2026 Projections






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  • General Projections
    Steamer:
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  • Overall - No Split
  • vs LHP
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  • Steamer (RoS):
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  • Overall - No Split
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  • Context Neutral
    Steamer:
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  • Overall - No Split
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  • Overall - No Split
  • vs LHP
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  • 3-Year
    Historical Projections
    Members Exclusive Data
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  • Steamer:
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  • Splits - Steamer Projections
    Members Exclusive Data
    Steamer:
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  • Overall - No Split
  • vs LHP
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  • Steamer Ros:
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  • Overall - No Split
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  • Steamer
    (Context Neutral):
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  • Overall - No Split
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  • Steamer RoS
    (Context Neutral):
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  • Overall - No Split
  • vs LHP
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  • Data Export [Members Only]
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Ketel MarteARI140612288885511.0%16.2%.223.289.275.361.499.367136-0.625.50.24.7
    2Brendan DonovanSEA13356913665858.5%13.9%.135.294.268.341.402.326116-1.19.40.73.0
    3Jazz Chisholm Jr.NYY140585288077329.6%26.6%.207.283.238.317.445.3291102.49.60.23.0
    4Brice TurangMIL149633158167299.1%20.8%.135.308.257.326.392.3151022.33.73.52.9
    5Nico HoernerCHC14660877456266.4%9.3%.096.298.278.333.374.312992.11.25.82.8
    6Gleyber TorresDET147631177868511.1%17.2%.143.289.257.343.400.327110-1.75.5-0.22.8
    7Luke KeaschallMIN126534116857249.2%17.2%.134.307.267.346.401.3291100.97.30.22.6
    8Jose AltuveHOU138600207868128.4%17.1%.162.289.262.329.424.327110-0.46.8-3.82.4
    9Marcus SemienNYM13757718736799.0%16.5%.157.260.240.312.397.310970.1-1.75.42.4
    10Bryson StottPHI136555136658238.7%16.6%.134.287.255.322.389.311971.80.13.92.3
    11Xavier EdwardsMIA13357246844278.3%14.4%.079.323.278.339.357.308952.1-1.04.32.3
    12Otto LopezMIA136563126361166.8%15.3%.127.296.265.318.392.309960.6-2.04.52.2
    13Brandon LowePIT12452723677248.2%25.7%.196.286.241.308.437.321104-0.81.61.62.1
    14Jackson HollidayBAL118505136649139.9%22.3%.146.302.248.328.394.317104-0.12.60.42.1
    15Andrés GiménezTOR138558116355205.6%17.5%.116.281.245.305.361.293871.4-7.18.02.1
    16Jordan WestburgBAL9339416545046.3%22.5%.193.303.261.316.454.332114-0.36.5-0.82.0
    17JJ WetherholtSTL115486105846129.3%17.7%.126.285.247.327.373.310970.3-1.23.01.9
    18Jeff McNeilATH13153212605648.1%12.7%.141.276.257.328.398.317102-1.40.10.01.9
    19Ozzie AlbiesATL140588176970117.3%14.8%.156.267.250.309.406.310970.1-1.60.01.8
    20Jake CronenworthSDP140579146660410.7%19.9%.143.276.235.331.379.314101-0.6-0.2-2.31.8
    21Matt McLainCIN131546176757169.2%28.1%.159.306.235.313.394.310930.7-3.81.91.7
    22Chase MeidrothCHW126537762401310.2%15.1%.088.291.252.339.341.30795-0.3-3.31.41.7
    23Colt KeithDET12349315625538.8%20.9%.165.300.257.325.423.3241080.14.5-5.71.6
    24Luis ArraezPHI1406064675585.2%4.0%.083.305.299.339.383.315101-0.30.6-5.41.6
    25Ernie ClementTOR13955410645684.4%10.3%.120.276.262.298.383.295880.1-7.53.61.6
    26Jonathan IndiaKCR119504126049610.2%19.3%.138.286.244.337.382.320104-0.32.2-5.21.4
    27Jorge PolancoNYM12350721616859.2%20.5%.188.274.247.320.435.326109-0.84.5-7.61.4
    28José CaballeroNYY97367747314010.9%25.2%.115.295.226.323.341.299902.5-1.93.01.4
    29Tommy EdmanLAD10743312544996.4%17.6%.149.270.243.297.392.299900.6-4.43.01.4
    30Davis SchneiderTOR86327144039412.2%28.3%.195.273.220.322.415.323108-0.32.7-0.91.3
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Ketel MarteARI140612288885511.0%16.2%.223.289.275.361.499.367136-0.625.50.24.7
    2Brendan DonovanSEA13356913665858.5%13.9%.135.294.268.341.402.326116-1.19.40.73.0
    3Jazz Chisholm Jr.NYY140585288077329.6%26.6%.207.283.238.317.445.3291102.49.60.23.0
    4Brice TurangMIL149633158167299.1%20.8%.135.308.257.326.392.3151022.33.73.52.9
    5Nico HoernerCHC14660877456266.4%9.3%.096.298.278.333.374.312992.11.25.82.8
    6Gleyber TorresDET147631177868511.1%17.2%.143.289.257.343.400.327110-1.75.5-0.22.8
    7Luke KeaschallMIN126534116857249.2%17.2%.134.307.267.346.401.3291100.97.30.22.6
    8Jose AltuveHOU138600207868128.4%17.1%.162.289.262.329.424.327110-0.46.8-3.82.4
    9Marcus SemienNYM13757718736799.0%16.5%.157.260.240.312.397.310970.1-1.75.42.4
    10Bryson StottPHI136555136658238.7%16.6%.134.287.255.322.389.311971.80.13.92.3
    11Xavier EdwardsMIA13357246844278.3%14.4%.079.323.278.339.357.308952.1-1.04.32.3
    12Otto LopezMIA136563126361166.8%15.3%.127.296.265.318.392.309960.6-2.04.52.2
    13Brandon LowePIT12452723677248.2%25.7%.196.286.241.308.437.321104-0.81.61.62.1
    14Jackson HollidayBAL118505136649139.9%22.3%.146.302.248.328.394.317104-0.12.60.42.1
    15Andrés GiménezTOR138558116355205.6%17.5%.116.281.245.305.361.293871.4-7.18.02.1
    16Jordan WestburgBAL9339416545046.3%22.5%.193.303.261.316.454.332114-0.36.5-0.82.0
    17JJ WetherholtSTL115486105846129.3%17.7%.126.285.247.327.373.310970.3-1.23.01.9
    18Jeff McNeilATH13153212605648.1%12.7%.141.276.257.328.398.317102-1.40.10.01.9
    19Ozzie AlbiesATL140588176970117.3%14.8%.156.267.250.309.406.310970.1-1.60.01.8
    20Jake CronenworthSDP140579146660410.7%19.9%.143.276.235.331.379.314101-0.6-0.2-2.31.8
    21Matt McLainCIN131546176757169.2%28.1%.159.306.235.313.394.310930.7-3.81.91.7
    22Chase MeidrothCHW126537762401310.2%15.1%.088.291.252.339.341.30795-0.3-3.31.41.7
    23Colt KeithDET12349315625538.8%20.9%.165.300.257.325.423.3241080.14.5-5.71.6
    24Luis ArraezPHI1406064675585.2%4.0%.083.305.299.339.383.315101-0.30.6-5.41.6
    25Ernie ClementTOR13955410645684.4%10.3%.120.276.262.298.383.295880.1-7.53.61.6
    26Jonathan IndiaKCR119504126049610.2%19.3%.138.286.244.337.382.320104-0.32.2-5.21.4
    27Jorge PolancoNYM12350721616859.2%20.5%.188.274.247.320.435.326109-0.84.5-7.61.4
    28José CaballeroNYY97367747314010.9%25.2%.115.295.226.323.341.299902.5-1.93.01.4
    29Tommy EdmanLAD10743312544996.4%17.6%.149.270.243.297.392.299900.6-4.43.01.4
    30Davis SchneiderTOR86327144039412.2%28.3%.195.273.220.322.415.323108-0.32.7-0.91.3
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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
    • 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.