Cy Young Award Projections


About the Cy Young Award Projections:

These Cy Young Award Projections utilize a simple model created by Tangotiger. The original Cy Young Points model predicts the top two vote getters with high accuracy through 2020. The FIP Adjusted model may be a better predictor of more recent voting behavior. (The report is limited to pitchers with at least 50 projected IP.)

  • Cy Young Points (CYP): IP/2 - ER + SO/10 + W
  • FIP Adjusted Cy Young Points (FIP CYP): (IP/2 - ER) + (IP/2 - FIP Runs) + SO/10 + W
Data Export [Members Only]

American League

#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
Season StatsProjected Stats
#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
1Tarik Skubal83.16233.4%2.2%2.161.853.43.338.262.7200.115731.4%3.7%2.472.317.16.684.6133.4
2Max Fried81.08124.1%5.6%1.782.792.12.940.255.6193.016623.2%6.3%2.663.184.45.173.7102.1
3Garrett Crochet88.06431.3%7.7%2.352.672.53.038.055.9184.013831.2%7.6%2.692.735.45.673.3109.6
4Hunter Brown79.08331.1%8.4%1.822.692.43.540.856.7185.016928.0%8.3%2.823.184.55.271.398.4
5Kris Bubic75.15326.9%7.5%1.432.452.53.738.655.8172.111825.2%7.8%2.663.064.25.263.991.4
6Jacob deGrom76.16225.3%5.8%2.123.411.63.133.642.8164.112627.4%5.6%2.743.323.84.961.983.3
7Framber Valdez85.06425.1%8.1%3.073.072.02.427.941.4202.014923.8%8.0%3.253.354.24.661.687.3
8Carlos Rodón84.28431.0%9.0%2.873.271.82.133.645.2190.2161029.1%8.5%3.453.623.73.560.979.6
9Nathan Eovaldi69.14327.4%3.8%1.562.322.23.134.050.8158.19825.3%5.1%2.793.053.94.455.280.6
10Joe Ryan73.07228.3%5.2%2.963.411.52.027.736.5173.014827.4%5.4%3.433.593.63.553.771.1
#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
Season StatsProjected Stats
#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
1Tarik Skubal83.16233.4%2.2%2.161.853.43.338.262.7200.115731.4%3.7%2.472.317.16.684.6133.4
2Max Fried81.08124.1%5.6%1.782.792.12.940.255.6193.016623.2%6.3%2.663.184.45.173.7102.1
3Garrett Crochet88.06431.3%7.7%2.352.672.53.038.055.9184.013831.2%7.6%2.692.735.45.673.3109.6
4Hunter Brown79.08331.1%8.4%1.822.692.43.540.856.7185.016928.0%8.3%2.823.184.55.271.398.4
5Kris Bubic75.15326.9%7.5%1.432.452.53.738.655.8172.111825.2%7.8%2.663.064.25.263.991.4
6Jacob deGrom76.16225.3%5.8%2.123.411.63.133.642.8164.112627.4%5.6%2.743.323.84.961.983.3
7Framber Valdez85.06425.1%8.1%3.073.072.02.427.941.4202.014923.8%8.0%3.253.354.24.661.687.3
8Carlos Rodón84.28431.0%9.0%2.873.271.82.133.645.2190.2161029.1%8.5%3.453.623.73.560.979.6
9Nathan Eovaldi69.14327.4%3.8%1.562.322.23.134.050.8158.19825.3%5.1%2.793.053.94.455.280.6
10Joe Ryan73.07228.3%5.2%2.963.411.52.027.736.5173.014827.4%5.4%3.433.593.63.553.771.1
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National League

#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
Season StatsProjected Stats
#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
1Paul Skenes91.04626.7%5.8%1.882.492.93.939.760.0196.0111127.8%6.3%2.482.735.76.676.5115.1
2Logan Webb87.15528.5%4.8%2.582.122.82.333.856.9207.1131025.0%5.1%2.912.685.44.970.9112.8
3Zack Wheeler82.06232.0%6.0%2.852.962.22.731.145.1201.014729.1%6.2%3.093.195.15.468.898.1
4Chris Sale80.24431.7%7.4%2.792.742.22.330.045.8188.212831.0%7.0%2.962.924.85.068.5101.6
5Yoshinobu Yamamoto73.26429.6%8.6%2.202.891.92.533.446.6173.214827.8%7.4%2.903.114.24.564.291.0
6Kodai Senga68.06323.7%10.9%1.593.291.42.934.543.6169.013824.3%10.5%2.823.682.94.461.677.0
7Robbie Ray77.18128.4%10.1%2.443.031.62.734.447.0174.114627.3%9.1%3.153.522.94.159.778.7
8MacKenzie Gore75.13535.4%7.2%2.872.582.42.427.543.5177.1101130.9%8.1%3.253.204.34.357.382.9
9Sonny Gray75.17126.5%4.6%3.353.111.81.524.836.4181.114625.9%5.6%3.423.343.83.455.078.4
10Clay Holmes73.17321.5%7.6%2.953.821.01.826.231.7176.115921.4%7.9%3.373.702.53.253.168.7
#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
Season StatsProjected Stats
#NameIPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
IPWLK%BB%ERAFIPWARRA9-
WAR
CYPFIP
CYP
1Paul Skenes91.04626.7%5.8%1.882.492.93.939.760.0196.0111127.8%6.3%2.482.735.76.676.5115.1
2Logan Webb87.15528.5%4.8%2.582.122.82.333.856.9207.1131025.0%5.1%2.912.685.44.970.9112.8
3Zack Wheeler82.06232.0%6.0%2.852.962.22.731.145.1201.014729.1%6.2%3.093.195.15.468.898.1
4Chris Sale80.24431.7%7.4%2.792.742.22.330.045.8188.212831.0%7.0%2.962.924.85.068.5101.6
5Yoshinobu Yamamoto73.26429.6%8.6%2.202.891.92.533.446.6173.214827.8%7.4%2.903.114.24.564.291.0
6Kodai Senga68.06323.7%10.9%1.593.291.42.934.543.6169.013824.3%10.5%2.823.682.94.461.677.0
7Robbie Ray77.18128.4%10.1%2.443.031.62.734.447.0174.114627.3%9.1%3.153.522.94.159.778.7
8MacKenzie Gore75.13535.4%7.2%2.872.582.42.427.543.5177.1101130.9%8.1%3.253.204.34.357.382.9
9Sonny Gray75.17126.5%4.6%3.353.111.81.524.836.4181.114625.9%5.6%3.423.343.83.455.078.4
10Clay Holmes73.17321.5%7.6%2.953.821.01.826.231.7176.115921.4%7.9%3.373.702.53.253.168.7
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