Luke Raley

RF Seattle Mariners

Age 32 L/R 6'3" / 235 lbs MLB K +7%HR -5% Svc 4.616 · Ctrl thru 2028 ILInjured 60-Day (D60)

Overview

MLBIL-6040-MANArb-2FA 2029

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	29	MLBSEA	455	.243/.322/.463	22	11	122	1.2
2025	30	AAASEA	38	.314/.368/.600	3	0	80	—	.250/.289/.444
2025	30	MLBSEA	219	.202/.321/.311	4	2	86	-0.4
2026	31	MLBSEA	287	.225/.285/.439	15	1	101	0.2
2027PROJ	32	MLBSEA	121	.237/.313/.444	6	5	115	0.4
2028PROJ	33	MLBSEA	184	.229/.303/.425	8	6	107	0.0

Last 3 seasons WAR 0.9 · Next 2 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2028Service4.616First FA2029

2027Arb-2$1M2028Arb-3$1M

Skills · percentileStatcast 2024-2026

Bat Spd89

Speed79

Barrel%78

Avg EV65

xwOBA64

CompsSeth Brown (age 32) · Curtis Granderson (age 32) · Raul Mondesi (age 31)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 84115vR 126

AVG/OBP/SLG.237 / .313 / .444

PA121

HR6

SB5

K%30

BB%7

BABIP294

ISO204

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$1M ctrl surplus

Tools · Splits · ContractCON 40 / POW 55

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT40

xAVG

200.227

POWER55

Barrel%

7812.3

Avg EV

6590.2

Bat Spd

8975.5

EYE50

scouting grade only

SPEED60

Sprint

7928.6

Platoon Splits2024-2026 · 754 PA

vs LHP

vs RHP

Edge

118

636

—

wRC+

125

▶▶R

wOBA

229

353

▶▶R

ISO

094

215

▶▶R

BABIP

219

327

▶▶R

29.7%

30.5%

—

BB%

7.6%

6.6%

◀L

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

Status Arb-2

MLB Debut 2021

Service 4.616 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-2	$1M	+0.4	$2M	+$0.3M
2028	Arb-3	$1M	—	—	—
Totals		$1M		$2M	+$0.3M

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)
2016	21	A	Great Lakes Loons	—	231	200	49	11	4	2	15	47	9	4	4	245	326	370	696	125	301	20	6	306	63	—	—	—	—	—	—
2016	21	ROK	Ogden Raptors	—	44	40	20	3	2	2	3	3	1	0	0	500	545	825	1.370	325	514	7	7	587	174	—	—	—	—	—	—
2017	22	A+	Rancho Cucamonga Quakes	—	541	478	141	21	11	14	43	124	19	9	1	295	376	473	849	178	372	23	8	377	80	—	—	—	—	—	—
2018	23	AA	Chattanooga Lookouts	—	551	484	133	19	8	20	36	137	24	4	0	275	355	471	826	196	338	25	7	362	86	—	—	—	—	—	—
2018	23	INTL	Salt River Rafters	—	18	14	3	0	1	0	3	4	0	1	0	214	353	357	710	143	273	22	17	307	94	—	—	—	—	—	—
2019	24	AAA	Rochester Red Wings	—	138	126	38	6	0	7	7	42	5	4	0	302	362	516	878	214	403	30	5	387	100	—	—	—	—	—	—
2019	24	ROK	GCL Twins	—	20	19	7	0	0	1	0	2	0	0	0	368	368	526	895	158	353	10	0	376	86	—	—	—	—	—	—
2019	24	INTL	Salt River Rafters	—	93	82	20	5	1	3	4	21	5	0	0	244	319	439	758	195	283	23	4	330	110	—	—	—	—	—	—
2021	26	MLB	Los Angeles Dodgers	—	72	66	12	1	0	2	2	25	4	0	0	182	250	288	538	106	256	35	3	249	48	-4	+0	-1	-4	+2	-0.8
2021	26	AAA	Oklahoma City Dodgers	—	318	272	80	14	2	19	27	74	18	8	3	294	394	570	964	276	339	23	8	420	115	—	—	—	—	—	—
2022	27	MLB	Tampa Bay Rays	—	72	61	12	2	0	1	7	24	3	0	0	197	310	279	589	82	297	33	10	276	73	-2	+0	+0	-4	+2	-0.4
2022	27	AAA	Durham Bulls	—	268	227	68	8	1	14	27	73	12	7	2	300	402	529	931	229	383	27	10	408	101	—	—	—	—	—	—
2023	28	MLB	Tampa Bay Rays	—	406	357	89	23	3	19	28	128	18	14	3	249	335	490	825	241	330	32	7	361	132	+15	+2	-2	-4	+9	1.9
2024	29	MLB	Seattle Mariners	—	455	404	98	19	2	22	27	135	20	11	2	243	322	463	784	220	305	30	6	344	122	+12	+1	-7	-5	+10	1.2
2025	30	MLB	Seattle Mariners	—	219	183	37	8	0	4	19	64	13	2	1	202	321	311	632	109	284	29	9	292	86	-4	+0	-3	-3	+5	-0.4
2025	30	AAA	Tacoma Rainiers	—	38	35	11	1	0	3	2	12	1	0	0	314	368	600	968	286	400	32	5	421	80	—	—	—	—	—	—
2026	31	MLB	Seattle Mariners	—	287	262	59	9	1	15	15	93	7	1	2	225	285	439	724	214	284	32	5	316	101	+0	-1	-1	-3	+6	0.2
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1511	1333	307	62	6	63	98	469	65	28	8	230	314	428	742	197	302	31	6	328	108	+15	+2	-13	-23	+33	1.4
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	21	A MLE	Great Lakes Loons	—	231	205	45	9	4	2	10	64	9	4	4	220	286	332	617	112	281	28	4	262	63	—	—	—	—	—	—
2016	21	ROK MLE	Ogden Raptors	—	44	41	14	2	1	1	2	4	1	0	0	341	386	512	899	171	391	9	5	426	174	—	—	—	—	—	—
2017	22	A+ MLE	Rancho Cucamonga Quakes	—	541	494	116	16	7	11	27	168	19	9	1	235	300	362	662	128	326	31	5	286	80	—	—	—	—	—	—
2018	23	AA MLE	Chattanooga Lookouts	—	551	497	115	18	8	16	23	174	24	4	0	231	298	396	694	165	304	32	4	296	86	—	—	—	—	—	—
2019	24	AAA MLE	Rochester Red Wings	—	138	129	32	4	0	6	4	51	5	4	0	248	297	419	716	171	368	37	3	316	100	—	—	—	—	—	—
2019	24	ROK MLE	GCL Twins	—	20	19	6	0	0	1	0	3	0	0	0	316	316	474	789	158	269	15	0	295	86	—	—	—	—	—	—
2021	26	MLB MLE	Los Angeles Dodgers	—	72	67	12	1	0	2	1	25	4	0	0	179	236	284	520	104	256	35	1	240	48	-4	+0	-1	-4	+2	-0.8
2021	26	AAA MLE	Oklahoma City Dodgers	—	318	281	70	12	2	13	18	89	18	8	3	249	334	445	779	196	317	28	6	338	115	—	—	—	—	—	—
2022	27	MLB MLE	Tampa Bay Rays	—	72	61	12	2	0	1	7	24	3	0	0	197	310	279	589	82	297	33	10	276	73	-2	+0	+0	-4	+2	-0.4
2022	27	AAA MLE	Durham Bulls	—	268	237	58	6	1	9	17	88	12	7	2	245	327	392	719	148	344	33	6	318	101	—	—	—	—	—	—
2023	28	MLB MLE	Tampa Bay Rays	—	406	357	90	24	3	20	28	128	18	14	3	252	337	504	842	252	330	32	7	363	132	+15	+2	-2	-4	+9	1.9
2024	29	MLB MLE	Seattle Mariners	—	455	404	99	19	2	23	27	135	20	11	2	245	324	473	796	228	305	30	6	349	122	+12	+1	-7	-5	+10	1.2
2025	30	MLB MLE	Seattle Mariners	—	219	183	37	8	0	4	19	64	13	2	1	202	321	311	632	109	284	29	9	295	86	-4	+0	-3	-3	+5	-0.4
2025	30	AAA MLE	Tacoma Rainiers	—	38	36	9	1	0	2	1	14	1	0	0	250	289	444	734	194	326	37	3	286	80	—	—	—	—	—	—
2026	31	MLB MLE	Seattle Mariners	—	287	263	59	9	1	15	14	93	7	1	2	224	282	437	719	213	284	32	5	318	101	+0	-1	-1	-3	+6	0.2
2016	21	A MLE	2 teams	—	275	246	59	11	5	3	12	69	10	4	4	240	302	362	664	122	313	25	4	288	81	—	—	—	—	—	—
2016	21	A RAW	2 teams	—	275	240	69	14	6	4	18	50	10	4	4	287	362	446	808	158	340	18	7	351	81	—	—	—	—	—	—
2017	22	A+ MLE	Rancho Cucamonga Quakes	—	541	494	116	16	7	11	27	168	19	9	1	235	300	362	662	128	332	31	5	286	80	—	—	—	—	—	—
2017	22	A+ RAW	Rancho Cucamonga Quakes	—	541	478	141	21	11	14	43	124	19	9	1	295	376	473	849	178	372	23	8	377	80	—	—	—	—	—	—
2018	23	AA MLE	2 teams	—	569	514	119	18	8	17	23	180	24	5	0	232	296	397	693	165	314	32	4	296	86	—	—	—	—	—	—
2018	23	AA RAW	2 teams	—	569	498	136	19	9	20	39	141	24	5	0	273	355	468	823	195	336	25	7	360	86	—	—	—	—	—	—
2019	24	AAA MLE	3 teams	—	251	232	61	7	0	11	6	85	10	4	0	263	310	435	746	172	360	34	2	313	98	—	—	—	—	—	—
2019	24	AAA RAW	3 teams	—	251	227	65	11	1	11	11	65	10	4	0	286	347	489	836	203	351	26	4	365	98	—	—	—	—	—	—
2021	26	AAA MLE	2 teams	—	390	348	82	13	2	15	19	114	22	8	3	236	316	414	730	178	305	29	5	320	103	—	—	—	—	—	—
2021	26	AAA RAW	2 teams	—	390	338	92	15	2	21	29	99	22	8	3	272	368	515	882	243	324	25	7	388	103	—	—	—	—	—	—
2022	27	AAA MLE	2 teams	—	340	298	70	8	1	10	24	112	15	7	2	235	323	369	693	134	337	33	7	309	95	—	—	—	—	—	—
2022	27	AAA RAW	2 teams	—	340	288	80	10	1	15	34	97	15	7	2	278	383	476	858	198	365	29	10	380	95	—	—	—	—	—	—
2023	28	MLB MLE	Tampa Bay Rays	—	406	357	90	24	3	20	28	128	18	14	3	252	337	504	842	252	332	32	7	363	132	+15	+2	-2	-4	+9	1.9
2023	28	MLB RAW	Tampa Bay Rays	—	406	357	89	23	3	19	28	128	18	14	3	249	335	490	825	241	330	32	7	361	132	+15	+2	-2	-4	+9	1.9
2024	29	MLB MLE	Seattle Mariners	—	455	404	99	19	2	23	27	135	20	11	2	245	324	473	796	228	306	30	6	349	122	+12	+1	-7	-5	+10	1.2
2024	29	MLB RAW	Seattle Mariners	—	455	404	98	19	2	22	27	135	20	11	2	243	322	463	784	220	305	30	6	344	122	+12	+1	-7	-5	+10	1.2
2025	30	MLB MLE	2 teams	—	257	219	46	9	0	6	20	78	14	2	1	210	316	333	650	123	294	30	8	293	85	-5	+0	-3	-3	+6	-0.5
2025	30	MLB RAW	2 teams	—	257	218	48	9	0	7	21	76	14	2	1	220	328	358	686	138	301	30	8	311	85	-5	+0	-3	-3	+6	-0.5
2026	31	MLB MLE	Seattle Mariners	—	287	263	59	9	1	15	14	93	7	1	2	224	282	437	719	213	282	32	5	318	101	+0	-1	-1	-3	+6	0.2
2026	31	MLB RAW	Seattle Mariners	—	287	262	59	9	1	15	15	93	7	1	2	225	285	439	724	214	284	32	5	316	101	+0	-1	-1	-3	+6	0.2
2016	21	A MLE	2 teams	—	275	251	59	11	5	3	12	69	10	4	4	235	302	355	657	120	299	25	4	288	81	—	—	—	—	—	—
2017	22	A+ MLE	Rancho Cucamonga Quakes	—	541	490	116	16	7	11	27	168	19	9	1	237	300	365	665	129	326	31	5	286	80	—	—	—	—	—	—
2018	23	AA MLE	2 teams	—	569	517	119	18	8	17	23	180	24	5	0	230	296	395	690	164	304	32	4	296	86	—	—	—	—	—	—
2019	24	AAA MLE	3 teams	—	251	233	61	7	0	11	6	85	10	4	0	262	310	433	744	172	355	34	2	313	98	—	—	—	—	—	—
2021	26	AAA MLE	2 teams	—	390	346	82	13	2	15	19	114	22	8	3	237	316	416	732	179	306	29	5	320	103	—	—	—	—	—	—
2022	27	AAA MLE	2 teams	—	340	298	70	8	1	10	24	112	15	7	2	235	323	369	693	134	334	33	7	309	95	—	—	—	—	—	—
2023	28	MLB MLE	Tampa Bay Rays	—	406	357	90	24	3	20	28	128	18	14	3	252	337	504	842	252	330	32	7	363	132	—	—	—	—	—	—
2024	29	MLB MLE	Seattle Mariners	—	455	405	99	19	2	23	27	135	20	11	2	244	324	472	795	227	305	30	6	349	122	—	—	—	—	—	—
2025	30	MLB MLE	2 teams	—	257	221	46	9	0	6	20	78	14	2	1	208	316	330	647	122	291	30	8	293	85	—	—	—	—	—	—
2026	31	MLB MLE	Seattle Mariners	—	287	264	59	9	1	15	14	93	7	1	2	223	282	436	717	212	284	32	5	318	101	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Seattle Mariners	—	455	405	99	19	2	23	27	135	20	11	2	244	324	472	795	227	305	30	6	349	122	—	—	—	—	—	—
2025	30	MLB MLE	2 teams	—	257	221	46	9	0	6	20	78	14	2	1	208	316	330	647	122	291	30	8	293	85	—	—	—	—	—	—
2026	31	MLB MLE	Seattle Mariners	—	287	264	59	9	1	15	14	93	7	1	2	223	282	436	717	212	284	32	5	318	101	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	SEA	100%	290	259	62	10	1	14	19	85	10	13	3	240	315	452	767	212	297	29	7	337	115	+5	+1	-0	-3	+6	0.4
▸ 2027 — real world (MLB)
2027	32	MLB CTX	SEA	100%	121	108	25	4	0	6	8	36	4	5	1	237	313	444	757	207	294	30	7	333	115	+2	+1	-0	-1	+3	0.4
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	SEA	100%	184	164	39	6	1	9	12	55	6	6	1	231	306	433	739	201	288	30	7	326	107	+1	+1	-4	-2	+4	0.0
2028	33	MLB CTX	SEA	100%	184	164	38	6	1	8	12	55	6	6	1	229	303	425	729	197	285	30	7	322	107	+1	+1	-4	-2	+4	0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1695	1497	345	68	7	71	110	524	71	34	9	230	313	428	741	197	301	31	6	327	99	+16	+3	-17	-25	+37	1.4
/ 162G	—	A+C		—	650	574	132	26	3	27	42	201	27	13	3	230	312	427	739	197	301	31	6	327	99	+6	+1	-7	-10	+14	0.5
Career	—	MLE		—	4076	3647	865	144	30	146	220	1253	169	76	20	237	311	413	724	176	316	31	5	315	99	+18	+4	-18	-26	+39	1.8
/ 162G	—	MLE		—	650	582	138	23	5	23	35	200	27	12	3	237	311	412	723	175	317	31	5	315	99	+7	+1	-6	-9	+14	0.7

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.

2025 AAATacoma Rainiers · 38 PAwOBA .408 → .286 (−123)K% 31.6% → 36.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.58%	÷1.035	×1.200	—	—	36.61%
BB% (unintentional) /PA	5.26%	÷1.023	×0.690	—	×0.962	3.41%
HBP% /PA	2.63%	—	×0.940	—	×0.962	2.38%
Singles /BIP	30.43%	÷1.019	×0.930	—	×0.962	26.73%
Doubles /BIP	4.35%	÷0.985	×0.830	—	×0.962	3.53%
Triples /BIP	0.00%	÷1.017	×0.970	—	×0.962	0.00%
Home runs /BIP	13.04%	÷1.204	×0.700	—	×0.962	7.29%

Factors used: league row International League. Park (home-season share, regressed): HR 141, 1B 104, 2B 97, 3B 103, K 107, BB 105 — 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).

Result: wOBA .408 → .286; ISO .286 → .159; BABIP .400 → .326. 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).

2022 AAADurham Bulls · 268 PAwOBA .399 → .318 (−81)K% 27.2% → 32.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.24%	÷0.999	×1.200	—	—	32.73%
BB% (unintentional) /PA	10.07%	÷1.059	×0.690	—	×0.992	6.51%
HBP% /PA	4.48%	—	×0.940	—	×0.992	4.18%
Singles /BIP	29.22%	÷0.988	×0.930	×1.024	×0.992	27.95%
Doubles /BIP	5.19%	÷1.091	×0.830	×1.024	×0.992	4.01%
Triples /BIP	0.65%	÷1.150	×0.970	×1.024	×0.992	0.56%
Home runs /BIP	9.09%	÷1.034	×0.700	—	×0.992	6.11%

Factors used: league row International League. Park (home-season share, regressed): HR 107, 1B 98, 2B 118, 3B 130, K 100, BB 112 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.024.

Result: wOBA .399 → .318; ISO .229 → .157; BABIP .383 → .344. 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 AAAOklahoma City Dodgers · 318 PAwOBA .410 → .338 (−72)K% 23.3% → 28.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.27%	÷0.994	×1.200	—	—	28.08%
BB% (unintentional) /PA	8.49%	÷1.015	×0.690	—	×1.003	5.79%
HBP% /PA	5.66%	—	×0.940	—	×1.003	5.34%
Singles /BIP	22.73%	÷0.958	×0.930	×1.012	×1.003	22.39%
Doubles /BIP	7.07%	÷0.941	×0.830	×1.012	×1.003	6.33%
Triples /BIP	1.01%	÷0.900	×0.920	×1.012	×1.003	1.05%
Home runs /BIP	9.60%	÷1.016	×0.700	—	×1.003	6.63%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 103, 1B 92, 2B 88, 3B 80, K 99, BB 103 — 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 ×1.012.

Result: wOBA .410 → .338; ISO .276 → .201; BABIP .339 → .317. 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 AAARochester Red Wings · 138 PAwOBA .374 → .316 (−58)K% 30.4% → 36.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.43%	÷0.999	×1.200	—	—	36.56%
BB% (unintentional) /PA	4.35%	÷1.095	×0.690	—	×1.033	2.83%
HBP% /PA	3.62%	—	×0.940	—	×1.033	3.52%
Singles /BIP	29.76%	÷0.982	×0.930	×0.975	×1.033	28.38%
Doubles /BIP	7.14%	÷1.063	×0.830	×0.975	×1.033	5.62%
Triples /BIP	0.00%	÷1.150	×0.970	×0.975	×1.033	0.00%
Home runs /BIP	8.33%	÷0.958	×0.840	—	×1.033	7.55%

Factors used: league row IL. Park (home-season share, regressed): HR 92, 1B 96, 2B 113, 3B 130, K 100, BB 119 — 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 ×0.975.

Result: wOBA .374 → .316; ISO .214 → .177; BABIP .403 → .368. 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 ROKGCL Twins · 20 PAwOBA .383 → .295 (−88)K% 10.0% → 14.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.00%	÷1.000	×1.440	—	—	14.40%
BB% (unintentional) /PA	0.00%	÷1.000	×0.620	—	×0.945	0.00%
HBP% /PA	0.00%	—	×0.720	—	×0.945	0.00%
Singles /BIP	35.29%	÷1.000	×0.820	—	×0.945	27.35%
Doubles /BIP	0.00%	÷1.000	×0.720	—	×0.945	0.00%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.945	0.00%
Home runs /BIP	5.88%	÷1.000	×0.780	—	×0.945	4.34%

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 25 vs a level average of 19.5 → −5.5% on BB/HBP/hit rates (5.5 yr older than average).

Result: wOBA .383 → .295; ISO .158 → .117; BABIP .353 → .269. 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 AAChattanooga Lookouts · 551 PAwOBA .356 → .296 (−60)K% 24.9% → 31.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.86%	÷0.961	×1.220	—	—	31.58%
BB% (unintentional) /PA	6.35%	÷1.078	×0.680	—	×1.012	4.06%
HBP% /PA	4.36%	—	×0.840	—	×1.012	3.70%
Singles /BIP	24.78%	÷1.072	×0.920	×1.021	×1.012	21.96%
Doubles /BIP	5.48%	÷0.979	×0.910	×1.021	×1.012	5.25%
Triples /BIP	2.31%	÷0.900	×0.880	×1.021	×1.012	2.33%
Home runs /BIP	5.76%	÷0.975	×0.800	—	×1.012	4.79%

Factors used: league row SL. Park (home-season share, regressed): HR 95, 1B 114, 2B 96, 3B 80, K 92, BB 116 — 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 ×1.021.

Result: wOBA .356 → .296; ISO .196 → .168; BABIP .338 → .304. 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+Rancho Cucamonga Quakes · 541 PAwOBA .366 → .286 (−80)K% 22.9% → 31.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.92%	÷0.990	×1.340	—	—	31.03%
BB% (unintentional) /PA	7.58%	÷1.099	×0.710	—	×0.998	4.89%
HBP% /PA	3.51%	—	×0.790	—	×0.998	2.77%
Singles /BIP	26.84%	÷1.006	×0.910	×1.025	×0.998	24.84%
Doubles /BIP	5.93%	÷1.064	×0.820	×1.025	×0.998	4.68%
Triples /BIP	3.11%	÷1.150	×0.760	×1.025	×0.998	2.10%
Home runs /BIP	3.95%	÷1.085	×0.920	—	×0.998	3.35%

Factors used: league row CAL. Park (home-season share, regressed): HR 117, 1B 101, 2B 113, 3B 130, K 98, BB 120 — 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 ×1.025.

Result: wOBA .366 → .286; ISO .178 → .131; BABIP .372 → .326. 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 AGreat Lakes Loons · 231 PAwOBA .305 → .262 (−43)K% 20.3% → 27.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.35%	÷0.990	×1.360	—	—	27.94%
BB% (unintentional) /PA	6.49%	÷1.011	×0.690	—	—	4.43%
HBP% /PA	3.90%	—	×0.780	—	—	3.04%
Singles /BIP	20.92%	÷0.977	×0.920	×1.006	—	19.81%
Doubles /BIP	7.19%	÷0.961	×0.830	×1.006	—	6.25%
Triples /BIP	2.61%	÷0.900	×0.910	×1.006	—	2.66%
Home runs /BIP	1.31%	÷0.960	×0.800	—	—	1.09%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 92, 1B 95, 2B 92, 3B 80, K 98, 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 ×1.006.

Result: wOBA .305 → .262; ISO .125 → .111; BABIP .301 → .281. 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 — .

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Scott Hairstonlast yr '14 career totals — 9 seasons, 2,624 PA	4.0	2,624	106	36	242	297	444	-18	-16	6.0	6.6
/162	664	27	9	-4.5	-4.1	1.5	pk7: 7
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 8 projected seasons	2.8	1,829	78	40	232	310	431	-20	-24	5.3	5.4
/162	664	28	14	-7.1	-8.7	1.9	pk7: 6
#2Jerry Turner'74-'83 * career totals — 7 seasons, 1,931 PA	2.9	1,931	45	45	251*	316*	413*	-22	-11	3.0	3.4
/162	664	15	15	-7.7	-3.7	1.0	pk7: 4
#3Ricky Ledee'98-'07 * career totals — 9 seasons, 2,307 PA	3.5	2,307	63	29	233*	311*	398*	-19	-6	2.4	3.1
/162	664	18	8	-5.5	-1.8	0.7	pk7: 4
#4Nolan Reimoldlast yr '16 career totals — 8 seasons, 1,556 PA	2.3	1,556	56	18	246	323	422	-17	-27	1.6	1.9
/162	664	24	8	-7.1	-11.6	0.7	pk7: 2
#5John Mayberry Jr.last yr '15 career totals — 6 seasons, 1,506 PA	2.3	1,506	54	15	234	298	417	-6	-18	1.7	1.7
/162	664	24	7	-2.8	-8.1	0.8	pk7: 2
#6Eric Anthony'89-'97 * career totals — 9 seasons, 2,243 PA	3.4	2,243	78	24	225*	300*	410*	-22	-22	0.1	0.6
/162	664	23	7	-6.7	-6.6	0.0	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
Luke Raley (OGILVIE)	32	40	55	60	50	238/313/448	210	297	7	6	29%	6%	115	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Seth Brown 2024 · MLB	32	42→48	60→65	50	47	231/295/445	214	270	28	9	27%	8%	106	+1.8	237/294/413	176	297	24	7	28%	7%	98	+1.2	229/286/392	163	292	24	6	29%	7%	88	+0.2
●Curtis Granderson 2013 · MLB	32	43→53	64→65	52→50	53	239/326/482	243	272	32	14	26%	11%	125	+3.2	241/331/437	196	291	24	11	24%	11%	117	+2.6	240/340/459	219	272	26	7	22%	12%	127	+3.4
●Raul Mondesi 2002 · MLB	31	48→52	59→60	54→55	54	257/333/470	213	278	27	26	19%	10%	125	+3.2	250/320/448	198	270	24	18	17%	9%	116	+2.5	246/317/442	196	264	23	16	17%	9%	114	+1.8
✕Brandon Dixon 2023 · AAA	31	48	67→60	55	44	265/322/528	263	314	36	16	28%	7%	135	+3.9	228/286/395	167	325	21	13	35%	6%	91	+0.7	203/263/342	139	302	19	12	37%	6%	68	-0.6
✕Brad Miller 2022 · MLB	32	43→53	60	50	52	235/323/453	218	286	29	6	28%	11%	118	+2.6	221/299/370	149	285	19	8	28%	10%	90	+0.6	198/275/305	107	258	15	6	28%	9%	65	-0.4
●Eric Thames 2019 · MLB	32	45→54	63→65	53→45	50	242/329/486	244	306	31	9	31%	11%	127	+3.3	240/326/454	214	312	26	7	30%	10%	120	+2.8	235/328/452	217	305	27	4	30%	10%	120	+1.4
✕Garrett Jones 2013 · MLB	32	48→52	59→60	47→50	49	258/314/472	214	283	27	6	20%	8%	118	+2.7	247/302/437	190	287	22	3	22%	7%	106	+1.8	239/295/415	176	282	19	1	22%	7%	99	+0.8
✕Adolis García 2024 · MLB	31	45→49	60	51→50	46	244/309/464	220	296	29	14	28%	8%	116	+2.5	226/287/403	177	280	22	12	27%	7%	93	+0.8	215/273/372	157	269	20	11	27%	6%	81	-0.0
✕Will Venable 2014 · MLB	31	52→55	53→55	61→60	45	262/312/449	187	310	19	26	22%	6%	112	+2.2	234/292/362	128	293	13	18	24%	7%	84	+0.2	215/277/310	95	275	9	16	24%	7%	66	-0.7
✕Luis Terrero 2013 · AAA	33	52→59	58→60	53→55	46	270/335/475	204	323	26	24	25%	7%	127	+3.3	254/328/413	159	311	20	17	24%	8%	110	+2.1	248/333/397	149	305	20	15	24%	9%	107	+0.8
●David Dellucci 2006 · MLB	32	46	60→65	50	59	247/349/470	223	281	28	11	23%	13%	130	+3.5	254/336/457	203	294	23	6	21%	10%	123	+3.0	250/322/435	185	291	19	4	20%	8%	114	+1.1
✕Colby Rasmus 2018 · MLB	31	42→52	59→65	48→50	45	230/295/433	203	289	28	6	31%	9%	103	+1.5	226/286/392	166	300	20	8	30%	7%	90	+0.6	168/225/279	110	236	12	0	33%	6%	40	-0.5
✕Mitch Jones 2010 · MLB	32	39→40	62→65	50→45	40	222/277/449	227	269	31	10	31%	6%	101	+1.4	207/251/377	170	260	21	9	29%	5%	74	-0.6	177/214/330	152	218	18	7	29%	3%	47	-1.9
✕Scott Hairston 2013 · MLB	33	48→51	59→60	50	45	255/304/472	217	284	27	11	21%	6%	116	+2.5	233/284/424	191	273	25	9	25%	6%	97	+1.1	184/235/398	214	183	34	7	25%	5%	74	-0.2
✕Patrick Wisdom 2024 · MLB	32	36→45	67→70	45→50	45	217/300/475	257	276	37	9	36%	10%	115	+2.4	214/285/450	236	272	33	10	34%	8%	104	+1.6	185/249/416	231	217	34	9	34%	7%	81	-0.0
✕Alex Dickerson 2022 · MLB	32	49→56	58→60	49→45	48	257/324/462	206	292	26	4	22%	8%	120	+2.8	217/275/369	152	264	18	5	25%	7%	80	-0.1	183/235/311	127	226	14	1	25%	6%	49	-1.6
●Michael Tucker 2001 · MLB	30	51	59→55	53→55	59	264/368/488	224	295	26	20	20%	12%	141	+4.3	249/323/417	168	293	17	19	20%	9%	109	+2.0	249/330/407	159	293	15	14	20%	10%	110	+1.7
✕Justin Maxwell 2014 · MLB	30	44→45	56→60	52→60	45	231/302/425	195	307	23	15	32%	8%	103	+1.6	211/275/344	133	302	15	9	33%	7%	74	-0.5	193/255/298	105	279	13	6	34%	6%	56	-0.8
✕Jacque Jones 2007 · MLB	32	50→60	57→60	49→50	45	263/312/457	194	291	25	11	20%	6%	115	+2.4	253/306/388	135	291	13	8	17%	7%	95	+1.0	243/287/337	94	298	6	6	20%	5%	75	-0.3
✕Aaron Boone 2005 · MLB	32	49→57	54→60	55	50	254/315/438	184	270	22	21	16%	7%	111	+2.1	247/309/384	137	276	15	10	17%	6%	97	+1.1	247/312/373	127	278	14	8	16%	6%	96	+0.7

Luke Raley

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps