2024 Projections

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#NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
1Riley GreeneDET136588177764108.7%26.4%.165.357.275.342.440.338115-0.210.5-4.42.6
2Spencer TorkelsonDET148629297984310.3%24.0%.216.277.242.326.457.337114-0.99.7-14.11.7
3Colt KeithDET11647814545738.1%22.6%.164.307.255.320.419.319102-0.80.3-1.81.5
4Jake RogersDET9535116414428.0%32.1%.200.277.216.285.416.30190-0.5-4.97.11.4
5Parker MeadowsDET124520136250168.5%24.4%.151.284.230.300.380.296860.4-8.33.51.3
6Mark CanhaDET125507125855710.2%17.3%.141.292.255.351.395.330110-1.14.8-9.71.2
7Kerry CarpenterDET12853423667257.1%24.6%.199.305.257.319.456.331110-1.35.2-12.11.1
8Gio UrshelaDET793177333525.9%17.8%.129.316.274.319.404.31398-1.1-2.01.31.0
9Javier BáezDET130534146060114.7%24.8%.141.296.239.284.380.288800.2-12.53.00.9
10Matt VierlingDET953788443567.8%20.6%.131.309.256.320.387.30995-0.4-2.8-1.70.8
11Carson KellyDET732626262619.1%22.4%.125.267.221.298.347.28578-0.5-7.35.60.7
12Andy IbáñezDET722757303026.9%17.5%.147.287.254.310.401.30995-0.6-2.2-0.30.7
13Zach McKinstryDET8834674031108.5%22.4%.140.289.235.307.376.29988-0.1-5.1-0.40.6
14Akil BaddooDET6524263023910.7%25.1%.150.294.232.315.382.305920.5-1.7-1.90.5
15Dillon DinglerDET62312207.0%31.2%.144.287.212.287.355.283770.0-0.71.10.1
16Jace JungDET93714409.7%27.6%.145.287.223.302.368.29485-0.1-0.70.60.1
17Ryan KreidlerDET113514318.8%30.0%.149.279.212.285.360.283770.0-1.00.80.1
18Keston HiuraDET176137817.7%35.0%.192.327.232.310.424.317100-0.1-0.1-1.90.0
19TJ HopkinsDET163313307.6%30.4%.129.312.226.293.356.285780.0-0.9-0.40.0
20Justyn-Henry MalloyDET1143154012.3%27.1%.142.310.235.337.378.318101-0.10.0-2.3-0.1
21Bligh MadrisDET164314319.1%25.8%.104.258.197.273.301.257590.0-2.1-0.8-0.1
#NameTeamGPAHRRRBISBBB%K%ISOBABIPAVGOBPSLGwOBAwRC+BsROffDefWAR
1Riley GreeneDET136588177764108.7%26.4%.165.357.275.342.440.338115-0.210.5-4.42.6
2Spencer TorkelsonDET148629297984310.3%24.0%.216.277.242.326.457.337114-0.99.7-14.11.7
3Colt KeithDET11647814545738.1%22.6%.164.307.255.320.419.319102-0.80.3-1.81.5
4Jake RogersDET9535116414428.0%32.1%.200.277.216.285.416.30190-0.5-4.97.11.4
5Parker MeadowsDET124520136250168.5%24.4%.151.284.230.300.380.296860.4-8.33.51.3
6Mark CanhaDET125507125855710.2%17.3%.141.292.255.351.395.330110-1.14.8-9.71.2
7Kerry CarpenterDET12853423667257.1%24.6%.199.305.257.319.456.331110-1.35.2-12.11.1
8Gio UrshelaDET793177333525.9%17.8%.129.316.274.319.404.31398-1.1-2.01.31.0
9Javier BáezDET130534146060114.7%24.8%.141.296.239.284.380.288800.2-12.53.00.9
10Matt VierlingDET953788443567.8%20.6%.131.309.256.320.387.30995-0.4-2.8-1.70.8
11Carson KellyDET732626262619.1%22.4%.125.267.221.298.347.28578-0.5-7.35.60.7
12Andy IbáñezDET722757303026.9%17.5%.147.287.254.310.401.30995-0.6-2.2-0.30.7
13Zach McKinstryDET8834674031108.5%22.4%.140.289.235.307.376.29988-0.1-5.1-0.40.6
14Akil BaddooDET6524263023910.7%25.1%.150.294.232.315.382.305920.5-1.7-1.90.5
15Dillon DinglerDET62312207.0%31.2%.144.287.212.287.355.283770.0-0.71.10.1
16Jace JungDET93714409.7%27.6%.145.287.223.302.368.29485-0.1-0.70.60.1
17Ryan KreidlerDET113514318.8%30.0%.149.279.212.285.360.283770.0-1.00.80.1
18Keston HiuraDET176137817.7%35.0%.192.327.232.310.424.317100-0.1-0.1-1.90.0
19TJ HopkinsDET163313307.6%30.4%.129.312.226.293.356.285780.0-0.9-0.40.0
20Justyn-Henry MalloyDET1143154012.3%27.1%.142.310.235.337.378.318101-0.10.0-2.3-0.1
21Bligh MadrisDET164314319.1%25.8%.104.258.197.273.301.257590.0-2.1-0.8-0.1
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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.