Skyler Weber
| Year | Age | Lvl / Team | PA | AVG/OBP/SLG | HR | SB | wRC+ | WAR | MLE AVG/OBP/SLG |
|---|---|---|---|---|---|---|---|---|---|
| 2017 | 22 | ROKAZL Athletics | 47 | .186/.239/.326 | 0 | 1 | -6 | — | .136/.174/.250 |
| 2018 | 23 | ABeloit Snappe… | 224 | .227/.324/.289 | 0 | 6 | 29 | — | .173/.248/.218 |
| 2019 | 24 | ABeloit Snappe… | 388 | .195/.279/.286 | 4 | 11 | 15 | — | .146/.211/.208 |
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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.
| 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 | 21 | ROK | AZL Athletics | — | 81 | 75 | 13 | 2 | 0 | 0 | 6 | 14 | 0 | 5 | 0 | 173 | 235 | 200 | 435 | 27 | 213 | 17 | 7 | 206 | -15 | — | — | — | — | — | — |
| 2017 | 22 | ROK | AZL Athletics | — | 47 | 43 | 8 | 4 | 1 | 0 | 2 | 12 | 1 | 1 | 0 | 186 | 239 | 326 | 565 | 140 | 250 | 26 | 4 | 247 | -6 | — | — | — | — | — | — |
| 2018 | 23 | A | Beloit Snappers | — | 224 | 194 | 44 | 10 | 1 | 0 | 28 | 51 | 0 | 6 | 1 | 227 | 324 | 289 | 613 | 62 | 303 | 23 | 12 | 285 | 29 | — | — | — | — | — | — |
| 2019 | 24 | A | Beloit Snappers | — | 388 | 343 | 67 | 19 | 0 | 4 | 35 | 87 | 5 | 11 | 3 | 195 | 279 | 286 | 564 | 90 | 248 | 22 | 9 | 259 | 15 | — | — | — | — | — | — |
| ▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents) | |||||||||||||||||||||||||||||||
| 2016 | 21 | ROK MLE | AZL Athletics | — | 81 | 77 | 10 | 1 | 0 | 0 | 4 | 20 | 0 | 5 | 0 | 130 | 173 | 143 | 316 | 13 | 175 | 25 | 5 | 146 | -15 | — | — | — | — | — | — |
| 2017 | 22 | ROK MLE | AZL Athletics | — | 47 | 44 | 6 | 3 | 1 | 0 | 1 | 17 | 1 | 1 | 0 | 136 | 174 | 250 | 424 | 114 | 184 | 36 | 2 | 160 | -6 | — | — | — | — | — | — |
| 2018 | 23 | A MLE | Beloit Snappers | — | 224 | 202 | 35 | 7 | 1 | 0 | 20 | 67 | 0 | 6 | 1 | 173 | 248 | 218 | 466 | 45 | 245 | 30 | 9 | 211 | 29 | — | — | — | — | — | — |
| 2019 | 24 | A MLE | Beloit Snappers | — | 388 | 355 | 52 | 13 | 0 | 3 | 24 | 116 | 5 | 11 | 3 | 146 | 211 | 208 | 419 | 62 | 204 | 30 | 6 | 191 | 15 | — | — | — | — | — | — |
| 2016 | 21 | ROK MLE | AZL Athletics | — | 81 | 77 | 10 | 1 | 0 | 0 | 4 | 20 | 0 | 5 | 0 | 130 | 173 | 143 | 316 | 13 | 175 | 25 | 5 | 146 | -15 | — | — | — | — | — | — |
| 2016 | 21 | ROK RAW | AZL Athletics | — | 81 | 75 | 13 | 2 | 0 | 0 | 6 | 14 | 0 | 5 | 0 | 173 | 235 | 200 | 435 | 27 | 213 | 17 | 7 | 206 | -15 | — | — | — | — | — | — |
| 2017 | 22 | ROK MLE | AZL Athletics | — | 47 | 44 | 6 | 3 | 1 | 0 | 1 | 17 | 1 | 1 | 0 | 136 | 174 | 250 | 424 | 114 | 214 | 36 | 2 | 160 | -6 | — | — | — | — | — | — |
| 2017 | 22 | ROK RAW | AZL Athletics | — | 47 | 43 | 8 | 4 | 1 | 0 | 2 | 12 | 1 | 1 | 0 | 186 | 239 | 326 | 565 | 140 | 250 | 26 | 4 | 247 | -6 | — | — | — | — | — | — |
| 2018 | 23 | A MLE | Beloit Snappers | — | 224 | 202 | 35 | 7 | 1 | 0 | 20 | 67 | 0 | 6 | 1 | 173 | 248 | 218 | 466 | 45 | 255 | 30 | 9 | 211 | 29 | — | — | — | — | — | — |
| 2018 | 23 | A RAW | Beloit Snappers | — | 224 | 194 | 44 | 10 | 1 | 0 | 28 | 51 | 0 | 6 | 1 | 227 | 324 | 289 | 613 | 62 | 303 | 23 | 12 | 285 | 29 | — | — | — | — | — | — |
| 2019 | 24 | A MLE | Beloit Snappers | — | 388 | 355 | 52 | 13 | 0 | 3 | 24 | 116 | 5 | 11 | 3 | 146 | 211 | 208 | 419 | 62 | 206 | 30 | 6 | 191 | 15 | — | — | — | — | — | — |
| 2019 | 24 | A RAW | Beloit Snappers | — | 388 | 343 | 67 | 19 | 0 | 4 | 35 | 87 | 5 | 11 | 3 | 195 | 279 | 286 | 564 | 90 | 248 | 22 | 9 | 259 | 15 | — | — | — | — | — | — |
| 2016 | 21 | ROK MLE | AZL Athletics | — | 81 | 77 | 10 | 1 | 0 | 0 | 4 | 20 | 0 | 5 | 0 | 130 | 173 | 143 | 316 | 13 | 175 | 25 | 5 | 146 | -15 | — | — | — | — | — | — |
| 2017 | 22 | ROK MLE | AZL Athletics | — | 47 | 45 | 6 | 3 | 1 | 0 | 1 | 17 | 1 | 1 | 0 | 133 | 174 | 244 | 418 | 111 | 184 | 36 | 2 | 160 | -6 | — | — | — | — | — | — |
| 2018 | 23 | A MLE | Beloit Snappers | — | 224 | 202 | 35 | 7 | 1 | 0 | 20 | 67 | 0 | 6 | 1 | 173 | 248 | 218 | 466 | 45 | 245 | 30 | 9 | 211 | 29 | — | — | — | — | — | — |
| 2019 | 24 | A MLE | Beloit Snappers | — | 388 | 356 | 52 | 13 | 0 | 3 | 24 | 116 | 5 | 11 | 3 | 146 | 211 | 208 | 419 | 62 | 204 | 30 | 6 | 191 | 15 | — | — | — | — | — | — |
| ▸ Career Totals | |||||||||||||||||||||||||||||||
| Career | — | MLE | — | 740 | 678 | 103 | 24 | 2 | 3 | 49 | 220 | 6 | 23 | 4 | 152 | 216 | 206 | 422 | 55 | 217 | 30 | 7 | 190 | 15 | -75 | +3 | +0 | +13 | +16 | -4.4 | |
| / 162G | — | MLE | — | 650 | 596 | 91 | 21 | 2 | 3 | 43 | 193 | 5 | 20 | 4 | 153 | 216 | 210 | 426 | 57 | 218 | 30 | 7 | 190 | 15 | -66 | +2 | +0 | +12 | +14 | -3.9 | |
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.
2019 ABeloit Snappers · 388 PAwOBA .254 → .191 (−63)K% 22.4% → 29.9%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 22.42% | ÷1.019 | ×1.360 | — | — | 29.93% |
| BB% (unintentional) /PA | 9.02% | ÷0.978 | ×0.690 | — | ×0.980 | 6.24% |
| HBP% /PA | 1.29% | — | ×0.780 | — | ×0.980 | 0.99% |
| Singles /BIP | 17.19% | ÷0.992 | ×0.920 | ×0.950 | ×0.980 | 14.85% |
| Doubles /BIP | 7.42% | ÷1.049 | ×0.830 | ×0.950 | ×0.980 | 5.46% |
| Triples /BIP | 0.00% | ÷1.150 | ×0.910 | ×0.950 | ×0.980 | 0.00% |
| Home runs /BIP | 1.56% | ÷1.014 | ×0.800 | — | ×0.980 | 1.21% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 103, 1B 98, 2B 110, 3B 130, K 104, BB 96 — 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 ×0.950.
Result: wOBA .254 → .191; ISO .090 → .065; BABIP .248 → .204. 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 ABeloit Snappers · 224 PAwOBA .281 → .211 (−70)K% 22.8% → 29.7%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 22.77% | ÷1.044 | ×1.360 | — | — | 29.65% |
| BB% (unintentional) /PA | 12.50% | ÷0.969 | ×0.690 | — | ×0.990 | 8.81% |
| HBP% /PA | 0.00% | — | ×0.780 | — | ×0.990 | 0.00% |
| Singles /BIP | 23.08% | ÷1.068 | ×0.920 | ×0.982 | ×0.990 | 19.31% |
| Doubles /BIP | 6.99% | ÷1.153 | ×0.830 | ×0.982 | ×0.990 | 4.89% |
| Triples /BIP | 0.70% | ÷0.994 | ×0.910 | ×0.982 | ×0.990 | 0.62% |
| Home runs /BIP | 0.00% | ÷0.895 | ×0.800 | — | ×0.990 | 0.00% |
Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 79, 1B 114, 2B 131, 3B 99, K 109, 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 ×0.982.
Result: wOBA .281 → .211; ISO .062 → .044; BABIP .303 → .245. 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 Athletics · 47 PAwOBA .245 → .160 (−85)K% 25.5% → 36.8%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 25.53% | ÷1.000 | ×1.440 | — | — | 36.77% |
| BB% (unintentional) /PA | 4.26% | ÷1.000 | ×0.620 | — | ×0.975 | 2.57% |
| HBP% /PA | 2.13% | — | ×0.720 | — | ×0.975 | 1.49% |
| Singles /BIP | 9.68% | ÷1.000 | ×0.820 | — | ×0.975 | 7.74% |
| Doubles /BIP | 12.90% | ÷1.000 | ×0.720 | — | ×0.975 | 9.06% |
| Triples /BIP | 3.23% | ÷1.000 | ×0.720 | — | ×0.975 | 2.26% |
| Home runs /BIP | 0.00% | ÷1.000 | ×0.780 | — | ×0.975 | 0.00% |
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 22 vs a level average of 19.5 → −2.5% on BB/HBP/hit rates (2.5 yr older than average).
Result: wOBA .245 → .160; ISO .140 → .088; BABIP .250 → .184. 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 ROKAZL Athletics · 81 PAwOBA .201 → .146 (−55)K% 17.3% → 24.9%
| Component | Raw | Park ÷ | Level factor × | GB/FB × | Age × | = MLE |
|---|---|---|---|---|---|---|
| K% /PA | 17.28% | ÷1.000 | ×1.440 | — | — | 24.89% |
| BB% (unintentional) /PA | 7.41% | ÷1.000 | ×0.620 | — | ×0.985 | 4.52% |
| HBP% /PA | 0.00% | — | ×0.720 | — | ×0.985 | 0.00% |
| Singles /BIP | 18.03% | ÷1.000 | ×0.820 | ×1.036 | ×0.985 | 15.09% |
| Doubles /BIP | 3.28% | ÷1.000 | ×0.720 | ×1.036 | ×0.985 | 2.41% |
| Triples /BIP | 0.00% | ÷1.000 | ×0.720 | ×1.036 | ×0.985 | 0.00% |
| Home runs /BIP | 0.00% | ÷1.000 | ×0.780 | — | ×0.985 | 0.00% |
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 21 vs a level average of 19.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.036.
Result: wOBA .201 → .146; ISO .027 → .018; BABIP .213 → .175. 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).