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 Skubal166.011433.5%3.9%2.282.276.15.973.2114.4197.013533.1%4.1%2.332.367.16.985.5132.2
2Garrett Crochet172.114531.1%6.1%2.402.635.46.475.6111.4200.116631.0%6.2%2.472.726.27.386.1125.6
3Hunter Brown155.210629.1%7.6%2.372.934.35.564.591.6185.212728.6%7.6%2.573.044.96.072.8102.9
4Nathan Eovaldi130.011326.0%4.2%1.732.783.85.863.988.7130.011326.0%4.2%1.732.833.85.863.988.1
5Max Fried162.014523.1%6.3%3.063.213.63.255.478.7193.016623.0%6.4%3.123.304.33.863.889.6
6Framber Valdez164.112723.4%8.3%3.183.064.14.352.078.3197.114823.3%8.3%3.193.204.85.061.690.1
7Bryan Woo164.212725.6%4.8%2.953.563.24.256.974.2192.214825.3%4.9%3.043.643.74.664.683.1
8Jacob deGrom145.110627.5%5.7%2.793.503.24.853.269.3171.112727.9%5.7%2.893.483.85.361.380.8
9Carlos Rodón164.115726.5%10.0%3.183.822.63.556.969.3194.117926.5%9.8%3.293.873.13.964.277.7
10Trevor Rogers90.18223.8%5.6%1.392.423.34.947.368.1116.110323.0%6.2%1.932.823.75.353.675.2
#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 Skubal166.011433.5%3.9%2.282.276.15.973.2114.4197.013533.1%4.1%2.332.367.16.985.5132.2
2Garrett Crochet172.114531.1%6.1%2.402.635.46.475.6111.4200.116631.0%6.2%2.472.726.27.386.1125.6
3Hunter Brown155.210629.1%7.6%2.372.934.35.564.591.6185.212728.6%7.6%2.573.044.96.072.8102.9
4Nathan Eovaldi130.011326.0%4.2%1.732.783.85.863.988.7130.011326.0%4.2%1.732.833.85.863.988.1
5Max Fried162.014523.1%6.3%3.063.213.63.255.478.7193.016623.0%6.4%3.123.304.33.863.889.6
6Framber Valdez164.112723.4%8.3%3.183.064.14.352.078.3197.114823.3%8.3%3.193.204.85.061.690.1
7Bryan Woo164.212725.6%4.8%2.953.563.24.256.974.2192.214825.3%4.9%3.043.643.74.664.683.1
8Jacob deGrom145.110627.5%5.7%2.793.503.24.853.269.3171.112727.9%5.7%2.893.483.85.361.380.8
9Carlos Rodón164.115726.5%10.0%3.183.822.63.556.969.3194.117926.5%9.8%3.293.873.13.964.277.7
10Trevor Rogers90.18223.8%5.6%1.392.423.34.947.368.1116.110323.0%6.2%1.932.823.75.353.675.2
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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 Skenes167.09928.6%5.8%2.052.455.57.073.2111.2194.0111028.7%5.9%2.182.526.37.782.9125.6
2Cristopher Sánchez169.111526.3%6.0%2.662.585.26.063.899.8200.113625.8%6.0%2.742.746.06.773.3112.4
3Logan Webb173.212926.1%5.2%3.162.684.44.056.591.6205.2141125.5%5.2%3.192.815.14.665.5104.1
4Zack Wheeler149.210533.3%5.6%2.712.994.05.159.384.5149.210533.3%5.6%2.713.034.05.159.383.7
5Freddy Peralta153.216526.7%9.2%2.583.603.25.565.681.1181.218726.7%9.1%2.773.693.76.072.789.0
6Nick Pivetta158.113426.8%6.7%2.903.343.54.557.978.2188.115626.9%6.8%3.063.504.04.965.386.3
7Matthew Boyd153.112722.6%5.9%2.823.413.34.454.473.0182.114922.7%6.1%2.963.533.84.961.781.2
8Yoshinobu Yamamoto139.211827.9%8.5%2.903.183.64.051.572.1168.213927.7%8.3%2.993.244.34.760.183.8
9Ranger Suárez131.010623.1%5.6%3.023.043.64.143.965.1160.012722.8%5.8%3.093.194.34.852.075.3
10Andrew Abbott139.08522.1%6.9%2.653.613.34.549.062.8167.010722.1%7.0%2.913.753.84.954.668.5
#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 Skenes167.09928.6%5.8%2.052.455.57.073.2111.2194.0111028.7%5.9%2.182.526.37.782.9125.6
2Cristopher Sánchez169.111526.3%6.0%2.662.585.26.063.899.8200.113625.8%6.0%2.742.746.06.773.3112.4
3Logan Webb173.212926.1%5.2%3.162.684.44.056.591.6205.2141125.5%5.2%3.192.815.14.665.5104.1
4Zack Wheeler149.210533.3%5.6%2.712.994.05.159.384.5149.210533.3%5.6%2.713.034.05.159.383.7
5Freddy Peralta153.216526.7%9.2%2.583.603.25.565.681.1181.218726.7%9.1%2.773.693.76.072.789.0
6Nick Pivetta158.113426.8%6.7%2.903.343.54.557.978.2188.115626.9%6.8%3.063.504.04.965.386.3
7Matthew Boyd153.112722.6%5.9%2.823.413.34.454.473.0182.114922.7%6.1%2.963.533.84.961.781.2
8Yoshinobu Yamamoto139.211827.9%8.5%2.903.183.64.051.572.1168.213927.7%8.3%2.993.244.34.760.183.8
9Ranger Suárez131.010623.1%5.6%3.023.043.64.143.965.1160.012722.8%5.8%3.093.194.34.852.075.3
10Andrew Abbott139.08522.1%6.9%2.653.613.34.549.062.8167.010722.1%7.0%2.913.753.84.954.668.5
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