José Azocar
CF Gwinnett Stripers| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR | MLE AVG/OBP/SLG |
|---|---|---|---|---|---|---|---|---|---|
| 2024 | 28 | AAANYM | 281 | .296/.332/.438 | 6 | 30 | 79 | — | .259/.288/.369 |
| 2024 | 28 | MLBSD | 79 | .219/.269/.247 | 0 | 5 | 49 | -0.5 | |
| 2025 | 29 | AAANYM | 291 | .241/.315/.352 | 4 | 17 | 52 | — | .204/.260/.279 |
| 2025 | 29 | MLBATL | 21 | .263/.333/.263 | 0 | 1 | 77 | -0.5 | |
| 2026 | 30 | AAAATL | 411 | .260/.305/.344 | 5 | 24 | 50 | — | .227/.261/.289 |
| 2026 | 30 | MLBATL | 18 | .353/.389/.471 | 0 | 1 | 145 | 0.3 | |
| 2027PROJ10% MLB | 31 | MLBATL | 24 | .247/.292/.349 | 0 | 1 | 80 | 0.0 | |
| 2028PROJ27% MLB | 32 | MLBATL | 68 | .241/.286/.336 | 1 | 3 | 75 | -0.1 |
Tools · Splits · ContractCON 50 / POW 40
Career Stats + Projections
Methodology▸ how these numbers are built
All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2027 = full-season projection (no games played yet). 2028+ via Advanced Marcel + aging curve.
| Year | Age | Lvl | Team | MLB% | PA | AB | H | 2B | 3B | HR | BB | SO | HBP | SB | CS | AVG | OBP | SLG | OPS | ISO | BABIP | K% | BB% | wOBA | wRC+ | BAT | RUN | FLD | POS | REP | WAR |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| ▸ Career — actual stats, one row per stint (as recorded, no adjustments) | |||||||||||||||||||||||||||||||
| 2013 | 17 | ROK | VSL Tigers | — | 212 | 205 | 48 | 11 | 2 | 0 | 3 | 43 | 2 | 5 | 2 | 234 | 252 | 307 | 560 | 73 | 294 | 20 | 1 | 248 | -6 | — | — | — | — | — | — |
| 2014 | 18 | ROK | VSL Tigers | — | 269 | 250 | 85 | 7 | 6 | 1 | 11 | 48 | 4 | 13 | 5 | 340 | 377 | 428 | 805 | 88 | 412 | 18 | 4 | 355 | 42 | — | — | — | — | — | — |
| 2015 | 19 | ROK | GCL Tigers | — | 211 | 194 | 63 | 10 | 5 | 0 | 7 | 31 | 2 | 6 | 4 | 325 | 355 | 428 | 783 | 103 | 380 | 15 | 3 | 335 | 59 | — | — | — | — | — | — |
| 2016 | 20 | A | West Michigan Whitecaps | — | 532 | 501 | 141 | 11 | 8 | 0 | 25 | 119 | 1 | 14 | 5 | 281 | 317 | 335 | 652 | 54 | 366 | 22 | 5 | 293 | 51 | — | — | — | — | — | — |
| 2017 | 21 | A+ | Lakeland Flying Tigers | — | 456 | 431 | 95 | 10 | 6 | 3 | 14 | 122 | 2 | 12 | 6 | 220 | 248 | 292 | 541 | 72 | 297 | 27 | 3 | 239 | 15 | — | — | — | — | — | — |
| 2018 | 22 | A+ | Lakeland Flying Tigers | — | 318 | 300 | 87 | 14 | 3 | 1 | 9 | 64 | 2 | 5 | 2 | 290 | 315 | 367 | 682 | 77 | 355 | 20 | 3 | 299 | 67 | — | — | — | — | — | — |
| 2018 | 22 | A | West Michigan Whitecaps | — | 110 | 104 | 33 | 3 | 6 | 1 | 5 | 21 | 1 | 6 | 2 | 317 | 355 | 490 | 845 | 173 | 390 | 19 | 5 | 370 | 86 | — | — | — | — | — | — |
| 2019 | 23 | AA | Erie SeaWolves | — | 538 | 504 | 144 | 21 | 3 | 10 | 21 | 132 | 5 | 10 | 3 | 286 | 321 | 399 | 720 | 113 | 363 | 25 | 4 | 317 | 62 | — | — | — | — | — | — |
| 2019 | 23 | INTL | Mesa Solar Sox | — | 68 | 61 | 17 | 1 | 0 | 0 | 7 | 17 | 0 | 5 | 3 | 279 | 353 | 295 | 648 | 16 | 386 | 25 | 10 | 304 | 92 | — | — | — | — | — | — |
| 2021 | 25 | AAA | El Paso Chihuahuas | — | 201 | 190 | 55 | 14 | 8 | 0 | 6 | 45 | 1 | 17 | 3 | 289 | 315 | 447 | 762 | 158 | 369 | 22 | 3 | 327 | 75 | — | — | — | — | — | — |
| 2021 | 25 | AA | San Antonio Missions | — | 343 | 301 | 83 | 8 | 6 | 9 | 35 | 71 | 5 | 15 | 11 | 276 | 361 | 432 | 793 | 156 | 333 | 21 | 10 | 353 | 89 | — | — | — | — | — | — |
| 2022 | 26 | MLB | San Diego Padres | — | 216 | 202 | 52 | 9 | 3 | 0 | 12 | 44 | 0 | 5 | 6 | 257 | 299 | 332 | 631 | 74 | 327 | 20 | 6 | 282 | 81 | -5 | -1 | +4 | +2 | +5 | 0.4 |
| 2022 | 26 | AAA | El Paso Chihuahuas | — | 105 | 98 | 30 | 6 | 0 | 5 | 7 | 24 | 0 | 3 | 1 | 306 | 352 | 520 | 873 | 214 | 362 | 23 | 7 | 383 | 69 | — | — | — | — | — | — |
| 2022 | 26 | INTL | Caribes de Anzoategui | — | 131 | 119 | 35 | 6 | 1 | 1 | 6 | 23 | 4 | 2 | 1 | 294 | 349 | 387 | 735 | 92 | 351 | 18 | 5 | 328 | 108 | — | — | — | — | — | — |
| 2023 | 27 | MLB | San Diego Padres | — | 102 | 91 | 21 | 6 | 0 | 2 | 4 | 24 | 2 | 8 | 2 | 231 | 278 | 363 | 641 | 132 | 292 | 24 | 4 | 273 | 75 | -3 | +1 | -2 | -5 | +2 | -0.6 |
| 2023 | 27 | AAA | El Paso Chihuahuas | — | 212 | 201 | 54 | 9 | 0 | 5 | 9 | 45 | 2 | 18 | 5 | 269 | 307 | 388 | 695 | 119 | 325 | 21 | 4 | 311 | 57 | — | — | — | — | — | — |
| 2023 | 27 | INTL | Caribes de Anzoategui | — | 124 | 113 | 31 | 8 | 1 | 1 | 7 | 25 | 2 | 2 | 2 | 274 | 328 | 389 | 717 | 115 | 337 | 20 | 6 | 317 | 101 | — | — | — | — | — | — |
| 2024 | 28 | MLB | San Diego Padres | — | 79 | 73 | 16 | 2 | 0 | 0 | 5 | 19 | 0 | 5 | 1 | 219 | 269 | 247 | 516 | 27 | 296 | 24 | 6 | 237 | 49 | -5 | +1 | +1 | -4 | +2 | -0.5 |
| 2024 | 28 | AAA | Syracuse Mets | — | 281 | 260 | 77 | 13 | 3 | 6 | 9 | 42 | 5 | 30 | 6 | 296 | 332 | 438 | 771 | 142 | 326 | 15 | 3 | 334 | 79 | — | — | — | — | — | — |
| 2025 | 29 | MLB | Atlanta Braves | — | 21 | 19 | 5 | 0 | 0 | 0 | 2 | 1 | 0 | 1 | 0 | 263 | 333 | 263 | 596 | 278 | 5 | 10 | 282 | 77 | -1 | +0 | -1 | -3 | +0 | -0.5 | |
| 2025 | 29 | AAA | Syracuse Mets | — | 291 | 261 | 63 | 13 | 2 | 4 | 24 | 59 | 4 | 17 | 6 | 241 | 315 | 352 | 667 | 111 | 296 | 20 | 8 | 302 | 52 | — | — | — | — | — | — |
| 2026 | 30 | MLB | Atlanta Braves | — | 18 | 17 | 6 | 2 | 0 | 0 | 1 | 4 | 0 | 1 | 0 | 353 | 389 | 471 | 859 | 118 | 462 | 22 | 6 | 383 | 145 | +1 | +0 | +0 | +2 | +0 | 0.3 |
| 2026 | 30 | AAA | Gwinnett Stripers | — | 411 | 381 | 99 | 13 | 2 | 5 | 22 | 72 | 3 | 24 | 7 | 260 | 305 | 344 | 649 | 84 | 305 | 18 | 5 | 290 | 50 | — | — | — | — | — | — |
| ▸ Career Totals (raw MLB only — historical actual) | |||||||||||||||||||||||||||||||
| MLB Career | — | — | 436 | 402 | 100 | 19 | 3 | 2 | 24 | 92 | 2 | 20 | 9 | 249 | 294 | 326 | 620 | 77 | 317 | 21 | 6 | 276 | 73 | -14 | +0 | +2 | -9 | +9 | -1.1 | ||
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2013 | 17 | ROK MLE | VSL Tigers | — | 212 | 206 | 32 | 7 | 1 | 0 | 2 | 52 | 2 | 5 | 2 | 155 | 171 | 199 | 370 | 44 | 202 | 25 | 1 | 160 | -6 | — | — | — | — | — | — |
| 2014 | 18 | ROK MLE | VSL Tigers | — | 269 | 255 | 56 | 4 | 4 | 0 | 6 | 59 | 4 | 13 | 5 | 220 | 249 | 267 | 516 | 47 | 276 | 22 | 2 | 231 | 42 | — | — | — | — | — | — |
| 2015 | 19 | ROK MLE | GCL Tigers | — | 211 | 197 | 50 | 7 | 4 | 0 | 4 | 45 | 2 | 6 | 4 | 254 | 276 | 330 | 606 | 76 | 306 | 21 | 2 | 256 | 59 | — | — | — | — | — | — |
| 2016 | 20 | A MLE | West Michigan Whitecaps | — | 532 | 509 | 123 | 9 | 7 | 0 | 17 | 164 | 1 | 14 | 5 | 242 | 268 | 287 | 554 | 45 | 347 | 31 | 3 | 243 | 51 | — | — | — | — | — | — |
| 2017 | 21 | A+ MLE | Lakeland Flying Tigers | — | 456 | 435 | 79 | 10 | 4 | 1 | 10 | 174 | 2 | 12 | 6 | 182 | 204 | 230 | 433 | 48 | 287 | 38 | 2 | 191 | 15 | — | — | — | — | — | — |
| 2018 | 22 | A+ MLE | Lakeland Flying Tigers | — | 318 | 303 | 80 | 13 | 2 | 1 | 6 | 92 | 2 | 5 | 2 | 264 | 283 | 330 | 613 | 66 | 354 | 29 | 2 | 267 | 67 | — | — | — | — | — | — |
| 2018 | 22 | A MLE | West Michigan Whitecaps | — | 110 | 105 | 28 | 2 | 5 | 1 | 4 | 29 | 1 | 6 | 2 | 267 | 300 | 410 | 710 | 143 | 356 | 26 | 4 | 295 | 86 | — | — | — | — | — | — |
| 2019 | 23 | AA MLE | Erie SeaWolves | — | 538 | 512 | 126 | 16 | 2 | 6 | 13 | 162 | 5 | 10 | 3 | 246 | 272 | 320 | 592 | 74 | 336 | 30 | 2 | 260 | 62 | — | — | — | — | — | — |
| 2021 | 25 | AAA MLE | El Paso Chihuahuas | — | 201 | 192 | 49 | 11 | 7 | 0 | 4 | 56 | 1 | 17 | 3 | 255 | 274 | 385 | 660 | 130 | 338 | 28 | 2 | 279 | 75 | — | — | — | — | — | — |
| 2021 | 25 | AA MLE | San Antonio Missions | — | 343 | 313 | 78 | 8 | 5 | 8 | 23 | 91 | 5 | 15 | 11 | 249 | 311 | 383 | 694 | 134 | 320 | 27 | 7 | 300 | 89 | — | — | — | — | — | — |
| 2022 | 26 | MLB MLE | San Diego Padres | — | 216 | 202 | 53 | 10 | 3 | 0 | 12 | 44 | 0 | 5 | 6 | 262 | 304 | 342 | 645 | 79 | 327 | 20 | 6 | 288 | 81 | -5 | -1 | +4 | +2 | +5 | 0.4 |
| 2022 | 26 | AAA MLE | El Paso Chihuahuas | — | 105 | 100 | 23 | 4 | 0 | 3 | 5 | 30 | 0 | 3 | 1 | 230 | 267 | 360 | 627 | 130 | 296 | 29 | 5 | 270 | 69 | — | — | — | — | — | — |
| 2023 | 27 | MLB MLE | San Diego Padres | — | 102 | 91 | 21 | 6 | 0 | 2 | 4 | 24 | 2 | 8 | 2 | 231 | 278 | 363 | 641 | 132 | 292 | 24 | 4 | 279 | 75 | -3 | +1 | -2 | -5 | +2 | -0.6 |
| 2023 | 27 | AAA MLE | El Paso Chihuahuas | — | 212 | 204 | 47 | 7 | 0 | 3 | 6 | 55 | 2 | 18 | 5 | 230 | 259 | 309 | 568 | 78 | 302 | 26 | 3 | 253 | 57 | — | — | — | — | — | — |
| 2024 | 28 | MLB MLE | San Diego Padres | — | 79 | 73 | 16 | 2 | 0 | 0 | 5 | 19 | 0 | 5 | 1 | 219 | 269 | 247 | 516 | 27 | 296 | 24 | 6 | 241 | 49 | -5 | +1 | +1 | -4 | +2 | -0.5 |
| 2024 | 28 | AAA MLE | Syracuse Mets | — | 281 | 263 | 68 | 11 | 3 | 4 | 6 | 52 | 5 | 30 | 6 | 259 | 288 | 369 | 657 | 110 | 292 | 19 | 2 | 285 | 79 | — | — | — | — | — | — |
| 2025 | 29 | MLB MLE | Atlanta Braves | — | 21 | 19 | 5 | 0 | 0 | 0 | 2 | 1 | 0 | 1 | 0 | 263 | 333 | 263 | 596 | 278 | 5 | 10 | 282 | 77 | -1 | +0 | -1 | -3 | +0 | -0.5 | |
| 2025 | 29 | AAA MLE | Syracuse Mets | — | 291 | 269 | 55 | 10 | 2 | 2 | 16 | 72 | 4 | 17 | 6 | 204 | 260 | 279 | 538 | 74 | 273 | 25 | 5 | 245 | 52 | — | — | — | — | — | — |
| 2026 | 30 | MLB MLE | Atlanta Braves | — | 18 | 17 | 6 | 2 | 0 | 0 | 1 | 4 | 0 | 1 | 0 | 353 | 389 | 471 | 859 | 118 | 462 | 22 | 6 | 383 | 145 | +1 | +0 | +0 | +2 | +0 | 0.3 |
| 2026 | 30 | AAA MLE | Gwinnett Stripers | — | 411 | 388 | 88 | 11 | 2 | 3 | 15 | 86 | 3 | 24 | 7 | 227 | 261 | 289 | 550 | 62 | 275 | 21 | 4 | 242 | 50 | — | — | — | — | — | — |
| 2013 | 17 | ROK MLE | VSL Tigers | — | 212 | 206 | 32 | 7 | 1 | 0 | 2 | 52 | 2 | 5 | 2 | 155 | 171 | 199 | 370 | 44 | 206 | 25 | 1 | 160 | -6 | — | — | — | — | — | — |
| 2013 | 17 | ROK RAW | VSL Tigers | — | 212 | 205 | 48 | 11 | 2 | 0 | 3 | 43 | 2 | 5 | 2 | 234 | 252 | 307 | 560 | 73 | 294 | 20 | 1 | 248 | -6 | — | — | — | — | — | — |
| 2014 | 18 | ROK MLE | VSL Tigers | — | 269 | 255 | 56 | 4 | 4 | 0 | 6 | 59 | 4 | 13 | 5 | 220 | 249 | 267 | 516 | 47 | 281 | 22 | 2 | 231 | 42 | — | — | — | — | — | — |
| 2014 | 18 | ROK RAW | VSL Tigers | — | 269 | 250 | 85 | 7 | 6 | 1 | 11 | 48 | 4 | 13 | 5 | 340 | 377 | 428 | 805 | 88 | 412 | 18 | 4 | 355 | 42 | — | — | — | — | — | — |
| 2015 | 19 | ROK MLE | GCL Tigers | — | 211 | 197 | 50 | 7 | 4 | 0 | 4 | 45 | 2 | 6 | 4 | 254 | 276 | 330 | 606 | 76 | 323 | 21 | 2 | 256 | 59 | — | — | — | — | — | — |
| 2015 | 19 | ROK RAW | GCL Tigers | — | 211 | 194 | 63 | 10 | 5 | 0 | 7 | 31 | 2 | 6 | 4 | 325 | 355 | 428 | 783 | 103 | 380 | 15 | 3 | 335 | 59 | — | — | — | — | — | — |
| 2016 | 20 | A MLE | West Michigan Whitecaps | — | 532 | 509 | 123 | 9 | 7 | 0 | 17 | 164 | 1 | 14 | 5 | 242 | 268 | 287 | 554 | 45 | 353 | 31 | 3 | 243 | 51 | — | — | — | — | — | — |
| 2016 | 20 | A RAW | West Michigan Whitecaps | — | 532 | 501 | 141 | 11 | 8 | 0 | 25 | 119 | 1 | 14 | 5 | 281 | 317 | 335 | 652 | 54 | 366 | 22 | 5 | 293 | 51 | — | — | — | — | — | — |
| 2017 | 21 | A+ MLE | Lakeland Flying Tigers | — | 456 | 435 | 79 | 10 | 4 | 1 | 10 | 174 | 2 | 12 | 6 | 182 | 204 | 230 | 433 | 48 | 295 | 38 | 2 | 191 | 15 | — | — | — | — | — | — |
| 2017 | 21 | A+ RAW | Lakeland Flying Tigers | — | 456 | 431 | 95 | 10 | 6 | 3 | 14 | 122 | 2 | 12 | 6 | 220 | 248 | 292 | 541 | 72 | 297 | 27 | 3 | 239 | 15 | — | — | — | — | — | — |
| 2018 | 22 | A+ MLE | 2 teams | — | 428 | 408 | 108 | 16 | 7 | 1 | 10 | 122 | 3 | 11 | 4 | 265 | 287 | 346 | 633 | 81 | 366 | 29 | 2 | 274 | 72 | — | — | — | — | — | — |
| 2018 | 22 | A+ RAW | 2 teams | — | 428 | 404 | 120 | 17 | 9 | 2 | 14 | 85 | 3 | 11 | 4 | 297 | 325 | 399 | 724 | 101 | 364 | 20 | 3 | 317 | 72 | — | — | — | — | — | — |
| 2019 | 23 | AA MLE | 2 teams | — | 606 | 578 | 143 | 18 | 3 | 7 | 15 | 182 | 5 | 15 | 6 | 247 | 273 | 325 | 598 | 78 | 343 | 30 | 2 | 260 | 62 | — | — | — | — | — | — |
| 2019 | 23 | AA RAW | 2 teams | — | 606 | 565 | 161 | 22 | 3 | 10 | 28 | 149 | 5 | 15 | 6 | 285 | 324 | 388 | 712 | 103 | 366 | 25 | 5 | 315 | 62 | — | — | — | — | — | — |
| 2021 | 25 | AA MLE | 2 teams | — | 544 | 504 | 126 | 18 | 12 | 8 | 28 | 148 | 6 | 32 | 14 | 250 | 297 | 381 | 678 | 131 | 334 | 27 | 5 | 292 | 84 | — | — | — | — | — | — |
| 2021 | 25 | AA RAW | 2 teams | — | 544 | 491 | 138 | 22 | 14 | 9 | 41 | 116 | 6 | 32 | 14 | 281 | 344 | 438 | 782 | 157 | 348 | 21 | 8 | 343 | 84 | — | — | — | — | — | — |
| 2022 | 26 | MLB MLE | 3 teams | — | 452 | 420 | 106 | 19 | 4 | 4 | 24 | 104 | 4 | 10 | 8 | 252 | 299 | 345 | 644 | 93 | 324 | 23 | 5 | 282 | 77 | -12 | -1 | +4 | +2 | +10 | 0.2 |
| 2022 | 26 | MLB RAW | 3 teams | — | 452 | 419 | 117 | 21 | 4 | 6 | 25 | 91 | 4 | 10 | 8 | 279 | 326 | 391 | 717 | 112 | 342 | 20 | 6 | 319 | 77 | -12 | -1 | +4 | +2 | +10 | 0.2 |
| 2023 | 27 | AAA MLE | 3 teams | — | 438 | 411 | 96 | 19 | 0 | 7 | 14 | 110 | 6 | 28 | 9 | 234 | 269 | 331 | 600 | 97 | 301 | 25 | 3 | 261 | 63 | — | — | — | — | — | — |
| 2023 | 27 | AAA RAW | 3 teams | — | 438 | 405 | 106 | 23 | 1 | 8 | 20 | 94 | 6 | 28 | 9 | 262 | 306 | 383 | 689 | 121 | 321 | 21 | 5 | 304 | 63 | — | — | — | — | — | — |
| 2024 | 28 | AAA MLE | 2 teams | — | 360 | 336 | 84 | 13 | 3 | 4 | 11 | 71 | 5 | 35 | 7 | 250 | 284 | 342 | 626 | 92 | 300 | 20 | 3 | 275 | 72 | — | — | — | — | — | — |
| 2024 | 28 | AAA RAW | 2 teams | — | 360 | 333 | 93 | 15 | 3 | 6 | 14 | 61 | 5 | 35 | 7 | 279 | 318 | 396 | 715 | 117 | 320 | 17 | 4 | 312 | 72 | — | — | — | — | — | — |
| 2025 | 29 | AAA MLE | 2 teams | — | 312 | 288 | 60 | 10 | 2 | 2 | 18 | 73 | 4 | 18 | 6 | 208 | 265 | 278 | 542 | 69 | 271 | 23 | 6 | 247 | 54 | — | — | — | — | — | — |
| 2025 | 29 | AAA RAW | 2 teams | — | 312 | 280 | 68 | 13 | 2 | 4 | 26 | 60 | 4 | 18 | 6 | 243 | 316 | 346 | 663 | 104 | 295 | 19 | 8 | 300 | 54 | — | — | — | — | — | — |
| 2026 | 30 | AAA MLE | 2 teams | — | 429 | 405 | 94 | 13 | 2 | 3 | 16 | 90 | 3 | 25 | 7 | 232 | 267 | 296 | 563 | 64 | 288 | 21 | 4 | 248 | 54 | — | — | — | — | — | — |
| 2026 | 30 | AAA RAW | 2 teams | — | 429 | 398 | 105 | 15 | 2 | 5 | 23 | 76 | 3 | 25 | 7 | 264 | 309 | 349 | 658 | 85 | 312 | 18 | 5 | 294 | 54 | — | — | — | — | — | — |
| 2013 | 17 | ROK MLE | VSL Tigers | — | 212 | 206 | 32 | 7 | 1 | 0 | 2 | 52 | 2 | 5 | 2 | 155 | 171 | 199 | 370 | 44 | 202 | 25 | 1 | 160 | -6 | — | — | — | — | — | — |
| 2014 | 18 | ROK MLE | VSL Tigers | — | 269 | 257 | 56 | 4 | 4 | 0 | 6 | 59 | 4 | 13 | 5 | 218 | 249 | 265 | 514 | 47 | 276 | 22 | 2 | 231 | 42 | — | — | — | — | — | — |
| 2015 | 19 | ROK MLE | GCL Tigers | — | 211 | 203 | 50 | 7 | 4 | 0 | 4 | 45 | 2 | 6 | 4 | 246 | 276 | 320 | 596 | 74 | 306 | 21 | 2 | 256 | 59 | — | — | — | — | — | — |
| 2016 | 20 | A MLE | West Michigan Whitecaps | — | 532 | 509 | 123 | 9 | 7 | 0 | 17 | 164 | 1 | 14 | 5 | 242 | 268 | 287 | 554 | 45 | 347 | 31 | 3 | 243 | 51 | — | — | — | — | — | — |
| 2017 | 21 | A+ MLE | Lakeland Flying Tigers | — | 456 | 441 | 79 | 10 | 4 | 1 | 10 | 174 | 2 | 12 | 6 | 179 | 204 | 227 | 430 | 48 | 287 | 38 | 2 | 191 | 15 | — | — | — | — | — | — |
| 2018 | 22 | A+ MLE | 2 teams | — | 428 | 412 | 108 | 16 | 7 | 1 | 10 | 122 | 3 | 11 | 4 | 262 | 287 | 342 | 630 | 80 | 355 | 29 | 2 | 274 | 72 | — | — | — | — | — | — |
| 2019 | 23 | AA MLE | 2 teams | — | 606 | 581 | 143 | 18 | 3 | 7 | 15 | 182 | 5 | 15 | 6 | 246 | 273 | 324 | 596 | 77 | 336 | 30 | 2 | 260 | 62 | — | — | — | — | — | — |
| 2021 | 25 | AA MLE | 2 teams | — | 544 | 505 | 126 | 18 | 12 | 8 | 28 | 148 | 6 | 32 | 14 | 250 | 297 | 380 | 678 | 131 | 327 | 27 | 5 | 292 | 84 | — | — | — | — | — | — |
| 2022 | 26 | MLB MLE | 3 teams | — | 452 | 421 | 106 | 19 | 4 | 4 | 24 | 104 | 4 | 10 | 8 | 252 | 299 | 344 | 644 | 93 | 317 | 23 | 5 | 282 | 77 | — | — | — | — | — | — |
| 2023 | 27 | AAA MLE | 3 teams | — | 438 | 415 | 96 | 19 | 0 | 7 | 14 | 110 | 6 | 28 | 9 | 231 | 269 | 328 | 597 | 96 | 299 | 25 | 3 | 261 | 63 | — | — | — | — | — | — |
| 2024 | 28 | AAA MLE | 2 teams | — | 360 | 341 | 84 | 13 | 3 | 4 | 11 | 71 | 5 | 35 | 7 | 246 | 284 | 337 | 621 | 91 | 293 | 20 | 3 | 275 | 72 | — | — | — | — | — | — |
| 2025 | 29 | AAA MLE | 2 teams | — | 312 | 287 | 60 | 10 | 2 | 2 | 18 | 73 | 4 | 18 | 6 | 209 | 265 | 279 | 543 | 70 | 273 | 23 | 6 | 247 | 54 | — | — | — | — | — | — |
| 2026 | 30 | AAA MLE | 2 teams | — | 429 | 407 | 94 | 13 | 2 | 3 | 16 | 90 | 3 | 25 | 7 | 231 | 267 | 295 | 561 | 64 | 283 | 21 | 4 | 248 | 54 | — | — | — | — | — | — |
| ▸ Model inputs — neutral MLE (past 3 seasons) | |||||||||||||||||||||||||||||||
| 2024 | 28 | AAA MLE | 2 teams | — | 360 | 341 | 84 | 13 | 3 | 4 | 11 | 71 | 5 | 35 | 7 | 246 | 284 | 337 | 621 | 91 | 293 | 20 | 3 | 275 | 72 | — | — | — | — | — | — |
| 2025 | 29 | AAA MLE | 2 teams | — | 312 | 287 | 60 | 10 | 2 | 2 | 18 | 73 | 4 | 18 | 6 | 209 | 265 | 279 | 543 | 70 | 273 | 23 | 6 | 247 | 54 | — | — | — | — | — | — |
| 2026 | 30 | AAA MLE | 2 teams | — | 429 | 407 | 94 | 13 | 2 | 3 | 16 | 90 | 3 | 25 | 7 | 231 | 267 | 295 | 561 | 64 | 283 | 21 | 4 | 248 | 54 | — | — | — | — | — | — |
| ▸ 2027 season | |||||||||||||||||||||||||||||||
| ▸ 2027 — full MLE projection (neutral park, full availability) | |||||||||||||||||||||||||||||||
| 2027 | 31 | MLB MLE | ATL | 10% | 380 | 354 | 88 | 14 | 2 | 6 | 19 | 83 | 4 | 21 | 4 | 247 | 292 | 349 | 642 | 102 | 303 | 22 | 5 | 287 | 80 | -9 | +3 | +0 | +1 | +8 | -0.1 |
| ▸ 2027 — real world (MLB) | |||||||||||||||||||||||||||||||
| 2027 | 31 | MLB CTX | ATL | 10% | 24 | 23 | 5 | 1 | 0 | 0 | 1 | 5 | 0 | 1 | 0 | 247 | 292 | 349 | 642 | 102 | 303 | 21 | 4 | 287 | 80 | -1 | +0 | +0 | +0 | +1 | 0.0 |
| ▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%) | |||||||||||||||||||||||||||||||
| 2028 | 32 | MLB MLE | ATL | 27% | 250 | 234 | 57 | 9 | 1 | 4 | 12 | 56 | 2 | 10 | 2 | 241 | 286 | 336 | 622 | 95 | 299 | 22 | 5 | 279 | 75 | -8 | +1 | -3 | +1 | +5 | -0.4 |
| 2028 | 32 | MLB CTX | ATL | 27% | 68 | 64 | 15 | 2 | 0 | 1 | 3 | 15 | 1 | 3 | 1 | 241 | 286 | 336 | 622 | 95 | 299 | 22 | 4 | 279 | 75 | -2 | +0 | -1 | +0 | +1 | -0.1 |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| ▸ Career totals — MLB only (actual + projected) | |||||||||||||||||||||||||||||||
| Career | — | A+C | — | 504 | 466 | 115 | 21 | 3 | 3 | 27 | 107 | 3 | 23 | 10 | 247 | 292 | 324 | 616 | 77 | 314 | 21 | 5 | 276 | 59 | -16 | +1 | +1 | -9 | +11 | -1.2 | |
| / 162G | — | A+C | — | 650 | 601 | 148 | 27 | 4 | 4 | 35 | 138 | 4 | 30 | 13 | 246 | 292 | 324 | 617 | 78 | 313 | 21 | 5 | 276 | 59 | -21 | +1 | +2 | -11 | +14 | -1.5 | |
| Career | — | MLE | — | 5737 | 5408 | 1269 | 181 | 55 | 45 | 199 | 1502 | 51 | 247 | 87 | 235 | 268 | 313 | 582 | 79 | 313 | 26 | 3 | 255 | 59 | -27 | +3 | -1 | -7 | +20 | -1.2 | |
| / 162G | — | MLE | — | 650 | 613 | 144 | 21 | 6 | 5 | 23 | 170 | 6 | 28 | 10 | 235 | 270 | 313 | 583 | 78 | 313 | 26 | 4 | 255 | 59 | -19 | +2 | -1 | -5 | +14 | -0.8 | |
How the minor-league lines were translated
One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.
2026 AAAGwinnett Stripers · 411 PAwOBA .286 → .242 (−44)K% 17.5% → 21.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 17.52% | ÷1.000 | ×1.200 | — | — | 21.02% |
| BB% (unintentional) /PA | 5.35% | ÷1.000 | ×0.690 | — | ×0.972 | 3.59% |
| HBP% /PA | 0.73% | — | ×0.940 | — | ×0.972 | 0.67% |
| Singles /BIP | 25.57% | ÷1.000 | ×0.930 | ×1.014 | ×0.972 | 23.45% |
| Doubles /BIP | 4.21% | ÷1.000 | ×0.830 | ×1.014 | ×0.972 | 3.44% |
| Triples /BIP | 0.65% | ÷1.000 | ×0.970 | ×1.014 | ×0.972 | 0.62% |
| Home runs /BIP | 1.62% | ÷1.000 | ×0.700 | — | ×0.972 | 1.10% |
Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.014.
Result: wOBA .286 → .242; ISO .084 → .064; BABIP .305 → .275. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
2025 AAASyracuse Mets · 291 PAwOBA .295 → .245 (−50)K% 20.3% → 24.8%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 20.27% | ÷0.981 | ×1.200 | — | — | 24.81% |
| BB% (unintentional) /PA | 8.25% | ÷1.005 | ×0.690 | — | ×0.982 | 5.56% |
| HBP% /PA | 1.37% | — | ×0.940 | — | ×0.982 | 1.27% |
| Singles /BIP | 21.78% | ÷0.975 | ×0.930 | ×1.023 | ×0.982 | 20.86% |
| Doubles /BIP | 6.44% | ÷1.022 | ×0.830 | ×1.023 | ×0.982 | 5.25% |
| Triples /BIP | 0.99% | ÷0.959 | ×0.970 | ×1.023 | ×0.982 | 1.01% |
| Home runs /BIP | 1.98% | ÷1.167 | ×0.700 | — | ×0.982 | 1.17% |
Factors used: league row International League. Park (home-season share, regressed): HR 133, 1B 95, 2B 104, 3B 92, K 96, BB 101 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.023.
Result: wOBA .295 → .245; ISO .111 → .082; BABIP .296 → .273. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
2024 AAASyracuse Mets · 281 PAwOBA .330 → .285 (−45)K% 14.9% → 18.5%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 14.95% | ÷0.968 | ×1.200 | — | — | 18.54% |
| BB% (unintentional) /PA | 2.85% | ÷0.933 | ×0.690 | — | ×0.992 | 2.09% |
| HBP% /PA | 1.78% | — | ×0.940 | — | ×0.992 | 1.66% |
| Singles /BIP | 25.23% | ÷1.006 | ×0.930 | ×0.993 | ×0.992 | 22.99% |
| Doubles /BIP | 5.96% | ÷0.972 | ×0.830 | ×0.993 | ×0.992 | 5.02% |
| Triples /BIP | 1.38% | ÷0.900 | ×0.970 | ×0.993 | ×0.992 | 1.46% |
| Home runs /BIP | 2.75% | ÷1.059 | ×0.700 | — | ×0.992 | 1.80% |
Factors used: league row International League. Park (home-season share, regressed): HR 112, 1B 101, 2B 94, 3B 80, K 94, BB 87 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.
Result: wOBA .330 → .285; ISO .142 → .112; BABIP .326 → .292. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
2023 AAAEl Paso Chihuahuas · 212 PAwOBA .302 → .253 (−49)K% 21.2% → 25.9%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 21.23% | ÷0.985 | ×1.200 | — | — | 25.87% |
| BB% (unintentional) /PA | 4.25% | ÷0.963 | ×0.690 | — | ×1.003 | 3.05% |
| HBP% /PA | 0.94% | — | ×0.940 | — | ×1.003 | 0.89% |
| Singles /BIP | 25.64% | ÷0.958 | ×0.930 | ×0.990 | ×1.003 | 24.72% |
| Doubles /BIP | 5.77% | ÷0.975 | ×0.830 | ×0.990 | ×1.003 | 4.88% |
| Triples /BIP | 0.00% | ÷1.150 | ×0.970 | ×0.990 | ×1.003 | 0.00% |
| Home runs /BIP | 3.21% | ÷1.052 | ×0.700 | — | ×1.003 | 2.14% |
Factors used: league row International League. Park (home-season share, regressed): HR 110, 1B 92, 2B 95, 3B 130, K 97, BB 93 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.990.
Result: wOBA .302 → .253; ISO .119 → .084; BABIP .325 → .302. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
2022 AAAEl Paso Chihuahuas · 105 PAwOBA .372 → .270 (−102)K% 22.9% → 28.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 22.86% | ÷0.959 | ×1.200 | — | — | 28.62% |
| BB% (unintentional) /PA | 6.67% | ÷0.990 | ×0.690 | — | ×1.018 | 4.73% |
| HBP% /PA | 0.00% | — | ×0.940 | — | ×1.018 | 0.00% |
| Singles /BIP | 25.68% | ÷1.047 | ×0.930 | ×0.969 | ×1.018 | 22.51% |
| Doubles /BIP | 8.11% | ÷1.133 | ×0.830 | ×0.969 | ×1.018 | 5.86% |
| Triples /BIP | 0.00% | ÷1.002 | ×0.970 | ×0.969 | ×1.018 | 0.00% |
| Home runs /BIP | 6.76% | ÷1.138 | ×0.700 | — | ×1.018 | 4.23% |
Factors used: league row International League. Park (home-season share, regressed): HR 128, 1B 109, 2B 127, 3B 100, K 92, BB 98 — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.969.
Result: wOBA .372 → .270; ISO .214 → .133; BABIP .362 → .296. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
2021 AASan Antonio Missions · 343 PAwOBA .345 → .300 (−45)K% 20.7% → 26.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 20.70% | ÷0.949 | ×1.220 | — | — | 26.62% |
| BB% (unintentional) /PA | 10.20% | ÷1.028 | ×0.690 | — | ×0.998 | 6.84% |
| HBP% /PA | 1.46% | — | ×0.850 | — | ×0.998 | 1.24% |
| Singles /BIP | 26.09% | ÷0.989 | ×0.940 | ×1.027 | ×0.998 | 25.41% |
| Doubles /BIP | 3.48% | ÷0.925 | ×0.870 | ×1.027 | ×0.998 | 3.35% |
| Triples /BIP | 2.61% | ÷1.071 | ×0.920 | ×1.027 | ×0.998 | 2.30% |
| Home runs /BIP | 3.91% | ÷0.868 | ×0.780 | — | ×0.998 | 3.51% |
Factors used: level-wide AA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 74, 1B 98, 2B 85, 3B 114, K 90, BB 106 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.027.
Result: wOBA .345 → .300; ISO .156 → .138; BABIP .333 → .320. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
2021 AAAEl Paso Chihuahuas · 201 PAwOBA .324 → .279 (−46)K% 22.4% → 28.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 22.39% | ÷0.960 | ×1.200 | — | — | 27.99% |
| BB% (unintentional) /PA | 2.99% | ÷0.980 | ×0.690 | — | ×1.033 | 2.17% |
| HBP% /PA | 0.50% | — | ×0.940 | — | ×1.033 | 0.48% |
| Singles /BIP | 22.76% | ÷1.003 | ×0.930 | ×1.023 | ×1.033 | 22.29% |
| Doubles /BIP | 9.66% | ÷1.116 | ×0.830 | ×1.023 | ×1.033 | 7.58% |
| Triples /BIP | 5.52% | ÷1.099 | ×0.920 | ×1.023 | ×1.033 | 4.88% |
| Home runs /BIP | 0.00% | ÷1.154 | ×0.700 | — | ×1.033 | 0.00% |
Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 131, 1B 101, 2B 123, 3B 120, K 92, BB 96 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.023.
Result: wOBA .324 → .279; ISO .158 → .127; BABIP .369 → .338. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
2019 AAErie SeaWolves · 538 PAwOBA .312 → .260 (−51)K% 24.5% → 30.1%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 24.54% | ÷0.994 | ×1.220 | — | — | 30.10% |
| BB% (unintentional) /PA | 3.72% | ÷1.050 | ×0.700 | — | ×1.027 | 2.54% |
| HBP% /PA | 0.93% | — | ×0.850 | — | ×1.027 | 0.81% |
| Singles /BIP | 29.57% | ÷0.978 | ×0.970 | ×0.950 | ×1.027 | 28.61% |
| Doubles /BIP | 5.65% | ÷1.077 | ×0.860 | ×0.950 | ×1.027 | 4.40% |
| Triples /BIP | 0.81% | ÷1.127 | ×0.950 | ×0.950 | ×1.027 | 0.66% |
| Home runs /BIP | 2.69% | ÷1.294 | ×0.780 | — | ×1.027 | 1.66% |
Factors used: league row EL. Park (home-season share, regressed): HR 159, 1B 96, 2B 115, 3B 125, K 99, BB 110 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.
Result: wOBA .312 → .260; ISO .113 → .076; BABIP .363 → .336. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).
Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .