Chris Betts

PosC
B/TL/R
Born1997-03-10
Age (2027)30
No MLB projection yet. Career stats below are historical.
Overview
AALAST SEASON 2022
YearAgeLvl / TeamPAAVG/OBP/SLGHRSBwRC+WARMLE AVG/OBP/SLG
201922ATB472.210/.335/.40019334—.139/.235/.237
202124AA/ROKTB89.149/.284/.2842013—.104/.206/.181
202225AALAD102.146/.255/.3605011—.097/.176/.226
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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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)
201619 ROKGCL Rays — 5542 9210 10131 20 214377310687 95290 2418 315 42 — — — — — —
201821 ABowling Green Hot Rods — 6556 13101 6161 00 232317304621 71300 259 281 40 — — — — — —
201821 INTLPerth Heat — 9887 27203 8193 00 310388437825 126369 198 373 138 — — — — — —
201922 ABowling Green Hot Rods — 472395 8314219 671367 30 210335400735 190263 2914 331 34 — — — — — —
202124 AAMontgomery Biscuits — 7160 7102 10281 00 117254233487 117167 3914 236 2 — — — — — —
202124 ROKFCL Rays — 1814 4300 360 00 286412500912 214444 3317 381 58 — — — — — —
202225 AATulsa Drillers — 10289 13405 13480 00 146255360614 213222 4713 277 11 — — — — — —
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
201619 ROK MLEGCL Rays — 5546 7110 6191 20 152264217482 65230 3511 231 42 — — — — — —
201821 A MLEBowling Green Hot Rods — 6558 12101 4221 00 207270276546 69274 346 227 40 — — — — — —
201922 A MLEBowling Green Hot Rods — 472417 589110 451967 30 139235237472 98221 4210 219 34 — — — — — —
202124 AA MLEMontgomery Biscuits — 7163 5101 7351 00 79183143326 63151 4910 171 2 — — — — — —
202124 ROK MLEFCL Rays — 1815 3200 290 00 200294333627 133314 5011 254 58 — — — — — —
202225 AA MLETulsa Drillers — 10293 9303 9600 00 97176226402 129194 599 184 11 — — — — — —
201619 ROK MLEGCL Rays — 5546 7110 6191 20 152264217482 65241 3511 231 42 — — — — — —
201619 ROK RAWGCL Rays — 5542 9210 10131 20 214377310687 95290 2418 315 42 — — — — — —
201821 INTL MLE2 teams — 163146 28202 11554 00 192267247514 55289 347 227 40 — — — — — —
201821 INTL RAW2 teams — 163143 40304 14354 00 280360385745 105343 219 336 40 — — — — — —
201922 A MLEBowling Green Hot Rods — 472417 589110 451967 30 139235237472 98224 4210 219 34 — — — — — —
201922 A RAWBowling Green Hot Rods — 472395 8314219 671367 30 210335400735 190263 2914 331 34 — — — — — —
202124 AA MLE2 teams — 8978 8301 9441 00 103205179384 77206 4910 188 13 — — — — — —
202124 AA RAW2 teams — 8974 11402 13341 00 149284284568 135231 3815 265 13 — — — — — —
202225 AA MLETulsa Drillers — 10293 9303 9600 00 97176226402 129200 599 184 11 — — — — — —
202225 AA RAWTulsa Drillers — 10289 13405 13480 00 146255360614 213222 4713 277 11 — — — — — —
201619 ROK MLEGCL Rays — 5548 7110 6191 20 146264208472 62230 3511 231 42 — — — — — —
201821 INTL MLE2 teams — 163147 28202 11554 00 190267245512 54274 347 227 40 — — — — — —
201922 A MLEBowling Green Hot Rods — 472417 589110 451967 30 139235237472 98221 4210 219 34 — — — — — —
202124 AA MLE2 teams — 8979 8301 9441 00 101205177382 76184 4910 188 13 — — — — — —
202225 AA MLETulsa Drillers — 10292 9303 9600 00 98176228405 130194 599 184 11 — — — — — —
▸ Career Totals
Career— MLE — 881780 11018216 8037413 50 141233231463 90237 429 214 31 -72 +1 +0 +16 +19 -3.7
/ 162G— MLE — 650575 8113112 5927610 40 141233230462 89236 429 214 31 -53 +1 +0 +12 +14 -2.7

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.

2022 AATulsa Drillers · 102 PAwOBA .270 → .184 (−86)K% 47.1% → 59.1%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA47.06%÷0.971×1.220——59.12%
BB% (unintentional) /PA12.75%÷0.975×0.700—×0.9989.13%
HBP% /PA0.00%—×0.870—×0.9980.00%
Singles /BIP9.76%÷0.953×0.920—×0.9989.40%
Doubles /BIP9.76%÷1.006×0.840—×0.9988.13%
Triples /BIP0.00%÷1.150×0.940—×0.9980.00%
Home runs /BIP12.20%÷0.993×0.800—×0.9989.80%

Factors used: league row TL. Park (home-season share, regressed): HR 99, 1B 91, 2B 101, 3B 130, K 94, BB 95 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average).

Result: wOBA .270 → .184; ISO .213 → .137; BABIP .222 → .194. 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).

2021 AAMontgomery Biscuits · 71 PAwOBA .231 → .171 (−60)K% 39.4% → 49.6%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA39.44%÷0.970×1.220——49.61%
BB% (unintentional) /PA14.08%÷1.015×0.690—×1.0129.69%
HBP% /PA1.41%—×0.850—×1.0121.21%
Singles /BIP12.50%÷1.019×0.940—×1.01211.67%
Doubles /BIP3.12%÷1.046×0.870—×1.0122.63%
Triples /BIP0.00%÷0.950×0.920—×1.0120.00%
Home runs /BIP6.25%÷0.938×0.780—×1.0125.26%

Factors used: level-wide AA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 88, 1B 104, 2B 109, 3B 90, K 94, BB 103 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average).

Result: wOBA .231 → .171; ISO .117 → .086; BABIP .167 → .151. 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).

2021 ROKFCL Rays · 18 PAwOBA .393 → .254 (−139)K% 33.3% → 47.7%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA33.33%÷1.005×1.440——47.74%
BB% (unintentional) /PA16.67%÷0.999×0.620—×0.9559.88%
HBP% /PA0.00%—×0.720—×0.9550.00%
Singles /BIP12.50%÷0.990×0.820—×0.9559.88%
Doubles /BIP37.50%÷1.006×0.720—×0.95525.62%
Triples /BIP0.00%÷1.065×0.720—×0.9550.00%
Home runs /BIP0.00%÷0.948×0.780—×0.9550.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 90, 1B 98, 2B 101, 3B 113, K 101, BB 100 — applied at half strength. Age: age 24 vs a level average of 19.5 → −4.5% on BB/HBP/hit rates (4.5 yr older than average).

Result: wOBA .393 → .254; ISO .214 → .140; BABIP .444 → .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).

2019 ABowling Green Hot Rods · 472 PAwOBA .324 → .219 (−105)K% 28.8% → 41.5%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA28.81%÷0.944×1.360——41.52%
BB% (unintentional) /PA13.98%÷1.012×0.690——9.53%
HBP% /PA1.48%—×0.780——1.16%
Singles /BIP18.53%÷0.960×0.920×0.950—16.88%
Doubles /BIP5.41%÷1.103×0.830×0.950—3.87%
Triples /BIP0.77%÷1.124×0.910×0.950—0.59%
Home runs /BIP7.34%÷1.270×0.800——4.62%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 154, 1B 92, 2B 121, 3B 125, K 89, BB 102 — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .324 → .219; ISO .190 → .108; BABIP .263 → .221. 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).

2018 ABowling Green Hot Rods · 65 PAwOBA .278 → .227 (−51)K% 24.6% → 33.5%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA24.62%÷1.000×1.360——33.49%
BB% (unintentional) /PA9.23%÷0.991×0.690—×1.0156.53%
HBP% /PA1.54%—×0.780—×1.0151.22%
Singles /BIP27.50%÷1.004×0.920—×1.01525.57%
Doubles /BIP2.50%÷1.057×0.830—×1.0151.99%
Triples /BIP0.00%÷0.900×0.910—×1.0150.00%
Home runs /BIP2.50%÷1.037×0.800—×1.0151.96%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 107, 1B 101, 2B 111, 3B 80, K 100, BB 98 — 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 .278 → .227; ISO .071 → .054; BABIP .300 → .274. 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 ROKGCL Rays · 55 PAwOBA .320 → .231 (−89)K% 23.6% → 34.0%
ComponentRawPark ÷Level factor ×GB/FB ×Age ×= MLE
K% /PA23.64%÷1.000×1.440——34.04%
BB% (unintentional) /PA18.18%÷1.000×0.620—×1.00811.36%
HBP% /PA1.82%—×0.720—×1.0081.32%
Singles /BIP20.69%÷1.000×0.820—×1.00817.09%
Doubles /BIP6.90%÷1.000×0.720—×1.0085.00%
Triples /BIP3.45%÷1.000×0.720—×1.0082.50%
Home runs /BIP0.00%÷1.000×0.780—×1.0080.00%

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 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average).

Result: wOBA .320 → .231; ISO .095 → .070; BABIP .290 → .230. 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 — .