Bryant Aragon

PosC
B/TL/R
Born1998-04-10
Age (2027)29
No MLB projection yet. Career stats below are historical.
Overview
AAALAST SEASON 2019
YearAgeLvl / TeamPAAVG/OBP/SLGHRSBwRC+WARMLE AVG/OBP/SLG
201517ROKAZL Padres64.224/.286/.345008—.136/.190/.203
201618ROKAZL Padres127.243/.304/.3833030—.169/.216/.254
201921AAA/INTL2 orgs263.277/.338/.3532159—.239/.289/.291
Contract
No contract data on file.

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.
basis chips: RAW = as recorded · CTX = with park/league context · A+C = actual + context combined · MLE = level/park-neutral
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.

YearAge LvlTeam MLB% PAAB H2B3BHR BBSOHBP SBCS AVGOBPSLGOPS ISOBABIP K%BB% wOBAwRC+ BATRUNFLDPOSREP WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
201517 ROKAZL Padres — 6458 13320 3222 01 224286345631 121351 345 279 8 — — — — — —
201618 ROKAZL Padres — 127115 28323 9271 00 243304383687 139287 217 303 30 — — — — — —
201921 AAAAlgodoneros Union Laguna — 231207 601102 19642 11 290355372727 82408 288 327 64 — — — — — —
201921 INTLAlgodoneros de Guasave — 3231 6100 1150 00 194219226445 32375 473 203 24 — — — — — —
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
201517 ROK MLEAZL Padres — 6459 8210 2322 01 136190203394 68283 503 180 8 — — — — — —
201618 ROK MLEAZL Padres — 127118 20212 6391 00 169216254470 85222 315 212 30 — — — — — —
201921 AAA MLEAlgodoneros Union Laguna — 231213 51801 13802 11 239289291581 52371 356 263 64 — — — — — —
201517 ROK MLEAZL Padres — 6459 8210 2322 01 136190203394 68286 503 180 8 — — — — — —
201517 ROK RAWAZL Padres — 6458 13320 3222 01 224286345631 121351 345 279 8 — — — — — —
201618 ROK MLEAZL Padres — 127118 20212 6391 00 169216254470 85228 315 212 30 — — — — — —
201618 ROK RAWAZL Padres — 127115 28323 9271 00 243304383687 139287 217 303 30 — — — — — —
201921 AAA MLE2 teams — 263243 59902 15922 11 243292305597 62380 356 263 64 — — — — — —
201921 AAA RAW2 teams — 263238 661202 20792 11 277338353691 76405 308 312 64 — — — — — —
201517 ROK MLEAZL Padres — 6460 8210 2322 01 133190200390 67283 503 180 8 — — — — — —
201618 ROK MLEAZL Padres — 127119 20212 6391 00 168216252468 84222 315 212 30 — — — — — —
201921 AAA MLE2 teams — 263244 59902 15922 11 242292303596 61371 356 263 64 — — — — — —
▸ Career Totals
Career— MLE — 454420 871324 231635 12 207257276533 69323 365 237 47 -29 -1 +0 +8 +10 -1.2
/ 162G— MLE — 650601 1251936 332337 13 208257280537 72323 365 237 47 -41 -1 +0 +12 +14 -1.7

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 AAAAlgodoneros Union Laguna · 231 PAwOBA .318 → .263 (−55)K% 27.7% → 34.8%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA27.71%÷0.956×1.200——34.76%
BB% (unintentional) /PA7.79%÷1.004×0.690—×1.0505.62%
HBP% /PA0.87%—×0.940—×1.0500.85%
Singles /BIP32.87%÷0.981×0.930×0.950×1.05031.08%
Doubles /BIP7.69%÷1.076×0.830×0.950×1.0505.92%
Triples /BIP0.00%÷1.116×0.920×0.950×1.0500.00%
Home runs /BIP1.40%÷1.028×0.700—×1.0501.00%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 106, 1B 96, 2B 115, 3B 123, K 91, BB 101 — 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 .318 → .263; ISO .082 → .058; BABIP .408 → .371. 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 Padres · 127 PAwOBA .299 → .212 (−87)K% 21.3% → 30.6%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA21.26%÷1.000×1.440——30.61%
BB% (unintentional) /PA7.09%÷1.000×0.620—×1.0224.49%
HBP% /PA0.79%—×0.720—×1.0220.58%
Singles /BIP22.73%÷1.000×0.820×0.955×1.02218.20%
Doubles /BIP3.41%÷1.000×0.720×0.955×1.0222.40%
Triples /BIP2.27%÷1.000×0.720×0.955×1.0221.60%
Home runs /BIP3.41%÷1.000×0.780—×1.0222.72%

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 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.955.

Result: wOBA .299 → .212; ISO .139 → .098; BABIP .287 → .222. 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 ROKAZL Padres · 64 PAwOBA .277 → .180 (−97)K% 34.4% → 49.5%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA34.38%÷1.000×1.440——49.50%
BB% (unintentional) /PA4.69%÷1.000×0.620—×1.0383.02%
HBP% /PA3.12%—×0.720—×1.0382.33%
Singles /BIP22.22%÷1.000×0.820—×1.03818.91%
Doubles /BIP8.33%÷1.000×0.720—×1.0386.22%
Triples /BIP5.56%÷1.000×0.720—×1.0384.15%
Home runs /BIP0.00%÷1.000×0.780—×1.0380.00%

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 17 vs a level average of 19.5 → +3.8% on BB/HBP/hit rates (2.5 yr younger than average).

Result: wOBA .277 → .180; ISO .121 → .072; BABIP .351 → .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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .