2024 Projections

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#NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
1Trea TurnerPHI152665239782296.8%19.9%.180.322.279.332.460.3401123.213.34.64.0
2Bryce HarperPHI1466312994911314.1%21.4%.233.325.282.388.515.383141-1.830.4-11.64.0
3J.T. RealmutoPHI133530206970157.1%24.2%.189.306.256.319.444.3271040.63.212.83.4
4Bryson StottPHI141584137161227.1%17.3%.134.302.264.320.398.312941.1-3.45.92.2
5Kyle SchwarberPHI147644409495315.2%29.3%.264.252.220.345.484.355123-1.916.1-16.22.2
6Brandon MarshPHI1264921358541210.3%30.7%.163.356.254.336.417.3271040.42.8-0.61.9
7Alec BohmPHI14159416707646.8%17.2%.145.306.272.325.417.321100-1.6-1.6-2.61.6
8Johan RojasPHI9735454334225.0%22.5%.116.324.257.302.373.294821.0-6.95.41.1
9Nick CastellanosPHI14361324748585.9%25.4%.188.315.260.308.447.323101-1.5-0.8-14.00.6
10Edmundo SosaPHI602125252343.8%23.8%.145.303.246.295.390.297840.0-4.22.30.5
11Whit MerrifieldPHI10041775043176.1%16.7%.116.297.260.307.377.297840.7-7.6-3.00.4
12Jordan LuplowPHI2172399110.9%25.6%.209.252.217.310.426.31997-0.1-0.30.20.2
13Garrett StubbsPHI331142131129.4%23.8%.113.278.218.299.331.28173-0.1-3.92.20.2
14Rafael MarchánPHI114104407.6%14.5%.081.275.239.311.320.28475-0.1-1.41.70.2
15Rodolfo CastroPHI26933101117.8%28.9%.167.278.219.286.387.29281-0.2-2.50.70.1
16Darick HallPHI114325507.4%27.1%.202.266.224.286.425.30589-0.1-0.7-0.90.0
17Símon MuzziottiPHI82503216.4%19.6%.103.298.244.302.346.286760.1-0.7-0.30.0
18Kody ClemensPHI176127807.8%26.3%.163.266.219.281.382.28877-0.1-1.8-0.60.0
19Weston WilsonPHI92413218.8%30.5%.149.267.203.278.352.277700.1-0.8-0.30.0
20Cristian PachePHI541744191637.9%27.3%.126.288.218.284.344.27770-0.3-6.8-1.2-0.2
21Cam GallagherPHI339017705.0%28.0%.075.252.185.232.260.22032-0.1-7.71.6-0.3
#NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
1Trea TurnerPHI152665239782296.8%19.9%.180.322.279.332.460.3401123.213.34.64.0
2Bryce HarperPHI1466312994911314.1%21.4%.233.325.282.388.515.383141-1.830.4-11.64.0
3J.T. RealmutoPHI133530206970157.1%24.2%.189.306.256.319.444.3271040.63.212.83.4
4Bryson StottPHI141584137161227.1%17.3%.134.302.264.320.398.312941.1-3.45.92.2
5Kyle SchwarberPHI147644409495315.2%29.3%.264.252.220.345.484.355123-1.916.1-16.22.2
6Brandon MarshPHI1264921358541210.3%30.7%.163.356.254.336.417.3271040.42.8-0.61.9
7Alec BohmPHI14159416707646.8%17.2%.145.306.272.325.417.321100-1.6-1.6-2.61.6
8Johan RojasPHI9735454334225.0%22.5%.116.324.257.302.373.294821.0-6.95.41.1
9Nick CastellanosPHI14361324748585.9%25.4%.188.315.260.308.447.323101-1.5-0.8-14.00.6
10Edmundo SosaPHI602125252343.8%23.8%.145.303.246.295.390.297840.0-4.22.30.5
11Whit MerrifieldPHI10041775043176.1%16.7%.116.297.260.307.377.297840.7-7.6-3.00.4
12Jordan LuplowPHI2172399110.9%25.6%.209.252.217.310.426.31997-0.1-0.30.20.2
13Garrett StubbsPHI331142131129.4%23.8%.113.278.218.299.331.28173-0.1-3.92.20.2
14Rafael MarchánPHI114104407.6%14.5%.081.275.239.311.320.28475-0.1-1.41.70.2
15Rodolfo CastroPHI26933101117.8%28.9%.167.278.219.286.387.29281-0.2-2.50.70.1
16Darick HallPHI114325507.4%27.1%.202.266.224.286.425.30589-0.1-0.7-0.90.0
17Símon MuzziottiPHI82503216.4%19.6%.103.298.244.302.346.286760.1-0.7-0.30.0
18Kody ClemensPHI176127807.8%26.3%.163.266.219.281.382.28877-0.1-1.8-0.60.0
19Weston WilsonPHI92413218.8%30.5%.149.267.203.278.352.277700.1-0.8-0.30.0
20Cristian PachePHI541744191637.9%27.3%.126.288.218.284.344.27770-0.3-6.8-1.2-0.2
21Cam GallagherPHI339017705.0%28.0%.075.252.185.232.260.22032-0.1-7.71.6-0.3
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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

  • 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.