2024 Projections
Pre-Season Projections
600 PA / 200 IP Projections
Updated In-Season Projections
ZiPS (RoS)
ZiPS (Update)
ZiPS DC (RoS)
Steamer (RoS)
Steamer (Update)
Depth Charts (RoS)
ATC DC (RoS)
THE BAT (RoS)
THE BAT X (RoS)
ZiPS (Update)
ZiPS DC (RoS)
Steamer (RoS)
Steamer (Update)
Depth Charts (RoS)
ATC DC (RoS)
THE BAT (RoS)
THE BAT X (RoS)
3 Year Projections
On-Pace Leaders
Pre-Season
ATC
600 PA / 200 IP
600 PA / 200 IP
In-Season
In-Season
3 Year
3 Year
On-Pace
On-Pace
Data Export [Members Only]
| # | Name | Team | G | PA | HR | R | RBI | SB | BB% | K% | ISO | BABIP | AVG | OBP | SLG | wOBA | wRC+ | BsR | Off | Def | WAR |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Francisco Lindor | NYM | 153 | 657 | 27 | 92 | 87 | 22 | 9.3% | 19.2% | .195 | .276 | .252 | .330 | .446 | .334 | 111 | 0.6 | 9.3 | 9.9 | 4.1 |
| 2 | Brandon Nimmo | NYM | 145 | 640 | 19 | 86 | 65 | 4 | 11.3% | 20.1% | .171 | .315 | .266 | .361 | .437 | .349 | 121 | -1.5 | 14.6 | -3.3 | 3.3 |
| 3 | Pete Alonso | NYM | 152 | 649 | 41 | 89 | 109 | 4 | 10.1% | 21.5% | .265 | .257 | .250 | .340 | .515 | .360 | 128 | -2.3 | 20.0 | -12.5 | 3.0 |
| 4 | Francisco Alvarez | NYM | 121 | 463 | 24 | 56 | 65 | 2 | 9.6% | 26.2% | .215 | .260 | .227 | .311 | .442 | .324 | 104 | -1.0 | 1.2 | 4.6 | 2.1 |
| 5 | Jeff McNeil | NYM | 132 | 556 | 8 | 64 | 55 | 6 | 6.5% | 10.9% | .114 | .300 | .277 | .338 | .391 | .320 | 102 | -1.5 | -0.4 | -1.1 | 1.7 |
| 6 | Harrison Bader | NYM | 107 | 413 | 11 | 50 | 44 | 21 | 6.1% | 19.4% | .143 | .279 | .243 | .297 | .386 | .296 | 85 | 1.2 | -6.2 | 5.6 | 1.3 |
| 7 | Starling Marte | NYM | 115 | 487 | 11 | 61 | 49 | 26 | 6.0% | 19.8% | .130 | .309 | .260 | .319 | .390 | .310 | 95 | 1.9 | -1.3 | -6.4 | 0.9 |
| 8 | Brett Baty | NYM | 112 | 445 | 13 | 51 | 49 | 2 | 8.5% | 26.9% | .142 | .304 | .237 | .309 | .379 | .302 | 89 | -1.0 | -6.9 | -0.2 | 0.8 |
| 9 | J.D. Martinez | NYM | 117 | 491 | 22 | 59 | 71 | 1 | 8.4% | 28.1% | .206 | .308 | .249 | .315 | .455 | .329 | 107 | -2.3 | 1.9 | -12.6 | 0.6 |
| 10 | Tyrone Taylor | NYM | 81 | 298 | 11 | 37 | 38 | 7 | 5.4% | 23.5% | .185 | .269 | .233 | .286 | .417 | .302 | 89 | 0.3 | -3.7 | -0.8 | 0.6 |
| 11 | Omar Narváez | NYM | 62 | 222 | 4 | 21 | 19 | 0 | 9.5% | 19.7% | .109 | .275 | .231 | .310 | .340 | .289 | 80 | -0.7 | -6.2 | 3.9 | 0.5 |
| 12 | Ji Man Choi | NYM | 26 | 87 | 3 | 10 | 10 | 0 | 12.4% | 28.6% | .167 | .281 | .219 | .320 | .386 | .310 | 95 | -0.2 | -0.7 | 1.7 | 0.4 |
| 13 | Mark Vientos | NYM | 68 | 265 | 11 | 29 | 34 | 1 | 7.2% | 29.1% | .184 | .293 | .233 | .294 | .417 | .305 | 91 | -0.7 | -3.5 | -2.8 | 0.3 |
| 14 | Zack Short | NYM | 27 | 91 | 2 | 9 | 9 | 1 | 11.5% | 29.4% | .136 | .254 | .194 | .291 | .330 | .276 | 72 | -0.2 | -3.3 | 1.2 | 0.1 |
| 15 | Ronny Mauricio | NYM | 6 | 25 | 1 | 3 | 3 | 1 | 5.3% | 23.4% | .159 | .296 | .247 | .291 | .406 | .300 | 88 | 0.0 | -0.4 | 0.2 | 0.1 |
| 16 | DJ Stewart | NYM | 37 | 135 | 6 | 16 | 16 | 1 | 10.1% | 29.3% | .192 | .267 | .215 | .311 | .407 | .314 | 97 | -0.2 | -0.7 | -3.2 | 0.1 |
| 17 | Luisangel Acuña | NYM | 9 | 27 | 0 | 3 | 2 | 1 | 6.6% | 22.3% | .102 | .299 | .240 | .293 | .342 | .279 | 73 | 0.1 | -0.8 | 0.3 | 0.0 |
| 18 | Ben Gamel | NYM | 23 | 71 | 2 | 8 | 7 | 1 | 10.8% | 23.3% | .131 | .285 | .228 | .316 | .359 | .299 | 87 | -0.1 | -1.2 | -0.8 | 0.0 |
| 19 | Trayce Thompson | NYM | 35 | 96 | 4 | 10 | 11 | 1 | 10.4% | 38.8% | .170 | .286 | .192 | .284 | .362 | .285 | 77 | -0.1 | -2.8 | -0.4 | 0.0 |
| 20 | Joey Wendle | NYM | 74 | 275 | 3 | 30 | 23 | 7 | 4.8% | 20.1% | .103 | .292 | .240 | .284 | .343 | .274 | 70 | -0.1 | -10.2 | 0.8 | 0.0 |
| 21 | Jose Iglesias | NYM | 9 | 33 | 0 | 4 | 3 | 0 | 4.1% | 15.6% | .065 | .298 | .255 | .290 | .320 | .270 | 67 | -0.1 | -1.4 | 0.1 | 0.0 |
| 22 | Tomás Nido | NYM | 9 | 29 | 0 | 3 | 3 | 0 | 4.7% | 25.2% | .066 | .285 | .218 | .257 | .284 | .240 | 46 | -0.1 | -2.0 | 0.7 | 0.0 |
| 23 | Taylor Kohlwey | NYM | 9 | 25 | 0 | 2 | 2 | 0 | 8.8% | 25.0% | .096 | .287 | .219 | .296 | .315 | .274 | 70 | 0.0 | -0.9 | -0.3 | 0.0 |
| # | Name | Team | G | PA | HR | R | RBI | SB | BB% | K% | ISO | BABIP | AVG | OBP | SLG | wOBA | wRC+ | BsR | Off | Def | WAR |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Francisco Lindor | NYM | 153 | 657 | 27 | 92 | 87 | 22 | 9.3% | 19.2% | .195 | .276 | .252 | .330 | .446 | .334 | 111 | 0.6 | 9.3 | 9.9 | 4.1 |
| 2 | Brandon Nimmo | NYM | 145 | 640 | 19 | 86 | 65 | 4 | 11.3% | 20.1% | .171 | .315 | .266 | .361 | .437 | .349 | 121 | -1.5 | 14.6 | -3.3 | 3.3 |
| 3 | Pete Alonso | NYM | 152 | 649 | 41 | 89 | 109 | 4 | 10.1% | 21.5% | .265 | .257 | .250 | .340 | .515 | .360 | 128 | -2.3 | 20.0 | -12.5 | 3.0 |
| 4 | Francisco Alvarez | NYM | 121 | 463 | 24 | 56 | 65 | 2 | 9.6% | 26.2% | .215 | .260 | .227 | .311 | .442 | .324 | 104 | -1.0 | 1.2 | 4.6 | 2.1 |
| 5 | Jeff McNeil | NYM | 132 | 556 | 8 | 64 | 55 | 6 | 6.5% | 10.9% | .114 | .300 | .277 | .338 | .391 | .320 | 102 | -1.5 | -0.4 | -1.1 | 1.7 |
| 6 | Harrison Bader | NYM | 107 | 413 | 11 | 50 | 44 | 21 | 6.1% | 19.4% | .143 | .279 | .243 | .297 | .386 | .296 | 85 | 1.2 | -6.2 | 5.6 | 1.3 |
| 7 | Starling Marte | NYM | 115 | 487 | 11 | 61 | 49 | 26 | 6.0% | 19.8% | .130 | .309 | .260 | .319 | .390 | .310 | 95 | 1.9 | -1.3 | -6.4 | 0.9 |
| 8 | Brett Baty | NYM | 112 | 445 | 13 | 51 | 49 | 2 | 8.5% | 26.9% | .142 | .304 | .237 | .309 | .379 | .302 | 89 | -1.0 | -6.9 | -0.2 | 0.8 |
| 9 | J.D. Martinez | NYM | 117 | 491 | 22 | 59 | 71 | 1 | 8.4% | 28.1% | .206 | .308 | .249 | .315 | .455 | .329 | 107 | -2.3 | 1.9 | -12.6 | 0.6 |
| 10 | Tyrone Taylor | NYM | 81 | 298 | 11 | 37 | 38 | 7 | 5.4% | 23.5% | .185 | .269 | .233 | .286 | .417 | .302 | 89 | 0.3 | -3.7 | -0.8 | 0.6 |
| 11 | Omar Narváez | NYM | 62 | 222 | 4 | 21 | 19 | 0 | 9.5% | 19.7% | .109 | .275 | .231 | .310 | .340 | .289 | 80 | -0.7 | -6.2 | 3.9 | 0.5 |
| 12 | Ji Man Choi | NYM | 26 | 87 | 3 | 10 | 10 | 0 | 12.4% | 28.6% | .167 | .281 | .219 | .320 | .386 | .310 | 95 | -0.2 | -0.7 | 1.7 | 0.4 |
| 13 | Mark Vientos | NYM | 68 | 265 | 11 | 29 | 34 | 1 | 7.2% | 29.1% | .184 | .293 | .233 | .294 | .417 | .305 | 91 | -0.7 | -3.5 | -2.8 | 0.3 |
| 14 | Zack Short | NYM | 27 | 91 | 2 | 9 | 9 | 1 | 11.5% | 29.4% | .136 | .254 | .194 | .291 | .330 | .276 | 72 | -0.2 | -3.3 | 1.2 | 0.1 |
| 15 | Ronny Mauricio | NYM | 6 | 25 | 1 | 3 | 3 | 1 | 5.3% | 23.4% | .159 | .296 | .247 | .291 | .406 | .300 | 88 | 0.0 | -0.4 | 0.2 | 0.1 |
| 16 | DJ Stewart | NYM | 37 | 135 | 6 | 16 | 16 | 1 | 10.1% | 29.3% | .192 | .267 | .215 | .311 | .407 | .314 | 97 | -0.2 | -0.7 | -3.2 | 0.1 |
| 17 | Luisangel Acuña | NYM | 9 | 27 | 0 | 3 | 2 | 1 | 6.6% | 22.3% | .102 | .299 | .240 | .293 | .342 | .279 | 73 | 0.1 | -0.8 | 0.3 | 0.0 |
| 18 | Ben Gamel | NYM | 23 | 71 | 2 | 8 | 7 | 1 | 10.8% | 23.3% | .131 | .285 | .228 | .316 | .359 | .299 | 87 | -0.1 | -1.2 | -0.8 | 0.0 |
| 19 | Trayce Thompson | NYM | 35 | 96 | 4 | 10 | 11 | 1 | 10.4% | 38.8% | .170 | .286 | .192 | .284 | .362 | .285 | 77 | -0.1 | -2.8 | -0.4 | 0.0 |
| 20 | Joey Wendle | NYM | 74 | 275 | 3 | 30 | 23 | 7 | 4.8% | 20.1% | .103 | .292 | .240 | .284 | .343 | .274 | 70 | -0.1 | -10.2 | 0.8 | 0.0 |
| 21 | Jose Iglesias | NYM | 9 | 33 | 0 | 4 | 3 | 0 | 4.1% | 15.6% | .065 | .298 | .255 | .290 | .320 | .270 | 67 | -0.1 | -1.4 | 0.1 | 0.0 |
| 22 | Tomás Nido | NYM | 9 | 29 | 0 | 3 | 3 | 0 | 4.7% | 25.2% | .066 | .285 | .218 | .257 | .284 | .240 | 46 | -0.1 | -2.0 | 0.7 | 0.0 |
| 23 | Taylor Kohlwey | NYM | 9 | 25 | 0 | 2 | 2 | 0 | 8.8% | 25.0% | .096 | .287 | .219 | .296 | .315 | .274 | 70 | 0.0 | -0.9 | -0.3 | 0.0 |
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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
- 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.
