2025 Projections






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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
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  • Steamer (RoS)
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  • Overall - No Split
  • vs LHP
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  • 600 PA / 200 IP
    3-Year
    Historical Projections
    New! Members Exclusive Data
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  • Splits - Steamer Projections
    New! 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
  • vs LHP
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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
    1Aaron JudgeNYY14563546104114817.5%25.6%.319.321.283.413.602.425179-0.558.0-10.57.1
    2Julio RodríguezSEA146635278883277.0%23.9%.193.328.274.334.468.3451332.225.95.35.4
    3Jackson MerrillSDP151627257986165.8%16.6%.198.298.277.320.475.3391200.215.17.04.4
    4Corbin CarrollARI15065023107753910.4%19.4%.205.291.258.345.463.3491235.223.0-4.74.1
    5Michael Harris IIATL139583218272185.6%19.4%.183.318.280.326.463.3381161.212.65.33.8
    6Mike TroutLAA104451276565712.1%26.0%.267.296.257.356.525.375146-0.423.1-4.53.5
    7Jarren DuranBOS146636189068297.5%22.8%.185.328.269.329.454.3371152.613.7-1.83.4
    8Jazz Chisholm Jr.NYY141598268276388.4%25.5%.201.294.247.315.448.3281122.711.41.33.4
    9Oneil CruzPIT143609257981228.8%29.1%.203.323.252.321.455.3331111.39.4-0.93.0
    10Colton CowserBAL135553217466910.4%29.7%.186.318.242.330.428.3301180.312.0-3.32.8
    11Luis Robert Jr.CHW133566247368236.1%29.2%.190.312.246.300.436.3171051.64.61.22.6
    12Pete Crow-ArmstrongCHC134533146759316.2%25.5%.157.312.246.302.403.305971.8-0.37.12.5
    13JJ BledayATH143594217166411.4%21.5%.186.268.233.324.419.324110-1.25.6-2.12.4
    14Brenton DoyleCOL142595217768276.7%28.3%.176.316.247.302.424.313872.4-6.79.92.4
    15Cody BellingerNYY134575217476127.9%17.2%.179.273.254.315.433.3211070.45.3-1.82.3
    16Jung Hoo LeeSFG1164938605177.6%9.0%.133.296.282.340.415.328113-1.06.3-0.22.3
    17Byron BuxtonMIN10342521606087.3%27.7%.235.289.242.309.477.3361210.710.9-2.72.3
    18Cedric MullinsBAL130516156559278.3%20.1%.154.273.238.306.392.3051011.92.41.72.2
    19Brandon MarshPHI1274951460561610.2%31.2%.162.343.246.326.407.3201051.34.00.52.2
    20Victor RoblesSEA12750486342387.5%20.2%.111.310.253.328.364.3081072.96.7-2.82.1
    21Tommy EdmanLAD129526136855236.9%17.9%.143.282.249.306.392.304962.1-0.43.32.1
    22Parker MeadowsDET113464135846178.8%23.5%.163.288.237.308.400.3081021.32.22.72.1
    23Daulton VarshoTOR130527206662128.6%25.0%.185.260.220.293.405.303981.10.12.22.1
    24Lane ThomasCLE127533166760227.9%25.4%.164.302.243.310.406.3121041.03.7-2.42.0
    25Jake MeyersHOU11543912494897.0%24.1%.145.288.234.298.378.297940.5-2.44.81.8
    26Garrett MitchellMIL115452135749209.7%30.5%.156.331.240.320.396.3151011.01.5-0.21.7
    27TJ FriedlCIN117495146157168.1%16.5%.156.268.244.321.400.316961.1-1.30.61.6
    28Heliot RamosSFG13054620646677.3%26.6%.178.313.251.311.430.320107-0.93.6-7.21.5
    29Andy PagesLAD8333213454128.1%24.4%.193.292.245.317.438.326111-0.43.9-0.61.5
    30Jake McCarthyARI12449486448276.9%17.7%.121.309.262.325.383.311982.51.1-3.31.5
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Aaron JudgeNYY14563546104114817.5%25.6%.319.321.283.413.602.425179-0.558.0-10.57.1
    2Julio RodríguezSEA146635278883277.0%23.9%.193.328.274.334.468.3451332.225.95.35.4
    3Jackson MerrillSDP151627257986165.8%16.6%.198.298.277.320.475.3391200.215.17.04.4
    4Corbin CarrollARI15065023107753910.4%19.4%.205.291.258.345.463.3491235.223.0-4.74.1
    5Michael Harris IIATL139583218272185.6%19.4%.183.318.280.326.463.3381161.212.65.33.8
    6Mike TroutLAA104451276565712.1%26.0%.267.296.257.356.525.375146-0.423.1-4.53.5
    7Jarren DuranBOS146636189068297.5%22.8%.185.328.269.329.454.3371152.613.7-1.83.4
    8Jazz Chisholm Jr.NYY141598268276388.4%25.5%.201.294.247.315.448.3281122.711.41.33.4
    9Oneil CruzPIT143609257981228.8%29.1%.203.323.252.321.455.3331111.39.4-0.93.0
    10Colton CowserBAL135553217466910.4%29.7%.186.318.242.330.428.3301180.312.0-3.32.8
    11Luis Robert Jr.CHW133566247368236.1%29.2%.190.312.246.300.436.3171051.64.61.22.6
    12Pete Crow-ArmstrongCHC134533146759316.2%25.5%.157.312.246.302.403.305971.8-0.37.12.5
    13JJ BledayATH143594217166411.4%21.5%.186.268.233.324.419.324110-1.25.6-2.12.4
    14Brenton DoyleCOL142595217768276.7%28.3%.176.316.247.302.424.313872.4-6.79.92.4
    15Cody BellingerNYY134575217476127.9%17.2%.179.273.254.315.433.3211070.45.3-1.82.3
    16Jung Hoo LeeSFG1164938605177.6%9.0%.133.296.282.340.415.328113-1.06.3-0.22.3
    17Byron BuxtonMIN10342521606087.3%27.7%.235.289.242.309.477.3361210.710.9-2.72.3
    18Cedric MullinsBAL130516156559278.3%20.1%.154.273.238.306.392.3051011.92.41.72.2
    19Brandon MarshPHI1274951460561610.2%31.2%.162.343.246.326.407.3201051.34.00.52.2
    20Victor RoblesSEA12750486342387.5%20.2%.111.310.253.328.364.3081072.96.7-2.82.1
    21Tommy EdmanLAD129526136855236.9%17.9%.143.282.249.306.392.304962.1-0.43.32.1
    22Parker MeadowsDET113464135846178.8%23.5%.163.288.237.308.400.3081021.32.22.72.1
    23Daulton VarshoTOR130527206662128.6%25.0%.185.260.220.293.405.303981.10.12.22.1
    24Lane ThomasCLE127533166760227.9%25.4%.164.302.243.310.406.3121041.03.7-2.42.0
    25Jake MeyersHOU11543912494897.0%24.1%.145.288.234.298.378.297940.5-2.44.81.8
    26Garrett MitchellMIL115452135749209.7%30.5%.156.331.240.320.396.3151011.01.5-0.21.7
    27TJ FriedlCIN117495146157168.1%16.5%.156.268.244.321.400.316961.1-1.30.61.6
    28Heliot RamosSFG13054620646677.3%26.6%.178.313.251.311.430.320107-0.93.6-7.21.5
    29Andy PagesLAD8333213454128.1%24.4%.193.292.245.317.438.326111-0.43.9-0.61.5
    30Jake McCarthyARI12449486448276.9%17.7%.121.309.262.325.383.311982.51.1-3.31.5
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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. Peak version and 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.