2024 Projections

Data Export [Members Only]
#NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
1Shane BieberCLE10802626164.28.542.341.10.29572.1%3.783.812.9
2Tanner BibeeCLE10802828163.29.202.731.16.29273.3%3.763.912.8
3Alex CobbCLE7702323128.08.052.540.88.31071.6%3.843.692.5
4Triston McKenzieCLE8902525141.09.013.001.42.27471.9%4.134.391.9
5Gavin WilliamsCLE7702424125.09.243.521.09.28471.6%3.964.091.7
6Logan AllenCLE8802525135.08.553.271.26.29072.5%4.144.351.6
7Emmanuel ClaseCLE443466067.18.812.100.65.29974.3%3.013.031.0
8Sam HentgesCLE32050054.19.653.490.85.31273.6%3.673.590.5
9Carlos CarrascoCLE450281272.07.563.091.37.30568.4%4.874.730.4
10Tim HerrinCLE32043046.29.473.940.89.30571.9%3.963.890.3
11Joey CantilloCLE2206633.18.694.261.25.28471.7%4.394.690.3
12James KarinchakCLE22145043.111.945.131.15.28174.7%3.854.130.2
13Eli MorganCLE33054159.19.362.781.38.29772.2%4.154.210.2
14Cade SmithCLE22038040.210.063.891.08.30272.1%4.074.060.2
15Pedro AvilaCLE23030452.28.444.011.12.29872.4%4.264.570.2
16Matthew BoydCLE1102212.28.783.071.44.29570.9%4.464.550.1
17Will DionCLE1208111.18.703.161.13.29074.7%3.754.120.1
18Nic EnrightCLE11010010.09.272.621.26.29472.6%3.934.000.1
19Peter StrzeleckiCLE11019019.28.823.461.10.30069.4%4.354.290.0
20Anthony GoseCLE11012012.111.174.951.15.29075.7%3.854.250.0
21Zak KentCLE000607.18.292.971.27.29770.9%4.314.350.0
22Ben LivelyCLE23030241.08.022.851.43.30070.0%4.614.650.0
23Jack LeftwichCLE000505.07.652.791.27.29970.4%4.404.400.0
24Erik SabrowskiCLE110909.19.074.971.17.29572.0%4.504.680.0
25Tanner BurnsCLE11014015.18.354.191.24.30070.5%4.664.750.0
26Nick SandlinCLE43058059.09.534.011.48.26476.1%3.964.78-0.1
27Tyler BeedeCLE23021336.06.744.521.23.30568.4%5.225.35-0.2
28Hunter GaddisCLE23024235.17.013.291.71.28267.7%5.205.44-0.2
#NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
1Shane BieberCLE10802626164.28.542.341.10.29572.1%3.783.812.9
2Tanner BibeeCLE10802828163.29.202.731.16.29273.3%3.763.912.8
3Alex CobbCLE7702323128.08.052.540.88.31071.6%3.843.692.5
4Triston McKenzieCLE8902525141.09.013.001.42.27471.9%4.134.391.9
5Gavin WilliamsCLE7702424125.09.243.521.09.28471.6%3.964.091.7
6Logan AllenCLE8802525135.08.553.271.26.29072.5%4.144.351.6
7Emmanuel ClaseCLE443466067.18.812.100.65.29974.3%3.013.031.0
8Sam HentgesCLE32050054.19.653.490.85.31273.6%3.673.590.5
9Carlos CarrascoCLE450281272.07.563.091.37.30568.4%4.874.730.4
10Tim HerrinCLE32043046.29.473.940.89.30571.9%3.963.890.3
11Joey CantilloCLE2206633.18.694.261.25.28471.7%4.394.690.3
12James KarinchakCLE22145043.111.945.131.15.28174.7%3.854.130.2
13Eli MorganCLE33054159.19.362.781.38.29772.2%4.154.210.2
14Cade SmithCLE22038040.210.063.891.08.30272.1%4.074.060.2
15Pedro AvilaCLE23030452.28.444.011.12.29872.4%4.264.570.2
16Matthew BoydCLE1102212.28.783.071.44.29570.9%4.464.550.1
17Will DionCLE1208111.18.703.161.13.29074.7%3.754.120.1
18Nic EnrightCLE11010010.09.272.621.26.29472.6%3.934.000.1
19Peter StrzeleckiCLE11019019.28.823.461.10.30069.4%4.354.290.0
20Anthony GoseCLE11012012.111.174.951.15.29075.7%3.854.250.0
21Zak KentCLE000607.18.292.971.27.29770.9%4.314.350.0
22Ben LivelyCLE23030241.08.022.851.43.30070.0%4.614.650.0
23Jack LeftwichCLE000505.07.652.791.27.29970.4%4.404.400.0
24Erik SabrowskiCLE110909.19.074.971.17.29572.0%4.504.680.0
25Tanner BurnsCLE11014015.18.354.191.24.30070.5%4.664.750.0
26Nick SandlinCLE43058059.09.534.011.48.26476.1%3.964.78-0.1
27Tyler BeedeCLE23021336.06.744.521.23.30568.4%5.225.35-0.2
28Hunter GaddisCLE23024235.17.013.291.71.28267.7%5.205.44-0.2
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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

  • 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.