Eric Meza
| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR |
|---|---|---|---|---|---|---|---|---|
| 2022 | 24 | INTLCaneros de lo… | 116 | .226/.274/.349 | 4 | 0 | 72 | — |
| 2023 | 25 | INTLCaneros de lo… | 82 | .203/.329/.319 | 2 | 0 | 92 | — |
| 2024 | 26 | INTLCaneros de lo… | 52 | .229/.275/.396 | 2 | 0 | 84 | — |
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 | 18 | A | Great Lakes Loons | — | 245 | 223 | 51 | 10 | 0 | 4 | 20 | 48 | 2 | 0 | 1 | 229 | 298 | 327 | 625 | 99 | 275 | 20 | 8 | 286 | 45 | — | — | — | — | — | — |
| 2017 | 19 | A | Great Lakes Loons | — | 114 | 103 | 24 | 5 | 0 | 1 | 7 | 19 | 2 | 0 | 0 | 233 | 295 | 311 | 605 | 78 | 271 | 17 | 6 | 273 | 45 | — | — | — | — | — | — |
| 2017 | 19 | ROK | AZL Dodgers | — | 159 | 146 | 32 | 9 | 0 | 4 | 8 | 31 | 2 | 1 | 0 | 219 | 269 | 363 | 632 | 144 | 246 | 19 | 5 | 278 | 17 | — | — | — | — | — | — |
| 2019 | 21 | AAA | Guerreros de Oaxaca | — | 157 | 146 | 44 | 8 | 0 | 6 | 8 | 29 | 2 | 0 | 1 | 301 | 346 | 479 | 826 | 178 | 339 | 18 | 5 | 363 | 78 | — | — | — | — | — | — |
| 2019 | 21 | INTL | Tomateros de Culiacan | — | 38 | 35 | 7 | 0 | 0 | 1 | 2 | 6 | 0 | 0 | 0 | 200 | 243 | 286 | 529 | 86 | 207 | 16 | 5 | 234 | 45 | — | — | — | — | — | — |
| 2020 | 22 | INTL | Tomateros de Culiacan | — | 87 | 80 | 21 | 4 | 0 | 1 | 7 | 11 | 0 | 1 | 0 | 263 | 322 | 350 | 672 | 87 | 294 | 13 | 8 | 306 | 93 | — | — | — | — | — | — |
| 2021 | 23 | INTL | Caneros de los Mochis | — | 133 | 122 | 29 | 1 | 0 | 1 | 8 | 25 | 0 | 0 | 0 | 238 | 285 | 270 | 555 | 33 | 283 | 19 | 6 | 251 | 56 | — | — | — | — | — | — |
| 2022 | 24 | INTL | Caneros de los Mochis | — | 116 | 106 | 24 | 1 | 0 | 4 | 4 | 22 | 3 | 0 | 1 | 226 | 274 | 349 | 623 | 123 | 241 | 19 | 3 | 274 | 72 | — | — | — | — | — | — |
| 2023 | 25 | INTL | Caneros de los Mochis | — | 82 | 69 | 14 | 2 | 0 | 2 | 10 | 17 | 3 | 0 | 0 | 203 | 329 | 319 | 648 | 116 | 240 | 21 | 12 | 304 | 92 | — | — | — | — | — | — |
| 2024 | 26 | INTL | Caneros de los Mochis | — | 52 | 48 | 11 | 2 | 0 | 2 | 2 | 15 | 1 | 0 | 0 | 229 | 275 | 396 | 670 | 167 | 281 | 29 | 4 | 292 | 84 | — | — | — | — | — | — |
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2016 | 18 | A MLE | Great Lakes Loons | — | 245 | 229 | 45 | 8 | 0 | 3 | 14 | 66 | 2 | 0 | 1 | 197 | 249 | 271 | 520 | 74 | 262 | 27 | 6 | 235 | 45 | — | — | — | — | — | — |
| 2017 | 19 | A MLE | Great Lakes Loons | — | 114 | 105 | 22 | 4 | 0 | 1 | 5 | 26 | 2 | 0 | 0 | 210 | 259 | 276 | 535 | 67 | 257 | 23 | 4 | 235 | 45 | — | — | — | — | — | — |
| 2017 | 19 | ROK MLE | AZL Dodgers | — | 159 | 149 | 23 | 6 | 0 | 3 | 5 | 45 | 2 | 1 | 0 | 154 | 192 | 255 | 447 | 101 | 185 | 28 | 3 | 193 | 17 | — | — | — | — | — | — |
| 2019 | 21 | AAA MLE | Guerreros de Oaxaca | — | 157 | 149 | 36 | 5 | 0 | 4 | 5 | 35 | 2 | 0 | 1 | 242 | 276 | 356 | 631 | 114 | 288 | 22 | 3 | 284 | 78 | — | — | — | — | — | — |
| 2016 | 18 | A MLE | Great Lakes Loons | — | 245 | 229 | 45 | 8 | 0 | 3 | 14 | 66 | 2 | 0 | 1 | 197 | 249 | 271 | 520 | 74 | 263 | 27 | 6 | 235 | 45 | — | — | — | — | — | — |
| 2016 | 18 | A RAW | Great Lakes Loons | — | 245 | 223 | 51 | 10 | 0 | 4 | 20 | 48 | 2 | 0 | 1 | 229 | 298 | 327 | 625 | 99 | 275 | 20 | 8 | 286 | 45 | — | — | — | — | — | — |
| 2017 | 19 | ROK MLE | 2 teams | — | 273 | 254 | 45 | 10 | 0 | 4 | 10 | 71 | 4 | 1 | 0 | 177 | 220 | 264 | 484 | 87 | 223 | 26 | 4 | 211 | 29 | — | — | — | — | — | — |
| 2017 | 19 | ROK RAW | 2 teams | — | 273 | 249 | 56 | 14 | 0 | 5 | 15 | 50 | 4 | 1 | 0 | 225 | 280 | 341 | 621 | 116 | 256 | 18 | 5 | 276 | 29 | — | — | — | — | — | — |
| 2019 | 21 | AAA MLE | 2 teams | — | 195 | 185 | 46 | 7 | 0 | 6 | 6 | 43 | 2 | 0 | 1 | 249 | 280 | 384 | 664 | 135 | 290 | 22 | 3 | 284 | 78 | — | — | — | — | — | — |
| 2019 | 21 | AAA RAW | 2 teams | — | 195 | 181 | 51 | 8 | 0 | 7 | 10 | 35 | 2 | 0 | 1 | 282 | 326 | 442 | 768 | 160 | 312 | 18 | 5 | 338 | 78 | — | — | — | — | — | — |
| 2020 | 22 | INTL MLE | Tomateros de Culiacan | — | 87 | 80 | 21 | 4 | 0 | 1 | 7 | 11 | 0 | 1 | 0 | 263 | 322 | 350 | 672 | 87 | 294 | 13 | 8 | — | — | — | — | — | — | — | — |
| 2020 | 22 | INTL RAW | Tomateros de Culiacan | — | 87 | 80 | 21 | 4 | 0 | 1 | 7 | 11 | 0 | 1 | 0 | 263 | 322 | 350 | 672 | 87 | 294 | 13 | 8 | 306 | 93 | — | — | — | — | — | — |
| 2021 | 23 | INTL MLE | Caneros de los Mochis | — | 133 | 122 | 29 | 1 | 0 | 1 | 8 | 25 | 0 | 0 | 0 | 238 | 285 | 270 | 555 | 33 | 283 | 19 | 6 | — | — | — | — | — | — | — | — |
| 2021 | 23 | INTL RAW | Caneros de los Mochis | — | 133 | 122 | 29 | 1 | 0 | 1 | 8 | 25 | 0 | 0 | 0 | 238 | 285 | 270 | 555 | 33 | 283 | 19 | 6 | 251 | 56 | — | — | — | — | — | — |
| 2022 | 24 | INTL MLE | Caneros de los Mochis | — | 116 | 106 | 24 | 1 | 0 | 4 | 4 | 22 | 3 | 0 | 1 | 226 | 274 | 349 | 623 | 123 | 241 | 19 | 3 | — | — | — | — | — | — | — | — |
| 2022 | 24 | INTL RAW | Caneros de los Mochis | — | 116 | 106 | 24 | 1 | 0 | 4 | 4 | 22 | 3 | 0 | 1 | 226 | 274 | 349 | 623 | 123 | 241 | 19 | 3 | 274 | 72 | — | — | — | — | — | — |
| 2023 | 25 | INTL MLE | Caneros de los Mochis | — | 82 | 69 | 14 | 2 | 0 | 2 | 10 | 17 | 3 | 0 | 0 | 203 | 329 | 319 | 648 | 116 | 240 | 21 | 12 | — | — | — | — | — | — | — | — |
| 2023 | 25 | INTL RAW | Caneros de los Mochis | — | 82 | 69 | 14 | 2 | 0 | 2 | 10 | 17 | 3 | 0 | 0 | 203 | 329 | 319 | 648 | 116 | 240 | 21 | 12 | 304 | 92 | — | — | — | — | — | — |
| 2024 | 26 | INTL MLE | Caneros de los Mochis | — | 52 | 48 | 11 | 2 | 0 | 2 | 2 | 15 | 1 | 0 | 0 | 229 | 275 | 396 | 670 | 167 | 281 | 29 | 4 | — | — | — | — | — | — | — | — |
| 2024 | 26 | INTL RAW | Caneros de los Mochis | — | 52 | 48 | 11 | 2 | 0 | 2 | 2 | 15 | 1 | 0 | 0 | 229 | 275 | 396 | 670 | 167 | 281 | 29 | 4 | 292 | 84 | — | — | — | — | — | — |
| 2016 | 18 | A MLE | Great Lakes Loons | — | 245 | 227 | 45 | 8 | 0 | 3 | 14 | 66 | 2 | 0 | 1 | 198 | 249 | 273 | 522 | 75 | 262 | 27 | 6 | 235 | 45 | — | — | — | — | — | — |
| 2017 | 19 | ROK MLE | 2 teams | — | 273 | 257 | 45 | 10 | 0 | 4 | 10 | 71 | 4 | 1 | 0 | 175 | 220 | 261 | 481 | 86 | 215 | 26 | 4 | 211 | 29 | — | — | — | — | — | — |
| 2019 | 21 | AAA MLE | 2 teams | — | 195 | 185 | 46 | 7 | 0 | 6 | 6 | 43 | 2 | 0 | 1 | 249 | 280 | 384 | 664 | 135 | 288 | 22 | 3 | 284 | 78 | — | — | — | — | — | — |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| Career | — | MLE | — | 1183 | 1093 | 235 | 35 | 0 | 23 | 61 | 270 | 15 | 2 | 3 | 215 | 266 | 310 | 576 | 95 | 260 | 23 | 5 | 144 | -16 | -164 | -1 | +0 | -21 | +26 | -16.3 | |
| / 162G | — | MLE | — | 650 | 601 | 129 | 19 | 0 | 13 | 34 | 148 | 8 | 1 | 2 | 215 | 266 | 311 | 578 | 97 | 259 | 23 | 5 | 144 | -16 | -90 | -1 | +0 | -12 | +14 | -9.0 | |
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 AAAGuerreros de Oaxaca · 157 PAwOBA .353 → .284 (−68)K% 18.5% → 22.2%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 18.47% | ÷0.998 | ×1.200 | — | — | 22.22% |
| BB% (unintentional) /PA | 4.46% | ÷1.036 | ×0.690 | — | ×1.050 | 3.12% |
| HBP% /PA | 1.27% | — | ×0.940 | — | ×1.050 | 1.26% |
| Singles /BIP | 25.64% | ÷1.025 | ×0.930 | ×0.950 | ×1.050 | 23.20% |
| Doubles /BIP | 6.84% | ÷1.200 | ×0.830 | ×0.950 | ×1.050 | 4.72% |
| Triples /BIP | 0.00% | ÷1.058 | ×0.920 | ×0.950 | ×1.050 | 0.00% |
| Home runs /BIP | 5.13% | ÷0.972 | ×0.700 | — | ×1.050 | 3.88% |
Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 94, 1B 105, 2B 140, 3B 112, K 100, BB 107 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.
Result: wOBA .353 → .284; ISO .178 → .129; BABIP .339 → .288. 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 ROKAZL Dodgers · 159 PAwOBA .275 → .193 (−82)K% 19.5% → 28.1%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 19.50% | ÷1.000 | ×1.440 | — | — | 28.08% |
| BB% (unintentional) /PA | 5.03% | ÷1.000 | ×0.620 | — | ×1.008 | 3.14% |
| HBP% /PA | 1.26% | — | ×0.720 | — | ×1.008 | 0.91% |
| Singles /BIP | 16.52% | ÷1.000 | ×0.820 | ×0.960 | ×1.008 | 13.10% |
| Doubles /BIP | 7.83% | ÷1.000 | ×0.720 | ×0.960 | ×1.008 | 5.45% |
| Triples /BIP | 0.00% | ÷1.000 | ×0.720 | ×0.960 | ×1.008 | 0.00% |
| Home runs /BIP | 3.48% | ÷1.000 | ×0.780 | — | ×1.008 | 2.73% |
Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.960.
Result: wOBA .275 → .193; ISO .144 → .101; BABIP .246 → .185. 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 AGreat Lakes Loons · 114 PAwOBA .271 → .235 (−36)K% 16.7% → 22.9%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 16.67% | ÷0.990 | ×1.360 | — | — | 22.90% |
| BB% (unintentional) /PA | 6.14% | ÷1.048 | ×0.690 | — | ×1.045 | 4.23% |
| HBP% /PA | 1.75% | — | ×0.780 | — | ×1.045 | 1.43% |
| Singles /BIP | 21.43% | ÷0.965 | ×0.920 | ×0.985 | ×1.045 | 21.03% |
| Doubles /BIP | 5.95% | ÷1.013 | ×0.830 | ×0.985 | ×1.045 | 5.02% |
| Triples /BIP | 0.00% | ÷1.013 | ×0.910 | ×0.985 | ×1.045 | 0.00% |
| Home runs /BIP | 1.19% | ÷0.970 | ×0.800 | — | ×1.045 | 1.03% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 94, 1B 93, 2B 103, 3B 103, K 98, BB 110 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.985.
Result: wOBA .271 → .235; ISO .078 → .064; BABIP .271 → .257. 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 AGreat Lakes Loons · 245 PAwOBA .277 → .235 (−42)K% 19.6% → 26.9%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 19.59% | ÷0.990 | ×1.360 | — | — | 26.90% |
| BB% (unintentional) /PA | 7.76% | ÷1.011 | ×0.690 | — | ×1.050 | 5.56% |
| HBP% /PA | 0.82% | — | ×0.780 | — | ×1.050 | 0.67% |
| Singles /BIP | 21.14% | ÷0.977 | ×0.920 | ×0.985 | ×1.050 | 20.59% |
| Doubles /BIP | 5.71% | ÷0.961 | ×0.830 | ×0.985 | ×1.050 | 5.10% |
| Triples /BIP | 0.00% | ÷0.900 | ×0.910 | ×0.985 | ×1.050 | 0.00% |
| Home runs /BIP | 2.29% | ÷0.960 | ×0.800 | — | ×1.050 | 2.00% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 92, 1B 95, 2B 92, 3B 80, K 98, BB 102 — applied at half strength. Age: age 18 vs a level average of 22.0 → +5.0% on BB/HBP/hit rates (4.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.985.
Result: wOBA .277 → .235; ISO .099 → .082; BABIP .275 → .262. 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 — .