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
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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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  • Overall - No Split
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  • Data Export [Members Only]
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1José RamírezCLE151656299496309.5%11.8%.222.271.274.344.496.3551352.728.73.15.5
    2Austin RileyATL15165232929228.2%24.3%.225.312.268.336.493.355127-1.020.4-0.64.3
    3Matt ChapmanSFG147619258176910.3%25.7%.203.290.241.326.444.3331160.512.15.03.9
    4Manny MachadoSDP14762629799487.9%19.3%.203.286.264.322.467.337119-1.112.60.83.5
    5Jordan WestburgBAL134561217072106.9%22.5%.192.311.264.323.456.336123-0.314.11.43.5
    6Alex BregmanBOS14663323828239.8%12.8%.182.266.260.339.441.339116-2.29.63.13.5
    7Jazz Chisholm Jr.NYY141598268276388.4%25.5%.201.294.247.315.448.3281122.711.41.33.4
    8Isaac ParedesHOU141593227176111.0%16.6%.182.252.238.338.420.332119-1.811.21.63.4
    9Rafael DeversBOS140606298490310.4%21.7%.232.303.269.350.502.361132-1.120.8-13.92.8
    10Max MuncyLAD123513247073214.4%26.4%.217.247.214.335.431.334116-0.98.8-1.22.5
    11Mark VientosNYM14460229718517.5%29.4%.207.300.242.303.449.324109-1.94.6-0.12.5
    12Junior CamineroTBR13055122647546.4%20.9%.179.300.263.315.442.326111-1.06.00.22.5
    13Royce LewisMIN10242620556148.2%23.1%.210.285.252.315.462.334119-0.48.90.52.4
    14Alec BohmPHI14159916697946.7%15.3%.149.301.274.326.423.325108-1.63.8-0.32.4
    15Nolan ArenadoSTL14360618677537.2%15.0%.153.271.253.310.406.311100-1.4-1.24.32.4
    16Eugenio SuárezARI14359824718229.0%28.6%.185.295.235.313.420.319103-1.70.32.02.3
    17Joey OrtizMIL136539126259118.5%20.3%.145.295.248.317.393.310980.0-1.22.72.0
    18Luis RengifoLAA123507136153206.4%16.4%.140.290.260.314.400.3121010.71.50.92.0
    19Jake BurgerTEX13957931718116.2%26.7%.227.284.245.303.472.331117-1.010.2-11.21.9
    20Josh JungTEX12049519586155.4%27.7%.178.309.248.294.425.310102-1.3-0.11.51.9
    21Matt ShawCHC114467145653178.1%21.4%.154.289.247.315.401.3131020.11.21.21.9
    22Maikel GarciaKCR12953076448277.2%18.0%.107.303.256.310.363.295902.1-4.24.31.8
    23Ryan McMahonCOL144612207168510.5%28.9%.164.315.240.322.404.31790-0.8-8.15.11.8
    24Ke'Bryan HayesPIT124513105649146.5%19.4%.124.296.251.303.375.296870.3-7.96.21.6
    25Josh SmithTEX993889453978.7%20.8%.137.287.240.326.377.311103-0.70.40.41.4
    26Connor NorbyMIA12148715605387.8%28.1%.161.313.242.305.402.30894-0.3-3.60.41.3
    27Dylan MooreSEA93339941332211.0%29.1%.158.272.205.313.363.3011021.32.1-0.61.3
    28Matt VierlingDET10945011564477.7%21.0%.147.302.253.315.400.312104-0.12.1-4.51.3
    29Ramón UríasBAL792969353417.5%21.5%.152.294.249.316.402.314108-0.42.20.51.3
    30Christopher MorelTBR12149522606389.1%27.5%.201.275.228.305.429.317105-0.12.8-7.31.2
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1José RamírezCLE151656299496309.5%11.8%.222.271.274.344.496.3551352.728.73.15.5
    2Austin RileyATL15165232929228.2%24.3%.225.312.268.336.493.355127-1.020.4-0.64.3
    3Matt ChapmanSFG147619258176910.3%25.7%.203.290.241.326.444.3331160.512.15.03.9
    4Manny MachadoSDP14762629799487.9%19.3%.203.286.264.322.467.337119-1.112.60.83.5
    5Jordan WestburgBAL134561217072106.9%22.5%.192.311.264.323.456.336123-0.314.11.43.5
    6Alex BregmanBOS14663323828239.8%12.8%.182.266.260.339.441.339116-2.29.63.13.5
    7Jazz Chisholm Jr.NYY141598268276388.4%25.5%.201.294.247.315.448.3281122.711.41.33.4
    8Isaac ParedesHOU141593227176111.0%16.6%.182.252.238.338.420.332119-1.811.21.63.4
    9Rafael DeversBOS140606298490310.4%21.7%.232.303.269.350.502.361132-1.120.8-13.92.8
    10Max MuncyLAD123513247073214.4%26.4%.217.247.214.335.431.334116-0.98.8-1.22.5
    11Mark VientosNYM14460229718517.5%29.4%.207.300.242.303.449.324109-1.94.6-0.12.5
    12Junior CamineroTBR13055122647546.4%20.9%.179.300.263.315.442.326111-1.06.00.22.5
    13Royce LewisMIN10242620556148.2%23.1%.210.285.252.315.462.334119-0.48.90.52.4
    14Alec BohmPHI14159916697946.7%15.3%.149.301.274.326.423.325108-1.63.8-0.32.4
    15Nolan ArenadoSTL14360618677537.2%15.0%.153.271.253.310.406.311100-1.4-1.24.32.4
    16Eugenio SuárezARI14359824718229.0%28.6%.185.295.235.313.420.319103-1.70.32.02.3
    17Joey OrtizMIL136539126259118.5%20.3%.145.295.248.317.393.310980.0-1.22.72.0
    18Luis RengifoLAA123507136153206.4%16.4%.140.290.260.314.400.3121010.71.50.92.0
    19Jake BurgerTEX13957931718116.2%26.7%.227.284.245.303.472.331117-1.010.2-11.21.9
    20Josh JungTEX12049519586155.4%27.7%.178.309.248.294.425.310102-1.3-0.11.51.9
    21Matt ShawCHC114467145653178.1%21.4%.154.289.247.315.401.3131020.11.21.21.9
    22Maikel GarciaKCR12953076448277.2%18.0%.107.303.256.310.363.295902.1-4.24.31.8
    23Ryan McMahonCOL144612207168510.5%28.9%.164.315.240.322.404.31790-0.8-8.15.11.8
    24Ke'Bryan HayesPIT124513105649146.5%19.4%.124.296.251.303.375.296870.3-7.96.21.6
    25Josh SmithTEX993889453978.7%20.8%.137.287.240.326.377.311103-0.70.40.41.4
    26Connor NorbyMIA12148715605387.8%28.1%.161.313.242.305.402.30894-0.3-3.60.41.3
    27Dylan MooreSEA93339941332211.0%29.1%.158.272.205.313.363.3011021.32.1-0.61.3
    28Matt VierlingDET10945011564477.7%21.0%.147.302.253.315.400.312104-0.12.1-4.51.3
    29Ramón UríasBAL792969353417.5%21.5%.152.294.249.316.402.314108-0.42.20.51.3
    30Christopher MorelTBR12149522606389.1%27.5%.201.275.228.305.429.317105-0.12.8-7.31.2
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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.