Bryant Flete
| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR |
|---|---|---|---|---|---|---|---|---|
| 2022 | 29 | INTLAguilas del Z… | 183 | .319/.483/.452 | 1 | 0 | 167 | — |
| 2023 | 30 | INTLAguilas del Z… | 82 | .262/.407/.431 | 0 | 0 | 139 | — |
| 2024 | 31 | INTLGigantes de C… | 32 | .233/.258/.267 | 0 | 0 | 43 | — |
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) | |||||||||||||||||||||||||||||||
| 2012 | 19 | ROK | DSL Cubs 2 | — | 220 | 179 | 53 | 5 | 7 | 1 | 33 | 26 | 5 | 10 | 9 | 296 | 419 | 419 | 838 | 123 | 342 | 12 | 15 | 376 | 61 | — | — | — | — | — | — |
| 2013 | 20 | ROK | DSL Cubs | — | 327 | 269 | 70 | 11 | 5 | 0 | 47 | 46 | 5 | 18 | 14 | 260 | 380 | 338 | 718 | 78 | 310 | 14 | 14 | 329 | 38 | — | — | — | — | — | — |
| 2014 | 21 | ROK | AZL Cubs | — | 62 | 54 | 17 | 2 | 0 | 0 | 6 | 9 | 1 | 3 | 0 | 315 | 393 | 352 | 745 | 37 | 378 | 15 | 10 | 340 | 54 | — | — | — | — | — | — |
| 2015 | 22 | AA | Tennessee Smokies | — | 145 | 123 | 24 | 3 | 1 | 1 | 18 | 27 | 1 | 0 | 1 | 195 | 303 | 260 | 563 | 65 | 242 | 19 | 12 | 262 | 41 | — | — | — | — | — | — |
| 2015 | 22 | A | South Bend Cubs | — | 43 | 40 | 3 | 1 | 0 | 0 | 2 | 12 | 0 | 1 | 0 | 75 | 119 | 100 | 219 | 25 | 107 | 28 | 5 | 104 | -64 | — | — | — | — | — | — |
| 2015 | 22 | INTL | Aguilas del Zulia | — | 75 | 69 | 19 | 2 | 1 | 0 | 6 | 14 | 0 | 0 | 5 | 275 | 333 | 333 | 667 | 58 | 345 | 19 | 8 | 305 | 92 | — | — | — | — | — | — |
| 2016 | 23 | A+ | Myrtle Beach Pelicans | — | 147 | 123 | 35 | 6 | 2 | 2 | 19 | 21 | 4 | 1 | 1 | 285 | 397 | 415 | 812 | 130 | 327 | 14 | 13 | 367 | 78 | — | — | — | — | — | — |
| 2016 | 23 | A | South Bend Cubs | — | 304 | 272 | 62 | 11 | 4 | 4 | 24 | 55 | 0 | 7 | 4 | 228 | 291 | 342 | 632 | 114 | 271 | 18 | 8 | 278 | 43 | — | — | — | — | — | — |
| 2016 | 23 | INTL | Aguilas del Zulia | — | 137 | 118 | 29 | 5 | 0 | 2 | 15 | 21 | 1 | 3 | 4 | 246 | 333 | 339 | 672 | 93 | 281 | 15 | 11 | 304 | 92 | — | — | — | — | — | — |
| 2017 | 24 | A+ | Winston-Salem Dash | — | 484 | 442 | 122 | 25 | 2 | 7 | 32 | 81 | 5 | 5 | 5 | 276 | 331 | 389 | 720 | 113 | 322 | 17 | 7 | 321 | 50 | — | — | — | — | — | — |
| 2017 | 24 | INTL | Aguilas del Zulia | — | 145 | 126 | 33 | 6 | 1 | 2 | 16 | 25 | 2 | 0 | 3 | 262 | 354 | 373 | 727 | 111 | 313 | 17 | 11 | 330 | 109 | — | — | — | — | — | — |
| 2018 | 25 | AAA | Charlotte Knights | — | 28 | 26 | 9 | 2 | 0 | 0 | 0 | 7 | 2 | 0 | 1 | 346 | 393 | 423 | 816 | 77 | 474 | 25 | 0 | 370 | 93 | — | — | — | — | — | — |
| 2018 | 25 | AA | Birmingham Barons | — | 303 | 258 | 62 | 10 | 2 | 2 | 34 | 70 | 9 | 4 | 6 | 240 | 349 | 318 | 667 | 78 | 321 | 23 | 11 | 310 | 57 | — | — | — | — | — | — |
| 2018 | 25 | INTL | Aguilas del Zulia | — | 35 | 27 | 2 | 0 | 1 | 0 | 6 | 10 | 0 | 0 | 1 | 74 | 242 | 148 | 391 | 74 | 118 | 29 | 17 | 192 | 16 | — | — | — | — | — | — |
| 2019 | 26 | AA | Chattanooga Lookouts | — | 15 | 14 | 1 | 0 | 0 | 0 | 1 | 6 | 0 | 0 | 0 | 71 | 133 | 71 | 205 | 125 | 40 | 7 | 107 | -60 | — | — | — | — | — | — | |
| 2019 | 26 | A+ | Daytona Tortugas | — | 137 | 112 | 31 | 2 | 0 | 3 | 18 | 26 | 6 | 0 | 0 | 277 | 404 | 375 | 779 | 98 | 337 | 19 | 13 | 360 | 80 | — | — | — | — | — | — |
| 2022 | 29 | INTL | Aguilas del Zulia | — | 183 | 135 | 43 | 9 | 3 | 1 | 38 | 27 | 5 | 0 | 1 | 319 | 483 | 452 | 935 | 133 | 393 | 15 | 21 | 414 | 167 | — | — | — | — | — | — |
| 2023 | 30 | INTL | Aguilas del Zulia | — | 82 | 65 | 17 | 5 | 3 | 0 | 14 | 11 | 2 | 0 | 1 | 262 | 407 | 431 | 838 | 169 | 315 | 13 | 17 | 374 | 139 | — | — | — | — | — | — |
| 2024 | 31 | INTL | Gigantes de Carolina | — | 32 | 30 | 7 | 1 | 0 | 0 | 1 | 7 | 0 | 0 | 1 | 233 | 258 | 267 | 525 | 33 | 304 | 22 | 3 | 232 | 43 | — | — | — | — | — | — |
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2012 | 19 | ROK MLE | DSL Cubs 2 | — | 220 | 189 | 38 | 3 | 5 | 0 | 23 | 32 | 5 | 10 | 9 | 201 | 304 | 270 | 574 | 69 | 234 | 15 | 10 | 259 | 61 | — | — | — | — | — | — |
| 2013 | 20 | ROK MLE | DSL Cubs | — | 327 | 284 | 49 | 7 | 3 | 0 | 32 | 56 | 5 | 18 | 14 | 173 | 268 | 218 | 486 | 46 | 207 | 17 | 10 | 225 | 38 | — | — | — | — | — | — |
| 2014 | 21 | ROK MLE | AZL Cubs | — | 62 | 56 | 13 | 1 | 0 | 0 | 4 | 13 | 1 | 3 | 0 | 232 | 295 | 250 | 545 | 18 | 301 | 21 | 6 | 248 | 54 | — | — | — | — | — | — |
| 2015 | 22 | AA MLE | Tennessee Smokies | — | 145 | 128 | 24 | 3 | 1 | 1 | 13 | 34 | 1 | 0 | 1 | 188 | 268 | 250 | 518 | 62 | 237 | 23 | 9 | 229 | 41 | — | — | — | — | — | — |
| 2015 | 22 | A MLE | South Bend Cubs | — | 43 | 41 | 3 | 1 | 0 | 0 | 1 | 17 | 0 | 1 | 0 | 73 | 95 | 98 | 193 | 24 | 90 | 40 | 2 | 74 | -64 | — | — | — | — | — | — |
| 2016 | 23 | A+ MLE | Myrtle Beach Pelicans | — | 147 | 132 | 30 | 5 | 2 | 1 | 10 | 31 | 4 | 1 | 1 | 227 | 301 | 318 | 620 | 91 | 283 | 21 | 7 | 283 | 78 | — | — | — | — | — | — |
| 2016 | 23 | A MLE | South Bend Cubs | — | 304 | 279 | 55 | 9 | 4 | 3 | 17 | 77 | 0 | 7 | 4 | 197 | 243 | 290 | 534 | 93 | 253 | 25 | 6 | 232 | 43 | — | — | — | — | — | — |
| 2017 | 24 | A+ MLE | Winston-Salem Dash | — | 484 | 458 | 101 | 18 | 2 | 5 | 17 | 119 | 5 | 5 | 5 | 221 | 256 | 301 | 558 | 81 | 278 | 25 | 4 | 242 | 50 | — | — | — | — | — | — |
| 2018 | 25 | AAA MLE | Charlotte Knights | — | 28 | 26 | 7 | 1 | 0 | 0 | 0 | 9 | 2 | 0 | 1 | 269 | 321 | 308 | 629 | 38 | 427 | 32 | 0 | 305 | 93 | — | — | — | — | — | — |
| 2018 | 25 | AA MLE | Birmingham Barons | — | 303 | 269 | 56 | 10 | 2 | 2 | 23 | 85 | 9 | 4 | 6 | 208 | 292 | 283 | 575 | 74 | 283 | 28 | 8 | 253 | 57 | — | — | — | — | — | — |
| 2019 | 26 | AA MLE | Chattanooga Lookouts | — | 15 | 14 | 1 | 0 | 0 | 0 | 1 | 8 | 0 | 0 | 0 | 71 | 133 | 71 | 205 | 117 | 53 | 7 | 79 | -60 | — | — | — | — | — | — | |
| 2019 | 26 | A+ MLE | Daytona Tortugas | — | 137 | 118 | 27 | 2 | 0 | 2 | 12 | 38 | 6 | 0 | 0 | 229 | 331 | 297 | 627 | 68 | 308 | 28 | 9 | 286 | 80 | — | — | — | — | — | — |
| 2012 | 19 | ROK MLE | DSL Cubs 2 | — | 220 | 189 | 38 | 3 | 5 | 0 | 23 | 32 | 5 | 10 | 9 | 201 | 304 | 270 | 574 | 69 | 242 | 15 | 10 | 259 | 61 | — | — | — | — | — | — |
| 2012 | 19 | ROK RAW | DSL Cubs 2 | — | 220 | 179 | 53 | 5 | 7 | 1 | 33 | 26 | 5 | 10 | 9 | 296 | 419 | 419 | 838 | 123 | 342 | 12 | 15 | 376 | 61 | — | — | — | — | — | — |
| 2013 | 20 | ROK MLE | DSL Cubs | — | 327 | 284 | 49 | 7 | 3 | 0 | 32 | 56 | 5 | 18 | 14 | 173 | 268 | 218 | 486 | 46 | 212 | 17 | 10 | 225 | 38 | — | — | — | — | — | — |
| 2013 | 20 | ROK RAW | DSL Cubs | — | 327 | 269 | 70 | 11 | 5 | 0 | 47 | 46 | 5 | 18 | 14 | 260 | 380 | 338 | 718 | 78 | 310 | 14 | 14 | 329 | 38 | — | — | — | — | — | — |
| 2014 | 21 | ROK MLE | AZL Cubs | — | 62 | 56 | 13 | 1 | 0 | 0 | 4 | 13 | 1 | 3 | 0 | 232 | 295 | 250 | 545 | 18 | 302 | 21 | 6 | 248 | 54 | — | — | — | — | — | — |
| 2014 | 21 | ROK RAW | AZL Cubs | — | 62 | 54 | 17 | 2 | 0 | 0 | 6 | 9 | 1 | 3 | 0 | 315 | 393 | 352 | 745 | 37 | 378 | 15 | 10 | 340 | 54 | — | — | — | — | — | — |
| 2015 | 22 | AA MLE | 3 teams | — | 263 | 237 | 36 | 5 | 1 | 1 | 21 | 71 | 1 | 1 | 6 | 152 | 224 | 194 | 418 | 42 | 212 | 27 | 8 | 194 | 17 | — | — | — | — | — | — |
| 2015 | 22 | AA RAW | 3 teams | — | 263 | 232 | 46 | 6 | 2 | 1 | 26 | 53 | 1 | 1 | 6 | 198 | 282 | 254 | 536 | 56 | 253 | 20 | 10 | 249 | 17 | — | — | — | — | — | — |
| 2016 | 23 | A MLE | 3 teams | — | 588 | 536 | 112 | 19 | 7 | 6 | 36 | 141 | 5 | 11 | 9 | 209 | 265 | 304 | 569 | 95 | 270 | 24 | 6 | 249 | 54 | — | — | — | — | — | — |
| 2016 | 23 | A RAW | 3 teams | — | 588 | 513 | 126 | 22 | 6 | 8 | 58 | 97 | 5 | 11 | 9 | 246 | 328 | 359 | 686 | 113 | 287 | 16 | 10 | 306 | 54 | — | — | — | — | — | — |
| 2017 | 24 | A+ MLE | 2 teams | — | 629 | 594 | 130 | 23 | 2 | 6 | 23 | 155 | 7 | 5 | 8 | 219 | 256 | 295 | 551 | 76 | 284 | 25 | 4 | 242 | 50 | — | — | — | — | — | — |
| 2017 | 24 | A+ RAW | 2 teams | — | 629 | 568 | 155 | 31 | 3 | 9 | 48 | 106 | 7 | 5 | 8 | 273 | 337 | 386 | 722 | 113 | 320 | 17 | 8 | 323 | 50 | — | — | — | — | — | — |
| 2018 | 25 | AA MLE | 3 teams | — | 366 | 325 | 69 | 12 | 2 | 2 | 26 | 103 | 11 | 4 | 8 | 212 | 293 | 280 | 573 | 68 | 303 | 28 | 7 | 257 | 60 | — | — | — | — | — | — |
| 2018 | 25 | AA RAW | 3 teams | — | 366 | 311 | 73 | 12 | 3 | 2 | 40 | 87 | 11 | 4 | 8 | 235 | 343 | 312 | 654 | 77 | 318 | 24 | 11 | 304 | 60 | — | — | — | — | — | — |
| 2019 | 26 | A+ MLE | 2 teams | — | 152 | 132 | 28 | 2 | 0 | 2 | 13 | 45 | 6 | 0 | 0 | 212 | 311 | 273 | 584 | 61 | 306 | 30 | 9 | 266 | 66 | — | — | — | — | — | — |
| 2019 | 26 | A+ RAW | 2 teams | — | 152 | 126 | 32 | 2 | 0 | 3 | 19 | 32 | 6 | 0 | 0 | 254 | 377 | 341 | 719 | 87 | 319 | 21 | 12 | 335 | 66 | — | — | — | — | — | — |
| 2022 | 29 | INTL MLE | Aguilas del Zulia | — | 183 | 135 | 43 | 9 | 3 | 1 | 38 | 27 | 5 | 0 | 1 | 319 | 483 | 452 | 935 | 133 | 393 | 15 | 21 | — | — | — | — | — | — | — | — |
| 2022 | 29 | INTL RAW | Aguilas del Zulia | — | 183 | 135 | 43 | 9 | 3 | 1 | 38 | 27 | 5 | 0 | 1 | 319 | 483 | 452 | 935 | 133 | 393 | 15 | 21 | 414 | 167 | — | — | — | — | — | — |
| 2023 | 30 | INTL MLE | Aguilas del Zulia | — | 82 | 65 | 17 | 5 | 3 | 0 | 14 | 11 | 2 | 0 | 1 | 262 | 407 | 431 | 838 | 169 | 315 | 13 | 17 | — | — | — | — | — | — | — | — |
| 2023 | 30 | INTL RAW | Aguilas del Zulia | — | 82 | 65 | 17 | 5 | 3 | 0 | 14 | 11 | 2 | 0 | 1 | 262 | 407 | 431 | 838 | 169 | 315 | 13 | 17 | 374 | 139 | — | — | — | — | — | — |
| 2024 | 31 | INTL MLE | Gigantes de Carolina | — | 32 | 30 | 7 | 1 | 0 | 0 | 1 | 7 | 0 | 0 | 1 | 233 | 258 | 267 | 525 | 33 | 304 | 22 | 3 | — | — | — | — | — | — | — | — |
| 2024 | 31 | INTL RAW | Gigantes de Carolina | — | 32 | 30 | 7 | 1 | 0 | 0 | 1 | 7 | 0 | 0 | 1 | 233 | 258 | 267 | 525 | 33 | 304 | 22 | 3 | 232 | 43 | — | — | — | — | — | — |
| 2012 | 19 | ROK MLE | DSL Cubs 2 | — | 220 | 190 | 38 | 3 | 5 | 0 | 23 | 32 | 5 | 10 | 9 | 200 | 304 | 268 | 573 | 68 | 234 | 15 | 10 | 259 | 61 | — | — | — | — | — | — |
| 2013 | 20 | ROK MLE | DSL Cubs | — | 327 | 287 | 49 | 7 | 3 | 0 | 32 | 56 | 5 | 18 | 14 | 171 | 268 | 216 | 484 | 45 | 207 | 17 | 10 | 225 | 38 | — | — | — | — | — | — |
| 2014 | 21 | ROK MLE | AZL Cubs | — | 62 | 57 | 13 | 1 | 0 | 0 | 4 | 13 | 1 | 3 | 0 | 228 | 295 | 246 | 541 | 18 | 301 | 21 | 6 | 248 | 54 | — | — | — | — | — | — |
| 2015 | 22 | AA MLE | 3 teams | — | 263 | 239 | 36 | 5 | 1 | 1 | 21 | 71 | 1 | 1 | 6 | 151 | 224 | 192 | 416 | 42 | 203 | 27 | 8 | 194 | 17 | — | — | — | — | — | — |
| 2016 | 23 | A MLE | 3 teams | — | 588 | 542 | 112 | 19 | 7 | 6 | 36 | 141 | 5 | 11 | 9 | 207 | 265 | 301 | 566 | 94 | 263 | 24 | 6 | 249 | 54 | — | — | — | — | — | — |
| 2017 | 24 | A+ MLE | 2 teams | — | 629 | 594 | 130 | 23 | 2 | 6 | 23 | 155 | 7 | 5 | 8 | 219 | 256 | 295 | 551 | 76 | 278 | 25 | 4 | 242 | 50 | — | — | — | — | — | — |
| 2018 | 25 | AA MLE | 3 teams | — | 366 | 326 | 69 | 12 | 2 | 2 | 26 | 103 | 11 | 4 | 8 | 212 | 293 | 279 | 572 | 67 | 295 | 28 | 7 | 257 | 60 | — | — | — | — | — | — |
| 2019 | 26 | A+ MLE | 2 teams | — | 152 | 132 | 28 | 2 | 0 | 2 | 13 | 45 | 6 | 0 | 0 | 212 | 311 | 273 | 584 | 61 | 289 | 30 | 9 | 266 | 66 | — | — | — | — | — | — |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| Career | — | MLE | — | 2904 | 2583 | 542 | 87 | 26 | 18 | 231 | 661 | 48 | 52 | 57 | 210 | 287 | 285 | 571 | 75 | 274 | 23 | 8 | 217 | 33 | -232 | -12 | +0 | +31 | +63 | -15.3 | |
| / 162G | — | MLE | — | 650 | 578 | 121 | 19 | 6 | 4 | 52 | 148 | 11 | 12 | 13 | 209 | 287 | 284 | 571 | 74 | 273 | 23 | 8 | 217 | 33 | -52 | -3 | +0 | +7 | +14 | -3.4 | |
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.
2019 A+Daytona Tortugas · 137 PAwOBA .349 → .286 (−62)K% 19.0% → 27.4%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 18.98% | ÷0.985 | ×1.420 | — | — | 27.36% |
| BB% (unintentional) /PA | 12.41% | ÷1.016 | ×0.750 | — | ×0.968 | 8.87% |
| HBP% /PA | 4.38% | — | ×0.930 | — | ×0.968 | 3.94% |
| Singles /BIP | 30.23% | ÷0.965 | ×0.920 | — | ×0.968 | 27.89% |
| Doubles /BIP | 2.33% | ÷1.042 | ×0.960 | — | ×0.968 | 2.07% |
| Triples /BIP | 0.00% | ÷1.150 | ×0.810 | — | ×0.968 | 0.00% |
| Home runs /BIP | 3.49% | ÷1.101 | ×0.880 | — | ×0.968 | 2.70% |
Factors used: league row FSL. Park (home-season share, regressed): HR 120, 1B 93, 2B 108, 3B 130, K 97, BB 103 — applied at half strength. Age: age 26 vs a level average of 22.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average).
Result: wOBA .349 → .286; ISO .098 → .074; BABIP .337 → .308. 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 AAChattanooga Lookouts · 15 PAwOBA .105 → .079 (−26)K% 40.0% → 50.5%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 40.00% | ÷0.967 | ×1.220 | — | — | 50.47% |
| BB% (unintentional) /PA | 6.67% | ÷0.949 | ×0.680 | — | ×0.988 | 4.72% |
| HBP% /PA | 0.00% | — | ×0.840 | — | ×0.988 | 0.00% |
| Singles /BIP | 12.50% | ÷0.974 | ×0.920 | — | ×0.988 | 11.66% |
| Doubles /BIP | 0.00% | ÷1.160 | ×0.910 | — | ×0.988 | 0.00% |
| Triples /BIP | 0.00% | ÷0.900 | ×0.880 | — | ×0.988 | 0.00% |
| Home runs /BIP | 0.00% | ÷0.979 | ×0.800 | — | ×0.988 | 0.00% |
Factors used: league row SL. Park (home-season share, regressed): HR 96, 1B 95, 2B 132, 3B 80, K 93, BB 90 — applied at half strength. Age: age 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average).
Result: wOBA .105 → .079; ISO .000 → .000; BABIP .125 → .117. 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 AABirmingham Barons · 303 PAwOBA .303 → .253 (−50)K% 23.1% → 28.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 23.10% | ÷1.006 | ×1.220 | — | — | 28.00% |
| BB% (unintentional) /PA | 10.89% | ÷0.954 | ×0.680 | — | ×0.998 | 7.75% |
| HBP% /PA | 2.97% | — | ×0.840 | — | ×0.998 | 2.49% |
| Singles /BIP | 25.53% | ÷1.069 | ×0.920 | ×1.019 | ×0.998 | 22.34% |
| Doubles /BIP | 5.32% | ÷0.969 | ×0.910 | ×1.019 | ×0.998 | 5.08% |
| Triples /BIP | 1.06% | ÷1.150 | ×0.880 | ×1.019 | ×0.998 | 0.83% |
| Home runs /BIP | 1.06% | ÷0.949 | ×0.800 | — | ×0.998 | 0.90% |
Factors used: league row SL. Park (home-season share, regressed): HR 90, 1B 114, 2B 94, 3B 130, K 101, BB 91 — 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 ×1.019.
Result: wOBA .303 → .253; ISO .078 → .068; BABIP .321 → .283. 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 AAACharlotte Knights · 28 PAwOBA .361 → .305 (−56)K% 25.0% → 30.4%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 25.00% | ÷0.986 | ×1.200 | — | — | 30.41% |
| BB% (unintentional) /PA | 0.00% | ÷1.030 | ×0.690 | — | ×1.033 | 0.00% |
| HBP% /PA | 7.14% | — | ×0.940 | — | ×1.033 | 6.94% |
| Singles /BIP | 36.84% | ÷1.030 | ×0.930 | — | ×1.033 | 34.36% |
| Doubles /BIP | 10.53% | ÷1.077 | ×0.830 | — | ×1.033 | 8.38% |
| Triples /BIP | 0.00% | ÷1.150 | ×0.970 | — | ×1.033 | 0.00% |
| Home runs /BIP | 0.00% | ÷1.319 | ×0.840 | — | ×1.033 | 0.00% |
Factors used: league row IL. Park (home-season share, regressed): HR 164, 1B 106, 2B 115, 3B 130, K 97, BB 106 — 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 .361 → .305; ISO .077 → .057; BABIP .474 → .427. 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+Winston-Salem Dash · 484 PAwOBA .312 → .242 (−71)K% 16.7% → 24.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 16.74% | ÷0.966 | ×1.420 | — | — | 24.59% |
| BB% (unintentional) /PA | 5.99% | ÷1.046 | ×0.630 | — | ×0.988 | 3.57% |
| HBP% /PA | 1.03% | — | ×0.860 | — | ×0.988 | 0.88% |
| Singles /BIP | 24.38% | ÷0.999 | ×0.940 | ×0.974 | ×0.988 | 22.07% |
| Doubles /BIP | 6.93% | ÷1.080 | ×0.830 | ×0.974 | ×0.988 | 5.12% |
| Triples /BIP | 0.55% | ÷0.902 | ×0.800 | ×0.974 | ×0.988 | 0.47% |
| Home runs /BIP | 1.94% | ÷1.275 | ×0.900 | — | ×0.988 | 1.35% |
Factors used: league row CAR. Park (home-season share, regressed): HR 155, 1B 100, 2B 116, 3B 80, K 93, BB 109 — 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 ×0.974.
Result: wOBA .312 → .242; ISO .113 → .079; BABIP .322 → .278. 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 ASouth Bend Cubs · 304 PAwOBA .272 → .232 (−40)K% 18.1% → 25.3%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 18.09% | ÷0.973 | ×1.360 | — | — | 25.30% |
| BB% (unintentional) /PA | 7.89% | ÷0.968 | ×0.690 | — | ×0.990 | 5.57% |
| HBP% /PA | 0.00% | — | ×0.780 | — | ×0.990 | 0.00% |
| Singles /BIP | 19.82% | ÷0.993 | ×0.920 | ×1.029 | ×0.990 | 18.71% |
| Doubles /BIP | 5.07% | ÷0.963 | ×0.830 | ×1.029 | ×0.990 | 4.45% |
| Triples /BIP | 1.84% | ÷0.900 | ×0.910 | ×1.029 | ×0.990 | 1.90% |
| Home runs /BIP | 1.84% | ÷0.997 | ×0.800 | — | ×0.990 | 1.46% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 99, 1B 99, 2B 93, 3B 80, K 95, BB 94 — 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 ×1.029.
Result: wOBA .272 → .232; ISO .114 → .098; BABIP .271 → .253. 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+Myrtle Beach Pelicans · 147 PAwOBA .356 → .283 (−73)K% 14.3% → 21.0%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 14.29% | ÷0.965 | ×1.420 | — | — | 21.03% |
| BB% (unintentional) /PA | 11.56% | ÷1.043 | ×0.630 | — | ×0.998 | 6.97% |
| HBP% /PA | 2.72% | — | ×0.860 | — | ×0.998 | 2.34% |
| Singles /BIP | 24.51% | ÷1.044 | ×0.940 | ×0.979 | ×0.998 | 21.56% |
| Doubles /BIP | 5.88% | ÷0.920 | ×0.830 | ×0.979 | ×0.998 | 5.19% |
| Triples /BIP | 1.96% | ÷1.038 | ×0.800 | ×0.979 | ×0.998 | 1.48% |
| Home runs /BIP | 1.96% | ÷1.311 | ×0.900 | — | ×0.998 | 1.34% |
Factors used: league row CAR. Park (home-season share, regressed): HR 162, 1B 109, 2B 84, 3B 108, K 93, BB 109 — 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 ×0.979.
Result: wOBA .356 → .283; ISO .130 → .101; BABIP .327 → .283. 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 AATennessee Smokies · 145 PAwOBA .256 → .229 (−28)K% 18.6% → 23.5%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 18.62% | ÷0.967 | ×1.220 | — | — | 23.49% |
| BB% (unintentional) /PA | 12.41% | ÷0.959 | ×0.680 | — | ×1.042 | 9.17% |
| HBP% /PA | 0.69% | — | ×0.840 | — | ×1.042 | 0.60% |
| Singles /BIP | 19.79% | ÷1.026 | ×0.920 | ×1.050 | ×1.042 | 19.42% |
| Doubles /BIP | 3.12% | ÷0.998 | ×0.910 | ×1.050 | ×1.042 | 3.12% |
| Triples /BIP | 1.04% | ÷1.058 | ×0.880 | ×1.050 | ×1.042 | 0.95% |
| Home runs /BIP | 1.04% | ÷1.048 | ×0.800 | — | ×1.042 | 0.83% |
Factors used: league row SL. Park (home-season share, regressed): HR 110, 1B 105, 2B 100, 3B 112, K 93, BB 92 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.
Result: wOBA .256 → .229; ISO .065 → .059; BABIP .242 → .237. 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 — .