Mike Gerber
| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR | MLE AVG/OBP/SLG | |
|---|---|---|---|---|---|---|---|---|---|---|
| 2017 | 25 | AAA/AA/A+DET | 432 | .304/.375/.496 | 14 | 10 | 89 | — | .255/.308/.395 | |
| 2018 | 26 | AAADET | 316 | .213/.278/.411 | 13 | 2 | 53 | — | .177/.230/.348 | |
| 2018 | 26 | MLBDET | 47 | .095/.174/.119 | 0 | 0 | -15 | -1.0 | ||
| 2019 | 27 | AAASF | 513 | .308/.371/.569 | 26 | 5 | 84 | — | .225/.278/.404 | |
| 2019 | 27 | MLBSF | 26 | .042/.115/.083 | 0 | 0 | -44 | -1.0 | ||
| 2020 | 28 | No MLB games played | ||||||||
| 2021 | 29 | No MLB games played | ||||||||
| 2022 | 30 | No MLB games played | ||||||||
| 2023 | 31 | No MLB games played | ||||||||
| 2024 | 32 | No MLB games played | ||||||||
| 2025 | 33 | No MLB games played | ||||||||
| 2026 | 34 | No MLB games played | ||||||||
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) | |||||||||||||||||||||||||||||||
| 2014 | 22 | A | West Michigan Whitecaps | — | 35 | 31 | 12 | 3 | 0 | 0 | 4 | 3 | 0 | 1 | 0 | 387 | 457 | 484 | 941 | 97 | 429 | 9 | 11 | 423 | 124 | — | — | — | — | — | — |
| 2015 | 23 | A | West Michigan Whitecaps | — | 583 | 513 | 150 | 31 | 10 | 13 | 49 | 97 | 7 | 16 | 4 | 292 | 362 | 468 | 830 | 175 | 330 | 17 | 8 | 359 | 84 | — | — | — | — | — | — |
| 2015 | 23 | INTL | Scottsdale Scorpions | — | 89 | 75 | 21 | 5 | 2 | 1 | 11 | 23 | 1 | 4 | 0 | 280 | 379 | 440 | 819 | 160 | 377 | 26 | 12 | 358 | 129 | — | — | — | — | — | — |
| 2016 | 24 | AA | Erie SeaWolves | — | 175 | 153 | 40 | 8 | 3 | 4 | 20 | 41 | 1 | 6 | 0 | 261 | 351 | 431 | 782 | 170 | 330 | 23 | 11 | 347 | 78 | — | — | — | — | — | — |
| 2016 | 24 | A+ | Lakeland Flying Tigers | — | 388 | 351 | 99 | 22 | 3 | 14 | 32 | 111 | 2 | 2 | 3 | 282 | 345 | 481 | 827 | 199 | 371 | 29 | 8 | 362 | 61 | — | — | — | — | — | — |
| 2017 | 25 | AAA | Toledo Mud Hens | — | 18 | 17 | 7 | 2 | 0 | 1 | 1 | 6 | 0 | 0 | 0 | 412 | 444 | 706 | 1.150 | 294 | 600 | 33 | 6 | 498 | 153 | — | — | — | — | — | — |
| 2017 | 25 | AA | Erie SeaWolves | — | 394 | 350 | 102 | 22 | 2 | 13 | 39 | 85 | 2 | 10 | 6 | 291 | 366 | 477 | 843 | 186 | 349 | 22 | 10 | 371 | 84 | — | — | — | — | — | — |
| 2017 | 25 | A+ | Lakeland Flying Tigers | — | 20 | 18 | 8 | 2 | 1 | 0 | 2 | 7 | 0 | 0 | 0 | 444 | 500 | 667 | 1.167 | 222 | 727 | 35 | 10 | 505 | 122 | — | — | — | — | — | — |
| 2018 | 26 | MLB | Detroit Tigers | — | 47 | 42 | 4 | 1 | 0 | 0 | 4 | 21 | 0 | 0 | 0 | 95 | 174 | 119 | 293 | 24 | 182 | 45 | 9 | 144 | -15 | -6 | +0 | -1 | -4 | +1 | -1.0 |
| 2018 | 26 | AAA | Toledo Mud Hens | — | 316 | 287 | 61 | 14 | 2 | 13 | 22 | 103 | 4 | 2 | 2 | 213 | 278 | 411 | 689 | 199 | 279 | 33 | 7 | 302 | 53 | — | — | — | — | — | — |
| 2019 | 27 | MLB | San Francisco Giants | — | 26 | 24 | 1 | 1 | 0 | 0 | 2 | 15 | 0 | 0 | 0 | 42 | 115 | 83 | 199 | 42 | 111 | 58 | 8 | 103 | -44 | -4 | +0 | -1 | -6 | +1 | -1.0 |
| 2019 | 27 | AAA | Sacramento River Cats | — | 513 | 464 | 143 | 41 | 1 | 26 | 39 | 140 | 7 | 5 | 4 | 308 | 371 | 569 | 940 | 261 | 389 | 27 | 8 | 407 | 84 | — | — | — | — | — | — |
| ▸ Career Totals (raw MLB only — historical actual) | |||||||||||||||||||||||||||||||
| MLB Career | — | — | 73 | 66 | 5 | 2 | 0 | 0 | 6 | 36 | 0 | 0 | 0 | 76 | 153 | 106 | 259 | 30 | 161 | 49 | 8 | 130 | -26 | -11 | +0 | -1 | -10 | +2 | -2.1 | ||
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2014 | 22 | A MLE | West Michigan Whitecaps | — | 35 | 32 | 11 | 3 | 0 | 0 | 3 | 4 | 0 | 1 | 0 | 344 | 400 | 438 | 838 | 94 | 385 | 11 | 9 | 351 | 124 | — | — | — | — | — | — |
| 2015 | 23 | A MLE | West Michigan Whitecaps | — | 583 | 531 | 131 | 26 | 8 | 11 | 31 | 135 | 7 | 16 | 4 | 247 | 297 | 388 | 685 | 141 | 289 | 23 | 5 | 293 | 84 | — | — | — | — | — | — |
| 2016 | 24 | AA MLE | Erie SeaWolves | — | 175 | 160 | 37 | 7 | 3 | 3 | 13 | 50 | 1 | 6 | 0 | 231 | 293 | 369 | 662 | 138 | 307 | 29 | 7 | 284 | 78 | — | — | — | — | — | — |
| 2016 | 24 | A+ MLE | Lakeland Flying Tigers | — | 388 | 360 | 74 | 17 | 2 | 9 | 23 | 156 | 2 | 2 | 3 | 206 | 257 | 339 | 596 | 133 | 320 | 40 | 6 | 258 | 61 | — | — | — | — | — | — |
| 2017 | 25 | AAA MLE | Toledo Mud Hens | — | 18 | 17 | 6 | 2 | 0 | 1 | 1 | 7 | 0 | 0 | 0 | 353 | 389 | 647 | 1.036 | 294 | 542 | 39 | 6 | 395 | 153 | — | — | — | — | — | — |
| 2017 | 25 | AA MLE | Erie SeaWolves | — | 394 | 363 | 89 | 19 | 2 | 8 | 26 | 106 | 2 | 10 | 6 | 245 | 299 | 375 | 674 | 129 | 317 | 27 | 7 | 292 | 84 | — | — | — | — | — | — |
| 2017 | 25 | A+ MLE | Lakeland Flying Tigers | — | 20 | 19 | 7 | 2 | 1 | 0 | 1 | 10 | 0 | 0 | 0 | 368 | 400 | 579 | 979 | 211 | 659 | 50 | 5 | 348 | 122 | — | — | — | — | — | — |
| 2018 | 26 | MLB MLE | Detroit Tigers | — | 47 | 42 | 4 | 1 | 0 | 0 | 4 | 21 | 0 | 0 | 0 | 95 | 174 | 119 | 293 | 24 | 182 | 45 | 9 | 146 | -15 | -6 | +0 | -1 | -4 | +1 | -1.0 |
| 2018 | 26 | AAA MLE | Toledo Mud Hens | — | 316 | 293 | 52 | 10 | 2 | 12 | 16 | 122 | 4 | 2 | 2 | 177 | 230 | 348 | 578 | 171 | 244 | 39 | 5 | 246 | 53 | — | — | — | — | — | — |
| 2019 | 27 | MLB MLE | San Francisco Giants | — | 26 | 24 | 1 | 1 | 0 | 0 | 2 | 15 | 0 | 0 | 0 | 42 | 115 | 83 | 199 | 42 | 111 | 58 | 8 | 103 | -44 | -4 | +0 | -1 | -6 | +1 | -1.0 |
| 2019 | 27 | AAA MLE | Sacramento River Cats | — | 513 | 475 | 107 | 29 | 1 | 18 | 28 | 186 | 7 | 5 | 4 | 225 | 278 | 404 | 683 | 179 | 320 | 36 | 5 | 293 | 84 | — | — | — | — | — | — |
| 2014 | 22 | A MLE | West Michigan Whitecaps | — | 35 | 32 | 11 | 3 | 0 | 0 | 3 | 4 | 0 | 1 | 0 | 344 | 400 | 438 | 838 | 94 | 393 | 11 | 9 | 351 | 124 | — | — | — | — | — | — |
| 2014 | 22 | A RAW | West Michigan Whitecaps | — | 35 | 31 | 12 | 3 | 0 | 0 | 4 | 3 | 0 | 1 | 0 | 387 | 457 | 484 | 941 | 97 | 429 | 9 | 11 | 423 | 124 | — | — | — | — | — | — |
| 2015 | 23 | A MLE | 2 teams | — | 672 | 612 | 150 | 30 | 9 | 12 | 36 | 156 | 8 | 20 | 4 | 245 | 296 | 382 | 678 | 137 | 301 | 23 | 5 | 293 | 84 | — | — | — | — | — | — |
| 2015 | 23 | A RAW | 2 teams | — | 672 | 588 | 171 | 36 | 12 | 14 | 60 | 120 | 8 | 20 | 4 | 291 | 364 | 464 | 829 | 173 | 335 | 18 | 9 | 359 | 84 | — | — | — | — | — | — |
| 2016 | 24 | A+ MLE | 2 teams | — | 563 | 520 | 109 | 24 | 4 | 12 | 36 | 206 | 3 | 8 | 3 | 210 | 265 | 340 | 605 | 131 | 317 | 37 | 6 | 266 | 66 | — | — | — | — | — | — |
| 2016 | 24 | A+ RAW | 2 teams | — | 563 | 504 | 139 | 30 | 6 | 18 | 52 | 152 | 3 | 8 | 3 | 276 | 347 | 466 | 813 | 190 | 358 | 27 | 9 | 357 | 66 | — | — | — | — | — | — |
| 2017 | 25 | AA MLE | 3 teams | — | 432 | 399 | 101 | 23 | 2 | 9 | 28 | 124 | 2 | 10 | 6 | 253 | 305 | 388 | 694 | 135 | 342 | 29 | 6 | 299 | 88 | — | — | — | — | — | — |
| 2017 | 25 | AA RAW | 3 teams | — | 432 | 385 | 117 | 26 | 3 | 14 | 42 | 98 | 2 | 10 | 6 | 304 | 375 | 496 | 871 | 192 | 373 | 23 | 10 | 382 | 88 | — | — | — | — | — | — |
| 2018 | 26 | AAA MLE | 2 teams | — | 363 | 335 | 56 | 11 | 2 | 12 | 20 | 143 | 4 | 2 | 2 | 167 | 223 | 319 | 542 | 152 | 242 | 39 | 6 | 233 | 44 | — | — | — | — | — | — |
| 2018 | 26 | AAA RAW | 2 teams | — | 363 | 329 | 65 | 15 | 2 | 13 | 26 | 124 | 4 | 2 | 2 | 198 | 265 | 374 | 638 | 176 | 268 | 34 | 7 | 282 | 44 | — | — | — | — | — | — |
| 2019 | 27 | AAA MLE | 2 teams | — | 539 | 499 | 108 | 30 | 1 | 18 | 30 | 201 | 7 | 5 | 4 | 216 | 271 | 389 | 659 | 172 | 318 | 37 | 6 | 284 | 78 | — | — | — | — | — | — |
| 2019 | 27 | AAA RAW | 2 teams | — | 539 | 488 | 144 | 42 | 1 | 26 | 41 | 155 | 7 | 5 | 4 | 295 | 358 | 545 | 903 | 250 | 381 | 29 | 8 | 392 | 78 | — | — | — | — | — | — |
| 2014 | 22 | A MLE | West Michigan Whitecaps | — | 35 | 32 | 11 | 3 | 0 | 0 | 3 | 4 | 0 | 1 | 0 | 344 | 400 | 438 | 838 | 94 | 385 | 11 | 9 | 351 | 124 | — | — | — | — | — | — |
| 2015 | 23 | A MLE | 2 teams | — | 672 | 623 | 150 | 30 | 9 | 12 | 36 | 156 | 8 | 20 | 4 | 241 | 296 | 376 | 671 | 135 | 289 | 23 | 5 | 293 | 84 | — | — | — | — | — | — |
| 2016 | 24 | A+ MLE | 2 teams | — | 563 | 519 | 109 | 24 | 4 | 12 | 36 | 206 | 3 | 8 | 3 | 210 | 265 | 341 | 606 | 131 | 316 | 37 | 6 | 266 | 66 | — | — | — | — | — | — |
| 2017 | 25 | AA MLE | 3 teams | — | 432 | 399 | 101 | 23 | 2 | 9 | 28 | 124 | 2 | 10 | 6 | 253 | 305 | 388 | 694 | 135 | 342 | 29 | 6 | 299 | 88 | — | — | — | — | — | — |
| 2018 | 26 | AAA MLE | 2 teams | — | 363 | 336 | 56 | 11 | 2 | 12 | 20 | 143 | 4 | 2 | 2 | 167 | 223 | 318 | 541 | 152 | 236 | 39 | 6 | 233 | 44 | — | — | — | — | — | — |
| 2019 | 27 | AAA MLE | 2 teams | — | 539 | 497 | 108 | 30 | 1 | 18 | 30 | 201 | 7 | 5 | 4 | 217 | 271 | 390 | 661 | 173 | 310 | 37 | 6 | 284 | 78 | — | — | — | — | — | — |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| ▸ Career totals — MLB only (actual + projected) | |||||||||||||||||||||||||||||||
| Career | — | A+C | — | 73 | 66 | 5 | 2 | 0 | 0 | 6 | 36 | 0 | 0 | 0 | 76 | 153 | 106 | 259 | 30 | 161 | 49 | 8 | 130 | 75 | -11 | +0 | -1 | -10 | +2 | -2.1 | |
| / 162G | — | A+C | — | 650 | 588 | 45 | 18 | 0 | 0 | 53 | 321 | 0 | 0 | 0 | 77 | 153 | 107 | 260 | 31 | 163 | 49 | 8 | 130 | 75 | -97 | +0 | -10 | -86 | +14 | -18.3 | |
| Career | — | MLE | — | 2604 | 2397 | 535 | 121 | 18 | 63 | 153 | 834 | 24 | 46 | 19 | 223 | 277 | 368 | 644 | 144 | 309 | 32 | 6 | 279 | 75 | -11 | +0 | -1 | -10 | +2 | -2.1 | |
| / 162G | — | MLE | — | 650 | 598 | 133 | 30 | 4 | 16 | 38 | 208 | 6 | 11 | 5 | 222 | 275 | 366 | 641 | 144 | 308 | 32 | 6 | 279 | 75 | -97 | +0 | -10 | -86 | +14 | -18.3 | |
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.
2019 AAASacramento River Cats · 513 PAwOBA .397 → .293 (−104)K% 27.3% → 36.2%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 27.29% | ÷0.971 | ×1.290 | — | — | 36.24% |
| BB% (unintentional) /PA | 7.60% | ÷0.980 | ×0.710 | — | ×1.003 | 5.52% |
| HBP% /PA | 1.36% | — | ×0.980 | — | ×1.003 | 1.34% |
| Singles /BIP | 23.15% | ÷0.982 | ×0.900 | ×0.950 | ×1.003 | 20.21% |
| Doubles /BIP | 12.65% | ÷0.981 | ×0.810 | ×0.950 | ×1.003 | 9.96% |
| Triples /BIP | 0.31% | ÷1.008 | ×0.810 | ×0.950 | ×1.003 | 0.24% |
| Home runs /BIP | 8.02% | ÷1.027 | ×0.780 | — | ×1.003 | 6.11% |
Factors used: league row PCL. Park (home-season share, regressed): HR 105, 1B 96, 2B 96, 3B 102, K 94, BB 96 — 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 ×0.950.
Result: wOBA .397 → .293; ISO .261 → .181; BABIP .389 → .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).
2018 AAAToledo Mud Hens · 316 PAwOBA .295 → .246 (−49)K% 32.6% → 38.7%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 32.59% | ÷1.011 | ×1.200 | — | — | 38.70% |
| BB% (unintentional) /PA | 6.96% | ÷0.980 | ×0.690 | — | ×1.018 | 4.99% |
| HBP% /PA | 1.27% | — | ×0.940 | — | ×1.018 | 1.21% |
| Singles /BIP | 17.39% | ÷1.005 | ×0.930 | ×0.971 | ×1.018 | 15.91% |
| Doubles /BIP | 7.61% | ÷1.038 | ×0.830 | ×0.971 | ×1.018 | 6.01% |
| Triples /BIP | 1.09% | ÷1.038 | ×0.970 | ×0.971 | ×1.018 | 1.00% |
| Home runs /BIP | 7.07% | ÷0.893 | ×0.840 | — | ×1.018 | 6.76% |
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 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 ×0.971.
Result: wOBA .295 → .246; ISO .199 → .172; BABIP .279 → .244. 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 AAErie SeaWolves · 394 PAwOBA .364 → .292 (−71)K% 21.6% → 27.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 21.57% | ÷0.973 | ×1.220 | — | — | 27.05% |
| BB% (unintentional) /PA | 9.90% | ÷1.059 | ×0.700 | — | ×0.998 | 6.53% |
| HBP% /PA | 0.51% | — | ×0.850 | — | ×0.998 | 0.43% |
| Singles /BIP | 24.53% | ÷1.020 | ×0.970 | ×0.989 | ×0.998 | 23.01% |
| Doubles /BIP | 8.30% | ÷0.944 | ×0.860 | ×0.989 | ×0.998 | 7.46% |
| Triples /BIP | 0.75% | ÷1.094 | ×0.950 | ×0.989 | ×0.998 | 0.65% |
| Home runs /BIP | 4.91% | ÷1.259 | ×0.780 | — | ×0.998 | 3.03% |
Factors used: league row EL. Park (home-season share, regressed): HR 152, 1B 104, 2B 89, 3B 119, K 95, BB 112 — 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 ×0.989.
Result: wOBA .364 → .292; ISO .186 → .133; BABIP .349 → .317. 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 · 20 PAwOBA .492 → .348 (−144)K% 35.0% → 50.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 35.00% | ÷0.995 | ×1.420 | — | — | 49.97% |
| BB% (unintentional) /PA | 10.00% | ÷1.138 | ×0.750 | — | ×0.978 | 6.45% |
| HBP% /PA | 0.00% | — | ×0.930 | — | ×0.978 | 0.00% |
| Singles /BIP | 45.45% | ÷1.012 | ×0.920 | — | ×0.978 | 40.41% |
| Doubles /BIP | 18.18% | ÷0.918 | ×0.960 | — | ×0.978 | 18.59% |
| Triples /BIP | 9.09% | ÷1.039 | ×0.810 | — | ×0.978 | 6.93% |
| Home runs /BIP | 0.00% | ÷1.747 | ×0.880 | — | ×0.978 | 0.00% |
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 25 vs a level average of 22.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average).
Result: wOBA .492 → .348; ISO .222 → .157; BABIP .727 → .659. 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 AAAToledo Mud Hens · 18 PAwOBA .484 → .395 (−89)K% 33.3% → 39.8%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 33.33% | ÷1.004 | ×1.200 | — | — | 39.84% |
| BB% (unintentional) /PA | 5.56% | ÷0.996 | ×0.690 | — | ×1.033 | 3.98% |
| HBP% /PA | 0.00% | — | ×0.940 | — | ×1.033 | 0.00% |
| Singles /BIP | 36.36% | ÷1.054 | ×0.930 | — | ×1.033 | 33.15% |
| Doubles /BIP | 18.18% | ÷0.916 | ×0.830 | — | ×1.033 | 17.02% |
| Triples /BIP | 0.00% | ÷1.150 | ×0.970 | — | ×1.033 | 0.00% |
| Home runs /BIP | 9.09% | ÷1.049 | ×0.840 | — | ×1.033 | 7.52% |
Factors used: league row IL. Park (home-season share, regressed): HR 110, 1B 111, 2B 83, 3B 130, K 101, BB 99 — 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).
Result: wOBA .484 → .395; ISO .294 → .235; BABIP .600 → .542. 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).
2016 A+Lakeland Flying Tigers · 388 PAwOBA .354 → .258 (−95)K% 28.6% → 40.2%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 28.61% | ÷1.011 | ×1.420 | — | — | 40.16% |
| BB% (unintentional) /PA | 7.99% | ÷1.026 | ×0.750 | — | ×0.988 | 5.77% |
| HBP% /PA | 0.52% | — | ×0.930 | — | ×0.988 | 0.47% |
| Singles /BIP | 25.00% | ÷0.995 | ×0.920 | ×0.965 | ×0.988 | 22.04% |
| Doubles /BIP | 9.17% | ÷1.029 | ×0.960 | ×0.965 | ×0.988 | 8.16% |
| Triples /BIP | 1.25% | ÷1.145 | ×0.810 | ×0.965 | ×0.988 | 0.84% |
| Home runs /BIP | 5.83% | ÷1.161 | ×0.880 | — | ×0.988 | 4.37% |
Factors used: league row FSL. Park (home-season share, regressed): HR 132, 1B 99, 2B 106, 3B 129, K 102, BB 105 — 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 ×0.965.
Result: wOBA .354 → .258; ISO .199 → .136; BABIP .371 → .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).
2016 AAErie SeaWolves · 175 PAwOBA .338 → .284 (−54)K% 23.4% → 28.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 23.43% | ÷0.998 | ×1.220 | — | — | 28.64% |
| BB% (unintentional) /PA | 10.86% | ÷1.027 | ×0.700 | — | ×1.012 | 7.49% |
| HBP% /PA | 0.57% | — | ×0.850 | — | ×1.012 | 0.49% |
| Singles /BIP | 22.32% | ÷1.045 | ×0.970 | ×1.017 | ×1.012 | 21.33% |
| Doubles /BIP | 7.14% | ÷0.973 | ×0.860 | ×1.017 | ×1.012 | 6.50% |
| Triples /BIP | 2.68% | ÷1.127 | ×0.950 | ×1.017 | ×1.012 | 2.32% |
| Home runs /BIP | 3.57% | ÷1.095 | ×0.780 | — | ×1.012 | 2.57% |
Factors used: league row EL. Park (home-season share, regressed): HR 119, 1B 109, 2B 95, 3B 125, K 100, BB 105 — 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 ×1.017.
Result: wOBA .338 → .284; ISO .170 → .137; BABIP .330 → .307. 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).
2015 AWest Michigan Whitecaps · 583 PAwOBA .355 → .293 (−62)K% 16.6% → 23.2%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 16.64% | ÷0.977 | ×1.360 | — | — | 23.16% |
| BB% (unintentional) /PA | 7.89% | ÷1.006 | ×0.690 | — | ×0.990 | 5.36% |
| HBP% /PA | 1.20% | — | ×0.780 | — | ×0.990 | 0.93% |
| Singles /BIP | 23.08% | ÷0.996 | ×0.920 | ×0.986 | ×0.990 | 20.82% |
| Doubles /BIP | 7.45% | ÷0.969 | ×0.830 | ×0.986 | ×0.990 | 6.23% |
| Triples /BIP | 2.40% | ÷1.128 | ×0.910 | ×0.986 | ×0.990 | 1.89% |
| Home runs /BIP | 3.12% | ÷0.954 | ×0.800 | — | ×0.990 | 2.59% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 91, 1B 99, 2B 94, 3B 126, K 95, BB 101 — 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 ×0.986.
Result: wOBA .355 → .293; ISO .175 → .143; BABIP .330 → .289. 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).