Sergio Perez

PosCF
B/TL/R
Born1989-10-27
Age (2027)37
No MLB projection yet. Career stats below are historical.
Overview
INTLLAST SEASON 2024
YearAgeLvl / TeamPAAVG/OBP/SLGHRSBwRC+WAR
202232INTLCharros de Ja…69.234/.290/.4223099—
202333INTLMayos de Navo…38.324/.342/.48610133—
202434INTLMayos de Navo…49.200/.265/.2891059—
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)
200919 AAADorados de Chihuahua — 387351 991142 26533 57 282337353690 71326 147 308 83 — — — — — —
201020 AAASultanes de Monterrey — 215189 54820 16373 43 286351349700 63348 177 310 87 — — — — — —
201020 INTLYaquis de Obregon — 2623 3000 360 31 130231130361 176 2312 185 11 — — — — — —
201121 AAASultanes de Monterrey — 282245 801133 31422 610 327405433838 106385 1511 373 118 — — — — — —
201222 AAASultanes de Monterrey — 239213 58821 20353 72 272343343686 70320 158 311 74 — — — — — —
201222 INTLCaneros de los Mochis — 117106 37530 5233 00 349395453848 104440 204 369 136 — — — — — —
201323 AAASultanes de Monterrey — 262235 72912 13506 73 306358379737 72378 195 325 94 — — — — — —
201323 INTLCaneros de los Mochis — 141128 35611 11170 01 273331359690 86309 128 309 95 — — — — — —
201424 AAASultanes de Monterrey — 270235 771354 24434 62 328399477876 149386 169 380 125 — — — — — —
201525 AAAPericos de Puebla — 282246 761111 27382 03 309382374756 65359 1310 337 80 — — — — — —
201626 AAAPericos de Puebla — 218190 55601 21271 06 289363337700 47327 1210 315 70 — — — — — —
201727 AAAPericos de Puebla — 261235 681520 22392 71 289355370725 81347 158 327 72 — — — — — —
201929 AAAPericos de Puebla — 239219 721216 13361 13 329369475844 146367 155 365 79 — — — — — —
201929 INTLSultanes de Monterrey — 147127 33400 12194 03 260343291634 31306 138 290 83 — — — — — —
202030 INTLCharros de Jalisco — 2525 3000 080 00 120120120240 176 320 109 -40 — — — — — —
202131 INTLCharros de Jalisco — 8268 19301 11152 10 279395368763 88346 1813 349 123 — — — — — —
202232 INTLCharros de Jalisco — 6964 15303 5140 00 234290422712 188255 207 315 99 — — — — — —
202333 INTLMayos de Navojoa — 3837 12301 1100 00 324342486829 162423 263 365 133 — — — — — —
202434 INTLMayos de Navojoa — 4945 9101 3151 00 200265289554 89276 316 256 59 — — — — — —
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
200919 AAA MLEDorados de Chihuahua — 387358 1001041 19633 57 279321338659 59329 165 291 83 — — — — — —
201020 AAA MLESultanes de Monterrey — 215194 56820 11443 43 289337351687 62348 205 297 87 — — — — — —
201121 AAA MLESultanes de Monterrey — 282259 821032 18522 610 317366402767 85386 186 342 118 — — — — — —
201222 AAA MLESultanes de Monterrey — 239218 57721 15433 72 261318326643 64310 186 278 74 — — — — — —
201323 AAA MLESultanes de Monterrey — 262240 72711 8586 73 300339350689 50376 223 307 94 — — — — — —
201424 AAA MLESultanes de Monterrey — 270243 781263 16544 62 321373457829 136386 206 353 125 — — — — — —
201525 AAA MLEPericos de Puebla — 282256 71911 17502 03 277327332659 55325 186 286 80 — — — — — —
201626 AAA MLEPericos de Puebla — 218200 53501 11351 06 265307305612 40301 165 272 70 — — — — — —
201727 AAA MLEPericos de Puebla — 261242 621420 15512 71 256305331636 74318 206 275 72 — — — — — —
201929 AAA MLEPericos de Puebla — 239226 611014 6441 13 270292376668 106304 183 285 79 — — — — — —
200919 AAA MLEDorados de Chihuahua — 387358 1001041 19633 57 279321338659 59334 165 291 83 — — — — — —
200919 AAA RAWDorados de Chihuahua — 387351 991142 26533 57 282337353690 71326 147 308 83 — — — — — —
201020 AAA MLE2 teams — 241219 63920 12493 74 288333347680 59364 205 297 87 — — — — — —
201020 AAA RAW2 teams — 241212 57820 19433 74 269338325663 57331 188 297 87 — — — — — —
201121 AAA MLESultanes de Monterrey — 282259 821032 18522 610 317366402767 85390 186 342 118 — — — — — —
201121 AAA RAWSultanes de Monterrey — 282245 801133 31422 610 327405433838 106385 1511 373 118 — — — — — —
201222 AAA MLE2 teams — 356322 841031 22646 72 261320320640 59320 186 278 74 — — — — — —
201222 AAA RAW2 teams — 356319 951351 25586 72 298360379739 82359 167 330 74 — — — — — —
201323 AAA MLE2 teams — 403374 1111112 13896 74 297331348678 51382 223 307 94 — — — — — —
201323 AAA RAW2 teams — 403363 1071523 24676 74 295349372721 77353 176 319 94 — — — — — —
201424 AAA MLESultanes de Monterrey — 270243 781263 16544 62 321373457829 136401 206 353 125 — — — — — —
201424 AAA RAWSultanes de Monterrey — 270235 771354 24434 62 328399477876 149386 169 380 125 — — — — — —
201525 AAA MLEPericos de Puebla — 282256 71911 17502 03 277327332659 55338 186 286 80 — — — — — —
201525 AAA RAWPericos de Puebla — 282246 761111 27382 03 309382374756 65359 1310 337 80 — — — — — —
201626 AAA MLEPericos de Puebla — 218200 53501 11351 06 265307305612 40311 165 272 70 — — — — — —
201626 AAA RAWPericos de Puebla — 218190 55601 21271 06 289363337700 47327 1210 315 70 — — — — — —
201727 AAA MLEPericos de Puebla — 261242 621420 15512 71 256305331636 74325 206 275 72 — — — — — —
201727 AAA RAWPericos de Puebla — 261235 681520 22392 71 289355370725 81347 158 327 72 — — — — — —
201929 AAA MLE2 teams — 386362 981616 9725 16 271298370668 99321 192 285 79 — — — — — —
201929 AAA RAW2 teams — 386346 1051616 25555 16 303359408767 104344 146 337 79 — — — — — —
202030 INTL MLECharros de Jalisco — 2525 3000 080 00 120120120240 176 320 — — — — — — — —
202030 INTL RAWCharros de Jalisco — 2525 3000 080 00 120120120240 176 320 109 -40 — — — — — —
202131 INTL MLECharros de Jalisco — 8268 19301 11152 10 279395368763 88346 1813 — — — — — — — —
202131 INTL RAWCharros de Jalisco — 8268 19301 11152 10 279395368763 88346 1813 349 123 — — — — — —
202232 INTL MLECharros de Jalisco — 6964 15303 5140 00 234290422712 188255 207 — — — — — — — —
202232 INTL RAWCharros de Jalisco — 6964 15303 5140 00 234290422712 188255 207 315 99 — — — — — —
202333 INTL MLEMayos de Navojoa — 3837 12301 1100 00 324342486829 162423 263 — — — — — — — —
202333 INTL RAWMayos de Navojoa — 3837 12301 1100 00 324342486829 162423 263 365 133 — — — — — —
202434 INTL MLEMayos de Navojoa — 4945 9101 3151 00 200265289554 89276 316 — — — — — — — —
202434 INTL RAWMayos de Navojoa — 4945 9101 3151 00 200265289554 89276 316 256 59 — — — — — —
200919 AAA MLEDorados de Chihuahua — 387362 1001041 19633 57 276321334655 58329 165 291 83 — — — — — —
201020 AAA MLE2 teams — 241224 63920 12493 74 281333339673 58348 205 297 87 — — — — — —
201121 AAA MLESultanes de Monterrey — 282260 821032 18522 610 315366400766 85386 186 342 118 — — — — — —
201222 AAA MLE2 teams — 356325 841031 22646 72 258320317637 58310 186 278 74 — — — — — —
201323 AAA MLE2 teams — 403381 1111112 13896 74 291331341672 50376 223 307 94 — — — — — —
201424 AAA MLESultanes de Monterrey — 270248 781263 16544 62 315373448820 133386 206 353 125 — — — — — —
201525 AAA MLEPericos de Puebla — 282261 71911 17502 03 272327326653 54325 186 286 80 — — — — — —
201626 AAA MLEPericos de Puebla — 218204 53501 11351 06 260307299606 39301 165 272 70 — — — — — —
201727 AAA MLEPericos de Puebla — 261242 621420 15512 71 256305331636 74318 206 275 72 — — — — — —
201929 AAA MLE2 teams — 386369 981616 9725 16 266298363661 98304 192 285 79 — — — — — —
▸ Career Totals
Career— MLE — 33493074 8601162323 17264137 4745 280326355681 75345 195 275 72 -111 -9 +0 +12 +73 -3.6
/ 162G— MLE — 650597 1662344 331247 99 278323350673 72343 195 275 72 -22 -2 +0 +2 +14 -0.7

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 AAAPericos de Puebla · 239 PAwOBA .354 → .285 (−69)K% 15.1% → 18.6%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA15.06%÷0.970×1.200——18.63%
BB% (unintentional) /PA3.77%÷1.043×0.690—×0.9722.42%
HBP% /PA0.42%—×0.940—×0.9720.38%
Singles /BIP28.96%÷1.008×0.930×0.950×0.97224.66%
Doubles /BIP6.56%÷0.964×0.830×0.950×0.9725.22%
Triples /BIP0.55%÷1.150×0.920×0.950×0.9720.40%
Home runs /BIP3.28%÷1.144×0.700—×0.9721.95%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 129, 1B 102, 2B 93, 3B 130, K 94, BB 109 — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .354 → .285; ISO .146 → .102; BABIP .367 → .304. 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 AAAPericos de Puebla · 261 PAwOBA .319 → .275 (−45)K% 14.9% → 19.5%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA14.94%÷0.920×1.200——19.49%
BB% (unintentional) /PA8.43%÷1.033×0.690—×0.9925.58%
HBP% /PA0.77%—×0.940—×0.9920.71%
Singles /BIP26.02%÷1.055×0.930×1.050×0.99223.90%
Doubles /BIP7.65%÷0.946×0.830×1.050×0.9927.00%
Triples /BIP1.02%÷1.114×0.920×1.050×0.9920.88%
Home runs /BIP0.00%÷0.910×0.700—×0.9920.00%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 82, 1B 111, 2B 89, 3B 123, K 84, BB 107 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .319 → .275; ISO .081 → .072; BABIP .347 → .318. 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 AAAPericos de Puebla · 218 PAwOBA .304 → .272 (−32)K% 12.4% → 16.1%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA12.39%÷0.921×1.200——16.14%
BB% (unintentional) /PA7.80%÷1.091×0.690—×1.0034.95%
HBP% /PA0.46%—×0.940—×1.0030.43%
Singles /BIP29.45%÷1.048×0.930×1.049×1.00327.51%
Doubles /BIP3.68%÷1.075×0.830×1.049×1.0032.99%
Triples /BIP0.00%÷1.008×0.920×1.049×1.0030.00%
Home runs /BIP0.61%÷1.024×0.700—×1.0030.42%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 105, 1B 110, 2B 115, 3B 102, K 84, BB 118 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.049.

Result: wOBA .304 → .272; ISO .047 → .038; BABIP .327 → .301. 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 AAAPericos de Puebla · 282 PAwOBA .330 → .286 (−45)K% 13.5% → 17.7%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA13.48%÷0.913×1.200——17.71%
BB% (unintentional) /PA9.22%÷1.080×0.690—×1.0186.00%
HBP% /PA0.71%—×0.940—×1.0180.68%
Singles /BIP30.29%÷1.075×0.930×1.050×1.01828.00%
Doubles /BIP5.29%÷1.100×0.830×1.050×1.0184.26%
Triples /BIP0.48%÷1.150×0.920×1.050×1.0180.41%
Home runs /BIP0.48%÷1.062×0.700—×1.0180.32%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 112, 1B 115, 2B 120, 3B 130, K 83, BB 116 — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .330 → .286; ISO .065 → .052; BABIP .359 → .325. 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 AAASultanes de Monterrey · 270 PAwOBA .371 → .353 (−19)K% 15.9% → 19.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA15.93%÷0.961×1.200——19.88%
BB% (unintentional) /PA8.89%÷1.030×0.690—×1.0336.15%
HBP% /PA1.48%—×0.940—×1.0331.44%
Singles /BIP28.65%÷0.999×0.930×1.050×1.03328.92%
Doubles /BIP6.77%÷0.963×0.830×1.050×1.0336.33%
Triples /BIP2.60%÷0.900×0.920×1.050×1.0332.89%
Home runs /BIP2.08%÷0.917×0.700—×1.0331.64%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 83, 1B 100, 2B 93, 3B 80, K 92, BB 106 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .371 → .353; ISO .149 → .142; BABIP .386 → .386. 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 AAASultanes de Monterrey · 262 PAwOBA .316 → .307 (−8)K% 19.1% → 22.0%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA19.08%÷1.039×1.200——22.04%
BB% (unintentional) /PA4.20%÷0.952×0.690—×1.0483.19%
HBP% /PA2.29%—×0.940—×1.0482.26%
Singles /BIP32.43%÷0.991×0.930×1.045×1.04833.33%
Doubles /BIP4.86%÷1.140×0.830×1.045×1.0483.88%
Triples /BIP0.54%÷1.150×0.920×1.045×1.0480.47%
Home runs /BIP1.08%÷1.011×0.700—×1.0480.78%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 102, 1B 98, 2B 128, 3B 130, K 108, BB 90 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.045.

Result: wOBA .316 → .307; ISO .072 → .058; BABIP .378 → .376. 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).

2012 AAASultanes de Monterrey · 239 PAwOBA .304 → .278 (−26)K% 14.6% → 17.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA14.64%÷0.984×1.200——17.86%
BB% (unintentional) /PA8.37%÷0.984×0.690—×1.0506.16%
HBP% /PA1.26%—×0.940—×1.0501.24%
Singles /BIP26.40%÷1.015×0.930×1.037×1.05026.34%
Doubles /BIP4.49%÷1.092×0.830×1.037×1.0503.72%
Triples /BIP1.12%÷1.128×0.920×1.037×1.0501.00%
Home runs /BIP0.56%÷1.081×0.700—×1.0500.38%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 116, 1B 103, 2B 118, 3B 126, K 97, BB 97 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.037.

Result: wOBA .304 → .278; ISO .070 → .058; BABIP .320 → .310. 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).

2011 AAASultanes de Monterrey · 282 PAwOBA .358 → .342 (−16)K% 14.9% → 18.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA14.89%÷0.972×1.200——18.40%
BB% (unintentional) /PA9.22%÷1.026×0.690—×1.0506.51%
HBP% /PA0.71%—×0.940—×1.0500.70%
Singles /BIP31.03%÷1.003×0.930×1.050×1.05031.73%
Doubles /BIP5.42%÷0.997×0.830×1.050×1.0504.97%
Triples /BIP1.48%÷1.020×0.920×1.050×1.0501.47%
Home runs /BIP1.48%÷1.053×0.700—×1.0501.03%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 111, 1B 101, 2B 99, 3B 104, K 94, BB 105 — applied at half strength. Age: age 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .358 → .342; ISO .106 → .094; BABIP .385 → .386. 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 — .