DataBaseball
2026

2024 season · rankings

2024 MLB Pitching Leaders

58 players qualified at 161.9 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.

RoleLeaguePool
Who
58 of 58 qualifiedDownload Parquet
#
1Chris Sale352929177.218302252.382.091.0111.431.0%15.2%5.6%26.5%515.8
2Tarik Skubal283131192.018402282.392.490.9210.731.9%16.5%4.6%25.6%615.4
3Logan Webb283333204.2131001723.472.951.237.620.8%9.6%5.9%14.5%724.7
4Zack Wheeler343232200.016702242.563.130.9510.127.5%14.1%6.6%21.9%774.2
5Cole Ragans273232186.111902233.142.991.1410.832.0%15.7%8.8%20.5%734.2
6Cristopher Sánchez283131181.211901533.323.001.247.624.3%12.5%5.8%14.5%734.1
7Seth Lugo353333206.216901813.003.251.097.922.5%10.5%5.7%15.9%804.1
8Logan Gilbert273333208.291202203.233.270.899.531.7%15.9%4.6%22.8%804.1
9Dylan Cease293333189.1141102243.473.101.0710.632.4%15.6%8.5%20.9%764.1
10George Kirby263333191.0141101793.533.261.078.424.1%12.8%3.0%20.1%803.7
11Sonny Gray352828166.113902033.843.121.0911.029.8%14.5%5.8%24.4%773.5
12Framber Valdez312828176.115701692.913.251.118.627.2%12.2%7.8%16.2%803.5
13Tanner Houck283030178.291001543.123.321.147.822.6%10.6%6.5%14.3%813.4
14Max Fried302929174.1111001663.253.331.168.624.1%11.1%8.0%15.3%823.3
15Michael King293130173.213902012.953.331.1910.429.3%13.3%8.7%19.0%823.2
16Corbin Burnes303232194.115901812.923.551.108.428.6%14.0%6.1%17.0%873.2
17Yusei Kikuchi333232175.291002064.053.461.2010.629.1%14.1%6.0%22.0%853.0
18Bryce Miller263131180.112801712.943.580.988.524.4%11.9%6.4%17.9%882.9
19Brandon Pfaadt263232181.2111001854.713.611.249.225.4%12.5%5.5%18.8%882.8
20Pablo López283232185.1151001984.083.651.199.627.0%14.0%5.3%20.3%892.8
21Tanner Bibee253131173.212801873.473.561.129.726.9%13.7%6.2%20.1%872.8
22Jack Flaherty292828162.013701943.173.481.0710.832.1%14.9%5.9%24.0%852.8
23MacKenzie Gore253232166.1101201813.903.531.429.828.6%14.4%8.9%15.9%872.7
24Hunter Brown263130170.011901793.493.581.279.525.1%11.6%8.4%16.7%882.7
25Michael Wacha332929166.213801453.353.651.197.823.3%11.3%6.6%14.6%902.5
26Shota Imanaga312929173.115301742.913.721.029.028.4%15.8%4.0%21.0%912.5
27Kevin Gausman333131181.0141101623.833.771.228.123.4%11.7%7.4%14.0%932.5
28Sean Manaea323232181.212601843.473.831.089.126.1%12.8%8.5%16.4%942.4
29Bailey Ober293131178.212901913.983.821.009.629.0%15.2%6.1%20.9%942.4
30Aaron Nola313333199.114801973.573.941.208.925.2%12.2%6.1%17.9%972.3
31Zach Eflin302828165.110901343.593.771.157.321.6%10.8%3.5%16.1%922.3
32Erick Fedde313131177.19901543.303.861.167.821.6%9.8%7.2%14.0%952.3
33Nestor Cortes303130174.191001623.773.841.158.424.2%12.2%5.5%17.3%942.2
34Nathan Eovaldi342929170.212801663.803.831.118.826.8%14.0%6.0%17.8%942.2
35Brady Singer283232179.291301703.713.931.278.525.1%11.2%7.1%15.2%962.1
36Luis Castillo323030175.1111201753.643.911.179.025.9%13.1%6.5%17.8%962.1
37Jameson Taillon332828165.112801253.273.921.136.819.5%9.4%4.9%13.6%962.0
38Mitch Keller283131178.0111201664.254.081.308.421.5%10.2%6.5%15.0%1001.8
39Chris Bassitt353131171.0101401684.164.081.468.821.7%9.8%9.2%12.9%1001.8
40Freddy Peralta283232173.211902003.684.161.2110.431.1%14.6%9.4%18.2%1021.6
41Luis Severino303131182.011701613.914.211.248.022.0%11.1%7.9%13.3%1031.6
42Ronel Blanco313029167.113601662.804.151.098.929.0%14.1%10.1%14.5%1021.6
43Ryan Feltner283030162.131001384.494.161.347.723.8%11.5%7.5%12.4%1021.5
44Brayan Bello253030162.114801534.494.191.368.525.9%12.0%9.1%12.7%1031.5
45Miles Mikolas363232171.2101101225.354.241.286.416.4%8.2%3.5%13.5%1041.4
46Jake Irvin273333187.2101401564.414.411.207.522.3%10.8%6.8%13.5%1081.2
47Carlos Rodón323232175.016901953.964.391.2210.030.1%14.9%7.7%18.8%1081.2
48Patrick Corbin353232174.261301395.624.411.507.222.4%10.8%7.1%11.1%1081.1
49Kyle Gibson373030169.28801514.244.421.358.025.9%11.1%9.4%11.5%1081.1
50Charlie Morton413030165.181001674.194.461.329.126.1%12.2%9.3%14.6%1091.0
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 →