2025 Projections






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  • General Projections
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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
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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
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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
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  • Overall - No Split
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  • Data Export [Members Only]
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Yordan AlvarezHOU138599379098312.4%16.6%.283.305.298.394.581.409173-1.548.7-13.95.7
    2Riley GreeneDET142610228073610.2%25.6%.192.332.265.345.457.346129-0.519.5-3.63.7
    3Jarren DuranBOS146636189068297.5%22.8%.185.328.269.329.454.3371152.613.7-1.83.4
    4Wyatt LangfordTEX136579207873199.4%20.2%.187.300.262.336.449.3391220.915.6-4.13.2
    5Steven KwanCLE14462788354169.8%9.8%.108.297.277.352.385.3251140.810.7-2.43.0
    6Jackson ChourioMIL147626228483276.7%20.7%.182.311.269.322.451.3321132.111.6-4.92.8
    7Colton CowserBAL135553217466910.4%29.7%.186.318.242.330.428.3301180.312.0-3.32.8
    8Taylor WardLAA14763424807379.8%23.1%.181.296.251.332.432.333116-0.610.9-6.12.7
    9Ian HappCHC1486382183761211.9%24.3%.178.296.242.338.420.332115-0.110.9-6.52.7
    10Randy ArozarenaSEA1456172179692110.5%25.3%.171.294.237.336.409.328121-0.314.5-10.42.6
    11James WoodWSN1335701974701910.9%27.4%.181.340.261.345.442.3421200.013.6-8.72.5
    12Teoscar HernándezLAD14561928819197.2%28.7%.204.326.259.319.463.336118-1.011.9-9.22.4
    13Bryan ReynoldsPIT14764322797998.7%22.0%.175.314.264.338.440.337114-0.110.4-8.62.4
    14Lars NootbaarSTL120499176155912.9%20.2%.181.281.247.345.429.337118-0.110.7-4.22.4
    15Brendan DonovanSTL13155312655958.6%13.4%.131.300.274.349.405.331115-1.08.5-4.12.4
    16Brandon NimmoNYM131564177463811.2%22.1%.165.296.247.343.412.332115-0.99.1-5.52.3
    17Christian YelichMIL1175091571582112.7%21.2%.161.324.268.365.430.3461221.915.5-10.52.3
    18Brandon MarshPHI1274951460561610.2%31.2%.162.343.246.326.407.3201051.34.00.52.2
    19Evan CarterTEX1114421257481110.6%24.8%.166.304.242.330.408.3231110.15.60.32.1
    20Daulton VarshoTOR130527206662128.6%25.0%.185.260.220.293.405.303981.10.12.22.1
    21Tyler O'NeillBAL112467236262610.2%30.5%.216.295.235.321.451.333121-0.310.7-6.62.0
    22Trevor LarnachMIN114466175959310.5%26.1%.183.302.244.328.427.328115-1.17.0-7.41.6
    23Heliot RamosSFG13054620646677.3%26.6%.178.313.251.311.430.320107-0.93.6-7.21.5
    24Jurickson ProfarATL138586157463710.8%16.1%.145.284.255.346.400.329110-1.15.8-10.91.5
    25Luke RaleySEA122471205858116.8%30.4%.191.296.230.305.421.3161120.16.8-8.41.5
    26Jasson DomínguezNYY125512166759219.6%25.2%.154.304.244.318.397.3131020.82.0-5.71.4
    27Lourdes Gurriel Jr.ARI13155217667165.7%18.0%.159.306.272.319.431.324106-1.03.0-8.81.3
    28Nolan JonesCLE89364114341811.4%30.5%.162.336.243.334.404.323112-0.24.9-4.51.3
    29Christopher MorelTBR12149522606389.1%27.5%.201.275.228.305.429.317105-0.12.8-7.31.2
    30Michael ConfortoLAD11948119586329.8%23.7%.187.276.237.320.424.323109-1.04.1-8.41.2
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Yordan AlvarezHOU138599379098312.4%16.6%.283.305.298.394.581.409173-1.548.7-13.95.7
    2Riley GreeneDET142610228073610.2%25.6%.192.332.265.345.457.346129-0.519.5-3.63.7
    3Jarren DuranBOS146636189068297.5%22.8%.185.328.269.329.454.3371152.613.7-1.83.4
    4Wyatt LangfordTEX136579207873199.4%20.2%.187.300.262.336.449.3391220.915.6-4.13.2
    5Steven KwanCLE14462788354169.8%9.8%.108.297.277.352.385.3251140.810.7-2.43.0
    6Jackson ChourioMIL147626228483276.7%20.7%.182.311.269.322.451.3321132.111.6-4.92.8
    7Colton CowserBAL135553217466910.4%29.7%.186.318.242.330.428.3301180.312.0-3.32.8
    8Taylor WardLAA14763424807379.8%23.1%.181.296.251.332.432.333116-0.610.9-6.12.7
    9Ian HappCHC1486382183761211.9%24.3%.178.296.242.338.420.332115-0.110.9-6.52.7
    10Randy ArozarenaSEA1456172179692110.5%25.3%.171.294.237.336.409.328121-0.314.5-10.42.6
    11James WoodWSN1335701974701910.9%27.4%.181.340.261.345.442.3421200.013.6-8.72.5
    12Teoscar HernándezLAD14561928819197.2%28.7%.204.326.259.319.463.336118-1.011.9-9.22.4
    13Bryan ReynoldsPIT14764322797998.7%22.0%.175.314.264.338.440.337114-0.110.4-8.62.4
    14Lars NootbaarSTL120499176155912.9%20.2%.181.281.247.345.429.337118-0.110.7-4.22.4
    15Brendan DonovanSTL13155312655958.6%13.4%.131.300.274.349.405.331115-1.08.5-4.12.4
    16Brandon NimmoNYM131564177463811.2%22.1%.165.296.247.343.412.332115-0.99.1-5.52.3
    17Christian YelichMIL1175091571582112.7%21.2%.161.324.268.365.430.3461221.915.5-10.52.3
    18Brandon MarshPHI1274951460561610.2%31.2%.162.343.246.326.407.3201051.34.00.52.2
    19Evan CarterTEX1114421257481110.6%24.8%.166.304.242.330.408.3231110.15.60.32.1
    20Daulton VarshoTOR130527206662128.6%25.0%.185.260.220.293.405.303981.10.12.22.1
    21Tyler O'NeillBAL112467236262610.2%30.5%.216.295.235.321.451.333121-0.310.7-6.62.0
    22Trevor LarnachMIN114466175959310.5%26.1%.183.302.244.328.427.328115-1.17.0-7.41.6
    23Heliot RamosSFG13054620646677.3%26.6%.178.313.251.311.430.320107-0.93.6-7.21.5
    24Jurickson ProfarATL138586157463710.8%16.1%.145.284.255.346.400.329110-1.15.8-10.91.5
    25Luke RaleySEA122471205858116.8%30.4%.191.296.230.305.421.3161120.16.8-8.41.5
    26Jasson DomínguezNYY125512166759219.6%25.2%.154.304.244.318.397.3131020.82.0-5.71.4
    27Lourdes Gurriel Jr.ARI13155217667165.7%18.0%.159.306.272.319.431.324106-1.03.0-8.81.3
    28Nolan JonesCLE89364114341811.4%30.5%.162.336.243.334.404.323112-0.24.9-4.51.3
    29Christopher MorelTBR12149522606389.1%27.5%.201.275.228.305.429.317105-0.12.8-7.31.2
    30Michael ConfortoLAD11948119586329.8%23.7%.187.276.237.320.424.323109-1.04.1-8.41.2
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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. 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.