Jake Noll
| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR | MLE AVG/OBP/SLG |
|---|---|---|---|---|---|---|---|---|---|
| 2021 | 27 | AAAWSH | 474 | .300/.349/.494 | 17 | 4 | 84 | — | .247/.285/.386 |
| 2022 | 28 | AAAWSH | 423 | .256/.310/.415 | 10 | 6 | 63 | — | .217/.262/.336 |
| 2023 | 29 | AAAWSH | 213 | .247/.308/.418 | 6 | 0 | 48 | — | .192/.242/.303 |
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 | 22 | A | Hagerstown Suns | — | 126 | 116 | 30 | 4 | 1 | 3 | 7 | 16 | 2 | 2 | 0 | 259 | 312 | 388 | 700 | 129 | 276 | 13 | 6 | 312 | 61 | — | — | — | — | — | — |
| 2016 | 22 | ROK | GCL Nationals | — | 34 | 25 | 6 | 1 | 0 | 1 | 6 | 2 | 1 | 0 | 0 | 240 | 406 | 400 | 806 | 160 | 217 | 6 | 18 | 350 | 72 | — | — | — | — | — | — |
| 2017 | 23 | A+ | Potomac Nationals | — | 65 | 58 | 11 | 2 | 1 | 1 | 5 | 12 | 0 | 0 | 1 | 190 | 254 | 310 | 564 | 121 | 217 | 18 | 8 | 247 | 6 | — | — | — | — | — | — |
| 2017 | 23 | A | Hagerstown Suns | — | 438 | 400 | 108 | 19 | 2 | 16 | 20 | 64 | 8 | 12 | 4 | 270 | 318 | 448 | 765 | 177 | 280 | 15 | 5 | 331 | 66 | — | — | — | — | — | — |
| 2018 | 24 | AA | Harrisburg Senators | — | 260 | 237 | 66 | 8 | 1 | 3 | 14 | 39 | 5 | 4 | 1 | 278 | 332 | 359 | 691 | 80 | 318 | 15 | 5 | 309 | 70 | — | — | — | — | — | — |
| 2018 | 24 | A+ | Potomac Nationals | — | 289 | 265 | 80 | 12 | 3 | 8 | 19 | 51 | 3 | 3 | 1 | 302 | 355 | 460 | 816 | 158 | 346 | 18 | 7 | 360 | 78 | — | — | — | — | — | — |
| 2018 | 24 | INTL | Salt River Rafters | — | 55 | 49 | 13 | 2 | 0 | 2 | 2 | 10 | 2 | 1 | 0 | 265 | 321 | 429 | 749 | 163 | 282 | 18 | 4 | 323 | 104 | — | — | — | — | — | — |
| 2019 | 25 | AAA | Fresno Grizzlies | — | 489 | 456 | 130 | 24 | 0 | 11 | 26 | 89 | 4 | 5 | 2 | 285 | 329 | 410 | 739 | 125 | 331 | 18 | 5 | 329 | 65 | — | — | — | — | — | — |
| 2020 | 26 | MLB | Washington Nationals | — | 17 | 17 | 6 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 353 | 353 | 412 | 765 | 59 | 462 | 24 | 0 | 342 | 117 | +0 | +0 | -1 | -0 | +0 | -0.0 |
| 2021 | 27 | AAA | Rochester Red Wings | — | 474 | 437 | 131 | 28 | 3 | 17 | 29 | 74 | 4 | 4 | 1 | 300 | 349 | 494 | 843 | 195 | 326 | 16 | 6 | 368 | 84 | — | — | — | — | — | — |
| 2022 | 28 | AAA | Rochester Red Wings | — | 423 | 390 | 100 | 26 | 3 | 10 | 20 | 77 | 10 | 6 | 0 | 256 | 310 | 415 | 725 | 159 | 294 | 18 | 5 | 320 | 63 | — | — | — | — | — | — |
| 2023 | 29 | AAA | Rochester Red Wings | — | 213 | 194 | 48 | 15 | 0 | 6 | 15 | 42 | 2 | 0 | 0 | 247 | 308 | 418 | 726 | 170 | 284 | 20 | 7 | 320 | 48 | — | — | — | — | — | — |
| ▸ Career Totals (raw MLB only — historical actual) | |||||||||||||||||||||||||||||||
| MLB Career | — | — | 17 | 17 | 6 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 353 | 353 | 412 | 765 | 59 | 462 | 24 | 0 | 342 | 117 | +0 | +0 | -1 | -0 | +0 | -0.0 | ||
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2016 | 22 | A MLE | Hagerstown Suns | — | 126 | 118 | 27 | 3 | 1 | 2 | 5 | 21 | 2 | 2 | 0 | 229 | 272 | 322 | 594 | 93 | 258 | 17 | 4 | 259 | 61 | — | — | — | — | — | — |
| 2016 | 22 | ROK MLE | GCL Nationals | — | 34 | 27 | 6 | 1 | 0 | 1 | 4 | 3 | 1 | 0 | 0 | 222 | 344 | 370 | 714 | 148 | 169 | 9 | 12 | 275 | 72 | — | — | — | — | — | — |
| 2017 | 23 | A+ MLE | Potomac Nationals | — | 65 | 60 | 9 | 1 | 1 | 1 | 3 | 18 | 0 | 0 | 1 | 150 | 190 | 250 | 440 | 100 | 176 | 28 | 5 | 177 | 6 | — | — | — | — | — | — |
| 2017 | 23 | A MLE | Hagerstown Suns | — | 438 | 408 | 91 | 13 | 2 | 14 | 12 | 85 | 8 | 12 | 4 | 223 | 259 | 368 | 627 | 145 | 233 | 19 | 3 | 266 | 66 | — | — | — | — | — | — |
| 2018 | 24 | AA MLE | Harrisburg Senators | — | 260 | 243 | 63 | 7 | 1 | 3 | 8 | 48 | 5 | 4 | 1 | 259 | 297 | 333 | 630 | 74 | 297 | 18 | 3 | 271 | 70 | — | — | — | — | — | — |
| 2018 | 24 | A+ MLE | Potomac Nationals | — | 289 | 272 | 67 | 9 | 2 | 7 | 12 | 73 | 3 | 3 | 1 | 246 | 286 | 371 | 657 | 125 | 306 | 25 | 4 | 283 | 78 | — | — | — | — | — | — |
| 2019 | 25 | AAA MLE | Fresno Grizzlies | — | 489 | 463 | 109 | 18 | 0 | 9 | 19 | 120 | 4 | 5 | 2 | 235 | 272 | 333 | 604 | 97 | 296 | 25 | 4 | 265 | 65 | — | — | — | — | — | — |
| 2020 | 26 | MLB MLE | Washington Nationals | — | 17 | 17 | 6 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 353 | 353 | 412 | 765 | 59 | 462 | 24 | 0 | 340 | 117 | +0 | +0 | -1 | -0 | +0 | -0.0 |
| 2021 | 27 | AAA MLE | Rochester Red Wings | — | 474 | 446 | 110 | 22 | 2 | 12 | 20 | 91 | 4 | 4 | 1 | 247 | 285 | 386 | 671 | 139 | 281 | 19 | 4 | 292 | 84 | — | — | — | — | — | — |
| 2022 | 28 | AAA MLE | Rochester Red Wings | — | 423 | 396 | 86 | 23 | 3 | 6 | 14 | 88 | 10 | 6 | 0 | 217 | 262 | 336 | 598 | 119 | 259 | 21 | 3 | 262 | 63 | — | — | — | — | — | — |
| 2023 | 29 | AAA MLE | Rochester Red Wings | — | 213 | 198 | 38 | 10 | 0 | 4 | 11 | 51 | 2 | 0 | 0 | 192 | 242 | 303 | 545 | 111 | 234 | 24 | 5 | 239 | 48 | — | — | — | — | — | — |
| 2016 | 22 | A MLE | 2 teams | — | 160 | 146 | 32 | 4 | 1 | 3 | 8 | 24 | 3 | 2 | 0 | 219 | 274 | 322 | 596 | 103 | 240 | 15 | 5 | 262 | 64 | — | — | — | — | — | — |
| 2016 | 22 | A RAW | 2 teams | — | 160 | 141 | 36 | 5 | 1 | 4 | 13 | 18 | 3 | 2 | 0 | 255 | 331 | 390 | 721 | 135 | 264 | 11 | 8 | 320 | 64 | — | — | — | — | — | — |
| 2017 | 23 | A MLE | 2 teams | — | 503 | 468 | 99 | 14 | 2 | 15 | 15 | 103 | 8 | 12 | 5 | 212 | 248 | 346 | 595 | 135 | 234 | 20 | 3 | 254 | 58 | — | — | — | — | — | — |
| 2017 | 23 | A RAW | 2 teams | — | 503 | 458 | 119 | 21 | 3 | 17 | 25 | 76 | 8 | 12 | 5 | 260 | 310 | 430 | 740 | 170 | 273 | 15 | 5 | 320 | 58 | — | — | — | — | — | — |
| 2018 | 24 | A+ MLE | 3 teams | — | 604 | 564 | 142 | 17 | 4 | 10 | 22 | 133 | 10 | 8 | 2 | 252 | 292 | 349 | 641 | 98 | 308 | 22 | 4 | 277 | 74 | — | — | — | — | — | — |
| 2018 | 24 | A+ RAW | 3 teams | — | 604 | 551 | 159 | 22 | 4 | 13 | 35 | 100 | 10 | 8 | 2 | 289 | 342 | 414 | 756 | 125 | 328 | 17 | 6 | 335 | 74 | — | — | — | — | — | — |
| 2019 | 25 | AAA MLE | Fresno Grizzlies | — | 489 | 463 | 109 | 18 | 0 | 9 | 19 | 120 | 4 | 5 | 2 | 235 | 272 | 333 | 604 | 97 | 297 | 25 | 4 | 265 | 65 | — | — | — | — | — | — |
| 2019 | 25 | AAA RAW | Fresno Grizzlies | — | 489 | 456 | 130 | 24 | 0 | 11 | 26 | 89 | 4 | 5 | 2 | 285 | 329 | 410 | 739 | 125 | 331 | 18 | 5 | 329 | 65 | — | — | — | — | — | — |
| 2020 | 26 | MLB MLE | Washington Nationals | — | 17 | 17 | 6 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 353 | 353 | 412 | 765 | 59 | 462 | 24 | 0 | 340 | 117 | +0 | +0 | -1 | -0 | +0 | -0.0 |
| 2020 | 26 | MLB RAW | Washington Nationals | — | 17 | 17 | 6 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 353 | 353 | 412 | 765 | 59 | 462 | 24 | 0 | 342 | 117 | +0 | +0 | -1 | -0 | +0 | -0.0 |
| 2021 | 27 | AAA MLE | Rochester Red Wings | — | 474 | 446 | 110 | 22 | 2 | 12 | 20 | 91 | 4 | 4 | 1 | 247 | 285 | 386 | 671 | 139 | 282 | 19 | 4 | 292 | 84 | — | — | — | — | — | — |
| 2021 | 27 | AAA RAW | Rochester Red Wings | — | 474 | 437 | 131 | 28 | 3 | 17 | 29 | 74 | 4 | 4 | 1 | 300 | 349 | 494 | 843 | 195 | 326 | 16 | 6 | 368 | 84 | — | — | — | — | — | — |
| 2022 | 28 | AAA MLE | Rochester Red Wings | — | 423 | 396 | 86 | 23 | 3 | 6 | 14 | 88 | 10 | 6 | 0 | 217 | 262 | 336 | 598 | 119 | 262 | 21 | 3 | 262 | 63 | — | — | — | — | — | — |
| 2022 | 28 | AAA RAW | Rochester Red Wings | — | 423 | 390 | 100 | 26 | 3 | 10 | 20 | 77 | 10 | 6 | 0 | 256 | 310 | 415 | 725 | 159 | 294 | 18 | 5 | 320 | 63 | — | — | — | — | — | — |
| 2023 | 29 | AAA MLE | Rochester Red Wings | — | 213 | 198 | 38 | 10 | 0 | 4 | 11 | 51 | 2 | 0 | 0 | 192 | 242 | 303 | 545 | 111 | 234 | 24 | 5 | 239 | 48 | — | — | — | — | — | — |
| 2023 | 29 | AAA RAW | Rochester Red Wings | — | 213 | 194 | 48 | 15 | 0 | 6 | 15 | 42 | 2 | 0 | 0 | 247 | 308 | 418 | 726 | 170 | 284 | 20 | 7 | 320 | 48 | — | — | — | — | — | — |
| 2016 | 22 | A MLE | 2 teams | — | 160 | 148 | 32 | 4 | 1 | 3 | 8 | 24 | 3 | 2 | 0 | 216 | 274 | 318 | 591 | 101 | 239 | 15 | 5 | 262 | 64 | — | — | — | — | — | — |
| 2017 | 23 | A MLE | 2 teams | — | 503 | 475 | 99 | 14 | 2 | 15 | 15 | 103 | 8 | 12 | 5 | 208 | 248 | 341 | 590 | 133 | 226 | 20 | 3 | 254 | 58 | — | — | — | — | — | — |
| 2018 | 24 | A+ MLE | 3 teams | — | 604 | 567 | 142 | 17 | 4 | 10 | 22 | 133 | 10 | 8 | 2 | 250 | 292 | 347 | 639 | 97 | 302 | 22 | 4 | 277 | 74 | — | — | — | — | — | — |
| 2019 | 25 | AAA MLE | Fresno Grizzlies | — | 489 | 463 | 109 | 18 | 0 | 9 | 19 | 120 | 4 | 5 | 2 | 235 | 272 | 333 | 604 | 97 | 296 | 25 | 4 | 265 | 65 | — | — | — | — | — | — |
| 2020 | 26 | MLB MLE | Washington Nationals | — | 17 | 17 | 6 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 353 | 353 | 412 | 765 | 59 | 462 | 24 | 0 | 340 | 117 | — | — | — | — | — | — |
| 2021 | 27 | AAA MLE | Rochester Red Wings | — | 474 | 447 | 110 | 22 | 2 | 12 | 20 | 91 | 4 | 4 | 1 | 246 | 285 | 385 | 670 | 139 | 281 | 19 | 4 | 292 | 84 | — | — | — | — | — | — |
| 2022 | 28 | AAA MLE | Rochester Red Wings | — | 423 | 396 | 86 | 23 | 3 | 6 | 14 | 88 | 10 | 6 | 0 | 217 | 262 | 336 | 598 | 119 | 259 | 21 | 3 | 262 | 63 | — | — | — | — | — | — |
| 2023 | 29 | AAA MLE | Rochester Red Wings | — | 213 | 198 | 38 | 10 | 0 | 4 | 11 | 51 | 2 | 0 | 0 | 192 | 242 | 303 | 545 | 111 | 234 | 24 | 5 | 239 | 48 | — | — | — | — | — | — |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| ▸ Career totals — MLB only (actual + projected) | |||||||||||||||||||||||||||||||
| Career | — | A+C | — | 17 | 17 | 6 | 1 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 353 | 353 | 412 | 765 | 59 | 462 | 24 | 0 | 342 | 68 | +0 | +0 | -1 | -0 | +0 | -0.0 | |
| / 162G | — | A+C | — | 650 | 650 | 229 | 38 | 0 | 0 | 0 | 153 | 0 | 0 | 0 | 352 | 352 | 411 | 763 | 58 | 461 | 24 | 0 | 342 | 68 | +13 | +0 | -30 | -12 | +14 | -1.5 | |
| Career | — | MLE | — | 2883 | 2698 | 622 | 109 | 12 | 59 | 109 | 614 | 41 | 37 | 10 | 231 | 271 | 345 | 617 | 115 | 274 | 21 | 4 | 268 | 68 | +0 | +0 | -1 | -0 | +0 | -0.0 | |
| / 162G | — | MLE | — | 650 | 608 | 141 | 25 | 3 | 13 | 25 | 138 | 9 | 8 | 2 | 232 | 273 | 347 | 620 | 115 | 276 | 21 | 4 | 268 | 68 | +13 | +0 | -30 | -12 | +14 | -1.5 | |
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.
2023 AAARochester Red Wings · 213 PAwOBA .314 → .239 (−75)K% 19.7% → 24.1%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 19.72% | ÷0.980 | ×1.200 | — | — | 24.14% |
| BB% (unintentional) /PA | 7.04% | ÷0.956 | ×0.690 | — | ×0.982 | 4.99% |
| HBP% /PA | 0.94% | — | ×0.940 | — | ×0.982 | 0.87% |
| Singles /BIP | 17.76% | ÷0.996 | ×0.930 | ×0.991 | ×0.982 | 16.15% |
| Doubles /BIP | 9.87% | ÷1.137 | ×0.830 | ×0.991 | ×0.982 | 7.01% |
| Triples /BIP | 0.00% | ÷1.150 | ×0.970 | ×0.991 | ×0.982 | 0.00% |
| Home runs /BIP | 3.95% | ÷1.058 | ×0.700 | — | ×0.982 | 2.57% |
Factors used: league row International League. Park (home-season share, regressed): HR 112, 1B 99, 2B 127, 3B 130, K 96, BB 91 — 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 ×0.991.
Result: wOBA .314 → .239; ISO .170 → .113; BABIP .284 → .234. 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 AAARochester Red Wings · 423 PAwOBA .313 → .262 (−51)K% 18.2% → 20.8%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 18.20% | ÷1.049 | ×1.200 | — | — | 20.83% |
| BB% (unintentional) /PA | 4.49% | ÷0.973 | ×0.690 | — | ×0.992 | 3.16% |
| HBP% /PA | 2.36% | — | ×0.940 | — | ×0.992 | 2.20% |
| Singles /BIP | 19.49% | ÷1.011 | ×0.930 | ×0.981 | ×0.992 | 17.45% |
| Doubles /BIP | 8.31% | ÷0.930 | ×0.830 | ×0.981 | ×0.992 | 7.21% |
| Triples /BIP | 0.96% | ÷0.913 | ×0.970 | ×0.981 | ×0.992 | 0.99% |
| Home runs /BIP | 3.19% | ÷1.084 | ×0.700 | — | ×0.992 | 2.05% |
Factors used: league row International League. Park (home-season share, regressed): HR 117, 1B 102, 2B 86, 3B 83, K 110, BB 95 — 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 ×0.981.
Result: wOBA .313 → .262; ISO .159 → .123; BABIP .294 → .259. 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 AAARochester Red Wings · 474 PAwOBA .361 → .292 (−69)K% 15.6% → 19.1%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 15.61% | ÷0.979 | ×1.200 | — | — | 19.13% |
| BB% (unintentional) /PA | 6.12% | ÷1.014 | ×0.690 | — | ×1.003 | 4.17% |
| HBP% /PA | 0.84% | — | ×0.940 | — | ×1.003 | 0.80% |
| Singles /BIP | 22.87% | ÷0.994 | ×0.930 | ×0.962 | ×1.003 | 20.63% |
| Doubles /BIP | 7.71% | ÷1.005 | ×0.830 | ×0.962 | ×1.003 | 6.15% |
| Triples /BIP | 0.83% | ÷1.150 | ×0.920 | ×0.962 | ×1.003 | 0.64% |
| Home runs /BIP | 4.68% | ÷0.968 | ×0.700 | — | ×1.003 | 3.40% |
Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 94, 1B 99, 2B 101, 3B 130, K 96, BB 103 — 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 ×0.962.
Result: wOBA .361 → .292; ISO .195 → .145; BABIP .326 → .281. 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 AAAFresno Grizzlies · 489 PAwOBA .322 → .265 (−57)K% 18.2% → 24.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 18.20% | ÷0.953 | ×1.290 | — | — | 24.64% |
| BB% (unintentional) /PA | 5.32% | ÷0.990 | ×0.710 | — | ×1.033 | 3.94% |
| HBP% /PA | 0.82% | — | ×0.980 | — | ×1.033 | 0.83% |
| Singles /BIP | 25.89% | ÷0.959 | ×0.900 | ×0.950 | ×1.033 | 23.83% |
| Doubles /BIP | 6.54% | ÷0.976 | ×0.810 | ×0.950 | ×1.033 | 5.33% |
| Triples /BIP | 0.00% | ÷1.140 | ×0.810 | ×0.950 | ×1.033 | 0.00% |
| Home runs /BIP | 3.00% | ÷0.962 | ×0.780 | — | ×1.033 | 2.51% |
Factors used: league row PCL. Park (home-season share, regressed): HR 92, 1B 92, 2B 95, 3B 128, K 91, BB 98 — 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 .322 → .265; ISO .125 → .097; BABIP .331 → .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).
2018 A+Potomac Nationals · 289 PAwOBA .352 → .283 (−69)K% 17.6% → 25.1%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 17.65% | ÷0.998 | ×1.420 | — | — | 25.10% |
| BB% (unintentional) /PA | 6.57% | ÷1.013 | ×0.630 | — | ×0.988 | 4.04% |
| HBP% /PA | 1.04% | — | ×0.860 | — | ×0.988 | 0.88% |
| Singles /BIP | 26.64% | ÷0.992 | ×0.940 | ×0.976 | ×0.988 | 24.34% |
| Doubles /BIP | 5.61% | ÷1.020 | ×0.830 | ×0.976 | ×0.988 | 4.40% |
| Triples /BIP | 1.40% | ÷0.900 | ×0.800 | ×0.976 | ×0.988 | 1.20% |
| Home runs /BIP | 3.74% | ÷1.017 | ×0.900 | — | ×0.988 | 3.27% |
Factors used: league row CAR. Park (home-season share, regressed): HR 103, 1B 98, 2B 104, 3B 80, K 100, BB 103 — applied at half strength. Age: age 24 vs a level average of 22.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.976.
Result: wOBA .352 → .283; ISO .158 → .127; BABIP .346 → .306. 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 AAHarrisburg Senators · 260 PAwOBA .302 → .271 (−31)K% 15.0% → 18.5%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 15.00% | ÷0.987 | ×1.220 | — | — | 18.54% |
| BB% (unintentional) /PA | 4.62% | ÷1.037 | ×0.700 | — | ×1.012 | 3.15% |
| HBP% /PA | 1.92% | — | ×0.850 | — | ×1.012 | 1.65% |
| Singles /BIP | 27.27% | ÷1.017 | ×0.970 | ×0.982 | ×1.012 | 25.87% |
| Doubles /BIP | 4.04% | ÷1.012 | ×0.860 | ×0.982 | ×1.012 | 3.41% |
| Triples /BIP | 0.51% | ÷1.070 | ×0.950 | ×0.982 | ×1.012 | 0.45% |
| Home runs /BIP | 1.52% | ÷0.925 | ×0.780 | — | ×1.012 | 1.29% |
Factors used: league row EL. Park (home-season share, regressed): HR 85, 1B 103, 2B 102, 3B 114, K 97, BB 107 — 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 ×0.982.
Result: wOBA .302 → .271; ISO .080 → .069; BABIP .318 → .297. 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 AHagerstown Suns · 438 PAwOBA .328 → .266 (−62)K% 14.6% → 19.4%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 14.61% | ÷1.009 | ×1.340 | — | — | 19.41% |
| BB% (unintentional) /PA | 4.57% | ÷1.101 | ×0.660 | — | ×0.990 | 2.71% |
| HBP% /PA | 1.83% | — | ×0.770 | — | ×0.990 | 1.39% |
| Singles /BIP | 21.13% | ÷0.986 | ×0.920 | ×0.952 | ×0.990 | 18.57% |
| Doubles /BIP | 5.65% | ÷1.156 | ×0.820 | ×0.952 | ×0.990 | 3.78% |
| Triples /BIP | 0.60% | ÷1.043 | ×0.940 | ×0.952 | ×0.990 | 0.51% |
| Home runs /BIP | 4.76% | ÷0.909 | ×0.820 | — | ×0.990 | 4.25% |
Factors used: league row SAL. Park (home-season share, regressed): HR 82, 1B 97, 2B 131, 3B 109, K 102, BB 120 — 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 ×0.952.
Result: wOBA .328 → .266; ISO .177 → .147; BABIP .280 → .233. 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+Potomac Nationals · 65 PAwOBA .245 → .177 (−68)K% 18.5% → 27.2%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 18.46% | ÷0.963 | ×1.420 | — | — | 27.21% |
| BB% (unintentional) /PA | 7.69% | ÷0.982 | ×0.630 | — | ×0.998 | 4.92% |
| HBP% /PA | 0.00% | — | ×0.860 | — | ×0.998 | 0.00% |
| Singles /BIP | 15.22% | ÷1.050 | ×0.940 | ×0.950 | ×0.998 | 12.92% |
| Doubles /BIP | 4.35% | ÷1.012 | ×0.830 | ×0.950 | ×0.998 | 3.38% |
| Triples /BIP | 2.17% | ÷1.150 | ×0.800 | ×0.950 | ×0.998 | 1.43% |
| Home runs /BIP | 2.17% | ÷1.368 | ×0.900 | — | ×0.998 | 1.43% |
Factors used: league row CAR. Park (home-season share, regressed): HR 174, 1B 110, 2B 102, 3B 130, K 93, BB 96 — 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 ×0.950.
Result: wOBA .245 → .177; ISO .121 → .080; BABIP .217 → .176. 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 — .