Jacob Robson
| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR |
|---|---|---|---|---|---|---|---|---|
| 2023 | 28 | INTLSydney Blue S… | 124 | .269/.377/.308 | 0 | 9 | 101 | — |
| 2024 | 29 | INTLBrisbane Band… | 113 | .239/.381/.446 | 5 | 12 | 137 | — |
| 2026 | 31 | INTLCharros de Ja… | 49 | .267/.327/.533 | 2 | 3 | 138 | — |
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) | |||||||||||||||||||||||||||||||
| 2016 | 21 | ROK | GCL Tigers West | — | 118 | 101 | 27 | 4 | 2 | 0 | 16 | 22 | 0 | 14 | 4 | 267 | 368 | 347 | 714 | 79 | 342 | 19 | 14 | 327 | 44 | — | — | — | — | — | — |
| 2017 | 22 | A+ | Lakeland Flying Tigers | — | 255 | 224 | 62 | 11 | 4 | 2 | 23 | 59 | 3 | 16 | 9 | 277 | 352 | 388 | 740 | 112 | 366 | 23 | 9 | 328 | 64 | — | — | — | — | — | — |
| 2017 | 22 | A | West Michigan Whitecaps | — | 267 | 228 | 75 | 10 | 1 | 1 | 31 | 59 | 1 | 5 | 9 | 329 | 412 | 395 | 806 | 66 | 435 | 22 | 12 | 359 | 82 | — | — | — | — | — | — |
| 2018 | 23 | AAA | Toledo Mud Hens | — | 245 | 220 | 67 | 13 | 1 | 4 | 23 | 62 | 0 | 7 | 6 | 305 | 370 | 427 | 798 | 123 | 406 | 25 | 9 | 355 | 102 | — | — | — | — | — | — |
| 2018 | 23 | AA | Erie SeaWolves | — | 311 | 262 | 75 | 16 | 3 | 7 | 39 | 78 | 2 | 11 | 4 | 286 | 383 | 450 | 833 | 164 | 382 | 25 | 13 | 363 | 103 | — | — | — | — | — | — |
| 2018 | 23 | INTL | Estrellas Orientales | — | 29 | 25 | 6 | 0 | 1 | 0 | 4 | 5 | 0 | 2 | 1 | 240 | 345 | 320 | 665 | 80 | 300 | 17 | 14 | 308 | 95 | — | — | — | — | — | — |
| 2019 | 24 | AAA | Toledo Mud Hens | — | 473 | 409 | 109 | 21 | 3 | 9 | 53 | 132 | 3 | 25 | 10 | 267 | 355 | 399 | 753 | 132 | 368 | 28 | 11 | 335 | 79 | — | — | — | — | — | — |
| 2019 | 24 | INTL | Aguilas Cibaenas | — | 76 | 68 | 15 | 3 | 1 | 2 | 6 | 22 | 0 | 1 | 3 | 221 | 284 | 382 | 666 | 162 | 295 | 29 | 8 | 289 | 82 | — | — | — | — | — | — |
| 2020 | 25 | INTL | Sydney Blue Sox | — | 44 | 38 | 7 | 1 | 0 | 1 | 4 | 9 | 1 | 0 | 1 | 184 | 279 | 289 | 569 | 105 | 207 | 20 | 9 | 259 | 62 | — | — | — | — | — | — |
| 2021 | 26 | AAA | Toledo Mud Hens | — | 288 | 239 | 62 | 10 | 3 | 5 | 46 | 104 | 3 | 15 | 9 | 259 | 385 | 389 | 775 | 130 | 438 | 36 | 16 | 355 | 77 | — | — | — | — | — | — |
| 2021 | 26 | AA | Erie SeaWolves | — | 82 | 66 | 28 | 9 | 2 | 2 | 14 | 21 | 1 | 4 | 1 | 424 | 531 | 712 | 1.243 | 288 | 605 | 26 | 17 | 525 | 180 | — | — | — | — | — | — |
| 2022 | 27 | AAA | Toledo Mud Hens | — | 179 | 151 | 29 | 9 | 2 | 3 | 28 | 67 | 0 | 13 | 4 | 192 | 318 | 338 | 656 | 146 | 321 | 37 | 16 | 302 | 41 | — | — | — | — | — | — |
| 2022 | 27 | INTL | Melbourne Aces | — | 141 | 119 | 31 | 7 | 1 | 4 | 20 | 36 | 1 | 9 | 3 | 261 | 371 | 437 | 808 | 176 | 338 | 26 | 14 | 360 | 130 | — | — | — | — | — | — |
| 2023 | 28 | INTL | Sydney Blue Sox | — | 124 | 104 | 28 | 4 | 0 | 0 | 18 | 30 | 0 | 9 | 3 | 269 | 377 | 308 | 685 | 38 | 368 | 24 | 15 | 318 | 101 | — | — | — | — | — | — |
| 2024 | 29 | INTL | Brisbane Bandits | — | 113 | 92 | 22 | 4 | 0 | 5 | 21 | 35 | 0 | 12 | 1 | 239 | 381 | 446 | 826 | 207 | 327 | 31 | 19 | 371 | 137 | — | — | — | — | — | — |
| 2026 | 31 | INTL | Charros de Jalisco | — | 49 | 45 | 12 | 4 | 1 | 2 | 4 | 17 | 0 | 3 | 1 | 267 | 327 | 533 | 860 | 267 | 385 | 35 | 8 | 372 | 138 | — | — | — | — | — | — |
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2016 | 21 | ROK MLE | GCL Tigers West | — | 118 | 107 | 21 | 3 | 1 | 0 | 10 | 32 | 0 | 14 | 4 | 196 | 265 | 243 | 508 | 47 | 279 | 27 | 8 | 233 | 44 | — | — | — | — | — | — |
| 2017 | 22 | A+ MLE | Lakeland Flying Tigers | — | 255 | 232 | 54 | 11 | 3 | 1 | 15 | 84 | 3 | 16 | 9 | 233 | 288 | 319 | 607 | 86 | 345 | 33 | 6 | 263 | 64 | — | — | — | — | — | — |
| 2017 | 22 | A MLE | West Michigan Whitecaps | — | 267 | 240 | 65 | 9 | 1 | 1 | 19 | 82 | 1 | 5 | 9 | 271 | 327 | 329 | 656 | 58 | 385 | 31 | 7 | 289 | 82 | — | — | — | — | — | — |
| 2018 | 23 | AAA MLE | Toledo Mud Hens | — | 245 | 226 | 65 | 11 | 1 | 4 | 17 | 74 | 0 | 7 | 6 | 288 | 337 | 398 | 736 | 111 | 402 | 30 | 7 | 319 | 102 | — | — | — | — | — | — |
| 2018 | 23 | AA MLE | Erie SeaWolves | — | 311 | 275 | 74 | 15 | 3 | 5 | 26 | 95 | 2 | 11 | 4 | 269 | 337 | 400 | 737 | 131 | 378 | 31 | 8 | 320 | 103 | — | — | — | — | — | — |
| 2019 | 24 | AAA MLE | Toledo Mud Hens | — | 473 | 425 | 100 | 18 | 3 | 9 | 37 | 150 | 3 | 25 | 10 | 235 | 301 | 355 | 656 | 120 | 324 | 32 | 8 | 285 | 79 | — | — | — | — | — | — |
| 2021 | 26 | AAA MLE | Toledo Mud Hens | — | 288 | 254 | 56 | 8 | 3 | 3 | 31 | 125 | 3 | 15 | 9 | 220 | 312 | 311 | 624 | 91 | 418 | 43 | 11 | 282 | 77 | — | — | — | — | — | — |
| 2021 | 26 | AA MLE | Erie SeaWolves | — | 82 | 70 | 25 | 8 | 2 | 1 | 10 | 25 | 1 | 4 | 1 | 357 | 444 | 571 | 1.016 | 214 | 531 | 30 | 12 | 434 | 180 | — | — | — | — | — | — |
| 2022 | 27 | AAA MLE | Toledo Mud Hens | — | 179 | 159 | 25 | 7 | 2 | 2 | 20 | 80 | 0 | 13 | 4 | 157 | 251 | 264 | 516 | 107 | 290 | 45 | 11 | 229 | 41 | — | — | — | — | — | — |
| 2016 | 21 | ROK MLE | GCL Tigers West | — | 118 | 107 | 21 | 3 | 1 | 0 | 10 | 32 | 0 | 14 | 4 | 196 | 265 | 243 | 508 | 47 | 280 | 27 | 8 | 233 | 44 | — | — | — | — | — | — |
| 2016 | 21 | ROK RAW | GCL Tigers West | — | 118 | 101 | 27 | 4 | 2 | 0 | 16 | 22 | 0 | 14 | 4 | 267 | 368 | 347 | 714 | 79 | 342 | 19 | 14 | 327 | 44 | — | — | — | — | — | — |
| 2017 | 22 | A MLE | 2 teams | — | 522 | 472 | 119 | 20 | 4 | 2 | 34 | 166 | 4 | 21 | 18 | 252 | 308 | 324 | 632 | 72 | 381 | 32 | 7 | 276 | 73 | — | — | — | — | — | — |
| 2017 | 22 | A RAW | 2 teams | — | 522 | 452 | 137 | 21 | 5 | 3 | 54 | 118 | 4 | 21 | 18 | 303 | 382 | 392 | 774 | 88 | 401 | 23 | 10 | 344 | 73 | — | — | — | — | — | — |
| 2018 | 23 | AA MLE | 3 teams | — | 585 | 528 | 147 | 28 | 5 | 9 | 45 | 177 | 2 | 20 | 11 | 278 | 337 | 402 | 739 | 123 | 401 | 30 | 8 | 320 | 102 | — | — | — | — | — | — |
| 2018 | 23 | AA RAW | 3 teams | — | 585 | 507 | 148 | 29 | 5 | 11 | 66 | 145 | 2 | 20 | 11 | 292 | 376 | 434 | 810 | 142 | 388 | 25 | 11 | 357 | 102 | — | — | — | — | — | — |
| 2019 | 24 | AAA MLE | 2 teams | — | 549 | 493 | 114 | 20 | 3 | 10 | 43 | 174 | 3 | 26 | 13 | 231 | 297 | 345 | 642 | 114 | 332 | 32 | 8 | 285 | 79 | — | — | — | — | — | — |
| 2019 | 24 | AAA RAW | 2 teams | — | 549 | 477 | 124 | 24 | 4 | 11 | 59 | 154 | 3 | 26 | 13 | 260 | 345 | 396 | 741 | 136 | 358 | 28 | 11 | 329 | 79 | — | — | — | — | — | — |
| 2020 | 25 | INTL MLE | Sydney Blue Sox | — | 44 | 38 | 7 | 1 | 0 | 1 | 4 | 9 | 1 | 0 | 1 | 184 | 279 | 289 | 569 | 105 | 207 | 20 | 9 | — | — | — | — | — | — | — | — |
| 2020 | 25 | INTL RAW | Sydney Blue Sox | — | 44 | 38 | 7 | 1 | 0 | 1 | 4 | 9 | 1 | 0 | 1 | 184 | 279 | 289 | 569 | 105 | 207 | 20 | 9 | 259 | 62 | — | — | — | — | — | — |
| 2021 | 26 | AAA MLE | 2 teams | — | 370 | 324 | 82 | 17 | 4 | 5 | 41 | 150 | 4 | 19 | 10 | 253 | 344 | 377 | 721 | 123 | 456 | 41 | 11 | 316 | 100 | — | — | — | — | — | — |
| 2021 | 26 | AAA RAW | 2 teams | — | 370 | 305 | 90 | 19 | 5 | 7 | 60 | 125 | 4 | 19 | 10 | 295 | 417 | 459 | 876 | 164 | 480 | 34 | 16 | 393 | 100 | — | — | — | — | — | — |
| 2022 | 27 | AAA MLE | 2 teams | — | 320 | 282 | 43 | 13 | 3 | 3 | 36 | 143 | 1 | 22 | 7 | 152 | 251 | 252 | 503 | 99 | 292 | 45 | 11 | 229 | 41 | — | — | — | — | — | — |
| 2022 | 27 | AAA RAW | 2 teams | — | 320 | 270 | 60 | 16 | 3 | 7 | 48 | 103 | 1 | 22 | 7 | 222 | 342 | 381 | 723 | 159 | 329 | 32 | 15 | 328 | 41 | — | — | — | — | — | — |
| 2023 | 28 | INTL MLE | Sydney Blue Sox | — | 124 | 104 | 28 | 4 | 0 | 0 | 18 | 30 | 0 | 9 | 3 | 269 | 377 | 308 | 685 | 38 | 368 | 24 | 15 | — | — | — | — | — | — | — | — |
| 2023 | 28 | INTL RAW | Sydney Blue Sox | — | 124 | 104 | 28 | 4 | 0 | 0 | 18 | 30 | 0 | 9 | 3 | 269 | 377 | 308 | 685 | 38 | 368 | 24 | 15 | 318 | 101 | — | — | — | — | — | — |
| 2024 | 29 | INTL MLE | Brisbane Bandits | — | 113 | 92 | 22 | 4 | 0 | 5 | 21 | 35 | 0 | 12 | 1 | 239 | 381 | 446 | 826 | 207 | 327 | 31 | 19 | — | — | — | — | — | — | — | — |
| 2024 | 29 | INTL RAW | Brisbane Bandits | — | 113 | 92 | 22 | 4 | 0 | 5 | 21 | 35 | 0 | 12 | 1 | 239 | 381 | 446 | 826 | 207 | 327 | 31 | 19 | 371 | 137 | — | — | — | — | — | — |
| 2026 | 31 | INTL MLE | Charros de Jalisco | — | 49 | 45 | 12 | 4 | 1 | 2 | 4 | 17 | 0 | 3 | 1 | 267 | 327 | 533 | 860 | 267 | 385 | 35 | 8 | — | — | — | — | — | — | — | — |
| 2026 | 31 | INTL RAW | Charros de Jalisco | — | 49 | 45 | 12 | 4 | 1 | 2 | 4 | 17 | 0 | 3 | 1 | 267 | 327 | 533 | 860 | 267 | 385 | 35 | 8 | 372 | 138 | — | — | — | — | — | — |
| 2016 | 21 | ROK MLE | GCL Tigers West | — | 118 | 107 | 21 | 3 | 1 | 0 | 10 | 32 | 0 | 14 | 4 | 196 | 265 | 243 | 508 | 47 | 279 | 27 | 8 | 233 | 44 | — | — | — | — | — | — |
| 2017 | 22 | A MLE | 2 teams | — | 522 | 479 | 119 | 20 | 4 | 2 | 34 | 166 | 4 | 21 | 18 | 248 | 308 | 319 | 627 | 71 | 365 | 32 | 7 | 276 | 73 | — | — | — | — | — | — |
| 2018 | 23 | AA MLE | 3 teams | — | 585 | 533 | 147 | 28 | 5 | 9 | 45 | 177 | 2 | 20 | 11 | 276 | 337 | 398 | 735 | 122 | 389 | 30 | 8 | 320 | 102 | — | — | — | — | — | — |
| 2019 | 24 | AAA MLE | 2 teams | — | 549 | 498 | 114 | 20 | 3 | 10 | 43 | 174 | 3 | 26 | 13 | 229 | 297 | 341 | 638 | 112 | 324 | 32 | 8 | 285 | 79 | — | — | — | — | — | — |
| 2021 | 26 | AAA MLE | 2 teams | — | 370 | 322 | 82 | 17 | 4 | 5 | 41 | 150 | 4 | 19 | 10 | 255 | 344 | 379 | 723 | 124 | 443 | 41 | 11 | 316 | 100 | — | — | — | — | — | — |
| 2022 | 27 | AAA MLE | 2 teams | — | 320 | 280 | 43 | 13 | 3 | 3 | 36 | 143 | 1 | 22 | 7 | 154 | 251 | 254 | 504 | 100 | 290 | 45 | 11 | 229 | 41 | — | — | — | — | — | — |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| Career | — | MLE | — | 2794 | 2485 | 595 | 114 | 21 | 37 | 256 | 933 | 15 | 146 | 69 | 239 | 314 | 347 | 661 | 107 | 365 | 33 | 9 | 252 | 57 | -143 | +2 | +0 | -19 | +61 | -10.1 | |
| / 162G | — | MLE | — | 650 | 578 | 139 | 27 | 5 | 9 | 60 | 217 | 3 | 34 | 16 | 240 | 315 | 351 | 666 | 111 | 366 | 33 | 9 | 252 | 57 | -33 | +0 | +0 | -4 | +14 | -2.4 | |
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.
2022 AAAToledo Mud Hens · 179 PAwOBA .295 → .229 (−66)K% 37.4% → 44.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 37.43% | ÷1.008 | ×1.200 | — | — | 44.57% |
| BB% (unintentional) /PA | 15.64% | ÷0.964 | ×0.690 | — | ×0.992 | 11.11% |
| HBP% /PA | 0.00% | — | ×0.940 | — | ×0.992 | 0.00% |
| Singles /BIP | 17.86% | ÷1.015 | ×0.930 | ×1.050 | ×0.992 | 17.04% |
| Doubles /BIP | 10.71% | ÷1.015 | ×0.830 | ×1.050 | ×0.992 | 9.13% |
| Triples /BIP | 2.38% | ÷1.150 | ×0.970 | ×1.050 | ×0.992 | 2.09% |
| Home runs /BIP | 3.57% | ÷1.026 | ×0.700 | — | ×0.992 | 2.42% |
Factors used: league row International League. Park (home-season share, regressed): HR 105, 1B 103, 2B 103, 3B 130, K 102, BB 93 — 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 ×1.050.
Result: wOBA .295 → .229; ISO .146 → .108; BABIP .321 → .290. 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 AAAToledo Mud Hens · 288 PAwOBA .347 → .282 (−65)K% 36.1% → 43.3%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 36.11% | ÷1.000 | ×1.200 | — | — | 43.34% |
| BB% (unintentional) /PA | 15.97% | ÷1.038 | ×0.690 | — | ×1.003 | 10.65% |
| HBP% /PA | 1.04% | — | ×0.940 | — | ×1.003 | 0.98% |
| Singles /BIP | 32.59% | ÷0.991 | ×0.930 | ×1.050 | ×1.003 | 32.22% |
| Doubles /BIP | 7.41% | ÷1.013 | ×0.830 | ×1.050 | ×1.003 | 6.39% |
| Triples /BIP | 2.22% | ÷0.981 | ×0.920 | ×1.050 | ×1.003 | 2.19% |
| Home runs /BIP | 3.70% | ÷1.052 | ×0.700 | — | ×1.003 | 2.47% |
Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 110, 1B 98, 2B 103, 3B 96, K 100, BB 108 — 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 ×1.050.
Result: wOBA .347 → .282; ISO .130 → .099; BABIP .438 → .418. 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 AAErie SeaWolves · 82 PAwOBA .511 → .434 (−78)K% 25.6% → 30.4%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 25.61% | ÷1.026 | ×1.220 | — | — | 30.44% |
| BB% (unintentional) /PA | 17.07% | ÷0.945 | ×0.690 | — | ×0.978 | 12.19% |
| HBP% /PA | 1.22% | — | ×0.850 | — | ×0.978 | 1.01% |
| Singles /BIP | 33.33% | ÷1.030 | ×0.940 | — | ×0.978 | 29.76% |
| Doubles /BIP | 20.00% | ÷0.935 | ×0.870 | — | ×0.978 | 18.19% |
| Triples /BIP | 4.44% | ÷1.150 | ×0.920 | — | ×0.978 | 3.48% |
| Home runs /BIP | 4.44% | ÷1.055 | ×0.780 | — | ×0.978 | 3.21% |
Factors used: level-wide AA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 111, 1B 106, 2B 87, 3B 130, K 105, BB 89 — applied at half strength. Age: age 27 vs a level average of 24.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average).
Result: wOBA .511 → .434; ISO .288 → .244; BABIP .605 → .531. 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 AAAToledo Mud Hens · 473 PAwOBA .329 → .285 (−44)K% 27.9% → 31.7%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 27.91% | ÷1.056 | ×1.200 | — | — | 31.72% |
| BB% (unintentional) /PA | 10.99% | ÷1.004 | ×0.690 | — | ×1.033 | 7.81% |
| HBP% /PA | 0.63% | — | ×0.940 | — | ×1.033 | 0.62% |
| Singles /BIP | 27.44% | ÷1.013 | ×0.930 | ×0.950 | ×1.033 | 24.72% |
| Doubles /BIP | 7.58% | ÷0.995 | ×0.830 | ×0.950 | ×1.033 | 6.20% |
| Triples /BIP | 1.08% | ÷1.096 | ×0.970 | ×0.950 | ×1.033 | 0.94% |
| Home runs /BIP | 3.25% | ÷0.888 | ×0.840 | — | ×1.033 | 3.17% |
Factors used: league row IL. Park (home-season share, regressed): HR 78, 1B 103, 2B 99, 3B 119, K 111, BB 101 — 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 ×0.950.
Result: wOBA .329 → .285; ISO .132 → .122; BABIP .368 → .324. 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).
2018 AAErie SeaWolves · 311 PAwOBA .353 → .320 (−33)K% 25.1% → 30.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 25.08% | ÷0.999 | ×1.220 | — | — | 30.64% |
| BB% (unintentional) /PA | 11.90% | ÷1.007 | ×0.700 | — | ×1.012 | 8.37% |
| HBP% /PA | 0.64% | — | ×0.850 | — | ×1.012 | 0.55% |
| Singles /BIP | 26.63% | ÷1.016 | ×0.970 | ×1.050 | ×1.012 | 27.01% |
| Doubles /BIP | 8.70% | ÷0.974 | ×0.860 | ×1.050 | ×1.012 | 8.16% |
| Triples /BIP | 1.63% | ÷0.901 | ×0.950 | ×1.050 | ×1.012 | 1.83% |
| Home runs /BIP | 3.80% | ÷1.112 | ×0.780 | — | ×1.012 | 2.70% |
Factors used: league row EL. Park (home-season share, regressed): HR 122, 1B 103, 2B 95, 3B 80, K 100, BB 101 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.
Result: wOBA .353 → .320; ISO .164 → .143; BABIP .382 → .378. 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).
2018 AAAToledo Mud Hens · 245 PAwOBA .347 → .319 (−28)K% 25.3% → 30.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 25.31% | ÷1.011 | ×1.200 | — | — | 30.05% |
| BB% (unintentional) /PA | 9.39% | ÷0.980 | ×0.690 | — | ×1.048 | 6.92% |
| HBP% /PA | 0.00% | — | ×0.940 | — | ×1.048 | 0.00% |
| Singles /BIP | 31.01% | ÷1.005 | ×0.930 | ×1.050 | ×1.048 | 31.57% |
| Doubles /BIP | 8.23% | ÷1.038 | ×0.830 | ×1.050 | ×1.048 | 7.24% |
| Triples /BIP | 0.63% | ÷1.038 | ×0.970 | ×1.050 | ×1.048 | 0.65% |
| Home runs /BIP | 2.53% | ÷0.893 | ×0.840 | — | ×1.048 | 2.49% |
Factors used: league row IL. Park (home-season share, regressed): HR 79, 1B 101, 2B 108, 3B 108, K 102, BB 96 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.
Result: wOBA .347 → .319; ISO .123 → .112; BABIP .406 → .402. 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).
2017 AWest Michigan Whitecaps · 267 PAwOBA .349 → .289 (−61)K% 22.1% → 30.7%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 22.10% | ÷0.978 | ×1.360 | — | — | 30.72% |
| BB% (unintentional) /PA | 10.49% | ÷0.992 | ×0.690 | — | ×0.990 | 7.22% |
| HBP% /PA | 0.37% | — | ×0.780 | — | ×0.990 | 0.29% |
| Singles /BIP | 37.28% | ÷1.084 | ×0.920 | ×1.050 | ×0.990 | 32.89% |
| Doubles /BIP | 5.92% | ÷0.958 | ×0.830 | ×1.050 | ×0.990 | 5.33% |
| Triples /BIP | 0.59% | ÷1.150 | ×0.910 | ×1.050 | ×0.990 | 0.49% |
| Home runs /BIP | 0.59% | ÷0.849 | ×0.800 | — | ×0.990 | 0.55% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 70, 1B 117, 2B 92, 3B 130, K 96, BB 98 — applied at half strength. Age: age 23 vs a level average of 22.0 → −1.0% on BB/HBP/hit rates (1.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.
Result: wOBA .349 → .289; ISO .066 → .058; BABIP .435 → .385. 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).
2017 A+Lakeland Flying Tigers · 255 PAwOBA .321 → .263 (−59)K% 23.1% → 33.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 23.14% | ÷0.995 | ×1.420 | — | — | 33.03% |
| BB% (unintentional) /PA | 9.02% | ÷1.138 | ×0.750 | — | ×0.998 | 5.93% |
| HBP% /PA | 1.18% | — | ×0.930 | — | ×0.998 | 1.09% |
| Singles /BIP | 27.27% | ÷1.012 | ×0.920 | ×1.027 | ×0.998 | 25.41% |
| Doubles /BIP | 6.67% | ÷0.918 | ×0.960 | ×1.027 | ×0.998 | 7.15% |
| Triples /BIP | 2.42% | ÷1.039 | ×0.810 | ×1.027 | ×0.998 | 1.94% |
| Home runs /BIP | 1.21% | ÷1.747 | ×0.880 | — | ×0.998 | 0.61% |
Factors used: league row FSL. Park (home-season share, regressed): HR 249, 1B 102, 2B 84, 3B 108, K 99, BB 128 — applied at half strength. Age: age 23 vs a level average of 22.8 → −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 .321 → .263; ISO .112 → .088; BABIP .366 → .345. 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 — .