Jorge Cantu

Pos3B
B/TR/R
Born1982-01-30
Age (2027)45
No MLB projection yet. Career stats below are historical.
Overview
AAALAST SEASON 2019
YearAgeLvl / TeamPAAVG/OBP/SLGHRSBwRC+WARMLE AVG/OBP/SLG
201634AAAToros de Tiju…346.225/.307/.3507340—.188/.240/.272
201735AAAToros de Tiju…398.282/.375/.45212277—.228/.291/.353
201937AAADiablos Rojos…277.283/.368/.48812156—.195/.257/.311
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)
200422 MLBTampa Bay Devil Rays — 185173 522012 9442 00 301342462805 162391 245 354 126 +6 +0 +0 +1 +4 1.1
200523 MLBTampa Bay Devil Rays — 631598 17140128 19836 10 286314497811 211289 133 351 123 +17 +0 -14 +2 +14 2.0
200624 MLBTampa Bay Devil Rays — 448413 10318214 26913 11 249299404703 155283 206 309 93 -4 -0 -10 +2 +10 -0.3
200624 AAMontgomery Biscuits — 3331 6002 190 00 194219387606 194190 273 257 30 — — — — — —
200725 MLBCincinnati Reds — 133115 29901 12263 00 252338357695 104308 209 311 97 -0 +0 -4 -6 +3 -0.8
200725 AAALouisville Bats — 202185 511413 13363 00 276333411744 135327 186 332 78 — — — — — —
200826 MLBFlorida Marlins — 685628 17441029 4011110 62 277330481811 204293 166 354 121 +17 +0 -4 +2 +15 3.2
200927 MLBFlorida Marlins — 643585 16942016 47816 31 289348443791 154310 137 350 120 +15 +0 -12 -11 +14 0.6
201028 MLBTexas Rangers — 515472 12129111 29956 00 256308392700 136295 186 308 87 -8 +0 -9 +2 +11 -0.4
201129 MLBSan Diego Padres — 155144 28403 7281 00 194237285522 90216 185 232 42 -11 +0 +1 -7 +3 -1.4
201129 AAAColorado Springs Sky Sox — 125118 33605 6161 00 280320458778 178289 135 344 57 — — — — — —
201129 INTLNaranjeros de Hermosillo — 124108 34309 15151 01 315403593996 278298 1212 433 179 — — — — — —
201230 AAASalt Lake Bees — 9086 25504 2110 00 291307488795 198288 122 340 72 — — — — — —
201230 INTLNaranjeros de Hermosillo — 223189 489113 28493 31 254359519878 265269 2213 379 143 — — — — — —
201331 AAATigres de Quintana Roo — 351300 8111031 42666 20 270371617987 347243 1912 421 103 — — — — — —
201331 INTLTomateros de Culiacan — 110100 22701 9220 00 220284320604 100269 208 273 71 — — — — — —
201533 AAATigres de Quintana Roo — 453385 13526225 49629 41 3514366231.059 273357 1411 450 126 — — — — — —
201533 INTLTomateros de Culiacan — 11095 22501 10183 00 232324316640 84269 169 292 84 — — — — — —
201634 AAAToros de Tijuana — 346306 691517 33603 30 225307350657 124255 1710 296 40 — — — — — —
201735 AAAToros de Tijuana — 398341 9620112 45866 20 282375452827 170339 2211 365 77 — — — — — —
201937 AAADiablos Rojos del Mexico — 277240 6813012 25567 13 283368487855 204320 209 372 56 — — — — — —
▸ Career Totals (raw MLB only — historical actual)
MLB Career— — 33953128 8472035104 18955937 114 271320439758 168297 166 332 111 +45 +1 -52 -16 +74 5.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
200422 MLB MLETampa Bay Devil Rays — 185173 522012 9442 00 301342462805 162391 245 354 126 +6 +0 +0 +1 +4 1.1
200523 MLB MLETampa Bay Devil Rays — 631600 17140128 18836 10 285312495807 210289 133 349 123 +17 +0 -14 +2 +14 2.0
200624 MLB MLETampa Bay Devil Rays — 448415 10318214 24913 11 248294402697 154283 205 306 93 -4 -0 -10 +2 +10 -0.3
200624 AA MLEMontgomery Biscuits — 3331 6002 1110 00 194219387606 194174 333 212 30 — — — — — —
200725 MLB MLECincinnati Reds — 133115 29901 12263 00 252338357695 104308 209 311 97 -0 +0 -4 -6 +3 -0.8
200725 AAA MLELouisville Bats — 202190 471213 8433 00 247289368657 121301 214 284 78 — — — — — —
200826 MLB MLEFlorida Marlins — 685634 17441029 3411110 62 274322476798 202293 165 348 121 +17 +0 -4 +2 +15 3.2
200927 MLB MLEFlorida Marlins — 643589 16942016 43816 31 287342440781 153310 137 345 120 +15 +0 -12 -11 +14 0.6
201028 MLB MLETexas Rangers — 515473 11927111 28956 00 252302383684 131295 185 297 87 -8 +0 -9 +2 +11 -0.4
201129 MLB MLESan Diego Padres — 155145 28403 6281 00 193230283513 90216 184 230 42 -11 +0 +1 -7 +3 -1.4
201129 AAA MLEColorado Springs Sky Sox — 125120 25404 4221 00 208240342582 133232 183 252 57 — — — — — —
201230 AAA MLESalt Lake Bees — 9086 21403 2140 00 244261395657 151245 162 274 72 — — — — — —
201331 AAA MLETigres de Quintana Roo — 351318 699023 24796 20 217284462747 245208 237 320 103 — — — — — —
201533 AAA MLETigres de Quintana Roo — 453407 11822216 27709 41 290348472819 182296 156 355 126 — — — — — —
201634 AAA MLEToros de Tijuana — 346320 601314 19683 30 188240272512 84219 205 228 40 — — — — — —
201735 AAA MLEToros de Tijuana — 398360 821619 261036 20 228291353644 125279 267 282 77 — — — — — —
201937 AAA MLEDiablos Rojos del Mexico — 277251 49807 14777 13 195257311568 116241 285 251 56 — — — — — —
200422 MLB MLETampa Bay Devil Rays — 185173 522012 9442 00 301342462805 162391 245 354 126 +6 +0 +0 +1 +4 1.1
200422 MLB RAWTampa Bay Devil Rays — 185173 522012 9442 00 301342462805 162391 245 354 126 +6 +0 +0 +1 +4 1.1
200523 MLB MLETampa Bay Devil Rays — 631600 17140128 18836 10 285312495807 210288 133 349 123 +17 +0 -14 +2 +14 2.0
200523 MLB RAWTampa Bay Devil Rays — 631598 17140128 19836 10 286314497811 211289 133 351 123 +17 +0 -14 +2 +14 2.0
200624 MLB MLE2 teams — 481446 10918216 251023 11 244289401690 157278 215 299 89 -7 -0 -10 +2 +10 -0.5
200624 MLB RAW2 teams — 481444 10918216 271003 11 245293403696 158278 216 305 89 -7 -0 -10 +2 +10 -0.5
200725 AAA MLE2 teams — 335305 762114 20696 00 249308364672 115305 216 295 86 — — — — — —
200725 AAA RAW2 teams — 335300 802314 25626 00 267335390725 123319 197 324 86 — — — — — —
200826 MLB MLEFlorida Marlins — 685634 17441029 3411110 62 274322476798 202289 165 348 121 +17 +0 -4 +2 +15 3.2
200826 MLB RAWFlorida Marlins — 685628 17441029 4011110 62 277330481811 204293 166 354 121 +17 +0 -4 +2 +15 3.2
200927 MLB MLEFlorida Marlins — 643589 16942016 43816 31 287342440781 153308 137 345 120 +15 +0 -12 -11 +14 0.6
200927 MLB RAWFlorida Marlins — 643585 16942016 47816 31 289348443791 154310 137 350 120 +15 +0 -12 -11 +14 0.6
201028 MLB MLETexas Rangers — 515473 11927111 28956 00 252302383684 131289 185 297 87 -8 +0 -9 +2 +11 -0.4
201028 MLB RAWTexas Rangers — 515472 12129111 29956 00 256308392700 136295 186 308 87 -8 +0 -9 +2 +11 -0.4
201129 MLB MLE3 teams — 404383 771209 15733 01 201237303540 102224 184 240 48 -25 -0 +1 -7 +9 -2.3
201129 MLB RAW3 teams — 404370 9513017 28593 01 257314430744 173263 157 328 48 -25 -0 +1 -7 +9 -2.3
201230 INTL MLE2 teams — 313300 7314010 5493 31 243263390653 147256 162 274 72 — — — — — —
201230 INTL RAW2 teams — 313275 7314117 30603 31 265344509853 244276 1910 368 72 — — — — — —
201331 AAA MLE2 teams — 461419 9112030 321036 20 217282461743 243210 227 320 103 — — — — — —
201331 AAA RAW2 teams — 461400 10318032 51886 20 258350542893 285250 1911 385 103 — — — — — —
201533 AAA MLE2 teams — 563506 14628220 338712 41 289347470817 182307 156 355 126 — — — — — —
201533 AAA RAW2 teams — 563480 15731226 598012 41 327414562976 235339 1410 419 126 — — — — — —
201634 AAA MLEToros de Tijuana — 346320 601314 19683 30 188240272512 84222 205 228 40 — — — — — —
201634 AAA RAWToros de Tijuana — 346306 691517 33603 30 225307350657 124255 1710 296 40 — — — — — —
201735 AAA MLEToros de Tijuana — 398360 821619 261036 20 228291353644 125289 267 282 77 — — — — — —
201735 AAA RAWToros de Tijuana — 398341 9620112 45866 20 282375452827 170339 2211 365 77 — — — — — —
201937 AAA MLEDiablos Rojos del Mexico — 277251 49807 14777 13 195257311568 116247 285 251 56 — — — — — —
201937 AAA RAWDiablos Rojos del Mexico — 277240 6813012 25567 13 283368487855 204320 209 372 56 — — — — — —
200422 MLB MLETampa Bay Devil Rays — 185172 522012 9442 00 302342465808 163391 245 354 126 — — — — — —
200523 MLB MLETampa Bay Devil Rays — 631602 17140128 18836 10 284312493806 209289 133 349 123 — — — — — —
200624 MLB MLE2 teams — 481450 10918216 251023 11 242289398687 156276 215 299 89 — — — — — —
200725 AAA MLE2 teams — 335306 762114 20696 00 248308363671 114304 216 295 86 — — — — — —
200826 MLB MLEFlorida Marlins — 685636 17441029 3411110 62 274322475796 201293 165 348 121 — — — — — —
200927 MLB MLEFlorida Marlins — 643589 16942016 43816 31 287342440781 153310 137 345 120 — — — — — —
201028 MLB MLETexas Rangers — 515476 11927111 28956 00 250302380682 130295 185 297 87 — — — — — —
201129 MLB MLE3 teams — 404383 771209 15733 01 201237303540 102223 184 240 48 — — — — — —
201230 INTL MLE2 teams — 313302 7314010 5493 31 242263387650 146245 162 274 72 — — — — — —
201331 AAA MLE2 teams — 461420 9112030 321036 20 217282460742 243208 227 320 103 — — — — — —
201533 AAA MLE2 teams — 563513 14628220 338712 41 285347464811 179296 156 355 126 — — — — — —
201634 AAA MLEToros de Tijuana — 346321 601314 19683 30 187240271511 84219 205 228 40 — — — — — —
201735 AAA MLEToros de Tijuana — 398363 821619 261036 20 226291350641 124279 267 282 77 — — — — — —
201937 AAA MLEDiablos Rojos del Mexico — 277254 49807 14777 13 193257307564 114241 285 251 56 — — — — — —
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career— A+C — 33953128 8472035104 18955937 114 271320439758 168297 166 332 96 +45 +1 -52 -16 +74 5.2
/ 162G— A+C — 650599 16239120 361077 21 270319439758 169296 166 332 96 +9 +0 -10 -3 +14 1.0
Career— MLE — 62375759 144831210195 321114579 2610 251300411711 159279 185 310 96 +45 +1 -52 -16 +74 5.2
/ 162G— MLE — 650600 15133120 331198 31 252299410709 158279 185 310 96 +9 +0 -10 -3 +14 1.0

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 AAADiablos Rojos del Mexico · 277 PAwOBA .364 → .251 (−113)K% 20.2% → 27.8%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA20.22%÷0.871×1.200——27.85%
BB% (unintentional) /PA8.30%÷1.035×0.690—×0.9405.20%
HBP% /PA2.53%—×0.940—×0.9402.23%
Singles /BIP23.37%÷1.013×0.930×0.950×0.94019.16%
Doubles /BIP7.07%÷1.185×0.830×0.950×0.9404.42%
Triples /BIP0.00%÷1.150×0.920×0.950×0.9400.00%
Home runs /BIP6.52%÷1.116×0.700—×0.9403.85%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 123, 1B 103, 2B 137, 3B 130, K 74, BB 107 — applied at half strength. Age: age 37 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (9.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .364 → .251; ISO .204 → .119; BABIP .320 → .241. 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 AAAToros de Tijuana · 398 PAwOBA .357 → .282 (−75)K% 21.6% → 26.0%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA21.61%÷0.999×1.200——25.96%
BB% (unintentional) /PA10.55%÷1.033×0.690—×0.9406.62%
HBP% /PA1.51%—×0.940—×0.9401.33%
Singles /BIP24.71%÷0.988×0.930×0.974×0.94021.28%
Doubles /BIP7.84%÷1.007×0.830×0.974×0.9405.92%
Triples /BIP0.39%÷1.150×0.920×0.974×0.9400.29%
Home runs /BIP4.71%÷0.892×0.700—×0.9403.47%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 78, 1B 98, 2B 101, 3B 130, K 100, BB 107 — applied at half strength. Age: age 35 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (7.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.974.

Result: wOBA .357 → .282; ISO .170 → .130; BABIP .339 → .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).

2016 AAAToros de Tijuana · 346 PAwOBA .289 → .228 (−61)K% 17.3% → 19.6%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA17.34%÷1.062×1.200——19.60%
BB% (unintentional) /PA8.96%÷1.055×0.690—×0.9405.51%
HBP% /PA0.87%—×0.940—×0.9400.77%
Singles /BIP18.70%÷0.967×0.930×0.978×0.94016.54%
Doubles /BIP6.10%÷0.926×0.830×0.978×0.9405.03%
Triples /BIP0.41%÷0.941×0.920×0.978×0.9400.37%
Home runs /BIP2.85%÷1.278×0.700—×0.9401.46%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 156, 1B 93, 2B 85, 3B 88, K 112, BB 111 — applied at half strength. Age: age 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.978.

Result: wOBA .289 → .228; ISO .124 → .085; BABIP .255 → .219. 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 AAATigres de Quintana Roo · 453 PAwOBA .443 → .355 (−88)K% 13.7% → 15.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA13.69%÷1.070×1.200——15.35%
BB% (unintentional) /PA9.27%÷1.023×0.690—×0.9425.89%
HBP% /PA1.99%—×0.940—×0.9421.76%
Singles /BIP25.39%÷0.961×0.930×0.961×0.94222.25%
Doubles /BIP8.05%÷0.953×0.830×0.961×0.9426.35%
Triples /BIP0.62%÷0.997×0.920×0.961×0.9420.52%
Home runs /BIP7.74%÷1.118×0.700—×0.9424.57%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 124, 1B 92, 2B 91, 3B 99, K 114, BB 105 — applied at half strength. Age: age 33 vs a level average of 27.2 → −5.8% on BB/HBP/hit rates (5.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.961.

Result: wOBA .443 → .355; ISO .273 → .191; BABIP .357 → .296. 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 AAATigres de Quintana Roo · 351 PAwOBA .410 → .320 (−90)K% 18.8% → 22.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA18.80%÷1.007×1.200——22.41%
BB% (unintentional) /PA11.11%÷1.073×0.690—×0.9626.87%
HBP% /PA1.71%—×0.940—×0.9621.55%
Singles /BIP16.67%÷0.970×0.930×0.991×0.96215.22%
Doubles /BIP4.70%÷0.953×0.830×0.991×0.9623.90%
Triples /BIP0.00%÷0.963×0.920×0.991×0.9620.00%
Home runs /BIP13.25%÷0.953×0.700—×0.9629.36%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 91, 1B 94, 2B 91, 3B 93, K 101, BB 115 — applied at half strength. Age: age 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.991.

Result: wOBA .410 → .320; ISO .347 → .259; BABIP .243 → .208. 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 AAASalt Lake Bees · 90 PAwOBA .338 → .274 (−64)K% 12.2% → 15.7%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA12.22%÷1.005×1.290——15.69%
BB% (unintentional) /PA2.22%÷0.914×0.710—×0.9721.68%
HBP% /PA0.00%—×0.980—×0.9720.00%
Singles /BIP21.33%÷1.029×0.900×1.041×0.97218.88%
Doubles /BIP6.67%÷1.022×0.810×1.041×0.9725.35%
Triples /BIP0.00%÷1.150×0.810×1.041×0.9720.00%
Home runs /BIP5.33%÷1.053×0.780—×0.9723.84%

Factors used: league row PCL. Park (home-season share, regressed): HR 111, 1B 106, 2B 104, 3B 130, K 101, BB 83 — 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 ×1.041.

Result: wOBA .338 → .274; ISO .198 → .146; BABIP .288 → .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).

2011 AAAColorado Springs Sky Sox · 125 PAwOBA .334 → .252 (−82)K% 12.8% → 17.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA12.80%÷0.925×1.290——17.86%
BB% (unintentional) /PA4.80%÷0.972×0.710—×0.9823.44%
HBP% /PA0.80%—×0.980—×0.9820.77%
Singles /BIP21.57%÷1.016×0.900×0.951×0.98217.84%
Doubles /BIP5.88%÷0.992×0.810×0.951×0.9824.49%
Triples /BIP0.00%÷1.150×0.810×0.951×0.9820.00%
Home runs /BIP4.90%÷1.029×0.780—×0.9823.65%

Factors used: league row PCL. Park (home-season share, regressed): HR 106, 1B 103, 2B 98, 3B 130, K 85, BB 94 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.951.

Result: wOBA .334 → .252; ISO .178 → .127; BABIP .289 → .232. 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).

2007 AAALouisville Bats · 202 PAwOBA .322 → .284 (−39)K% 17.8% → 21.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA17.82%÷1.000×1.200——21.39%
BB% (unintentional) /PA5.94%÷1.000×0.690—×1.0334.23%
HBP% /PA1.49%—×0.940—×1.0331.44%
Singles /BIP22.15%÷1.000×0.930×0.992×1.03321.12%
Doubles /BIP9.40%÷1.000×0.830×0.992×1.0338.00%
Triples /BIP0.67%÷1.000×0.970×0.992×1.0330.67%
Home runs /BIP2.01%÷1.000×0.840—×1.0331.75%

Factors used: league row IL. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×0.992.

Result: wOBA .322 → .284; ISO .135 → .116; 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).

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