2026 Projections






ZiPS:
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  • Steamer:
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  • General Projections
    Steamer:
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  • Overall - No Split
  • vs LHP
  • vs RHP
  • Steamer (RoS):
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  • Overall - No Split
  • vs LHP
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  • Context Neutral
    Steamer:
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  • Overall - No Split
  • vs LHP
  • vs RHP
  • Steamer (RoS)
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  • Overall - No Split
  • vs LHP
  • vs RHP
  • 600 PA / 200 IP
    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
  • vs RHP
  • Steamer Ros:
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  • Overall - No Split
  • vs LHP
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  • Steamer
    (Context Neutral):
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  • Overall - No Split
  • vs LHP
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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
    1Bobby Witt Jr.KCR1516592810092347.3%17.1%.225.315.291.347.516.3651363.331.112.06.7
    2Gunnar HendersonBAL1526602697822410.2%21.2%.207.311.270.349.477.3541302.525.86.75.6
    3Fernando Tatis Jr.SDP1496482999802610.9%19.8%.209.301.270.355.479.3591311.925.9-1.54.7
    4Francisco LindorNYM142628259277238.9%18.4%.189.282.258.335.447.3391170.913.89.04.5
    5Corey SeagerTEX123526267176211.3%18.6%.226.293.273.360.499.364136-1.521.24.34.5
    6Trea TurnerPHI143627188971286.4%18.1%.157.323.283.333.440.3351133.713.67.24.3
    7Mookie BettsLAD143622218881910.7%11.6%.180.273.268.349.448.345122-0.615.54.74.2
    8Zach NetoLAA148634278675277.0%24.5%.199.298.251.322.451.3331131.611.07.34.1
    9Elly De La CruzCIN149640239278419.6%26.8%.191.328.258.332.449.3351104.212.06.04.0
    10Geraldo PerdomoARI1516491388672011.7%13.4%.133.288.263.356.396.3321120.710.17.24.0
    11Jeremy PeñaHOU137590167665175.9%17.8%.149.311.273.327.422.3261091.07.66.93.6
    12Willy AdamesSFG1526492683831210.7%25.3%.187.275.231.316.418.319104-0.12.96.73.2
    13Jacob WilsonATH13757511716465.5%8.9%.122.308.294.340.416.329111-0.66.84.53.1
    14Dansby SwansonCHC153630227875168.4%25.3%.166.295.242.308.408.311981.1-0.19.53.1
    15Bo BichetteNYM13860217747666.3%16.4%.152.319.286.333.438.334114-0.69.30.93.1
    16Nico HoernerCHC14660877456266.4%9.3%.096.298.278.333.374.312992.11.25.82.8
    17Masyn WinnSTL144612137360146.7%18.1%.130.289.251.306.380.300910.8-5.712.52.8
    18Carlos CorreaHOU12954616646308.9%19.7%.150.307.264.332.414.325109-0.94.93.12.7
    19Xander BogaertsSDP137569136760168.1%17.5%.130.302.265.327.394.3151010.91.65.32.7
    20CJ AbramsWSN141614188164306.3%19.3%.164.284.248.310.412.3131003.03.12.52.7
    21Kevin McGonigleDET1084471456521010.0%14.5%.173.270.254.331.427.329111-0.15.74.92.7
    22Oneil CruzPIT1285382271652810.3%29.9%.197.307.237.319.433.3241062.76.50.12.5
    23J.P. CrawfordSEA139578116453511.4%19.3%.117.288.241.333.358.309104-0.71.92.12.4
    24Marcus SemienNYM13757718736799.0%16.5%.157.260.240.312.397.310970.1-1.75.42.4
    25Xavier EdwardsMIA13357246844278.3%14.4%.079.323.278.339.357.308952.1-1.04.32.3
    26Ezequiel TovarCOL14762620767184.9%24.9%.172.322.261.300.433.31588-0.1-9.310.62.3
    27Otto LopezMIA136563126361166.8%15.3%.127.296.265.318.392.309960.6-2.04.52.2
    28Trevor StoryBOS136575207272226.1%27.3%.165.313.248.300.412.308921.7-3.54.82.2
    29Konnor GriffinPIT94392105245186.2%24.5%.139.322.257.317.396.311970.8-0.78.22.1
    30Andrés GiménezTOR138558116355205.6%17.5%.116.281.245.305.361.293871.4-7.18.02.1
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Bobby Witt Jr.KCR1516592810092347.3%17.1%.225.315.291.347.516.3651363.331.112.06.7
    2Gunnar HendersonBAL1526602697822410.2%21.2%.207.311.270.349.477.3541302.525.86.75.6
    3Fernando Tatis Jr.SDP1496482999802610.9%19.8%.209.301.270.355.479.3591311.925.9-1.54.7
    4Francisco LindorNYM142628259277238.9%18.4%.189.282.258.335.447.3391170.913.89.04.5
    5Corey SeagerTEX123526267176211.3%18.6%.226.293.273.360.499.364136-1.521.24.34.5
    6Trea TurnerPHI143627188971286.4%18.1%.157.323.283.333.440.3351133.713.67.24.3
    7Mookie BettsLAD143622218881910.7%11.6%.180.273.268.349.448.345122-0.615.54.74.2
    8Zach NetoLAA148634278675277.0%24.5%.199.298.251.322.451.3331131.611.07.34.1
    9Elly De La CruzCIN149640239278419.6%26.8%.191.328.258.332.449.3351104.212.06.04.0
    10Geraldo PerdomoARI1516491388672011.7%13.4%.133.288.263.356.396.3321120.710.17.24.0
    11Jeremy PeñaHOU137590167665175.9%17.8%.149.311.273.327.422.3261091.07.66.93.6
    12Willy AdamesSFG1526492683831210.7%25.3%.187.275.231.316.418.319104-0.12.96.73.2
    13Jacob WilsonATH13757511716465.5%8.9%.122.308.294.340.416.329111-0.66.84.53.1
    14Dansby SwansonCHC153630227875168.4%25.3%.166.295.242.308.408.311981.1-0.19.53.1
    15Bo BichetteNYM13860217747666.3%16.4%.152.319.286.333.438.334114-0.69.30.93.1
    16Nico HoernerCHC14660877456266.4%9.3%.096.298.278.333.374.312992.11.25.82.8
    17Masyn WinnSTL144612137360146.7%18.1%.130.289.251.306.380.300910.8-5.712.52.8
    18Carlos CorreaHOU12954616646308.9%19.7%.150.307.264.332.414.325109-0.94.93.12.7
    19Xander BogaertsSDP137569136760168.1%17.5%.130.302.265.327.394.3151010.91.65.32.7
    20CJ AbramsWSN141614188164306.3%19.3%.164.284.248.310.412.3131003.03.12.52.7
    21Kevin McGonigleDET1084471456521010.0%14.5%.173.270.254.331.427.329111-0.15.74.92.7
    22Oneil CruzPIT1285382271652810.3%29.9%.197.307.237.319.433.3241062.76.50.12.5
    23J.P. CrawfordSEA139578116453511.4%19.3%.117.288.241.333.358.309104-0.71.92.12.4
    24Marcus SemienNYM13757718736799.0%16.5%.157.260.240.312.397.310970.1-1.75.42.4
    25Xavier EdwardsMIA13357246844278.3%14.4%.079.323.278.339.357.308952.1-1.04.32.3
    26Ezequiel TovarCOL14762620767184.9%24.9%.172.322.261.300.433.31588-0.1-9.310.62.3
    27Otto LopezMIA136563126361166.8%15.3%.127.296.265.318.392.309960.6-2.04.52.2
    28Trevor StoryBOS136575207272226.1%27.3%.165.313.248.300.412.308921.7-3.54.82.2
    29Konnor GriffinPIT94392105245186.2%24.5%.139.322.257.317.396.311970.8-0.78.22.1
    30Andrés GiménezTOR138558116355205.6%17.5%.116.281.245.305.361.293871.4-7.18.02.1
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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.