2024 Projections

Data Export [Members Only]
#NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
1Tarik SkubalDET10902828155.110.322.390.99.29872.9%3.443.283.8
2Kenta MaedaDET7802925132.09.322.581.25.30069.4%4.233.972.1
3Reese OlsonDET7802424131.18.653.331.19.28969.8%4.304.261.7
4Jack FlahertyDET8902626137.08.873.751.12.30769.7%4.494.361.5
5Casey MizeDET6702121114.06.982.671.24.28668.2%4.484.551.1
6Matt ManningDET570201998.16.642.921.29.27867.9%4.584.750.9
7Sawyer Gipson-LongDET44032968.18.922.631.22.30069.3%4.254.020.8
8Jason FoleyDET22761061.17.362.560.79.31172.4%3.733.750.5
9Andrew ChafinDET33356054.29.883.800.93.30271.5%3.943.780.5
10Will VestDET33256159.29.463.141.09.30774.0%3.813.890.4
11Tyler HoltonDET32050055.08.102.471.00.28473.0%3.593.850.4
12Alex FaedoDET23036455.18.662.871.40.28870.1%4.384.420.4
13Shelby MillerDET32350151.29.404.171.13.28272.5%4.054.320.2
14Beau BrieskeDET23041149.07.862.871.23.28670.7%4.194.340.2
15Matthew BoydDET1102212.28.783.071.44.29570.9%4.464.550.1
16Ty MaddenDET12016327.28.333.481.27.29569.9%4.514.540.1
17Joey WentzDET35042566.28.533.781.43.30069.6%4.844.770.1
18Alex LangeDET442160063.010.545.100.97.29273.6%3.964.220.1
19Brendan WhiteDET12020022.18.652.990.91.31068.0%4.263.880.1
20Keider MonteroDET11017119.28.383.011.12.30169.4%4.314.180.1
21Ty AdcockDET11019019.28.552.451.29.29371.6%4.074.120.1
22Wilmer FloresDET11010011.18.142.880.96.30369.4%4.143.980.1
23Andrew VasquezDET11017017.28.354.150.86.29970.2%4.224.380.0
24Easton LucasDET00011012.18.853.841.13.30268.2%4.644.270.0
25Trey WingenterDET11031032.09.564.191.07.30269.5%4.454.330.0
26Devin SweetDET00011011.27.993.181.37.29469.4%4.624.740.0
27Mason EnglertDET22022028.17.322.871.43.31168.7%4.944.80-0.1
28Garrett HillDET11016019.08.244.801.20.30370.5%4.834.97-0.1
#NameTeamWLSVGGSIPK/9BB/9HR/9BABIPLOB%GB%ERAFIPWAR
1Tarik SkubalDET10902828155.110.322.390.99.29872.9%3.443.283.8
2Kenta MaedaDET7802925132.09.322.581.25.30069.4%4.233.972.1
3Reese OlsonDET7802424131.18.653.331.19.28969.8%4.304.261.7
4Jack FlahertyDET8902626137.08.873.751.12.30769.7%4.494.361.5
5Casey MizeDET6702121114.06.982.671.24.28668.2%4.484.551.1
6Matt ManningDET570201998.16.642.921.29.27867.9%4.584.750.9
7Sawyer Gipson-LongDET44032968.18.922.631.22.30069.3%4.254.020.8
8Jason FoleyDET22761061.17.362.560.79.31172.4%3.733.750.5
9Andrew ChafinDET33356054.29.883.800.93.30271.5%3.943.780.5
10Will VestDET33256159.29.463.141.09.30774.0%3.813.890.4
11Tyler HoltonDET32050055.08.102.471.00.28473.0%3.593.850.4
12Alex FaedoDET23036455.18.662.871.40.28870.1%4.384.420.4
13Shelby MillerDET32350151.29.404.171.13.28272.5%4.054.320.2
14Beau BrieskeDET23041149.07.862.871.23.28670.7%4.194.340.2
15Matthew BoydDET1102212.28.783.071.44.29570.9%4.464.550.1
16Ty MaddenDET12016327.28.333.481.27.29569.9%4.514.540.1
17Joey WentzDET35042566.28.533.781.43.30069.6%4.844.770.1
18Alex LangeDET442160063.010.545.100.97.29273.6%3.964.220.1
19Brendan WhiteDET12020022.18.652.990.91.31068.0%4.263.880.1
20Keider MonteroDET11017119.28.383.011.12.30169.4%4.314.180.1
21Ty AdcockDET11019019.28.552.451.29.29371.6%4.074.120.1
22Wilmer FloresDET11010011.18.142.880.96.30369.4%4.143.980.1
23Andrew VasquezDET11017017.28.354.150.86.29970.2%4.224.380.0
24Easton LucasDET00011012.18.853.841.13.30268.2%4.644.270.0
25Trey WingenterDET11031032.09.564.191.07.30269.5%4.454.330.0
26Devin SweetDET00011011.27.993.181.37.29469.4%4.624.740.0
27Mason EnglertDET22022028.17.322.871.43.31168.7%4.944.80-0.1
28Garrett HillDET11016019.08.244.801.20.30370.5%4.834.97-0.1
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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.