Bryce Eldridge

1B San Francisco Giants
Age 22 L/R 6'7" / 251 lbs MLB HR -15%H -3% Svc 0.932 · Ctrl thru 2032
Overview
MLB40-MANPre-ArbFA 2033
YearAgeLvl / TeamPAAVG/OBP/SLGHRSBwRC+WARMLE AVG/OBP/SLG
202419AAA/AA/A+/A/INTL2 orgs565.292/.378/.515256103—.247/.314/.427
202520AAA/AASF426.259/.335/.51325187—.222/.275/.416
202520MLBSF37.107/.306/.1790052-1.0
202621AAASF137.333/.445/.51850122—.283/.372/.425
202621MLBSF448.269/.366/.4611711382.0
2027PROJ22MLBSF501.242/.335/.4091721161.1
2028PROJ98% MLB23MLBSF575.248/.342/.4332231241.9
2029PROJ98% MLB24MLBSF602.252/.346/.4492531302.4
Last 3 seasons WAR 1.0  ·  Next 3 projected WAR 5.4Projected rows: MLB playing time only, park and league context applied.
ContractESTIMATED
Control thru2032Service0.932First FA2033
2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Arb-1$7M2031Arb-2$12M2032Arb-3$18M
Skills · percentileStatcast 2025-2026
xwOBA90
Avg EV90
Barrel%79
Bat Spd52
Speed20
Form.249/.355/.426 ▲ rolling true talent (60d window) · proj .247/.337/.423
CompsMichael Conforto (age 23) · Rafael Devers (age 22) · Matt Joyce (age 24)
2027 FULL-SEASON PROJECTIONstats below = full-season projection
showingPROJ
wRC+†116
AVG/OBP/SLG.242 / .335 / .409
PA501
HR17
K%26
BB%12
BABIP303
ISO170
MLB%100%
Value2027 · WAR
BAT: +9.5 runs (wOBA-derived runs vs avg)+10BATRUN: -1.0 runs (SB/CS + UBR baserunning)-1RUNFLD: -0.6 runs (Defensive runs vs avg)-1FLDPOS: -8.9 runs (Positional adjustment)-9POSREP: +10.9 runs (Replacement-level credit)+11REPTotal WAR: +1.50+1.5WAR
0.01.53.01.51.92.42.62.82.627282930313233343536
━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$71M ctrl surplus
Tools · Recent Form · Contract
ToolsStatcast %ile · 2025-2026
CONTACT
xAVG
530.254
POWER
Barrel%
7912.5
Avg EV
9092.9
Bat Spd
5271.5
SPEED
Sprint
2026.0
Recent Formrolling true talent ⓘ
K%26%·25% over 83 PA (60d) · proj 26%
BB%14%▲▲17% over 83 PA (60d) · proj 12%
ISO.177·.179 over 67 AB (60d) · proj .177
HR/BB5.3%·4.2% over 48 BBE (60d) · proj 5.9%
BABIP.315▲.457 over 46 BIP (60d) · proj .307
SLASH.249/.355/.426▲proj .247/.337/.423
Contract ESTIMATED · service-time + WAR-based estimator (needs verification)
Status   Pre-Arb
MLB Debut   2025
Service   0.932 yrs.days
Team Control Through   2032
First FA Year   2033
YearStatusSalary Proj WAR Value Surplus
2027Pre-Arb$0.8M+1.5$12M+$11M
2028Pre-Arb$0.8M+1.9$14M+$13M
2029Pre-Arb$0.8M+2.4$16M+$16M
2030Arb-1$7M+2.6$17M+$12M
2031Arb-2$12M+2.8$18M+$10M
2032Arb-3$18M+2.6$15M+$4M
Totals $40M $92M +$66M

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)
202318 ASan Jose Giants — 6958 17201 11180 10 293406379785 86410 2616 362 71 — — — — — —
202318 ROKACL Giants Orange — 6151 15305 9160 00 2944006471.047 353323 2615 441 72 — — — — — —
202419 AAASacramento River Cats — 3531 8000 4110 00 258343258601 400 3111 287 59 — — — — — —
202419 AARichmond Flying Squirrels — 4037 10211 380 10 270325459784 189321 208 345 89 — — — — — —
202419 A+Eugene Emeralds — 215173 5811112 35522 30 3354526181.071 283404 2416 453 140 — — — — — —
202419 ASan Jose Giants — 229205 5414010 17613 20 263329478807 215319 277 349 70 — — — — — —
202419 INTLScottsdale Scorpions — 4641 12302 3161 00 293356512868 220417 357 373 139 — — — — — —
202520 MLBSan Francisco Giants — 3728 3200 7131 00 107306179484 71188 3519 246 52 -2 +0 -0 -8 +1 -1.0
202520 AAASacramento River Cats — 286253 6313018 28881 10 249326514840 265298 3110 361 86 — — — — — —
202520 AARichmond Flying Squirrels — 140125 35807 13391 01 280353512865 232350 289 377 89 — — — — — —
202621 MLBSan Francisco Giants — 448386 10423017 591190 11 269366461827 192344 2713 366 138 +20 -0 +0 -10 +10 2.0
202621 AAASacramento River Cats — 137114 38605 20413 00 333445518963 184485 3015 428 122 — — — — — —
▸ Career Totals (raw MLB only — historical actual)
MLB Career— — 485414 10725017 661321 11 258362442804 184335 2714 357 128 +16 -0 -0 -19 +11 0.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
202318 A MLESan Jose Giants — 6961 14201 8260 10 230319311630 82373 3812 273 71 — — — — — —
202318 ROK MLEACL Giants Orange — 6155 11203 5220 00 200267400667 200233 368 274 72 — — — — — —
202419 AAA MLESacramento River Cats — 3532 8000 3120 00 250314250564 400 349 256 59 — — — — — —
202419 AA MLERichmond Flying Squirrels — 4039 10211 1100 10 256275436711 179314 252 300 89 — — — — — —
202419 A+ MLEEugene Emeralds — 215184 5210110 24722 30 283371511882 228369 3311 375 140 — — — — — —
202419 A MLESan Jose Giants — 229209 441008 13873 20 211267373640 163291 386 271 70 — — — — — —
202520 MLB MLESan Francisco Giants — 3728 3200 7131 00 107306179484 71188 3519 246 52 -2 +0 -0 -8 +1 -1.0
202520 AAA MLESacramento River Cats — 286263 5612014 181041 10 213266418684 205275 366 295 86 — — — — — —
202520 AA MLERichmond Flying Squirrels — 140129 31705 9471 01 240295411706 171322 346 300 89 — — — — — —
202621 MLB MLESan Francisco Giants — 448387 10623018 581190 11 274369473841 199344 2713 373 138 +20 -0 +0 -10 +10 2.0
202621 AAA MLESacramento River Cats — 137120 34504 14493 00 283372425797 142452 3610 349 122 — — — — — —
202318 A MLE2 teams — 130116 24304 13480 10 207287336623 129308 3710 273 71 — — — — — —
202318 A RAW2 teams — 130109 32506 20340 10 294403505908 211371 2615 399 71 — — — — — —
202419 A MLE5 teams — 565505 12324220 441976 60 244312418730 174346 358 315 100 — — — — — —
202419 A RAW5 teams — 565487 14230225 621486 60 292378515894 224361 2611 386 100 — — — — — —
202520 AAA MLE3 teams — 463420 9021019 341643 11 214278400678 186292 357 293 84 — — — — — —
202520 AAA RAW3 teams — 463406 10123025 481403 11 249333490823 241308 3010 357 84 — — — — — —
202621 MLB MLE2 teams — 585507 14028022 721683 11 276369462831 185369 2912 367 135 +24 -0 +0 -10 +13 2.7
202621 MLB RAW2 teams — 585500 14229022 791603 11 284385474859 190374 2714 381 135 +24 -0 +0 -10 +13 2.7
202318 A MLE2 teams — 130116 24304 13480 10 207287336623 129307 3710 273 71 — — — — — —
202419 A MLE5 teams — 565510 12324220 441976 60 241312414725 173332 358 315 100 — — — — — —
202520 AAA MLE3 teams — 463423 9021019 341643 11 213278397675 184282 357 293 84 — — — — — —
202621 MLB MLE2 teams — 585505 14028022 721683 11 277369463833 186369 2912 367 135 — — — — — —
▸ Model inputs — neutral MLE (past 3 seasons)
202419 A MLE5 teams — 565510 12324220 441976 60 241312414725 173332 358 315 100 — — — — — —
202520 AAA MLE3 teams — 463423 9021019 341643 11 213278397675 184282 357 293 84 — — — — — —
202621 MLB MLE2 teams — 585505 14028022 721683 11 277369463833 186369 2912 367 135 — — — — — —
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
202722 MLB MLESF 100% 632550 13627123 731644 31 247340423763 176307 2612 340 116 +12 +0 -1 -11 +14 1.5
▸ 2027 — real world (MLB)
202722 MLB CTXSF 100% 501435 10621117 581303 21 242335409744 167303 2612 332 116 +10 +0 -1 -9 +11 1.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
202823 MLB MLESF 98% 587509 12925124 691504 31 254347449796 195309 2612 352 124 +17 +0 -1 -10 +13 1.9
202924 MLB MLESF 98% 614533 13826128 721564 31 258351467818 209310 2512 360 130 +22 +0 -1 -11 +13 2.4
203025 MLB MLESF 98% 614532 13926129 731554 31 261354478832 217311 2512 365 133 +24 +0 -1 -11 +13 2.7
203126 MLB MLESF 98% 614532 13926130 731554 31 262355484839 222311 2512 368 135 +26 +0 -1 -11 +13 2.8
203227 MLB MLESF 98% 606525 13725130 721544 21 260354480834 220310 2512 366 134 +24 +0 -1 -11 +13 2.7
203328 MLB MLESF 98% 592513 13325029 701524 11 258352475826 217308 2612 363 132 +22 -0 -1 -11 +13 2.4
203429 MLB MLESF 98% 571495 12623027 681483 10 255348467816 212306 2612 359 129 +20 +0 -2 -10 +12 2.1
203530 MLB MLESF 98% 555482 12122026 651463 00 251344458802 207303 2612 354 126 +17 +0 -3 -10 +12 1.7
203631 MLB MLESF 98% 536465 11521024 631433 00 247339448787 201299 2712 348 121 +14 +0 -3 -10 +12 1.3
203732 MLB MLESF 98% 512446 10719022 591392 00 241332434767 193294 2712 339 116 +10 +0 -4 -9 +11 0.8
203833 MLB MLESF 98% 476417 9717020 541322 00 233324417741 184288 2811 329 109 +5 +0 -5 -8 +10 0.2
203934 MLB MLESF 94% 419368 8314017 471191 00 224314396710 173279 2811 317 101 +0 +0 -5 -7 +9 -0.3
202823 MLB CTXSF 98% 575499 12425122 671474 31 248342433775 185304 2612 344 124 +17 +0 -1 -10 +12 1.9
202924 MLB CTXSF 98% 602522 13226125 711534 31 252346449795 197305 2512 352 130 +21 +0 -1 -11 +13 2.4
203025 MLB CTXSF 98% 602522 13426127 711524 31 255349460808 205306 2512 356 133 +24 +0 -1 -11 +13 2.6
203126 MLB CTXSF 98% 602521 13426127 721524 31 255350465814 209305 2512 359 135 +25 +0 -1 -11 +13 2.8
203227 MLB CTXSF 98% 594514 13125127 711514 21 254348462810 207304 2512 357 134 +24 +0 -1 -11 +13 2.6
203328 MLB CTXSF 98% 580502 12624026 691494 11 252346456802 204303 2612 354 132 +22 -0 -1 -10 +13 2.3
203429 MLB CTXSF 98% 560486 12123025 661453 10 249343449792 200301 2612 350 129 +19 +0 -2 -10 +12 2.0
203530 MLB CTXSF 98% 544472 11622023 641433 00 245339440779 195298 2612 345 126 +17 +0 -3 -10 +12 1.6
203631 MLB CTXSF 98% 525456 11021022 611403 00 241334430764 190294 2712 339 121 +13 +0 -3 -9 +11 1.2
203732 MLB CTXSF 98% 502437 10319020 581362 00 235327417745 182289 2712 331 116 +9 +0 -4 -9 +11 0.8
203833 MLB CTXSF 98% 466408 9317018 531292 00 228319401720 173283 2811 321 109 +5 +0 -5 -8 +10 0.2
203934 MLB CTXSF 94% 392344 7513014 441111 00 219309381690 163275 2811 309 101 +0 +0 -5 -7 +8 -0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career— A+C — 70296097 15062925293 833184039 177 247341441782 194303 2612 346 121 +213 +1 -25 -136 +152 20.9
/ 162G— A+C — 650564 13927027 771704 21 246342438780 191302 2612 346 121 +20 +0 -2 -13 +14 1.9
Career— MLE — 89407800 19493668389 1006245653 279 250340448788 199311 2711 347 121 +226 +1 -26 -147 +166 22.4
/ 162G— MLE — 650567 14227128 731794 21 250340450790 199313 2811 347 121 +19 +0 -2 -12 +14 1.9

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.

2026 AAASacramento River Cats · 137 PAwOBA .416 → .349 (−66)K% 29.9% → 35.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA29.93%÷1.000×1.200——35.91%
BB% (unintentional) /PA13.87%÷1.000×0.690—×1.05010.05%
HBP% /PA2.19%—×0.940—×1.0502.16%
Singles /BIP36.99%÷1.000×0.930×0.993×1.05035.86%
Doubles /BIP8.22%÷1.000×0.830×0.993×1.0507.11%
Triples /BIP0.00%÷1.000×0.970×0.993×1.0500.00%
Home runs /BIP6.85%÷1.000×0.700—×1.0505.03%

Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×0.993.

Result: wOBA .416 → .349; ISO .184 → .138; BABIP .485 → .452. 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).

2025 AAASacramento River Cats · 286 PAwOBA .353 → .295 (−58)K% 30.8% → 36.5%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA30.77%÷1.010×1.200——36.54%
BB% (unintentional) /PA8.74%÷1.011×0.690—×1.0506.27%
HBP% /PA0.35%—×0.940—×1.0500.35%
Singles /BIP19.39%÷1.030×0.930×1.012×1.05018.60%
Doubles /BIP7.88%÷0.959×0.830×1.012×1.0507.24%
Triples /BIP0.00%÷0.900×0.970×1.012×1.0500.00%
Home runs /BIP10.91%÷0.938×0.700—×1.0508.55%

Factors used: league row International League. Park (home-season share, regressed): HR 88, 1B 106, 2B 92, 3B 80, K 102, BB 102 — 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 ×1.012.

Result: wOBA .353 → .295; ISO .265 → .211; BABIP .298 → .275. 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).

2025 AARichmond Flying Squirrels · 140 PAwOBA .367 → .300 (−67)K% 27.9% → 33.4%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA27.86%÷1.018×1.220——33.40%
BB% (unintentional) /PA8.57%÷0.962×0.700—×1.0506.55%
HBP% /PA0.71%—×0.850—×1.0500.64%
Singles /BIP23.26%÷1.004×0.970×0.959×1.05022.64%
Doubles /BIP9.30%÷0.992×0.860×0.959×1.0508.13%
Triples /BIP0.00%÷1.150×0.950×0.959×1.0500.00%
Home runs /BIP8.14%÷1.183×0.780—×1.0505.64%

Factors used: league row EL. Park (home-season share, regressed): HR 137, 1B 101, 2B 98, 3B 130, K 104, BB 92 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.959.

Result: wOBA .367 → .300; ISO .232 → .167; BABIP .350 → .322. 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).

2024 ASan Jose Giants · 229 PAwOBA .346 → .271 (−74)K% 26.6% → 37.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA26.64%÷0.957×1.360——37.87%
BB% (unintentional) /PA7.42%÷0.966×0.690—×1.0305.46%
HBP% /PA1.31%—×0.780—×1.0301.05%
Singles /BIP20.83%÷0.961×0.920×0.983×1.03020.19%
Doubles /BIP9.72%÷1.012×0.830×0.983×1.0308.07%
Triples /BIP0.00%÷1.000×0.910×0.983×1.0300.00%
Home runs /BIP6.94%÷0.959×0.800—×1.0305.97%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 92, 1B 92, 2B 102, 3B 100, K 91, BB 93 — 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 ×0.983.

Result: wOBA .346 → .271; ISO .215 → .161; BABIP .319 → .291. 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).

2024 A+Eugene Emeralds · 215 PAwOBA .449 → .375 (−75)K% 24.2% → 33.7%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA24.19%÷0.968×1.350——33.75%
BB% (unintentional) /PA15.35%÷1.024×0.710—×1.04211.09%
HBP% /PA0.93%—×0.810—×1.0420.79%
Singles /BIP28.10%÷1.016×0.910×1.005×1.04226.36%
Doubles /BIP9.09%÷0.950×0.830×1.005×1.0428.32%
Triples /BIP0.83%÷1.150×0.820×1.005×1.0420.62%
Home runs /BIP9.92%÷1.010×0.830—×1.0428.50%

Factors used: level-wide A+ factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 102, 1B 103, 2B 90, 3B 130, K 94, BB 105 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.005.

Result: wOBA .449 → .375; ISO .283 → .237; BABIP .404 → .369. 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).

2024 AARichmond Flying Squirrels · 40 PAwOBA .326 → .300 (−26)K% 20.0% → 23.8%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA20.00%÷1.025×1.220——23.81%
BB% (unintentional) /PA5.00%÷0.988×0.700—×1.0503.72%
HBP% /PA0.00%—×0.850—×1.0500.00%
Singles /BIP20.69%÷0.999×0.970—×1.05021.09%
Doubles /BIP6.90%÷1.110×0.860—×1.0505.61%
Triples /BIP3.45%÷0.900×0.950—×1.0503.82%
Home runs /BIP3.45%÷1.062×0.780—×1.0502.66%

Factors used: league row EL. Park (home-season share, regressed): HR 112, 1B 100, 2B 122, 3B 80, K 105, BB 98 — applied at half strength. Age: age 20 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (4.8 yr younger than average).

Result: wOBA .326 → .300; ISO .189 → .166; BABIP .321 → .314. 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).

2024 AAASacramento River Cats · 35 PAwOBA .280 → .256 (−24)K% 31.4% → 34.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA31.43%÷1.081×1.200——34.88%
BB% (unintentional) /PA11.43%÷1.032×0.690—×1.0508.03%
HBP% /PA0.00%—×0.940—×1.0500.00%
Singles /BIP40.00%÷0.976×0.930—×1.05040.02%
Doubles /BIP0.00%÷1.052×0.830—×1.0500.00%
Triples /BIP0.00%÷1.091×0.970—×1.0500.00%
Home runs /BIP0.00%÷1.010×0.700—×1.0500.00%

Factors used: league row International League. Park (home-season share, regressed): HR 102, 1B 95, 2B 110, 3B 118, K 116, BB 106 — applied at half strength. Age: age 20 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (7.2 yr younger than average).

Result: wOBA .280 → .256; ISO .000 → .000; BABIP .400 → .400. 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).

2023 ASan Jose Giants · 69 PAwOBA .354 → .273 (−81)K% 26.1% → 37.9%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA26.09%÷0.935×1.360——37.94%
BB% (unintentional) /PA15.94%÷1.011×0.690—×1.04511.37%
HBP% /PA0.00%—×0.780—×1.0450.00%
Singles /BIP35.00%÷1.049×0.920—×1.04532.07%
Doubles /BIP5.00%÷1.005×0.830—×1.0454.32%
Triples /BIP0.00%÷0.900×0.910—×1.0450.00%
Home runs /BIP2.50%÷0.890×0.800—×1.0452.35%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 78, 1B 110, 2B 101, 3B 80, K 87, BB 102 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average).

Result: wOBA .354 → .273; ISO .086 → .068; BABIP .410 → .373. 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 — .