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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  • Steamer:
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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
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  • Overall - No Split
  • vs LHP
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  • Data Export [Members Only]
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Ketel MarteARI140608288888710.7%17.9%.226.297.276.358.502.367135-0.724.70.04.6
    2Marcus SemienTEX146643209072108.9%15.4%.166.266.248.318.414.3191080.46.46.93.6
    3Jordan WestburgBAL134561217072106.9%22.5%.192.311.264.323.456.336123-0.314.11.43.5
    4Andrés GiménezTOR142596116960265.5%16.8%.123.294.257.317.379.3051001.91.89.33.2
    5Xander BogaertsSDP142596157064137.6%17.4%.138.300.265.325.403.3181060.54.35.33.0
    6Ozzie AlbiesATL141610217979126.7%15.7%.180.280.262.317.442.3271080.97.10.82.9
    7Jose AltuveHOU140618198464178.2%17.1%.155.300.268.335.423.331118-0.212.6-6.42.8
    8Matt McLainCIN124534197266179.1%27.2%.191.326.256.332.447.3381110.16.82.02.7
    9Gleyber TorresDET14562216746579.5%18.2%.141.292.256.329.397.318109-1.25.1-0.12.7
    10Nico HoernerCHC12352066547256.7%11.2%.097.299.273.333.371.3101002.32.45.82.6
    11Brandon LoweTBR11447622626759.4%25.7%.215.280.239.318.454.3331160.29.00.32.6
    12Bryson StottPHI139565126757268.1%17.0%.126.292.256.319.382.307962.3-0.74.92.4
    13Luis García Jr.WSN135553166467175.4%15.8%.156.300.274.313.430.319105-0.52.81.82.4
    14Brendan DonovanSTL13155312655958.6%13.4%.131.300.274.349.405.331115-1.08.5-4.12.4
    15Jackson HollidayBAL118462116247811.5%26.9%.146.307.234.326.380.311106-0.22.72.42.1
    16Tommy EdmanLAD129526136855236.9%17.9%.143.282.249.306.392.304962.1-0.43.32.1
    17Jonathan IndiaKCR1355791475571210.8%19.4%.144.294.250.349.394.3291130.09.0-8.42.1
    18Luis RengifoLAA123507136153206.4%16.4%.140.290.260.314.400.3121010.71.50.92.0
    19Jake CronenworthSDP13857914676559.1%18.5%.151.275.240.321.391.313102-0.21.0-1.02.0
    20Kristian CampbellBOS101417115247129.3%22.1%.151.322.263.341.414.331111-0.24.9-0.61.9
    21Nick GonzalesPIT1094539525056.7%22.4%.147.322.261.320.409.317100-0.3-0.23.21.9
    22Brice TurangMIL13956486450378.3%18.2%.102.294.247.311.349.292863.5-6.15.41.9
    23Tyler FitzgeraldSFG132527166656196.7%30.7%.161.313.232.293.393.299931.6-3.01.41.6
    24Otto LopezMIA11345565041186.2%17.5%.112.318.270.320.382.307940.6-2.73.41.6
    25Jorge PolancoSEA114469164953410.0%26.9%.156.277.222.304.379.300101-0.60.0-0.51.6
    26Colt KeithDET13252516616257.7%20.4%.161.303.260.320.421.321111-0.75.7-8.41.5
    27Michael MasseyKCR11545915525645.2%18.9%.169.278.249.295.418.30798-0.1-1.30.71.5
    28Spencer HorwitzPIT9740094643211.2%18.9%.146.309.262.353.409.335112-1.44.6-5.61.3
    29Jeff McNeilNYM1014097464046.7%13.0%.121.280.257.320.378.30798-1.0-2.10.31.2
    30Zack GelofATH93385134640157.6%31.6%.166.302.225.288.390.296901.4-3.11.51.2
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Ketel MarteARI140608288888710.7%17.9%.226.297.276.358.502.367135-0.724.70.04.6
    2Marcus SemienTEX146643209072108.9%15.4%.166.266.248.318.414.3191080.46.46.93.6
    3Jordan WestburgBAL134561217072106.9%22.5%.192.311.264.323.456.336123-0.314.11.43.5
    4Andrés GiménezTOR142596116960265.5%16.8%.123.294.257.317.379.3051001.91.89.33.2
    5Xander BogaertsSDP142596157064137.6%17.4%.138.300.265.325.403.3181060.54.35.33.0
    6Ozzie AlbiesATL141610217979126.7%15.7%.180.280.262.317.442.3271080.97.10.82.9
    7Jose AltuveHOU140618198464178.2%17.1%.155.300.268.335.423.331118-0.212.6-6.42.8
    8Matt McLainCIN124534197266179.1%27.2%.191.326.256.332.447.3381110.16.82.02.7
    9Gleyber TorresDET14562216746579.5%18.2%.141.292.256.329.397.318109-1.25.1-0.12.7
    10Nico HoernerCHC12352066547256.7%11.2%.097.299.273.333.371.3101002.32.45.82.6
    11Brandon LoweTBR11447622626759.4%25.7%.215.280.239.318.454.3331160.29.00.32.6
    12Bryson StottPHI139565126757268.1%17.0%.126.292.256.319.382.307962.3-0.74.92.4
    13Luis García Jr.WSN135553166467175.4%15.8%.156.300.274.313.430.319105-0.52.81.82.4
    14Brendan DonovanSTL13155312655958.6%13.4%.131.300.274.349.405.331115-1.08.5-4.12.4
    15Jackson HollidayBAL118462116247811.5%26.9%.146.307.234.326.380.311106-0.22.72.42.1
    16Tommy EdmanLAD129526136855236.9%17.9%.143.282.249.306.392.304962.1-0.43.32.1
    17Jonathan IndiaKCR1355791475571210.8%19.4%.144.294.250.349.394.3291130.09.0-8.42.1
    18Luis RengifoLAA123507136153206.4%16.4%.140.290.260.314.400.3121010.71.50.92.0
    19Jake CronenworthSDP13857914676559.1%18.5%.151.275.240.321.391.313102-0.21.0-1.02.0
    20Kristian CampbellBOS101417115247129.3%22.1%.151.322.263.341.414.331111-0.24.9-0.61.9
    21Nick GonzalesPIT1094539525056.7%22.4%.147.322.261.320.409.317100-0.3-0.23.21.9
    22Brice TurangMIL13956486450378.3%18.2%.102.294.247.311.349.292863.5-6.15.41.9
    23Tyler FitzgeraldSFG132527166656196.7%30.7%.161.313.232.293.393.299931.6-3.01.41.6
    24Otto LopezMIA11345565041186.2%17.5%.112.318.270.320.382.307940.6-2.73.41.6
    25Jorge PolancoSEA114469164953410.0%26.9%.156.277.222.304.379.300101-0.60.0-0.51.6
    26Colt KeithDET13252516616257.7%20.4%.161.303.260.320.421.321111-0.75.7-8.41.5
    27Michael MasseyKCR11545915525645.2%18.9%.169.278.249.295.418.30798-0.1-1.30.71.5
    28Spencer HorwitzPIT9740094643211.2%18.9%.146.309.262.353.409.335112-1.44.6-5.61.3
    29Jeff McNeilNYM1014097464046.7%13.0%.121.280.257.320.378.30798-1.0-2.10.31.2
    30Zack GelofATH93385134640157.6%31.6%.166.302.225.288.390.296901.4-3.11.51.2
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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.