Garrett Hampson

CF Louisville Bats

Age 32 R/R 5'10" / 196 lbs AAA HR +16%BB +6% Svc 9.000 · Ctrl thru 2027

Overview

AAAExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	29	MLBKC	231	.230/.278/.300	0	7	62	0.2
2025	30	MLBSTL	91	.143/.250/.169	0	3	24	-0.4
2026	31	AAACIN	291	.242/.301/.356	4	8	37	—	.196/.241/.281
2027PROJ10% MLB	32	MLBCIN	16	.210/.263/.295	0	1	56	-0.0
2028PROJ	33	MLBCIN	141	.202/.254/.278	1	6	49	-0.8

Last 3 seasons WAR -0.2 · Next 2 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service9.000First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2023-2025

Speed87

Barrel%13

xwOBA12

Avg EV10

Bat Spd10

CompsTrent Durrington (age 31) · Billy Hamilton (age 32) · Craig Gentry (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 5956vR 47

AVG/OBP/SLG.210 / .263 / .295

PA16

HR0

K%25

BB%6

BABIP279

ISO67

MLB%10%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 35 / POW 40

Toolsscout grade · Statcast %ile · 2023-2025

CONTACT35

xAVG

100.210

POWER40

Barrel%

133.4

Avg EV

1086.0

Bat Spd

1067.1

EYE55

scouting grade only

SPEED60

Sprint

8728.9

Platoon Splits2024-2025 · 322 PA

vs LHP

vs RHP

Edge

165

157

—

wRC+

◀◀L

wOBA

252

233

◀L

ISO

080

035

◀◀L

BABIP

281

300

▶R

26.1%

28.7%

◀L

BB%

8.5%

7.0%

◀◀L

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status FA

MLB Debut 2018

Service 9.000 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	—	—	—
Totals		$1M		$-0.1M	-$1M

Career Stats + Projections

Real MLB stats plus park-adjusted projections — this season (so far / rest / full), then future seasons and career totals.

show model inputsbasis 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.

Year	Age	Lvl	Team	MLB%	PA	AB	H	2B	3B	HR	BB	SO	HBP	SB	CS	AVG	OBP	SLG	OPS	ISO	BABIP	K%	BB%	wOBA	wRC+	BAT	RUN	FLD	POS	REP	WAR
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2017	22	A+	Lancaster JetHawks	—	603	533	174	24	12	8	56	77	2	51	14	326	393	462	854	135	364	13	9	373	84	—	—	—	—	—	—
2018	23	MLB	Colorado Rockies	—	48	40	11	3	1	0	7	12	1	2	0	275	396	400	796	125	393	25	15	363	122	+1	+0	-1	+6	+1	0.8
2018	23	AAA	Albuquerque Isotopes	—	332	296	93	17	4	6	30	58	1	17	4	314	379	459	839	145	372	17	9	368	95	—	—	—	—	—	—
2018	23	AA	Hartford Yard Goats	—	172	148	45	8	2	4	21	17	0	19	1	304	391	466	857	162	323	10	12	375	103	—	—	—	—	—	—
2019	24	MLB	Colorado Rockies	—	327	299	74	9	4	8	24	88	0	15	3	247	303	385	688	137	322	27	7	304	79	-8	+2	+1	+2	+7	0.3
2019	24	AAA	Albuquerque Isotopes	—	117	109	29	9	1	2	5	25	2	7	2	266	310	422	732	156	329	21	4	322	52	—	—	—	—	—	—
2020	25	MLB	Colorado Rockies	—	184	167	39	4	3	5	13	60	0	6	1	234	289	383	672	150	330	33	7	293	72	-6	+1	+2	+1	+4	0.1
2021	26	MLB	Colorado Rockies	—	494	453	106	21	6	11	33	118	3	17	7	234	290	380	670	146	291	24	7	296	74	-15	+1	+5	+2	+11	0.3
2022	27	MLB	Colorado Rockies	—	226	199	42	7	3	2	21	63	1	12	2	211	290	307	596	95	294	28	9	268	59	-11	+2	-0	+2	+5	-0.3
2023	28	MLB	Miami Marlins	—	252	221	61	12	1	3	23	67	3	5	0	276	352	380	732	104	379	27	9	326	114	+4	+1	-3	+4	+5	1.2
2023	28	AAA	Jacksonville Jumbo Shrimp	—	103	92	32	6	1	0	9	15	1	6	0	348	412	435	847	87	416	15	9	378	112	—	—	—	—	—	—
2024	29	MLB	Kansas City Royals	—	231	213	49	13	1	0	14	59	0	7	2	230	278	300	578	70	314	26	6	259	62	-11	+1	+6	+1	+5	0.2
2025	30	MLB	St. Louis Cardinals	—	91	77	11	2	0	0	11	29	0	3	1	143	250	169	419	26	229	32	12	202	24	-8	+0	+2	+0	+2	-0.4
2026	31	AAA	Louisville Bats	—	291	264	64	16	1	4	19	69	3	8	1	242	301	356	657	114	314	24	7	292	37	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1853	1669	393	71	19	29	146	496	8	67	16	235	300	353	653	117	315	27	8	290	83	-38	+7	+11	+17	+40	3.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2017	22	A+ MLE	Lancaster JetHawks	—	603	550	148	19	8	5	39	115	2	51	14	269	320	360	680	91	315	19	6	293	84	—	—	—	—	—	—
2018	23	MLB MLE	Colorado Rockies	—	48	40	11	3	1	0	7	12	1	2	0	275	396	400	796	125	393	25	15	348	122	+1	+0	-1	+6	+1	0.8
2018	23	AAA MLE	Albuquerque Isotopes	—	332	304	84	15	4	4	22	77	1	17	4	276	327	391	719	115	343	23	7	308	95	—	—	—	—	—	—
2018	23	AA MLE	Hartford Yard Goats	—	172	155	44	7	2	3	14	20	0	19	1	284	343	413	756	129	302	12	8	321	103	—	—	—	—	—	—
2019	24	MLB MLE	Colorado Rockies	—	327	300	70	9	3	7	23	88	0	15	3	233	288	353	641	120	322	27	7	285	79	-8	+2	+1	+2	+7	0.3
2019	24	AAA MLE	Albuquerque Isotopes	—	117	110	23	6	1	1	4	34	2	7	2	209	250	309	559	100	286	29	3	245	52	—	—	—	—	—	—
2020	25	MLB MLE	Colorado Rockies	—	184	167	36	4	2	4	13	60	0	6	1	216	272	335	608	120	330	33	7	275	72	-6	+1	+2	+1	+4	0.1
2021	26	MLB MLE	Colorado Rockies	—	494	455	100	20	4	10	31	118	3	17	7	220	274	347	621	127	291	24	6	277	74	-15	+1	+5	+2	+11	0.3
2022	27	MLB MLE	Colorado Rockies	—	226	199	40	7	2	2	21	63	1	12	2	201	281	286	567	85	294	28	9	256	59	-11	+2	-0	+2	+5	-0.3
2023	28	MLB MLE	Miami Marlins	—	252	221	63	13	1	3	23	67	3	5	0	285	360	394	754	109	379	27	9	336	114	+4	+1	-3	+4	+5	1.2
2023	28	AAA MLE	Jacksonville Jumbo Shrimp	—	103	95	30	5	1	0	6	17	1	6	0	316	363	389	752	74	388	17	6	334	112	—	—	—	—	—	—
2024	29	MLB MLE	Kansas City Royals	—	231	213	49	13	1	0	14	59	0	7	2	230	278	300	578	70	314	26	6	259	62	-11	+1	+6	+1	+5	0.2
2025	30	MLB MLE	St. Louis Cardinals	—	91	77	11	2	0	0	11	29	0	3	1	143	250	169	419	26	229	32	12	203	24	-8	+0	+2	+0	+2	-0.4
2026	31	AAA MLE	Louisville Bats	—	291	270	53	12	1	3	13	83	3	8	1	196	241	281	523	85	263	29	4	223	37	—	—	—	—	—	—
2017	22	A+ MLE	Lancaster JetHawks	—	603	550	148	19	8	5	39	115	2	51	14	269	320	360	680	91	326	19	6	293	84	—	—	—	—	—	—
2017	22	A+ RAW	Lancaster JetHawks	—	603	533	174	24	12	8	56	77	2	51	14	326	393	462	854	135	364	13	9	373	84	—	—	—	—	—	—
2018	23	AAA MLE	3 teams	—	552	499	137	25	6	7	43	109	2	38	5	275	335	391	725	116	338	20	8	316	100	—	—	—	—	—	—
2018	23	AAA RAW	3 teams	—	552	484	149	28	7	10	58	87	2	38	5	308	384	457	841	149	357	16	11	370	100	—	—	—	—	—	—
2019	24	MLB MLE	2 teams	—	444	410	92	15	3	8	27	122	2	22	5	224	276	334	610	110	298	27	6	275	72	-15	+2	+1	+2	+10	-0.0
2019	24	MLB RAW	2 teams	—	444	408	103	18	5	10	29	113	2	22	5	252	305	395	700	142	324	25	7	309	72	-15	+2	+1	+2	+10	-0.0
2020	25	MLB MLE	Colorado Rockies	—	184	167	36	4	2	4	13	60	0	6	1	216	272	335	608	120	308	33	7	275	72	-6	+1	+2	+1	+4	0.1
2020	25	MLB RAW	Colorado Rockies	—	184	167	39	4	3	5	13	60	0	6	1	234	289	383	672	150	330	33	7	293	72	-6	+1	+2	+1	+4	0.1
2021	26	MLB MLE	Colorado Rockies	—	494	455	100	20	4	10	31	118	3	17	7	220	274	347	621	127	274	24	6	277	74	-15	+1	+5	+2	+11	0.3
2021	26	MLB RAW	Colorado Rockies	—	494	453	106	21	6	11	33	118	3	17	7	234	290	380	670	146	291	24	7	296	74	-15	+1	+5	+2	+11	0.3
2022	27	MLB MLE	Colorado Rockies	—	226	199	40	7	2	2	21	63	1	12	2	201	281	286	567	85	279	28	9	256	59	-11	+2	-0	+2	+5	-0.3
2022	27	MLB RAW	Colorado Rockies	—	226	199	42	7	3	2	21	63	1	12	2	211	290	307	596	95	294	28	9	268	59	-11	+2	-0	+2	+5	-0.3
2023	28	MLB MLE	2 teams	—	355	316	94	19	2	3	29	84	4	11	0	297	364	399	763	101	394	24	8	336	113	+6	+2	-3	+4	+8	1.7
2023	28	MLB RAW	2 teams	—	355	313	93	18	2	3	32	82	4	11	0	297	370	396	766	99	391	23	9	341	113	+6	+2	-3	+4	+8	1.7
2024	29	MLB MLE	Kansas City Royals	—	231	213	49	13	1	0	14	59	0	7	2	230	278	300	578	70	314	26	6	259	62	-11	+1	+6	+1	+5	0.2
2024	29	MLB RAW	Kansas City Royals	—	231	213	49	13	1	0	14	59	0	7	2	230	278	300	578	70	314	26	6	259	62	-11	+1	+6	+1	+5	0.2
2025	30	MLB MLE	St. Louis Cardinals	—	91	77	11	2	0	0	11	29	0	3	1	143	250	169	419	26	229	32	12	203	24	-8	+0	+2	+0	+2	-0.4
2025	30	MLB RAW	St. Louis Cardinals	—	91	77	11	2	0	0	11	29	0	3	1	143	250	169	419	26	229	32	12	202	24	-8	+0	+2	+0	+2	-0.4
2026	31	AAA MLE	Louisville Bats	—	291	270	53	12	1	3	13	83	3	8	1	196	241	281	523	85	272	29	4	223	37	—	—	—	—	—	—
2026	31	AAA RAW	Louisville Bats	—	291	264	64	16	1	4	19	69	3	8	1	242	301	356	657	114	314	24	7	292	37	—	—	—	—	—	—
2017	22	A+ MLE	Lancaster JetHawks	—	603	557	148	19	8	5	39	115	2	51	14	266	320	355	675	90	315	19	6	293	84	—	—	—	—	—	—
2018	23	AAA MLE	3 teams	—	552	502	137	25	6	7	43	109	2	38	5	273	335	388	723	116	335	20	8	316	100	—	—	—	—	—	—
2019	24	MLB MLE	2 teams	—	444	412	92	15	3	8	27	122	2	22	5	223	276	333	608	109	312	27	6	275	72	—	—	—	—	—	—
2020	25	MLB MLE	Colorado Rockies	—	184	169	36	4	2	4	13	60	0	6	1	213	272	331	604	118	330	33	7	275	72	—	—	—	—	—	—
2021	26	MLB MLE	Colorado Rockies	—	494	457	100	20	4	10	31	118	3	17	7	219	274	346	620	127	291	24	6	277	74	—	—	—	—	—	—
2022	27	MLB MLE	Colorado Rockies	—	226	202	40	7	2	2	21	63	1	12	2	198	281	282	563	84	294	28	9	256	59	—	—	—	—	—	—
2023	28	MLB MLE	2 teams	—	355	319	94	19	2	3	29	84	4	11	0	295	364	395	759	100	382	24	8	336	113	—	—	—	—	—	—
2024	29	MLB MLE	Kansas City Royals	—	231	215	49	13	1	0	14	59	0	7	2	228	278	298	575	70	314	26	6	259	62	—	—	—	—	—	—
2025	30	MLB MLE	St. Louis Cardinals	—	91	80	11	2	0	0	11	29	0	3	1	138	250	163	412	25	229	32	12	203	24	—	—	—	—	—	—
2026	31	AAA MLE	Louisville Bats	—	291	273	53	12	1	3	13	83	3	8	1	194	241	278	520	84	263	29	4	223	37	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Kansas City Royals	—	231	215	49	13	1	0	14	59	0	7	2	228	278	298	575	70	314	26	6	259	62	—	—	—	—	—	—
2025	30	MLB MLE	St. Louis Cardinals	—	91	80	11	2	0	0	11	29	0	3	1	138	250	163	412	25	229	32	12	203	24	—	—	—	—	—	—
2026	31	AAA MLE	Louisville Bats	—	291	273	53	12	1	3	13	83	3	8	1	194	241	278	520	84	263	29	4	223	37	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	CIN	10%	258	238	50	10	1	3	16	69	2	16	3	209	262	292	555	84	279	27	6	251	56	-13	+2	+1	+1	+6	-0.3
▸ 2027 — real world (MLB)
2027	32	MLB CTX	CIN	10%	16	15	3	1	0	0	1	4	0	1	0	210	263	295	559	86	279	25	6	253	56	-1	+0	+0	+0	+0	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	CIN	100%	141	131	25	5	0	1	8	38	1	6	1	201	254	276	529	75	272	27	6	241	49	-9	+1	-4	+1	+3	-0.8
2028	33	MLB CTX	CIN	100%	141	131	25	5	0	1	8	38	1	6	1	202	254	278	533	76	272	27	6	242	49	-9	+1	-4	+1	+3	-0.8
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1994	1800	418	76	19	30	154	534	9	73	17	232	296	346	642	113	311	27	8	287	75	-47	+8	+7	+18	+43	3.0
/ 162G	—	A+C		—	650	587	137	25	6	10	50	174	3	24	6	233	297	348	644	114	312	27	8	287	75	-15	+3	+2	+6	+14	1.0
Career	—	MLE		—	3772	3435	816	147	30	45	259	923	19	191	41	238	295	337	632	100	310	24	7	280	75	-55	+9	+8	+18	+47	2.7
/ 162G	—	MLE		—	650	592	140	25	5	8	45	159	3	33	7	236	294	336	630	100	308	24	7	280	75	-17	+3	+2	+6	+14	0.8

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 AAALouisville Bats · 291 PAwOBA .284 → .223 (−61)K% 23.7% → 28.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.71%	÷1.000	×1.200	—	—	28.45%
BB% (unintentional) /PA	6.53%	÷1.000	×0.690	—	×0.952	4.29%
HBP% /PA	1.03%	—	×0.940	—	×0.952	0.92%
Singles /BIP	22.05%	÷1.000	×0.930	×0.980	×0.952	19.13%
Doubles /BIP	8.21%	÷1.000	×0.830	×0.980	×0.952	6.35%
Triples /BIP	0.51%	÷1.000	×0.970	×0.980	×0.952	0.46%
Home runs /BIP	2.05%	÷1.000	×0.700	—	×0.952	1.37%

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 32 vs a level average of 27.2 → −4.8% on BB/HBP/hit rates (4.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.980.

Result: wOBA .284 → .223; ISO .114 → .083; BABIP .314 → .263. 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 AAAJacksonville Jumbo Shrimp · 103 PAwOBA .369 → .334 (−35)K% 14.6% → 16.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.56%	÷1.040	×1.200	—	—	16.80%
BB% (unintentional) /PA	8.74%	÷1.008	×0.690	—	×0.982	5.87%
HBP% /PA	0.97%	—	×0.940	—	×0.982	0.90%
Singles /BIP	32.47%	÷1.016	×0.930	×1.047	×0.982	30.54%
Doubles /BIP	7.79%	÷0.955	×0.830	×1.047	×0.982	6.96%
Triples /BIP	1.30%	÷1.039	×0.970	×1.047	×0.982	1.25%
Home runs /BIP	0.00%	÷1.031	×0.700	—	×0.982	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 106, 1B 103, 2B 91, 3B 108, K 108, BB 102 — 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 ×1.047.

Result: wOBA .369 → .334; ISO .087 → .081; BABIP .416 → .388. 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 AAAAlbuquerque Isotopes · 117 PAwOBA .313 → .245 (−68)K% 21.4% → 28.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.37%	÷0.957	×1.290	—	—	28.81%
BB% (unintentional) /PA	4.27%	÷0.974	×0.710	—	×1.033	3.22%
HBP% /PA	1.71%	—	×0.980	—	×1.033	1.73%
Singles /BIP	20.24%	÷0.974	×0.900	×0.984	×1.033	19.01%
Doubles /BIP	10.71%	÷1.071	×0.810	×0.984	×1.033	8.23%
Triples /BIP	1.19%	÷1.150	×0.810	×0.984	×1.033	0.85%
Home runs /BIP	2.38%	÷1.136	×0.780	—	×1.033	1.69%

Factors used: league row PCL. Park (home-season share, regressed): HR 127, 1B 95, 2B 114, 3B 130, K 91, BB 95 — 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 ×0.984.

Result: wOBA .313 → .245; ISO .156 → .107; BABIP .329 → .286. 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 AAAAlbuquerque Isotopes · 332 PAwOBA .361 → .308 (−53)K% 17.5% → 23.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.47%	÷0.978	×1.290	—	—	23.05%
BB% (unintentional) /PA	9.04%	÷1.024	×0.710	—	×1.048	6.57%
HBP% /PA	0.30%	—	×0.980	—	×1.048	0.31%
Singles /BIP	27.73%	÷1.034	×0.900	×1.028	×1.048	26.02%
Doubles /BIP	7.14%	÷0.960	×0.810	×1.028	×1.048	6.50%
Triples /BIP	1.68%	÷0.973	×0.810	×1.028	×1.048	1.51%
Home runs /BIP	2.52%	÷1.162	×0.780	—	×1.048	1.77%

Factors used: league row PCL. Park (home-season share, regressed): HR 132, 1B 107, 2B 92, 3B 95, K 96, BB 105 — 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 ×1.028.

Result: wOBA .361 → .308; ISO .145 → .117; BABIP .372 → .343. 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 AAHartford Yard Goats · 172 PAwOBA .366 → .321 (−45)K% 9.9% → 11.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.88%	÷1.035	×1.220	—	—	11.65%
BB% (unintentional) /PA	12.21%	÷1.051	×0.700	—	×1.012	8.23%
HBP% /PA	0.00%	—	×0.850	—	×1.012	0.00%
Singles /BIP	23.66%	÷1.011	×0.970	×1.004	×1.012	23.08%
Doubles /BIP	6.11%	÷1.081	×0.860	×1.004	×1.012	4.94%
Triples /BIP	1.53%	÷0.948	×0.950	×1.004	×1.012	1.56%
Home runs /BIP	3.05%	÷1.194	×0.780	—	×1.012	2.02%

Factors used: league row EL. Park (home-season share, regressed): HR 139, 1B 102, 2B 116, 3B 90, K 107, BB 110 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.004.

Result: wOBA .366 → .321; ISO .162 → .131; BABIP .323 → .302. 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 A+Lancaster JetHawks · 603 PAwOBA .368 → .293 (−75)K% 12.8% → 19.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.77%	÷0.897	×1.340	—	—	19.07%
BB% (unintentional) /PA	9.12%	÷1.017	×0.710	—	×0.998	6.35%
HBP% /PA	0.33%	—	×0.790	—	×0.998	0.26%
Singles /BIP	28.51%	÷1.004	×0.910	×1.002	×0.998	25.83%
Doubles /BIP	5.26%	÷1.039	×0.820	×1.002	×0.998	4.15%
Triples /BIP	2.63%	÷1.136	×0.760	×1.002	×0.998	1.76%
Home runs /BIP	1.75%	÷1.600	×0.920	—	×0.998	1.01%

Factors used: league row CAL. Park (home-season share, regressed): HR 220, 1B 101, 2B 108, 3B 127, K 79, BB 103 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .368 → .293; ISO .135 → .090; BABIP .364 → .315. 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).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Leury Garcíalast yr '22 career totals — 9 seasons, 2,387 PA	3.6	2,387	34	63	253	293	351	+5	+10	3.1	4.3
/162	664	9	18	+1.4	+2.7	0.9	pk7: 6
#2Luis Matos'00-'06 * career totals — 6 seasons, 1,773 PA	2.7	1,773	30	72	245*	304*	365*	+1	+10	3.2	3.2
/162	664	11	27	+0.3	+3.9	1.2	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 8 projected seasons	3.0	1,962	30	72	231	289	344	+7	+10	2.0	2.2
/162	664	10	24	+2.4	+3.4	0.7	pk7: 2
#3Milt Cuyler'90-'98 * career totals — 7 seasons, 1,567 PA	2.4	1,567	10	77	233*	299*	338*	+1	+4	0.6	0.9
/162	664	4	33	+0.6	+1.9	0.3	pk7: 1
#4Nick Senzellast yr '24 career totals — 6 seasons, 1,633 PA	2.5	1,633	40	33	232	299	363	+6	-14	0.9	0.9
/162	664	16	13	+2.4	-5.8	0.4	pk7: 1
#5Damon Buford'93-'01 * career totals — 8 seasons, 2,072 PA	3.1	2,072	54	56	230*	296*	371*	-1	-2	0.2	0.8
/162	664	17	18	-0.4	-0.5	0.1	pk7: 1
#6Herm Winningham'84-'92 * career totals — 8 seasons, 2,069 PA	3.1	2,069	19	105	238*	296*	357*	+1	-3	-0.5	0.2
/162	664	6	34	+0.3	-1.1	-0.2	pk7: 1

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Garrett Hampson (OGILVIE)	32	35	40	60	55	207/260/290	83	279	2	10	27%	6%	56	-0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Trent Durrington 2007 · MLB	31	47→43	38→40	59→60	43	223/275/304	81	286	6	35	24%	6%	64	-1.3	217/277/301	84	279	6	26	23%	7%	65	-1.2	201/270/253	52	258	2	33	21%	7%	49	-0.9
✕Billy Hamilton 2023 · MLB	32	38→48	40	64→70	37	188/236/282	94	284	7	38	35%	6%	45	-2.7	198/263/300	102	298	9	26	34%	8%	60	-1.6	135/211/191	56	219	3	36	37%	8%	14	-0.9
✕Craig Gentry 2016 · MLB	32	48→55	37→40	57→60	46	228/284/295	67	282	5	29	20%	6%	65	-1.2	218/278/298	80	277	6	24	22%	7%	64	-1.3	218/282/291	73	279	4	29	22%	7%	64	-0.4
✕Juan Ciriaco 2016 · AAA	32	43→48	40→45	55→50	41	211/240/299	88	248	8	22	19%	4%	50	-2.3	215/252/313	98	267	8	15	22%	5%	57	-1.8	212/248/304	92	263	7	13	22%	5%	53	-0.8
✕Darren Ford 2016 · AAA	30	45→53	41→45	57→65	43	218/270/309	91	280	9	39	25%	6%	64	-1.3	218/270/298	80	283	6	24	24%	6%	61	-1.5	212/261/258	46	279	1	23	23%	6%	45	-1.9
✕Wynton Bernard 2022 · AAA	31	42→52	41→45	61→60	41	204/255/307	102	269	8	27	27%	6%	58	-1.7	240/286/363	123	293	11	32	21%	6%	82	-0.0	245/290/364	119	296	10	37	20%	5%	81	-0.1
✕Jack Reinheimer 2024 · AAA	32	39→49	38→40	55	37	191/241/270	78	281	6	19	33%	5%	44	-2.8	191/238/280	89	267	8	13	30%	5%	45	-2.7	136/171/180	44	185	3	12	28%	4%	-4	-1.4
✕Christian Zazueta 2017 · AAA	32	47→54	44→45	58→60	37	236/258/352	117	277	12	29	20%	2%	69	-0.9	224/250/319	95	264	9	27	19%	2%	58	-1.7	220/244/297	77	255	7	27	17%	2%	47	-1.5
✕Jonathan Davis 2023 · MLB	31	46→52	40→45	57→55	51	219/314/311	92	297	8	27	27%	10%	82	+0.0	218/293/335	117	304	10	17	29%	8%	79	-0.2	204/277/324	120	289	10	14	31%	7%	68	-0.5
✕Todd Donovan 2009 · AAA	30	49→52	36→40	61→65	48	232/291/301	69	291	3	38	21%	7%	70	-0.9	224/300/306	82	289	5	31	22%	10%	75	-0.5	214/305/285	71	275	3	38	21%	11%	71	-0.6
✕Chase d'Arnaud 2018 · MLB	31	47→50	40→45	57→60	45	225/278/317	91	274	7	26	20%	6%	69	-0.9	207/270/334	127	283	14	19	30%	7%	71	-0.8	188/255/317	129	261	15	19	33%	7%	60	-1.0
✕Pete Orr 2011 · MLB	32	45	43→45	56→55	41	220/264/339	119	263	9	21	21%	4%	69	-0.9	221/260/319	98	272	7	20	21%	4%	62	-1.4	228/255/314	86	291	5	16	23%	3%	55	-1.2
✕Esix Snead 2006 · AAA	30	46	37→30	63→65	50	217/292/290	73	265	4	44	19%	8%	68	-1.0	218/284/303	85	265	7	33	19%	8%	68	-1.0	199/258/236	37	236	3	46	16%	7%	41	-0.8
✕Eric Young Jr. 2017 · MLB	32	45→55	37→45	61→65	47	213/273/283	70	263	4	36	20%	7%	59	-1.7	232/286/336	104	289	9	25	22%	6%	76	-0.4	233/288/340	107	291	8	24	22%	6%	76	-0.3
✕Quintin Berry 2018 · AAA	33	44→54	37→40	56→65	44	211/274/278	67	288	5	32	27%	7%	58	-1.7	213/269/319	106	311	11	24	33%	6%	66	-1.1	162/208/235	73	255	8	48	38%	5%	21	-0.8
✕Tyler Graham 2014 · AAA	30	47→54	39→40	60→65	45	225/290/311	86	287	6	33	23%	6%	72	-0.7	228/274/303	75	282	6	28	21%	5%	63	-1.3	230/270/276	46	284	3	38	19%	4%	52	-1.6
✕Zach Remillard 2024 · MLB	30	45→49	40	52→55	44	218/282/303	86	291	7	20	27%	7%	68	-1.0	200/261/295	95	269	8	14	27%	7%	58	-1.7	132/192/197	65	179	6	8	29%	6%	9	-1.9
✕Drew Maggi 2023 · AAA	34	38→48	40→45	54→60	41	185/260/274	89	272	7	23	33%	7%	53	-2.1	190/250/286	96	261	9	15	29%	6%	52	-2.2	155/205/234	78	202	9	9	28%	4%	20	-1.0
✕Tim Locastro 2024 · MLB	32	40→50	45	56→60	40	201/281/322	122	255	12	24	25%	5%	73	-0.6	222/301/340	118	272	11	29	22%	6%	84	+0.2	219/299/327	108	266	9	38	20%	5%	78	-0.1
✕Mike McCoy 2014 · MLB	33	46→56	38→40	54→60	54	220/298/295	75	265	6	30	19%	10%	72	-0.7	191/265/261	70	247	4	18	23%	8%	52	-2.2	159/236/208	49	212	2	14	24%	8%	28	-1.9

Garrett Hampson

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps