2024 Projections

Data Export [Members Only]
#NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
1Spencer StriderATL15602828176.112.662.970.95.30272.1%3.382.925.2
2Zack WheelerPHI13803030183.29.382.120.99.29171.7%3.513.454.8
3Logan WebbSFG121003030189.28.061.900.74.30571.7%3.443.284.6
4Aaron NolaPHI12903030185.29.451.941.23.29470.0%3.893.674.3
5Zac GallenARI13903030184.29.252.441.04.29271.5%3.693.643.6
6Yoshinobu YamamotoLAD12702626161.19.642.401.07.29271.2%3.693.563.5
7Blake SnellSFG11903029162.011.464.230.90.29575.0%3.463.503.5
8Max FriedATL13602727160.08.662.220.92.30174.1%3.413.503.4
9Freddy PeraltaMIL11902828160.010.853.081.19.28672.8%3.723.733.4
10Justin SteeleCHC11802929167.18.782.640.97.30072.9%3.673.713.2
11Jesús LuzardoMIA11902929166.110.242.921.17.29973.3%3.783.763.2
12Tyler GlasnowLAD11602424139.011.382.811.17.28873.9%3.503.423.1
13Mitch KellerPIT101003030177.28.673.011.02.30369.8%4.153.983.0
14Dylan CeaseSDP10803030171.110.513.821.13.29473.4%3.873.942.9
15Michael KingSDP9703424139.29.963.020.98.29573.3%3.563.602.8
16Jordan MontgomeryARI10802828162.08.172.421.05.29772.2%3.813.862.8
17Bobby MillerLAD12702626151.28.862.481.07.28369.9%3.833.802.8
18Sonny GraySTL9802626154.18.612.940.95.29172.7%3.673.822.8
19Chris SaleATL9702424131.010.642.611.22.29771.9%3.813.732.7
20Merrill KellyARI11903030177.28.593.051.09.29271.3%4.004.022.7
21Hunter GreeneCIN9902828148.111.293.451.42.29971.9%4.204.122.7
22Shota ImanagaCHC9802727153.19.102.561.23.29672.8%3.883.972.6
23Joe MusgroveSDP10802525149.08.962.301.15.28973.1%3.663.902.5
24Ranger SuárezPHI8702827146.17.963.270.94.29671.3%4.004.032.5
25Alex CobbSFG7702323128.08.052.540.88.31071.6%3.843.692.5
26Yu DarvishSDP9802323139.09.142.451.25.28769.4%4.094.002.4
27Aaron CivaleMIL9802525141.28.472.351.26.28770.6%4.044.122.3
28Braxton GarrettMIA7702524131.08.832.331.07.30972.0%3.863.792.3
29DL HallMIL7613217109.010.953.961.04.30372.5%3.903.752.3
30Cristopher SánchezPHI8803225144.08.092.671.12.29270.8%4.054.112.3
#NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
1Spencer StriderATL15602828176.112.662.970.95.30272.1%3.382.925.2
2Zack WheelerPHI13803030183.29.382.120.99.29171.7%3.513.454.8
3Logan WebbSFG121003030189.28.061.900.74.30571.7%3.443.284.6
4Aaron NolaPHI12903030185.29.451.941.23.29470.0%3.893.674.3
5Zac GallenARI13903030184.29.252.441.04.29271.5%3.693.643.6
6Yoshinobu YamamotoLAD12702626161.19.642.401.07.29271.2%3.693.563.5
7Blake SnellSFG11903029162.011.464.230.90.29575.0%3.463.503.5
8Max FriedATL13602727160.08.662.220.92.30174.1%3.413.503.4
9Freddy PeraltaMIL11902828160.010.853.081.19.28672.8%3.723.733.4
10Justin SteeleCHC11802929167.18.782.640.97.30072.9%3.673.713.2
11Jesús LuzardoMIA11902929166.110.242.921.17.29973.3%3.783.763.2
12Tyler GlasnowLAD11602424139.011.382.811.17.28873.9%3.503.423.1
13Mitch KellerPIT101003030177.28.673.011.02.30369.8%4.153.983.0
14Dylan CeaseSDP10803030171.110.513.821.13.29473.4%3.873.942.9
15Michael KingSDP9703424139.29.963.020.98.29573.3%3.563.602.8
16Jordan MontgomeryARI10802828162.08.172.421.05.29772.2%3.813.862.8
17Bobby MillerLAD12702626151.28.862.481.07.28369.9%3.833.802.8
18Sonny GraySTL9802626154.18.612.940.95.29172.7%3.673.822.8
19Chris SaleATL9702424131.010.642.611.22.29771.9%3.813.732.7
20Merrill KellyARI11903030177.28.593.051.09.29271.3%4.004.022.7
21Hunter GreeneCIN9902828148.111.293.451.42.29971.9%4.204.122.7
22Shota ImanagaCHC9802727153.19.102.561.23.29672.8%3.883.972.6
23Joe MusgroveSDP10802525149.08.962.301.15.28973.1%3.663.902.5
24Ranger SuárezPHI8702827146.17.963.270.94.29671.3%4.004.032.5
25Alex CobbSFG7702323128.08.052.540.88.31071.6%3.843.692.5
26Yu DarvishSDP9802323139.09.142.451.25.28769.4%4.094.002.4
27Aaron CivaleMIL9802525141.28.472.351.26.28770.6%4.044.122.3
28Braxton GarrettMIA7702524131.08.832.331.07.30972.0%3.863.792.3
29DL HallMIL7613217109.010.953.961.04.30372.5%3.903.752.3
30Cristopher SánchezPHI8803225144.08.092.671.12.29270.8%4.054.112.3
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  • ZiPS:ZiPS Projections courtesy of Dan Szymborski
  • ZiPS DC:ZiPS Projections pro-rated to Depth Charts playing time
  • Steamer:Steamer Projections courtesy of steamerprojections.com
  • Depth Charts:FanGraphs Depth Chart projections are a combination of ZiPS and Steamer projections with playing time allocated by our staff.
  • ATC:ATC Projections courtesy of Ariel Cohen
  • THE BAT:THE BAT projections courtesy of Derek Carty. DFS version of THE BAT available at RotoGrinders. Sports betting version of THE BAT available at EV Analytics
  • THE BAT X:THE BAT X projections courtesy of Derek Carty. DFS version of THE BAT X available at RotoGrinders. Sports betting version of THE BAT X available at EV Analytics

  • On-Pace - Every Game Played:Please note, these are not projections. They represent a player's current seasons stats pro-rated for the remaining games in the season if they were to play in every single remaining game*. This is not how a player will actually perform the rest of the season, and should not be used for anything other than your own personal amusement. (*Starters pitch every 4.5 days and relievers pitch every 2.5 days.)
  • On-Pace - Games Played %:Please note, these are not projections. They represent a player's current seasons stats prorated for the remaining games in the season if they were to play the same percentage of total games they have already played this season. This is not how a player will actually perform the rest of the season, and should not be used for anything other than your own personal amusement.
  • RoS:Rest of Season
  • Update:Updated In-Season

  • ADP:ADP data provided courtesy of National Fantasy Baseball Championship
  • Inter-Projection Standard Deviation (InterSD):The standard deviation of the underlying projections surrounding the ATC average auction value. InterSD describes how much the projections disagree about the value of a player. The larger the InterSD, the more projections differ.
  • Inter-Projection Skewness (InterSK):The skewness of the underlying projections surrounding the ATC average auction value. InterSK describes the symmetry of the underlying projections. A positive InterSK means that a player’s mean is being pulled to the upside; the majority of projections are lower than the ATC average. A negative InterSK means that a player’s mean is being pulled to the downside; the majority of projections are higher than the ATC average.
  • Intra-Projection Standard Deviation (IntraSD):The standard deviation of a player’s categorical Z-Scores. IntraSD is a measure of the dimension of a player’s statistical profile. The smaller the IntraSD, the more balanced the individual player’s category contributions are. The larger the IntraSD, the more unbalanced the player’s category contributions are.