2026 Projections






ZiPS:
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  • 2010
  • Steamer:
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  • General Projections
    Steamer:
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • Steamer (RoS):
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • Context Neutral
    Steamer:
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • Steamer (RoS)
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • 3-Year
    Historical Projections
    Members Exclusive Data
    ZiPS:
    Select
  • 2025
  • 2024
  • 2023
  • 2022
  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • 2011
  • 2010
  • Steamer:
    Select
  • 2025
  • 2024
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  • 2021
  • 2020
  • 2019
  • 2018
  • 2017
  • 2016
  • 2015
  • 2014
  • 2013
  • 2012
  • Splits - Steamer Projections
    Members Exclusive Data
    Steamer:
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • Steamer Ros:
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • Steamer
    (Context Neutral):
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • Steamer RoS
    (Context Neutral):
    Select
  • Overall - No Split
  • as SP
  • as RP
  • vs RHB
  • vs LHB
  • vs RHB as SP
  • vs LHB as SP
  • vs RHB as RP
  • vs LHB as RP
  • Data Export [Members Only]
    #NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
    1Eury PérezMIA9902727144.110.022.991.25.27871.5%3.903.822.6
    2Sandy AlcantaraMIA101102828177.07.562.611.05.29269.2%4.163.962.5
    3Max MeyerMIA6802723127.28.262.981.26.29770.8%4.324.221.4
    4Robby SnellingMIA560161583.17.893.201.06.29971.9%4.104.081.1
    5Janson JunkMIA450381189.16.642.041.21.30167.1%4.584.190.8
    6Pete FairbanksMIA342658059.29.223.160.92.28573.3%3.533.570.7
    7Andrew NardiMIA32051050.110.823.511.11.29572.7%3.813.620.4
    8Thomas WhiteMIA1206629.29.084.811.06.29072.7%4.224.390.3
    9Anthony BenderMIA33259059.28.433.400.93.29171.7%3.883.890.3
    10Victor VodnikMIA441759062.18.674.400.95.31271.5%4.374.150.3
    11Ryan GustoMIA33029447.17.913.161.32.29869.2%4.654.470.3
    12Calvin FaucherMIA34661063.08.883.771.00.29972.0%4.064.010.2
    13Josh WhiteMIA32037039.19.343.671.06.28971.7%3.993.940.2
    14Cade GibsonMIA34054060.27.203.510.82.29471.0%4.024.100.1
    15John KingMIA22044045.15.892.670.89.30471.7%4.054.080.1
    16Dax FultonMIA11013117.17.814.200.88.30170.4%4.344.200.1
    17Matt PushardMIA33046049.17.873.511.12.29270.7%4.304.290.1
    18Tyler PhillipsMIA33257065.16.692.991.06.29470.0%4.324.290.0
    19Zach PopMIA11018018.16.923.201.15.29668.8%4.594.480.0
    20Michael PetersenMIA11027029.18.423.651.31.29270.8%4.504.520.0
    21Josh EknessMIA01012013.07.984.161.12.29069.0%4.624.650.0
    22Karson MilbrandtMIA01011011.07.744.491.14.29170.2%4.664.760.0
    23Zach BrzykcyMIA000808.08.404.591.31.29569.4%4.934.85-0.1
    24William KempnerMIA12018019.08.654.811.12.29369.5%4.714.65-0.1
    25Bradley BlalockMIA11013116.16.393.651.32.29767.8%5.104.96-0.1
    26Tyler ZuberMIA11016020.09.014.611.38.30266.3%5.354.80-0.1
    27Brandan BidoisMIA23041043.28.304.401.19.28970.4%4.604.61-0.1
    28Wikelman GonzálezMIA22039043.28.755.621.06.28470.9%4.624.78-0.2
    #NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
    1Eury PérezMIA9902727144.110.022.991.25.27871.5%3.903.822.6
    2Sandy AlcantaraMIA101102828177.07.562.611.05.29269.2%4.163.962.5
    3Max MeyerMIA6802723127.28.262.981.26.29770.8%4.324.221.4
    4Robby SnellingMIA560161583.17.893.201.06.29971.9%4.104.081.1
    5Janson JunkMIA450381189.16.642.041.21.30167.1%4.584.190.8
    6Pete FairbanksMIA342658059.29.223.160.92.28573.3%3.533.570.7
    7Andrew NardiMIA32051050.110.823.511.11.29572.7%3.813.620.4
    8Thomas WhiteMIA1206629.29.084.811.06.29072.7%4.224.390.3
    9Anthony BenderMIA33259059.28.433.400.93.29171.7%3.883.890.3
    10Victor VodnikMIA441759062.18.674.400.95.31271.5%4.374.150.3
    11Ryan GustoMIA33029447.17.913.161.32.29869.2%4.654.470.3
    12Calvin FaucherMIA34661063.08.883.771.00.29972.0%4.064.010.2
    13Josh WhiteMIA32037039.19.343.671.06.28971.7%3.993.940.2
    14Cade GibsonMIA34054060.27.203.510.82.29471.0%4.024.100.1
    15John KingMIA22044045.15.892.670.89.30471.7%4.054.080.1
    16Dax FultonMIA11013117.17.814.200.88.30170.4%4.344.200.1
    17Matt PushardMIA33046049.17.873.511.12.29270.7%4.304.290.1
    18Tyler PhillipsMIA33257065.16.692.991.06.29470.0%4.324.290.0
    19Zach PopMIA11018018.16.923.201.15.29668.8%4.594.480.0
    20Michael PetersenMIA11027029.18.423.651.31.29270.8%4.504.520.0
    21Josh EknessMIA01012013.07.984.161.12.29069.0%4.624.650.0
    22Karson MilbrandtMIA01011011.07.744.491.14.29170.2%4.664.760.0
    23Zach BrzykcyMIA000808.08.404.591.31.29569.4%4.934.85-0.1
    24William KempnerMIA12018019.08.654.811.12.29369.5%4.714.65-0.1
    25Bradley BlalockMIA11013116.16.393.651.32.29767.8%5.104.96-0.1
    26Tyler ZuberMIA11016020.09.014.611.38.30266.3%5.354.80-0.1
    27Brandan BidoisMIA23041043.28.304.401.19.28970.4%4.604.61-0.1
    28Wikelman GonzálezMIA22039043.28.755.621.06.28470.9%4.624.78-0.2
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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
    • OOPSY:OOPSY projections courtesy of Jordan Rosenblum with Depth Charts playing time, and OOPSYPeak use neutral playing time. Other flavors available at scoutthestatline.com. Stuff+ courtesy of Eno Sarris.

    • 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.