Tyler Bortnick

Pos2B
B/TR/R
Born1987-07-03
Age (2027)40
No MLB projection yet. Career stats below are historical.
Overview
AAALAST SEASON 2017
YearAgeLvl / TeamPAAVG/OBP/SLGHRSBwRC+WARMLE AVG/OBP/SLG
201528AA/INTL2 orgs405.286/.370/.36322392—.252/.312/.330
201629AAA/AA/A+DET287.277/.351/.4156773—.239/.291/.354
201730AAA/AA2 orgs39.147/.237/.14701-8—.147/.237/.147
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)
201023 A+Charlotte Stone Crabs — 4134 7301 5100 20 206308382690 176250 2412 296 41 — — — — — —
201023 ABowling Green Hot Rods — 487406 1233228 636711 3914 303409451859 148344 1413 383 95 — — — — — —
201124 A+Charlotte Stone Crabs — 588474 1453474 796725 434 306431432863 127346 1113 387 119 — — — — — —
201124 INTLSurprise Saguaros — 5145 12301 581 22 267353400753 133306 1610 341 117 — — — — — —
201225 AAAReno Aces — 151132 28702 14261 52 212293311603 98250 179 271 34 — — — — — —
201225 AAMontgomery Biscuits — 404348 881884 46617 233 253352385737 132297 1511 332 74 — — — — — —
201225 INTLSalt River Rafters — 5745 12210 8103 41 267411356766 89333 1814 353 125 — — — — — —
201326 AAAReno Aces — 298251 731143 40545 192 291399402801 112359 1813 363 89 — — — — — —
201427 AAAReno Aces — 9885 19210 10211 30 224312271583 47297 2110 269 30 — — — — — —
201427 INTLSydney Blue Sox — 191164 39903 22314 33 238342348690 110277 1612 317 101 — — — — — —
201528 AAJackson Generals — 252222 611112 25383 125 275356360716 86324 1510 326 76 — — — — — —
201528 INTLSydney Blue Sox — 153131 40800 15184 110 305393366760 61345 1210 344 119 — — — — — —
201629 AAAToledo Mud Hens — 5345 10111 7100 02 222327356682 133265 1913 306 56 — — — — — —
201629 AAErie SeaWolves — 139122 34524 13241 40 279353451804 172312 179 350 78 — — — — — —
201629 A+Lakeland Flying Tigers — 9586 26501 7141 31 302362395757 93352 157 339 74 — — — — — —
201730 AAAColorado Springs Sky Sox — 2219 3000 131 10 158238158396 176 145 189 -1 — — — — — —
201730 AABiloxi Shuckers — 1715 2000 151 00 133235133369 200 296 191 -16 — — — — — —
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
201023 A+ MLECharlotte Stone Crabs — 4135 6201 4150 20 171256314571 143225 3710 229 41 — — — — — —
201023 A MLEBowling Green Hot Rods — 487429 1092527 429111 3914 254336371707 117299 199 309 95 — — — — — —
201124 A+ MLECharlotte Stone Crabs — 588498 1413463 558825 434 283382394776 110328 159 344 119 — — — — — —
201225 AAA MLEReno Aces — 151136 25502 10351 52 184245265510 81223 237 218 34 — — — — — —
201225 AA MLEMontgomery Biscuits — 404362 811773 32747 233 224299334634 110271 188 278 74 — — — — — —
201326 AAA MLEReno Aces — 298261 64932 30705 192 245334326660 80325 2310 300 89 — — — — — —
201427 AAA MLEReno Aces — 9888 17210 7281 30 193260239499 45261 297 212 30 — — — — — —
201528 AA MLEJackson Generals — 252230 581012 17483 125 252312330642 78305 197 280 76 — — — — — —
201629 AAA MLEToledo Mud Hens — 5348 10111 4120 02 208269333603 125234 238 251 56 — — — — — —
201629 AA MLEErie SeaWolves — 139127 30423 8291 40 236287370657 134276 216 284 78 — — — — — —
201629 A+ MLELakeland Flying Tigers — 9588 23401 5201 31 261309341649 80321 215 278 74 — — — — — —
201730 AAA MLEColorado Springs Sky Sox — 2219 3000 141 10 158238158396 152 185 166 -1 — — — — — —
201730 AA MLEBiloxi Shuckers — 1715 2000 161 00 133235133369 177 356 144 -16 — — — — — —
201023 A MLE2 teams — 528464 1152827 4610511 4114 248330362692 114303 209 303 91 — — — — — —
201023 A RAW2 teams — 528440 1303529 687711 4114 295401445847 150338 1513 376 91 — — — — — —
201124 A+ MLE2 teams — 639543 1543773 609526 456 284382394776 110336 159 344 119 — — — — — —
201124 A+ RAW2 teams — 639519 1573775 847526 456 303424430854 127343 1213 383 119 — — — — — —
201225 AA MLE3 teams — 612547 1172585 4612011 326 214288316604 102265 208 262 63 — — — — — —
201225 AA RAW3 teams — 612525 1282796 689711 326 244343364707 120288 1611 319 63 — — — — — —
201326 AAA MLEReno Aces — 298261 64932 30705 192 245334326660 80326 2310 300 89 — — — — — —
201326 AAA RAWReno Aces — 298251 731143 40545 192 291399402801 112359 1813 363 89 — — — — — —
201427 INTL MLE2 teams — 289261 48520 20835 63 184255218474 34270 297 212 30 — — — — — —
201427 INTL RAW2 teams — 289249 581113 32525 63 233332321653 88284 1811 301 30 — — — — — —
201528 AA MLE2 teams — 405365 931623 28777 235 255320334654 79312 197 280 76 — — — — — —
201528 AA RAW2 teams — 405353 1011912 40567 235 286370363733 76332 1410 333 76 — — — — — —
201629 AA MLE3 teams — 287263 631034 17612 73 240291346637 106295 216 276 73 — — — — — —
201629 AA RAW3 teams — 287253 701136 27482 73 277351415766 138318 179 338 73 — — — — — —
201730 AAA MLE2 teams — 3935 4000 1102 10 114184114298 154 263 156 -8 — — — — — —
201730 AAA RAW2 teams — 3934 5000 282 10 147237147384 185 215 189 -8 — — — — — —
201023 A MLE2 teams — 528466 1152827 4610511 4114 247330361691 114293 209 303 91 — — — — — —
201124 A+ MLE2 teams — 639548 1543773 609526 456 281382391772 109328 159 344 119 — — — — — —
201225 AA MLE3 teams — 612550 1172585 4612011 326 213288315603 102258 208 262 63 — — — — — —
201326 AAA MLEReno Aces — 298261 64932 30705 192 245334326660 80325 2310 300 89 — — — — — —
201427 INTL MLE2 teams — 289262 48520 20835 63 183255218473 34261 297 212 30 — — — — — —
201528 AA MLE2 teams — 405367 931623 28777 235 253320332652 79305 197 280 76 — — — — — —
201629 AA MLE3 teams — 287266 631034 17612 73 237291342633 105283 216 276 73 — — — — — —
201730 AAA MLE2 teams — 3936 4000 1102 10 111184111295 163 263 156 -8 — — — — — —
▸ Career Totals
Career— MLE — 30972739 6581302724 24862169 17439 240319334653 93300 208 287 80 -72 +19 +0 +11 +67 2.6
/ 162G— MLE — 650575 1382765 5213014 378 240318334652 94300 208 287 80 -15 +4 +0 +2 +14 0.6

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 AAAColorado Springs Sky Sox · 22 PAwOBA .193 → .166 (−27)K% 13.6% → 18.5%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA13.64%÷0.953×1.290——18.46%
BB% (unintentional) /PA4.55%÷0.995×0.710—×0.9723.15%
HBP% /PA4.55%—×0.980—×0.9724.33%
Singles /BIP18.75%÷1.018×0.900—×0.97216.11%
Doubles /BIP0.00%÷1.163×0.810—×0.9720.00%
Triples /BIP0.00%÷1.150×0.810—×0.9720.00%
Home runs /BIP0.00%÷0.933×0.780—×0.9720.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 87, 1B 104, 2B 133, 3B 130, K 91, BB 99 — 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).

Result: wOBA .193 → .166; ISO .000 → .000; BABIP .176 → .152. 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 AABiloxi Shuckers · 17 PAwOBA .187 → .144 (−43)K% 29.4% → 37.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA29.41%÷0.959×1.220——37.42%
BB% (unintentional) /PA5.88%÷1.035×0.680—×0.9483.67%
HBP% /PA5.88%—×0.840—×0.9484.68%
Singles /BIP20.00%÷0.986×0.920—×0.94817.68%
Doubles /BIP0.00%÷0.946×0.910—×0.9480.00%
Triples /BIP0.00%÷0.915×0.880—×0.9480.00%
Home runs /BIP0.00%÷1.393×0.800—×0.9480.00%

Factors used: league row SL. Park (home-season share, regressed): HR 179, 1B 97, 2B 89, 3B 83, K 92, BB 107 — applied at half strength. Age: age 30 vs a level average of 24.8 → −5.2% on BB/HBP/hit rates (5.2 yr older than average).

Result: wOBA .187 → .144; ISO .000 → .000; BABIP .200 → .177. 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 AAErie SeaWolves · 139 PAwOBA .345 → .284 (−61)K% 17.3% → 21.1%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA17.27%÷0.998×1.220——21.11%
BB% (unintentional) /PA9.35%÷1.027×0.700—×0.9586.11%
HBP% /PA0.72%—×0.850—×0.9580.59%
Singles /BIP23.47%÷1.045×0.970×1.018×0.95821.26%
Doubles /BIP5.10%÷0.973×0.860×1.018×0.9584.40%
Triples /BIP2.04%÷1.127×0.950×1.018×0.9581.68%
Home runs /BIP4.08%÷1.095×0.780—×0.9582.79%

Factors used: league row EL. Park (home-season share, regressed): HR 119, 1B 109, 2B 95, 3B 125, K 100, BB 105 — applied at half strength. Age: age 29 vs a level average of 24.8 → −4.2% on BB/HBP/hit rates (4.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.018.

Result: wOBA .345 → .284; ISO .172 → .133; BABIP .312 → .276. 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+Lakeland Flying Tigers · 95 PAwOBA .330 → .278 (−52)K% 14.7% → 20.7%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA14.74%÷1.011×1.420——20.69%
BB% (unintentional) /PA7.37%÷1.026×0.750—×0.9405.06%
HBP% /PA1.05%—×0.930—×0.9400.92%
Singles /BIP27.78%÷0.995×0.920×1.050×0.94025.35%
Doubles /BIP6.94%÷1.029×0.960×1.050×0.9406.40%
Triples /BIP0.00%÷1.145×0.810×1.050×0.9400.00%
Home runs /BIP1.39%÷1.161×0.880—×0.9400.99%

Factors used: league row FSL. Park (home-season share, regressed): HR 132, 1B 99, 2B 106, 3B 129, K 102, BB 105 — applied at half strength. Age: age 29 vs a level average of 22.8 → −6.0% on BB/HBP/hit rates (6.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .330 → .278; ISO .093 → .076; BABIP .352 → .321. 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 AAAToledo Mud Hens · 53 PAwOBA .291 → .251 (−40)K% 18.9% → 22.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA18.87%÷1.009×1.200——22.43%
BB% (unintentional) /PA11.32%÷1.004×0.690—×0.9827.64%
HBP% /PA0.00%—×0.940—×0.9820.00%
Singles /BIP20.00%÷1.001×0.930—×0.98218.24%
Doubles /BIP2.86%÷1.092×0.830—×0.9822.13%
Triples /BIP2.86%÷1.150×0.970—×0.9822.37%
Home runs /BIP2.86%÷0.899×0.840—×0.9822.62%

Factors used: league row IL. Park (home-season share, regressed): HR 80, 1B 100, 2B 118, 3B 130, K 102, BB 101 — 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).

Result: wOBA .291 → .251; ISO .133 → .121; BABIP .265 → .234. 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 AAJackson Generals · 252 PAwOBA .318 → .280 (−38)K% 15.1% → 18.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA15.08%÷0.973×1.220——18.91%
BB% (unintentional) /PA9.92%÷0.950×0.680—×0.9686.87%
HBP% /PA1.19%—×0.840—×0.9680.97%
Singles /BIP25.54%÷0.974×0.920×1.042×0.96824.35%
Doubles /BIP5.98%÷1.032×0.910×1.042×0.9685.32%
Triples /BIP0.54%÷0.900×0.880×1.042×0.9680.54%
Home runs /BIP1.09%÷0.890×0.800—×0.9680.95%

Factors used: league row SL. Park (home-season share, regressed): HR 78, 1B 95, 2B 106, 3B 80, K 95, BB 90 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.042.

Result: wOBA .318 → .280; ISO .086 → .077; BABIP .324 → .305. 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 AAAReno Aces · 98 PAwOBA .263 → .212 (−51)K% 21.4% → 28.6%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA21.43%÷0.965×1.290——28.65%
BB% (unintentional) /PA10.20%÷1.049×0.710—×1.0036.93%
HBP% /PA1.02%—×0.980—×1.0031.00%
Singles /BIP25.00%÷1.047×0.900×1.041×1.00322.45%
Doubles /BIP3.12%÷1.047×0.810×1.041×1.0032.52%
Triples /BIP1.56%÷1.150×0.810×1.041×1.0031.15%
Home runs /BIP0.00%÷1.116×0.780—×1.0030.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 123, 1B 109, 2B 109, 3B 130, K 93, BB 110 — 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 ×1.041.

Result: wOBA .263 → .212; ISO .047 → .035; BABIP .297 → .261. 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 AAAReno Aces · 298 PAwOBA .354 → .300 (−55)K% 18.1% → 23.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA18.12%÷1.000×1.290——23.38%
BB% (unintentional) /PA13.09%÷0.947×0.710—×1.0189.98%
HBP% /PA1.68%—×0.980—×1.0181.67%
Singles /BIP27.92%÷1.018×0.900×1.034×1.01825.98%
Doubles /BIP5.58%÷0.994×0.810×1.034×1.0184.79%
Triples /BIP2.03%÷1.150×0.810×1.034×1.0181.51%
Home runs /BIP1.52%÷1.121×0.780—×1.0181.08%

Factors used: league row PCL. Park (home-season share, regressed): HR 124, 1B 104, 2B 99, 3B 130, K 100, BB 89 — 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 ×1.034.

Result: wOBA .354 → .300; ISO .112 → .085; 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).

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