DataBaseball
2026

2019 season · rankings

2019 MLB Pitching Leaders

61 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.

TableBattingPitching
RoleLeaguePool
Who
61 of 61 qualifiedDownload Parquet
#
1Gerrit Cole293333212.120503262.502.640.8913.837.2%18.6%5.9%34.0%596.1
2Jacob deGrom313232204.011802552.432.670.9711.331.4%16.8%5.5%26.2%595.8
3Max Scherzer352727172.111702432.922.451.0312.733.9%17.8%4.8%30.3%545.3
4Charlie Morton363333194.216602403.052.811.0811.129.6%14.0%7.2%23.2%625.2
5Justin Verlander363434223.021603002.583.270.8012.133.6%17.5%5.0%30.5%734.9
6Lance Lynn323333208.1161102463.673.131.2210.628.5%14.0%6.7%21.4%694.9
7Zack Greinke363333208.218501872.933.220.988.124.1%11.3%3.7%19.4%714.7
8Stephen Strasburg313333209.018602513.323.251.0410.830.6%14.6%6.7%23.2%724.7
9Shane Bieber243433214.115802593.283.321.0510.930.7%14.6%4.7%25.5%744.6
10Walker Buehler253030182.114402153.263.011.0410.626.8%13.5%5.0%24.2%674.5
11Hyun Jin Ryu322929182.214501632.323.101.018.024.8%12.3%3.3%19.2%694.4
12Patrick Corbin303333202.014702383.253.491.1810.631.6%15.0%8.4%20.1%774.0
13Jack Flaherty243333196.111802312.753.460.9710.630.7%14.8%7.1%22.8%773.9
14Zack Wheeler293131195.111801953.963.481.269.023.0%11.7%6.0%17.5%773.9
15Noah Syndergaard273232197.210802024.283.601.239.226.8%13.6%6.1%18.4%803.7
16Sonny Gray303131175.111802052.873.421.0810.528.4%12.0%9.6%19.4%763.6
17Lucas Giolito252929176.214902283.413.431.0611.632.4%16.1%8.1%24.3%763.6
18Michael Soroka222929174.213401422.683.451.117.322.8%11.1%5.8%14.4%773.5
19Luis Castillo273232190.215802263.403.701.1410.735.8%17.0%10.1%18.8%823.4
20Kyle Hendricks303030177.0111001503.463.611.137.622.0%10.9%4.4%16.2%803.3
21Eduardo Rodriguez263434203.119602133.813.861.339.427.4%12.7%8.7%16.1%863.2
22Madison Bumgarner303434207.29902033.903.901.138.824.6%12.5%5.1%19.0%873.2
23José Berríos253232200.114801953.683.851.228.823.5%11.6%6.1%17.1%863.2
24Marcus Stroman283232184.1101301593.223.721.317.824.7%11.2%7.5%13.0%833.2
25Aaron Nola263434202.112702293.874.031.2710.226.7%11.9%9.4%17.5%902.9
26Max Fried253330165.217601734.023.721.339.426.0%12.3%6.7%17.9%822.8
27Clayton Kershaw312928178.116501893.033.861.049.527.7%14.2%5.8%21.0%862.8
28Jose Quintana303231171.013901524.683.801.398.020.9%9.3%6.2%14.2%842.8
29Joe Musgrove273231170.1111201574.443.821.228.324.6%12.8%5.4%16.4%852.8
30Marco Gonzales273434203.0161301473.994.151.316.518.0%8.6%6.5%10.5%922.6
31Mike Minor323232208.1141002003.594.251.248.626.2%12.5%7.9%15.3%942.5
32Germán Márquez242828174.012501754.764.061.209.126.6%13.2%4.9%19.4%902.4
33Trevor Bauer283434213.0111302534.484.341.2510.729.4%13.3%9.0%18.8%962.4
34Yu Darvish333131178.26802293.984.181.1011.530.4%14.7%7.7%23.7%932.3
35Homer Bailey333131163.113901494.574.111.328.224.2%11.8%7.6%13.8%912.2
36Miles Mikolas313232184.091401444.164.271.227.021.7%10.7%4.2%14.7%952.2
37Masahiro Tanaka313231182.011901494.454.271.247.423.2%11.7%5.3%14.4%952.1
38Joey Lucchesi263030163.2101001584.184.171.228.725.4%11.5%8.2%14.9%932.1
39Matthew Boyd283232185.191202384.564.321.2311.631.1%15.5%6.3%23.9%962.1
40Jon Lester353131171.2131001654.464.261.508.721.1%9.6%6.8%14.8%942.0
41Robbie Ray283333174.112802354.344.291.3412.132.7%14.8%11.2%20.2%952.0
42Adam Wainwright383131171.2141001534.194.361.438.019.5%8.2%8.6%11.9%971.9
43Brad Keller242828165.171401224.194.351.356.619.9%9.1%9.9%7.3%971.8
44Sandy Alcantara243232197.161401513.884.551.326.923.8%11.8%9.7%8.4%1011.7
45Merrill Kelly313232183.1131401584.424.511.317.822.4%10.6%7.3%13.0%1001.7
46Anthony DeSclafani293131166.29901673.894.431.209.023.6%11.4%7.0%17.0%981.7
47Aníbal Sánchez353030166.011801343.854.441.277.322.4%10.9%8.1%10.7%991.7
48Wade Miley333333167.114601403.984.511.347.522.9%10.2%8.5%11.0%1001.5
49Jeff Samardzija343232181.1111201403.524.591.116.920.2%9.7%6.6%12.3%1021.5
50Brett Anderson313131176.01390903.894.571.314.617.0%8.1%6.6%5.5%1011.5
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 →