2026 Projections






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  • General Projections
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  • Overall - No Split
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  • Steamer (RoS):
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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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  • 3-Year
    Historical Projections
    Members Exclusive Data
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  • Splits - Steamer Projections
    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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  • Steamer RoS
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  • Overall - No Split
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  • Data Export [Members Only]
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Julio RodríguezSEA152660309591287.2%22.1%.206.311.271.332.478.3461301.824.96.85.6
    2Jackson MerrillSDP14360622778286.6%19.6%.190.304.269.320.459.3331140.510.36.33.8
    3Wyatt LangfordTEX1436132484742311.7%23.4%.198.296.251.343.449.3431221.317.2-2.83.6
    4Pete Crow-ArmstrongCHC147619238478335.6%24.2%.191.291.246.297.437.3141003.03.311.33.6
    5Byron BuxtonMIN122525277873157.8%27.2%.243.295.249.318.492.3441212.114.9-2.23.1
    6Andy PagesLAD140574227376106.1%22.1%.189.294.256.310.444.3251080.05.22.92.8
    7Jackson ChourioMIL145629238784246.2%20.3%.191.306.269.317.460.3321142.012.4-7.12.7
    8Michael Harris IIATL139574206971184.4%19.4%.172.299.265.301.438.3171021.32.74.02.6
    9Oneil CruzPIT1285382271652810.3%29.9%.197.307.237.319.433.3241062.76.50.12.5
    10Mike TroutLAA118502246664313.6%29.8%.219.297.234.346.453.344120-1.011.0-5.82.3
    11Trent GrishamNYY124519237062512.8%25.0%.202.253.220.326.421.327109-0.55.3-0.82.3
    12Jakob MarseeMIA1315641270553311.0%21.9%.138.291.237.330.375.313992.41.41.12.2
    13Ceddanne RafaelaBOS140559167064204.6%21.6%.160.296.251.293.411.304901.2-5.67.32.1
    14Colton CowserBAL128513216462139.5%31.5%.189.300.227.310.417.3161040.62.8-0.32.1
    15Daulton VarshoHOU13354626717487.8%26.0%.218.254.223.288.441.3121000.00.11.22.1
    16Lawrence ButlerATH134553217164188.5%26.1%.183.294.240.306.423.3161021.32.5-1.32.0
    17Luis Robert Jr.NYM127523206662297.5%28.1%.170.293.234.297.404.303931.0-3.34.71.9
    18Evan CarterTEX109434115445189.7%22.6%.151.287.236.321.386.3111001.01.01.01.7
    19TJ FriedlCIN1335761369551210.0%16.8%.133.272.241.333.374.314960.3-2.40.21.7
    20Brenton DoyleCHW137561186864216.3%26.6%.164.310.247.297.411.306821.4-10.98.51.7
    21Jake MeyersHOU11645695343137.8%20.7%.123.296.246.312.368.300920.5-3.83.81.6
    22Brandon MarshPHI121475135852119.7%28.1%.156.340.256.330.412.3231050.33.4-3.91.6
    23Jung Hoo LeeSFG1365678665497.6%11.2%.126.289.266.327.392.3151010.41.0-7.21.3
    24Harrison BaderSFG122482135750136.5%23.7%.141.297.243.303.384.301910.1-4.91.41.3
    25Jo AdellCLE14056830688296.8%27.4%.222.271.233.296.456.322105-0.53.1-10.21.3
    26Justin CrawfordPHI11445665741247.1%20.8%.100.331.266.321.367.303911.6-3.0-0.81.2
    27Cedric MullinsTBR111451145349199.0%22.6%.159.263.224.299.383.299900.9-4.50.01.1
    28Dylan CrewsWSN107440125246207.0%22.2%.151.280.236.300.387.301911.0-3.5-0.51.1
    29Denzel ClarkeATH9938284534147.2%32.9%.138.326.225.292.363.288830.8-7.04.11.0
    30Parker MeadowsDET105417104939119.0%25.4%.147.284.225.298.372.294870.9-5.70.91.0
    #NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
    1Julio RodríguezSEA152660309591287.2%22.1%.206.311.271.332.478.3461301.824.96.85.6
    2Jackson MerrillSDP14360622778286.6%19.6%.190.304.269.320.459.3331140.510.36.33.8
    3Wyatt LangfordTEX1436132484742311.7%23.4%.198.296.251.343.449.3431221.317.2-2.83.6
    4Pete Crow-ArmstrongCHC147619238478335.6%24.2%.191.291.246.297.437.3141003.03.311.33.6
    5Byron BuxtonMIN122525277873157.8%27.2%.243.295.249.318.492.3441212.114.9-2.23.1
    6Andy PagesLAD140574227376106.1%22.1%.189.294.256.310.444.3251080.05.22.92.8
    7Jackson ChourioMIL145629238784246.2%20.3%.191.306.269.317.460.3321142.012.4-7.12.7
    8Michael Harris IIATL139574206971184.4%19.4%.172.299.265.301.438.3171021.32.74.02.6
    9Oneil CruzPIT1285382271652810.3%29.9%.197.307.237.319.433.3241062.76.50.12.5
    10Mike TroutLAA118502246664313.6%29.8%.219.297.234.346.453.344120-1.011.0-5.82.3
    11Trent GrishamNYY124519237062512.8%25.0%.202.253.220.326.421.327109-0.55.3-0.82.3
    12Jakob MarseeMIA1315641270553311.0%21.9%.138.291.237.330.375.313992.41.41.12.2
    13Ceddanne RafaelaBOS140559167064204.6%21.6%.160.296.251.293.411.304901.2-5.67.32.1
    14Colton CowserBAL128513216462139.5%31.5%.189.300.227.310.417.3161040.62.8-0.32.1
    15Daulton VarshoHOU13354626717487.8%26.0%.218.254.223.288.441.3121000.00.11.22.1
    16Lawrence ButlerATH134553217164188.5%26.1%.183.294.240.306.423.3161021.32.5-1.32.0
    17Luis Robert Jr.NYM127523206662297.5%28.1%.170.293.234.297.404.303931.0-3.34.71.9
    18Evan CarterTEX109434115445189.7%22.6%.151.287.236.321.386.3111001.01.01.01.7
    19TJ FriedlCIN1335761369551210.0%16.8%.133.272.241.333.374.314960.3-2.40.21.7
    20Brenton DoyleCHW137561186864216.3%26.6%.164.310.247.297.411.306821.4-10.98.51.7
    21Jake MeyersHOU11645695343137.8%20.7%.123.296.246.312.368.300920.5-3.83.81.6
    22Brandon MarshPHI121475135852119.7%28.1%.156.340.256.330.412.3231050.33.4-3.91.6
    23Jung Hoo LeeSFG1365678665497.6%11.2%.126.289.266.327.392.3151010.41.0-7.21.3
    24Harrison BaderSFG122482135750136.5%23.7%.141.297.243.303.384.301910.1-4.91.41.3
    25Jo AdellCLE14056830688296.8%27.4%.222.271.233.296.456.322105-0.53.1-10.21.3
    26Justin CrawfordPHI11445665741247.1%20.8%.100.331.266.321.367.303911.6-3.0-0.81.2
    27Cedric MullinsTBR111451145349199.0%22.6%.159.263.224.299.383.299900.9-4.50.01.1
    28Dylan CrewsWSN107440125246207.0%22.2%.151.280.236.300.387.301911.0-3.5-0.51.1
    29Denzel ClarkeATH9938284534147.2%32.9%.138.326.225.292.363.288830.8-7.04.11.0
    30Parker MeadowsDET105417104939119.0%25.4%.147.284.225.298.372.294870.9-5.70.91.0
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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, and OOPSYPeak use neutral playing time. 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.