DataBaseball
2026

2016 season · rankings

2016 MLB Pitching Leaders

74 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
74 of 74 qualifiedDownload Parquet
#
1Noah Syndergaard243130183.214902182.602.291.1510.730.4%15.4%5.8%23.5%555.7
2José Fernández242929182.116802532.862.301.1212.532.8%15.1%7.5%26.9%555.7
3Johnny Cueto303232219.218501982.792.961.098.121.8%10.5%5.1%17.4%715.2
4Max Scherzer323434228.120702842.963.240.9711.232.4%16.8%6.2%25.3%774.7
5Madison Bumgarner273434226.215902512.743.241.0310.025.9%12.4%5.9%21.6%774.7
6Corey Kluber303232215.018902273.143.261.069.528.2%13.7%6.6%19.8%784.4
7Rick Porcello283333223.022401893.153.401.017.618.6%9.0%3.6%17.6%814.2
8Chris Sale273232226.2171002333.343.461.049.324.7%12.2%5.0%20.7%834.1
9Justin Verlander333434227.216902543.043.481.0010.026.9%13.5%6.3%21.8%834.1
10Kyle Hendricks273130190.016801702.133.200.988.124.7%10.7%5.9%16.9%764.0
11David Price313535230.017902283.993.601.208.924.8%12.7%5.3%18.7%863.8
12Jon Lester323232202.219501972.443.411.028.724.0%11.3%6.5%18.2%813.8
13Jose Quintana273232208.0131201813.203.561.167.818.6%8.5%6.0%15.7%853.6
14Masahiro Tanaka283131199.214401653.073.511.087.423.3%11.7%4.5%16.0%843.5
15Jake Arrieta303131197.118801903.103.521.088.725.2%11.5%9.6%14.3%843.5
16Aaron Sanchez243030192.015201613.003.551.177.521.0%9.1%8.0%12.4%853.3
17Carlos Martinez253131195.116901743.043.611.228.023.1%10.9%8.7%12.9%863.2
18Marcus Stroman253232204.091001664.373.711.297.321.5%10.2%6.3%13.1%893.1
19Tanner Roark303433210.0161001722.833.791.177.421.9%9.6%8.5%11.6%903.0
20Kenta Maeda283232175.2161101793.483.581.149.227.5%12.6%7.0%18.0%853.0
21Julio Teheran253030188.071001673.213.691.058.024.1%11.7%5.4%16.6%882.9
22Chris Archer283333201.191902334.023.811.2410.429.6%13.5%7.9%19.5%912.9
23Jeff Samardzija313232203.1121101673.813.851.207.420.7%10.1%6.5%13.6%922.8
24Jon Gray252929168.0101001854.613.601.269.926.5%13.0%8.3%17.7%862.8
25John Lackey382929188.111801803.353.811.068.625.4%12.5%7.1%17.0%912.7
26Gio Gonzalez313232177.1111101714.573.761.348.723.4%10.3%7.7%14.6%902.6
27Ervin Santana343030181.171101493.383.811.227.422.9%10.8%7.1%12.8%912.6
28Robbie Ray253232174.181502184.903.761.4711.326.6%12.4%9.1%18.9%902.6
29Adam Wainwright353333198.213901614.623.931.407.320.1%8.9%7.0%12.0%942.6
30Michael Pineda273232175.261202074.823.801.3510.631.2%15.2%7.0%20.4%912.5
31Cole Hamels333232200.215502003.323.981.319.027.2%13.2%9.1%14.5%952.5
32Mike Leake293030176.291201254.693.831.326.416.3%7.8%4.0%12.5%912.5
33J.A. Happ343232195.020401633.183.961.177.522.3%10.5%7.5%12.9%942.5
34Drew Pomeranz283130170.2111201863.323.801.189.825.9%12.0%9.2%17.2%912.4
35Collin McHugh293333184.2131001774.343.951.418.623.9%11.4%6.8%15.5%942.4
36Jeremy Hellickson293232189.0121001543.713.981.157.324.0%11.5%5.8%14.1%952.3
37Bartolo Colon433433191.215801283.433.991.216.013.5%6.4%4.0%12.1%952.3
38Dallas Keuchel282626168.091201444.553.871.297.723.2%10.2%6.8%13.7%922.3
39Danny Duffy284226179.212301883.513.831.149.427.3%14.0%5.7%20.0%912.2
40Zach Davies232828163.111701353.973.891.257.420.3%9.0%5.6%14.2%932.2
41Trevor Bauer253528190.012801684.263.991.318.022.5%10.0%8.6%12.1%952.1
42Ricky Nolasco343232197.281401444.424.141.246.620.9%9.7%5.4%12.2%992.1
43Matt Moore273333198.1131201784.084.171.298.124.2%11.4%8.6%12.6%1002.0
44Carlos Rodón242828165.091001684.044.011.399.223.6%10.9%7.6%15.9%962.0
45Jerad Eickhoff263333197.1111401673.654.191.167.621.6%9.9%5.2%15.4%1002.0
46Kevin Gausman253030179.291201743.614.101.288.725.4%12.3%6.2%16.8%982.0
47Marco Estrada332929176.09901653.484.151.128.426.2%12.0%9.0%13.8%991.9
48Hisashi Iwakuma353333199.0161201474.124.271.336.617.4%8.5%5.5%12.1%1021.8
49Chad Bettis273232186.014801384.794.261.416.721.6%9.7%7.2%9.7%1021.7
50Chris Tillman283030172.016601403.774.231.287.321.9%10.0%9.2%10.3%1011.7
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 →