Brandon Diaz

PosCF
B/TR/R
Born1995-04-14
Age (2027)32
No MLB projection yet. Career stats below are historical.
Overview
A+LAST SEASON 2017
YearAgeLvl / TeamPAAVG/OBP/SLGHRSBwRC+WARMLE AVG/OBP/SLG
201520AMIL340.241/.359/.36262355—.193/.287/.275
201621A+/A2 orgs282.169/.258/.217010-6—.117/.190/.152
201722A+SEA119.204/.305/.3202824—.159/.237/.262
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.

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)
201318 ROKAZL Brewers — 192161 46953 28391 219 286395460854 174361 2015 377 68 — — — — — —
201419 ROKHelena Brewers — 299253 66934 33656 229 261360368727 107332 2211 326 49 — — — — — —
201520 AWisconsin Timber Rattlers — 340282 681416 46836 2310 241359362721 121318 2414 327 55 — — — — — —
201621 A+Brevard County Manatees — 186163 27400 19682 74 166261190451 25284 3710 219 -6 — — — — — —
201621 AWisconsin Timber Rattlers — 9686 15610 8431 32 174253267520 93349 458 238 -6 — — — — — —
201722 A+Inland Empire 66ers — 119103 21412 15430 81 204305320625 117328 3613 286 24 — — — — — —
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
201318 ROK MLEAZL Brewers — 192171 36642 18561 219 211289327617 117292 299 269 68 — — — — — —
201419 ROK MLEHelena Brewers — 299266 54723 20946 229 203274278552 75279 317 241 49 — — — — — —
201520 A MLEWisconsin Timber Rattlers — 340295 571014 331146 2310 193287275562 81283 3410 249 55 — — — — — —
201621 A+ MLEBrevard County Manatees — 186168 20300 14942 74 119196137333 18262 518 159 -6 — — — — — —
201621 A MLEWisconsin Timber Rattlers — 9688 10410 6571 32 114179182361 68312 596 159 -6 — — — — — —
201722 A+ MLEInland Empire 66ers — 119107 17312 11590 81 159237262499 103292 509 203 24 — — — — — —
201318 ROK MLEAZL Brewers — 192171 36642 18561 219 211289327617 117301 299 269 68 — — — — — —
201318 ROK RAWAZL Brewers — 192161 46953 28391 219 286395460854 174361 2015 377 68 — — — — — —
201419 ROK MLEHelena Brewers — 299266 54723 20946 229 203274278552 75297 317 241 49 — — — — — —
201419 ROK RAWHelena Brewers — 299253 66934 33656 229 261360368727 107332 2211 326 49 — — — — — —
201520 A MLEWisconsin Timber Rattlers — 340295 571014 331146 2310 193287275562 81296 3410 249 55 — — — — — —
201520 A RAWWisconsin Timber Rattlers — 340282 681416 46836 2310 241359362721 121318 2414 327 55 — — — — — —
201621 A+ MLE2 teams — 282256 30710 201523 106 117190152342 35288 547 159 -6 — — — — — —
201621 A+ RAW2 teams — 282249 421010 271113 106 169258217475 48304 3910 225 -6 — — — — — —
201722 A+ MLEInland Empire 66ers — 119107 17312 11590 81 159237262499 103326 509 203 24 — — — — — —
201722 A+ RAWInland Empire 66ers — 119103 21412 15430 81 204305320625 117328 3613 286 24 — — — — — —
201318 ROK MLEAZL Brewers — 192171 36642 18561 219 211289327617 117292 299 269 68 — — — — — —
201419 ROK MLEHelena Brewers — 299271 54723 20946 229 199274273547 74279 317 241 49 — — — — — —
201520 A MLEWisconsin Timber Rattlers — 340298 571014 331146 2310 191287272559 81283 3410 249 55 — — — — — —
201621 A+ MLE2 teams — 282257 30710 201523 106 117190152342 35279 547 159 -6 — — — — — —
201722 A+ MLEInland Empire 66ers — 119107 17312 11590 81 159237262499 103292 509 203 24 — — — — — —
▸ Career Totals
Career— MLE — 12321095 19433911 10247516 8435 177257254511 77298 398 225 39 -90 +3 +0 +4 +27 -5.7
/ 162G— MLE — 650578 1021756 542518 4418 176256254511 78296 398 225 39 -48 +2 +0 +2 +14 -3.0

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.

2017 A+Inland Empire 66ers · 119 PAwOBA .279 → .203 (−77)K% 36.1% → 49.7%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA36.13%÷0.975×1.340——49.67%
BB% (unintentional) /PA12.61%÷1.003×0.710—×1.0129.03%
HBP% /PA0.00%—×0.790—×1.0120.00%
Singles /BIP23.33%÷0.955×0.910×0.950×1.01221.37%
Doubles /BIP6.67%÷0.891×0.820×0.950×1.0125.90%
Triples /BIP1.67%÷1.150×0.760×0.950×1.0121.06%
Home runs /BIP3.33%÷1.008×0.920—×1.0123.08%

Factors used: league row CAL. Park (home-season share, regressed): HR 102, 1B 91, 2B 78, 3B 130, K 95, BB 101 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .279 → .203; ISO .117 → .082; BABIP .328 → .292. 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+Brevard County Manatees · 186 PAwOBA .214 → .159 (−55)K% 36.6% → 50.8%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA36.56%÷1.021×1.420——50.85%
BB% (unintentional) /PA10.22%÷1.036×0.750—×1.0277.59%
HBP% /PA1.08%—×0.930—×1.0271.03%
Singles /BIP24.21%÷1.014×0.920×0.980×1.02722.11%
Doubles /BIP4.21%÷1.001×0.960×0.980×1.0274.07%
Triples /BIP0.00%÷0.900×0.810×0.980×1.0270.00%
Home runs /BIP0.00%÷1.093×0.880—×1.0270.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 119, 1B 103, 2B 100, 3B 80, K 104, BB 107 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.980.

Result: wOBA .214 → .159; ISO .025 → .019; BABIP .284 → .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).

2016 AWisconsin Timber Rattlers · 96 PAwOBA .233 → .159 (−74)K% 44.8% → 59.6%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA44.79%÷1.022×1.360——59.60%
BB% (unintentional) /PA8.33%÷0.985×0.690—×1.0155.93%
HBP% /PA1.04%—×0.780—×1.0150.82%
Singles /BIP18.60%÷1.023×0.920—×1.01516.98%
Doubles /BIP13.95%÷0.953×0.830—×1.01512.33%
Triples /BIP2.33%÷1.150×0.910—×1.0151.87%
Home runs /BIP0.00%÷1.161×0.800—×1.0150.00%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 132, 1B 105, 2B 91, 3B 130, K 104, BB 97 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average).

Result: wOBA .233 → .159; ISO .093 → .060; BABIP .349 → .312. 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 AWisconsin Timber Rattlers · 340 PAwOBA .321 → .249 (−72)K% 24.4% → 33.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA24.41%÷0.993×1.360——33.43%
BB% (unintentional) /PA13.53%÷0.995×0.690—×1.0309.66%
HBP% /PA1.76%—×0.780—×1.0301.42%
Singles /BIP23.62%÷0.978×0.920×0.975×1.03022.30%
Doubles /BIP7.04%÷1.090×0.830×0.975×1.0305.38%
Triples /BIP0.50%÷1.085×0.910×0.975×1.0300.42%
Home runs /BIP3.02%÷1.331×0.800—×1.0301.87%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 166, 1B 96, 2B 118, 3B 117, K 99, BB 99 — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.975.

Result: wOBA .321 → .249; ISO .121 → .079; BABIP .318 → .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).

2014 ROKHelena Brewers · 299 PAwOBA .321 → .241 (−80)K% 21.7% → 31.3%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA21.74%÷1.000×1.440——31.30%
BB% (unintentional) /PA11.04%÷1.000×0.610—×1.0086.78%
HBP% /PA2.01%—×0.720—×1.0081.46%
Singles /BIP26.60%÷1.000×0.820×1.050×1.00823.07%
Doubles /BIP4.79%÷1.000×0.720×1.050×1.0083.65%
Triples /BIP1.60%÷1.000×0.720×1.050×1.0081.22%
Home runs /BIP2.13%÷1.000×0.750—×1.0081.61%

Factors used: league row PIO. 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 ×1.050.

Result: wOBA .321 → .241; ISO .107 → .078; BABIP .332 → .279. 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).

2013 ROKAZL Brewers · 192 PAwOBA .368 → .269 (−99)K% 20.3% → 29.2%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA20.31%÷1.000×1.440——29.25%
BB% (unintentional) /PA14.58%÷1.000×0.620—×1.0229.25%
HBP% /PA0.52%—×0.720—×1.0220.38%
Singles /BIP23.77%÷1.000×0.820×1.007×1.02220.07%
Doubles /BIP7.38%÷1.000×0.720×1.007×1.0225.47%
Triples /BIP4.10%÷1.000×0.720×1.007×1.0223.04%
Home runs /BIP2.46%÷1.000×0.780—×1.0221.96%

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 ×1.007.

Result: wOBA .368 → .269; ISO .174 → .127; BABIP .361 → .292. 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).