5%	7.6%	14.4%	92	3.2
23	Triston McKenzie	United States	25	31	30	191.1	11	11	190	2.96	3.59	0.95	8.9	26.8%	14.1%	5.9%	19.7%	91	3.1
24	Kyle Wright	United States	27	30	30	180.1	21	5	174	3.19	3.58	1.16	8.7	26.5%	12.9%	7.2%	16.4%	90	2.9
25	Adam Wainwright	United States	41	32	32	191.2	11	12	143	3.71	3.66	1.28	6.7	16.9%	7.3%	6.7%	11.1%	92	2.9
26	Jordan Montgomery	United States	30	32	32	178.1	9	6	158	3.48	3.61	1.09	8.0	27.5%	13.9%	5.0%	16.9%	91	2.9
27	Pablo López	Venezuela	26	32	32	180.0	10	10	174	3.75	3.71	1.17	8.7	28.2%	14.0%	7.2%	16.4%	94	2.8
28	Joe Musgrove	United States	30	30	30	181.0	10	7	184	2.93	3.59	1.08	9.1	25.5%	11.9%	5.7%	19.2%	90	2.8
29	Julio Urías	Mexico	26	31	31	175.0	17	7	166	2.16	3.71	0.96	8.5	23.9%	12.4%	6.0%	18.1%	94	2.7
30	Chris Bassitt	United States	33	30	30	181.2	15	9	167	3.42	3.66	1.14	8.3	23.6%	10.9%	6.6%	15.8%	92	2.7
31	Corey Kluber	United States	36	31	31	164.0	10	10	139	4.34	3.57	1.21	7.6	23.9%	12.3%	3.0%	17.1%	90	2.7
32	Miles Mikolas	United States	34	33	32	202.1	12	13	153	3.29	3.87	1.03	6.8	18.6%	9.1%	4.8%	14.2%	98	2.5
33	Jameson Taillon	United States	31	32	32	177.1	14	5	151	3.91	3.94	1.13	7.7	23.1%	11.3%	4.4%	16.3%	99	2.2
34	Kyle Freeland	United States	29	31	31	174.2	9	11	131	4.53	4.21	1.41	6.8	20.8%	9.9%	6.9%	10.2%	106	2.2
35	Cal Quantrill	Canada	27	32	32	186.1	15	5	128	3.38	4.12	1.21	6.2	18.5%	9.0%	6.1%	10.5%	104	1.9
36	Robbie Ray	United States	31	32	32	189.0	12	12	212	3.71	4.17	1.19	10.1	30.0%	15.4%	8.0%	19.4%	105	1.7
37	Cole Irvin	United States	28	30	30	181.0	9	13	128	3.98	4.21	1.16	6.4	20.5%	10.7%	4.9%	12.4%	106	1.6
38	Kyle Gibson	United States	35	31	31	167.2	10	8	144	5.05	4.28	1.34	7.7	25.2%	12.2%	6.7%	13.4%	108	1.5
39	Charlie Morton	United States	39	31	31	172.0	9	6	205	4.34	4.26	1.23	10.7	29.2%	13.3%	8.7%	19.5%	107	1.4
40	Nick Pivetta	Canada	29	33	33	179.2	10	12	175	4.56	4.42	1.38	8.8	23.5%	11.2%	9.4%	13.2%	111	1.4
41	Jordan Lyles	United States	32	32	32	179.0	12	11	144	4.42	4.40	1.39	7.2	21.9%	10.1%	6.7%	11.9%	111	1.2
42	Germán Márquez	Venezuela	27	31	31	181.2	9	13	150	4.95	4.71	1.37	7.4	23.2%	11.6%	8.1%	11.2%	119	1.2
43	José Berríos	Puerto Rico	28	32	32	172.0	12	7	149	5.23	4.55	1.42	7.8	21.3%	10.4%	6.0%	13.8%	115	0.9
44	José Urquidy	Mexico	27	29	28	164.1	13	8	134	3.94	4.60	1.17	7.3	22.3%	11.6%	5.6%	14.1%	116	0.7
45	Marco Gonzales	United States	30	32	32	183.0	10	15	103	4.13	5.05	1.33	5.1	18.3%	9.3%	6.4%	6.8%	127	-0.3

Reading this table

FIP estimates what a pitcher's ERA would be given only the outcomes they control directly — strikeouts, walks, hit batters and home runs. FIP− indexes that against the league, so 100 is average and lower is better. dbWAR is our own open implementation, not fWAR or bWAR. See the full derivation →