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
  • vs LHP
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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
    2Juan SotoNYM1526693410696819.1%16.7%.252.288.275.416.527.404165-2.648.0-11.16.1
    3Yordan AlvarezHOU138599379098312.4%16.6%.283.305.298.394.581.409173-1.548.7-13.95.7
    4Mookie BettsLAD1446342798881511.8%13.5%.216.286.279.368.495.3711420.431.42.15.6
    5Julio RodríguezSEA146635278883277.0%23.9%.193.328.274.334.468.3451332.225.95.35.4
    6Kyle TuckerCHC1456323092932012.9%15.4%.226.286.277.371.503.3731431.633.7-7.84.9
    7Fernando Tatis Jr.SDP143622329487208.4%21.9%.230.306.272.339.502.3611351.727.0-3.44.6
    8Jackson MerrillSDP151627257986165.8%16.6%.198.298.277.320.475.3391200.215.17.04.4
    9Corbin CarrollARI15065023107753910.4%19.4%.205.291.258.345.463.3491235.223.0-4.74.1
    10Bryce HarperPHI144626288889912.9%21.5%.221.321.278.374.498.371139-1.727.5-9.94.0
    11Ronald Acuña Jr.ATL1145112188612911.7%18.8%.204.319.284.377.488.3741403.628.0-6.74.0
    12Michael Harris IIATL139583218272185.6%19.4%.183.318.280.326.463.3381161.212.65.33.8
    13Riley GreeneDET142610228073610.2%25.6%.192.332.265.345.457.346129-0.519.5-3.63.7
    14Mike TroutLAA104451276565712.1%26.0%.267.296.257.356.525.375146-0.423.1-4.53.5
    15Jarren DuranBOS146636189068297.5%22.8%.185.328.269.329.454.3371152.613.7-1.83.4
    16Jazz Chisholm Jr.NYY141598268276388.4%25.5%.201.294.247.315.448.3281122.711.41.33.4
    17Wyatt LangfordTEX136579207873199.4%20.2%.187.300.262.336.449.3391220.915.6-4.13.2
    18Steven KwanCLE14462788354169.8%9.8%.108.297.277.352.385.3251140.810.7-2.43.0
    19Oneil CruzPIT143609257981228.8%29.1%.203.323.252.321.455.3331111.39.4-0.93.0
    20Jackson ChourioMIL147626228483276.7%20.7%.182.311.269.322.451.3321132.111.6-4.92.8
    21Colton CowserBAL135553217466910.4%29.7%.186.318.242.330.428.3301180.312.0-3.32.8
    22Brent RookerATH14260335809289.4%29.8%.248.310.253.332.501.356131-0.521.6-15.22.7
    23Taylor WardLAA14763424807379.8%23.1%.181.296.251.332.432.333116-0.610.9-6.12.7
    24Ian HappCHC1486382183761211.9%24.3%.178.296.242.338.420.332115-0.110.9-6.52.7
    25Matt WallnerMIN122499246165410.3%34.1%.227.327.236.337.463.346128-0.315.6-6.92.6
    26Luis Robert Jr.CHW133566247368236.1%29.2%.190.312.246.300.436.3171051.64.61.22.6
    27Randy ArozarenaSEA1456172179692110.5%25.3%.171.294.237.336.409.328121-0.314.5-10.42.6
    28Pete Crow-ArmstrongCHC134533146759316.2%25.5%.157.312.246.302.403.305971.8-0.37.12.5
    29James WoodWSN1335701974701910.9%27.4%.181.340.261.345.442.3421200.013.6-8.72.5
    30Anthony SantanderTOR14663033809328.6%20.5%.230.253.241.313.470.336121-0.914.4-12.02.4
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Aaron JudgeNYY14563546104114817.5%25.6%.319.321.283.413.602.425179-0.558.0-10.57.1
    2Juan SotoNYM1526693410696819.1%16.7%.252.288.275.416.527.404165-2.648.0-11.16.1
    3Yordan AlvarezHOU138599379098312.4%16.6%.283.305.298.394.581.409173-1.548.7-13.95.7
    4Mookie BettsLAD1446342798881511.8%13.5%.216.286.279.368.495.3711420.431.42.15.6
    5Julio RodríguezSEA146635278883277.0%23.9%.193.328.274.334.468.3451332.225.95.35.4
    6Kyle TuckerCHC1456323092932012.9%15.4%.226.286.277.371.503.3731431.633.7-7.84.9
    7Fernando Tatis Jr.SDP143622329487208.4%21.9%.230.306.272.339.502.3611351.727.0-3.44.6
    8Jackson MerrillSDP151627257986165.8%16.6%.198.298.277.320.475.3391200.215.17.04.4
    9Corbin CarrollARI15065023107753910.4%19.4%.205.291.258.345.463.3491235.223.0-4.74.1
    10Bryce HarperPHI144626288889912.9%21.5%.221.321.278.374.498.371139-1.727.5-9.94.0
    11Ronald Acuña Jr.ATL1145112188612911.7%18.8%.204.319.284.377.488.3741403.628.0-6.74.0
    12Michael Harris IIATL139583218272185.6%19.4%.183.318.280.326.463.3381161.212.65.33.8
    13Riley GreeneDET142610228073610.2%25.6%.192.332.265.345.457.346129-0.519.5-3.63.7
    14Mike TroutLAA104451276565712.1%26.0%.267.296.257.356.525.375146-0.423.1-4.53.5
    15Jarren DuranBOS146636189068297.5%22.8%.185.328.269.329.454.3371152.613.7-1.83.4
    16Jazz Chisholm Jr.NYY141598268276388.4%25.5%.201.294.247.315.448.3281122.711.41.33.4
    17Wyatt LangfordTEX136579207873199.4%20.2%.187.300.262.336.449.3391220.915.6-4.13.2
    18Steven KwanCLE14462788354169.8%9.8%.108.297.277.352.385.3251140.810.7-2.43.0
    19Oneil CruzPIT143609257981228.8%29.1%.203.323.252.321.455.3331111.39.4-0.93.0
    20Jackson ChourioMIL147626228483276.7%20.7%.182.311.269.322.451.3321132.111.6-4.92.8
    21Colton CowserBAL135553217466910.4%29.7%.186.318.242.330.428.3301180.312.0-3.32.8
    22Brent RookerATH14260335809289.4%29.8%.248.310.253.332.501.356131-0.521.6-15.22.7
    23Taylor WardLAA14763424807379.8%23.1%.181.296.251.332.432.333116-0.610.9-6.12.7
    24Ian HappCHC1486382183761211.9%24.3%.178.296.242.338.420.332115-0.110.9-6.52.7
    25Matt WallnerMIN122499246165410.3%34.1%.227.327.236.337.463.346128-0.315.6-6.92.6
    26Luis Robert Jr.CHW133566247368236.1%29.2%.190.312.246.300.436.3171051.64.61.22.6
    27Randy ArozarenaSEA1456172179692110.5%25.3%.171.294.237.336.409.328121-0.314.5-10.42.6
    28Pete Crow-ArmstrongCHC134533146759316.2%25.5%.157.312.246.302.403.305971.8-0.37.12.5
    29James WoodWSN1335701974701910.9%27.4%.181.340.261.345.442.3421200.013.6-8.72.5
    30Anthony SantanderTOR14663033809328.6%20.5%.230.253.241.313.470.336121-0.914.4-12.02.4
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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.