Karell Paz
| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR | MLE AVG/OBP/SLG |
|---|---|---|---|---|---|---|---|---|---|
| 2022 | 22 | ROKNYM | 114 | .309/.396/.557 | 4 | 5 | 76 | — | .220/.297/.390 |
| 2023 | 23 | ANYM | 224 | .261/.374/.388 | 4 | 10 | 53 | — | .185/.284/.262 |
| 2024 | 24 | A+NYM | 163 | .215/.298/.368 | 3 | 10 | 26 | — | .161/.224/.275 |
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) | |||||||||||||||||||||||||||||||
| 2022 | 22 | ROK | FCL Mets | — | 114 | 97 | 30 | 4 | 4 | 4 | 8 | 18 | 6 | 5 | 5 | 309 | 396 | 557 | 953 | 247 | 333 | 16 | 7 | 405 | 76 | — | — | — | — | — | — |
| 2023 | 23 | A | St. Lucie Mets | — | 224 | 188 | 49 | 10 | 1 | 4 | 24 | 50 | 10 | 10 | 3 | 261 | 374 | 388 | 762 | 128 | 331 | 22 | 11 | 347 | 53 | — | — | — | — | — | — |
| 2024 | 24 | A+ | Brooklyn Cyclones | — | 163 | 144 | 31 | 7 | 3 | 3 | 13 | 44 | 4 | 10 | 4 | 215 | 298 | 368 | 666 | 153 | 289 | 27 | 8 | 297 | 26 | — | — | — | — | — | — |
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2022 | 22 | ROK MLE | FCL Mets | — | 114 | 100 | 22 | 2 | 3 | 3 | 5 | 27 | 6 | 5 | 5 | 220 | 297 | 390 | 687 | 170 | 241 | 24 | 4 | 281 | 76 | — | — | — | — | — | — |
| 2023 | 23 | A MLE | St. Lucie Mets | — | 224 | 195 | 36 | 7 | 1 | 2 | 17 | 72 | 10 | 10 | 3 | 185 | 284 | 262 | 545 | 77 | 269 | 32 | 8 | 247 | 53 | — | — | — | — | — | — |
| 2024 | 24 | A+ MLE | Brooklyn Cyclones | — | 163 | 149 | 24 | 5 | 3 | 2 | 8 | 58 | 4 | 10 | 4 | 161 | 224 | 275 | 499 | 114 | 235 | 36 | 5 | 207 | 26 | — | — | — | — | — | — |
| 2022 | 22 | ROK MLE | FCL Mets | — | 114 | 100 | 22 | 2 | 3 | 3 | 5 | 27 | 6 | 5 | 5 | 220 | 297 | 390 | 687 | 170 | 260 | 24 | 4 | 281 | 76 | — | — | — | — | — | — |
| 2022 | 22 | ROK RAW | FCL Mets | — | 114 | 97 | 30 | 4 | 4 | 4 | 8 | 18 | 6 | 5 | 5 | 309 | 396 | 557 | 953 | 247 | 333 | 16 | 7 | 405 | 76 | — | — | — | — | — | — |
| 2023 | 23 | A MLE | St. Lucie Mets | — | 224 | 195 | 36 | 7 | 1 | 2 | 17 | 72 | 10 | 10 | 3 | 185 | 284 | 262 | 545 | 77 | 276 | 32 | 8 | 247 | 53 | — | — | — | — | — | — |
| 2023 | 23 | A RAW | St. Lucie Mets | — | 224 | 188 | 49 | 10 | 1 | 4 | 24 | 50 | 10 | 10 | 3 | 261 | 374 | 388 | 762 | 128 | 331 | 22 | 11 | 347 | 53 | — | — | — | — | — | — |
| 2024 | 24 | A+ MLE | Brooklyn Cyclones | — | 163 | 149 | 24 | 5 | 3 | 2 | 8 | 58 | 4 | 10 | 4 | 161 | 224 | 275 | 499 | 114 | 247 | 36 | 5 | 207 | 26 | — | — | — | — | — | — |
| 2024 | 24 | A+ RAW | Brooklyn Cyclones | — | 163 | 144 | 31 | 7 | 3 | 3 | 13 | 44 | 4 | 10 | 4 | 215 | 298 | 368 | 666 | 153 | 289 | 27 | 8 | 297 | 26 | — | — | — | — | — | — |
| 2022 | 22 | ROK MLE | FCL Mets | — | 114 | 102 | 22 | 2 | 3 | 3 | 5 | 27 | 6 | 5 | 5 | 216 | 297 | 382 | 680 | 167 | 241 | 24 | 4 | 281 | 76 | — | — | — | — | — | — |
| 2023 | 23 | A MLE | St. Lucie Mets | — | 224 | 195 | 36 | 7 | 1 | 2 | 17 | 72 | 10 | 10 | 3 | 185 | 284 | 262 | 545 | 77 | 269 | 32 | 8 | 247 | 53 | — | — | — | — | — | — |
| 2024 | 24 | A+ MLE | Brooklyn Cyclones | — | 163 | 150 | 24 | 5 | 3 | 2 | 8 | 58 | 4 | 10 | 4 | 160 | 224 | 273 | 497 | 113 | 235 | 36 | 5 | 207 | 26 | — | — | — | — | — | — |
| ▸ Model inputs — neutral MLE (past 3 seasons) | |||||||||||||||||||||||||||||||
| 2024 | 24 | A+ MLE | Brooklyn Cyclones | — | 163 | 150 | 24 | 5 | 3 | 2 | 8 | 58 | 4 | 10 | 4 | 160 | 224 | 273 | 497 | 113 | 235 | 36 | 5 | 207 | 26 | — | — | — | — | — | — |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| Career | — | MLE | — | 501 | 444 | 82 | 14 | 7 | 7 | 30 | 157 | 20 | 25 | 12 | 185 | 267 | 295 | 562 | 110 | 263 | 31 | 6 | 242 | 50 | -30 | +0 | +0 | -3 | +11 | -2.2 | |
| / 162G | — | MLE | — | 650 | 576 | 106 | 18 | 9 | 9 | 39 | 204 | 26 | 32 | 16 | 184 | 267 | 293 | 560 | 109 | 263 | 31 | 6 | 242 | 50 | -39 | +0 | +0 | -4 | +14 | -2.9 | |
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.
2024 A+Brooklyn Cyclones · 163 PAwOBA .289 → .207 (−82)K% 27.0% → 35.8%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 26.99% | ÷0.988 | ×1.310 | — | — | 35.81% |
| BB% (unintentional) /PA | 7.98% | ÷0.973 | ×0.600 | — | ×0.978 | 4.81% |
| HBP% /PA | 2.45% | — | ×0.770 | — | ×0.978 | 1.85% |
| Singles /BIP | 18.00% | ÷1.032 | ×0.870 | ×1.008 | ×0.978 | 14.96% |
| Doubles /BIP | 7.00% | ÷1.005 | ×0.780 | ×1.008 | ×0.978 | 5.36% |
| Triples /BIP | 3.00% | ÷0.929 | ×0.850 | ×1.008 | ×0.978 | 2.71% |
| Home runs /BIP | 3.00% | ÷1.341 | ×0.880 | — | ×0.978 | 1.93% |
Factors used: league row South Atlantic League. Park (home-season share, regressed): HR 168, 1B 106, 2B 101, 3B 86, K 98, BB 95 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.008.
Result: wOBA .289 → .207; ISO .153 → .108; BABIP .289 → .235. 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 ASt. Lucie Mets · 224 PAwOBA .341 → .247 (−94)K% 22.3% → 32.1%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 22.32% | ÷0.947 | ×1.360 | — | — | 32.06% |
| BB% (unintentional) /PA | 10.71% | ÷0.977 | ×0.690 | — | ×0.980 | 7.41% |
| HBP% /PA | 4.46% | — | ×0.780 | — | ×0.980 | 3.41% |
| Singles /BIP | 24.64% | ÷1.054 | ×0.920 | ×0.971 | ×0.980 | 20.46% |
| Doubles /BIP | 7.25% | ÷0.987 | ×0.830 | ×0.971 | ×0.980 | 5.80% |
| Triples /BIP | 0.72% | ÷1.150 | ×0.910 | ×0.971 | ×0.980 | 0.55% |
| Home runs /BIP | 2.90% | ÷1.274 | ×0.800 | — | ×0.980 | 1.78% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 155, 1B 111, 2B 97, 3B 130, K 89, BB 95 — applied at half strength. Age: age 24 vs a level average of 22.0 → −2.0% on BB/HBP/hit rates (2.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.
Result: wOBA .341 → .247; ISO .128 → .083; BABIP .331 → .269. 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 ROKFCL Mets · 114 PAwOBA .405 → .281 (−124)K% 15.8% → 23.6%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 15.79% | ÷0.964 | ×1.440 | — | — | 23.58% |
| BB% (unintentional) /PA | 7.02% | ÷1.014 | ×0.620 | — | ×0.965 | 4.14% |
| HBP% /PA | 5.26% | — | ×0.720 | — | ×0.965 | 3.66% |
| Singles /BIP | 22.78% | ÷1.015 | ×0.820 | ×0.990 | ×0.965 | 17.58% |
| Doubles /BIP | 5.06% | ÷1.103 | ×0.720 | ×0.990 | ×0.965 | 3.16% |
| Triples /BIP | 5.06% | ÷1.012 | ×0.720 | ×0.990 | ×0.965 | 3.44% |
| Home runs /BIP | 5.06% | ÷1.078 | ×0.780 | — | ×0.965 | 3.53% |
Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 116, 1B 103, 2B 121, 3B 102, K 93, BB 103 — applied at half strength. Age: age 23 vs a level average of 19.5 → −3.5% on BB/HBP/hit rates (3.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.990.
Result: wOBA .405 → .281; ISO .247 → .167; BABIP .333 → .241. 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).