Gavin Lux

2B Durham Bulls

Age 29 L/R 5'11" / 190 lbs AAA HR -6%H +4% Svc 6.663 · Ctrl thru 2027 ILInjured 60-Day (D60)

Overview

AAAIL-6040-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	26	MLBLAD	487	.251/.322/.383	10	5	105	1.3
2025	27	MLBCIN	503	.269/.351/.374	5	1	107	0.2
2026	28	AAATB	119	.223/.387/.298	1	2	65	—	.206/.319/.275
2027PROJ45% MLB	29	MLBTB	56	.251/.337/.360	1	1	99	0.1
2028PROJ	30	MLBTB	237	.247/.333/.351	3	1	95	0.2

Last 3 seasons WAR 1.5 · Next 2 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service6.663First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2022-2025

Speed60

xwOBA52

Avg EV38

Bat Spd33

Barrel%27

CompsGreg Garcia (age 29) · Nick Martini (age 29) · Andrew Knapp (age 29)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 6199vR 113

AVG/OBP/SLG.251 / .337 / .360

PA56

HR1

K%23

BB%11

BABIP324

ISO120

MLB%45%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 50 / POW 40

Toolsscout grade · Statcast %ile · 2022-2025

CONTACT50

xAVG

440.247

POWER40

Barrel%

275.2

Avg EV

3888.2

Bat Spd

3369.6

EYE60

scouting grade only

SPEED55

Sprint

6027.9

Platoon Splits2024-2025 · 990 PA

vs LHP

vs RHP

Edge

113

877

—

wRC+

112

▶▶R

wOBA

208

333

▶▶R

ISO

020

131

▶▶R

BABIP

258

340

▶▶R

31.9%

21.4%

▶▶R

BB%

8.8%

10.3%

▶R

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

Status FA

MLB Debut 2019

Service 6.663 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	+0.0	$0.2M	-$0.8M
Totals		$1M		$0.2M	-$0.8M

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	18	ROK	Ogden Raptors	—	253	223	66	13	5	0	28	51	1	2	0	296	377	399	776	103	382	20	11	350	55	—	—	—	—	—	—
2017	19	A	Great Lakes Loons	—	501	434	106	14	8	7	56	88	3	27	10	244	335	362	696	118	288	18	11	312	67	—	—	—	—	—	—
2018	20	AA	Tulsa Drillers	—	120	105	34	4	1	4	14	20	1	2	2	324	408	495	904	171	370	17	12	402	115	—	—	—	—	—	—
2018	20	A+	Rancho Cucamonga Quakes	—	404	358	116	23	7	11	43	68	1	11	7	324	398	520	918	196	374	17	11	402	94	—	—	—	—	—	—
2019	21	MLB	Los Angeles Dodgers	—	82	75	18	4	1	2	7	24	0	2	0	240	305	400	705	160	327	29	9	314	105	+0	+0	+1	+2	+2	0.6
2019	21	AAA	Oklahoma City Dodgers	—	232	199	78	18	4	13	33	42	0	3	3	392	478	719	1.197	327	451	18	14	511	151	—	—	—	—	—	—
2019	21	AA	Tulsa Drillers	—	291	259	81	7	4	13	28	60	0	7	3	313	380	521	901	208	358	21	10	390	109	—	—	—	—	—	—
2020	22	MLB	Los Angeles Dodgers	—	69	63	11	2	0	3	6	19	0	1	0	175	246	349	596	175	195	28	9	267	68	-3	+0	+1	+0	+1	0.0
2021	23	MLB	Los Angeles Dodgers	—	381	335	81	12	4	7	41	83	3	4	1	242	330	364	694	122	300	22	11	314	101	+0	+0	-1	+5	+8	1.3
2021	23	AAA	Oklahoma City Dodgers	—	74	68	19	4	0	1	6	15	0	0	0	279	338	382	720	103	346	20	8	325	86	—	—	—	—	—	—
2022	24	MLB	Los Angeles Dodgers	—	471	421	116	20	7	6	47	95	0	7	2	276	348	399	747	124	341	20	10	334	120	+11	+1	+1	+2	+10	2.6
2024	26	MLB	Los Angeles Dodgers	—	487	439	110	24	2	10	44	110	2	5	2	251	322	383	704	132	312	23	9	316	105	+3	+0	-3	+2	+11	1.3
2025	27	MLB	Cincinnati Reds	—	503	446	120	28	2	5	56	114	0	1	0	269	351	374	725	105	351	23	11	329	107	+4	+0	-8	-5	+11	0.2
2026	28	AAA	Durham Bulls	—	119	94	21	4	0	1	25	29	0	2	2	223	387	298	684	74	312	24	21	329	65	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1993	1779	456	90	16	33	201	445	5	20	5	256	334	381	714	124	323	22	10	322	104	+9	+2	-9	+5	+43	5.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2016	18	ROK MLE	Ogden Raptors	—	253	234	50	9	3	0	17	73	1	2	0	214	270	278	548	64	312	29	7	249	55	—	—	—	—	—	—
2017	19	A MLE	Great Lakes Loons	—	501	452	101	12	7	6	38	121	3	27	10	223	288	321	609	97	280	24	8	267	67	—	—	—	—	—	—
2018	20	AA MLE	Tulsa Drillers	—	120	110	32	4	1	3	9	25	1	2	2	291	350	427	777	136	351	21	8	338	115	—	—	—	—	—	—
2018	20	A+ MLE	Rancho Cucamonga Quakes	—	404	372	94	17	4	9	29	95	1	11	7	253	308	392	701	140	313	24	7	307	94	—	—	—	—	—	—
2019	21	MLB MLE	Los Angeles Dodgers	—	82	75	18	4	1	2	7	24	0	2	0	240	305	400	705	160	327	29	9	323	105	+0	+0	+1	+2	+2	0.6
2019	21	AAA MLE	Oklahoma City Dodgers	—	232	207	63	14	3	10	25	53	0	3	3	304	379	546	925	242	369	23	11	391	151	—	—	—	—	—	—
2019	21	AA MLE	Tulsa Drillers	—	291	268	72	5	4	12	19	77	0	7	3	269	317	451	769	183	322	26	7	330	109	—	—	—	—	—	—
2020	22	MLB MLE	Los Angeles Dodgers	—	69	63	11	2	0	3	6	19	0	1	0	175	246	349	596	175	195	28	9	269	68	-3	+0	+1	+0	+1	0.0
2021	23	MLB MLE	Los Angeles Dodgers	—	381	338	84	13	5	7	38	83	3	4	1	249	330	379	709	130	300	22	10	317	101	+0	+0	-1	+5	+8	1.3
2021	23	AAA MLE	Oklahoma City Dodgers	—	74	70	20	4	0	1	4	18	0	0	0	286	324	386	710	100	360	24	5	296	86	—	—	—	—	—	—
2022	24	MLB MLE	Los Angeles Dodgers	—	471	421	119	21	8	6	47	95	0	7	2	283	355	413	768	131	341	20	10	345	120	+11	+1	+1	+2	+10	2.6
2024	26	MLB MLE	Los Angeles Dodgers	—	487	439	112	25	2	10	44	110	2	5	2	255	326	390	715	134	312	23	9	323	105	+3	+0	-3	+2	+11	1.3
2025	27	MLB MLE	Cincinnati Reds	—	503	446	120	28	2	5	56	114	0	1	0	269	351	374	725	105	351	23	11	326	107	+4	+0	-8	-5	+11	0.2
2026	28	AAA MLE	Durham Bulls	—	119	102	21	4	0	1	17	35	0	2	2	206	319	275	594	69	292	29	14	265	65	—	—	—	—	—	—
2016	18	ROK MLE	Ogden Raptors	—	253	234	50	9	3	0	17	73	1	2	0	214	270	278	548	64	309	29	7	249	55	—	—	—	—	—	—
2016	18	ROK RAW	Ogden Raptors	—	253	223	66	13	5	0	28	51	1	2	0	296	377	399	776	103	382	20	11	350	55	—	—	—	—	—	—
2017	19	A MLE	Great Lakes Loons	—	501	452	101	12	7	6	38	121	3	27	10	223	288	321	609	97	288	24	8	267	67	—	—	—	—	—	—
2017	19	A RAW	Great Lakes Loons	—	501	434	106	14	8	7	56	88	3	27	10	244	335	362	696	118	288	18	11	312	67	—	—	—	—	—	—
2018	20	A+ MLE	2 teams	—	524	482	125	20	5	12	38	121	2	13	9	259	316	396	712	137	322	23	7	314	99	—	—	—	—	—	—
2018	20	A+ RAW	2 teams	—	524	463	150	27	8	15	57	88	2	13	9	324	400	514	914	190	373	17	11	402	99	—	—	—	—	—	—
2019	21	AA MLE	3 teams	—	605	551	153	24	8	23	50	154	0	12	6	278	338	475	813	198	344	25	8	352	125	—	—	—	—	—	—
2019	21	AA RAW	3 teams	—	605	533	177	29	9	28	68	126	0	12	6	332	408	578	986	246	389	21	11	426	125	—	—	—	—	—	—
2020	22	MLB MLE	Los Angeles Dodgers	—	69	63	11	2	0	3	6	19	0	1	0	175	246	349	596	175	195	28	9	269	68	-3	+0	+1	+0	+1	0.0
2020	22	MLB RAW	Los Angeles Dodgers	—	69	63	11	2	0	3	6	19	0	1	0	175	246	349	596	175	195	28	9	267	68	-3	+0	+1	+0	+1	0.0
2021	23	MLB MLE	2 teams	—	455	408	101	16	5	7	42	101	3	4	1	248	322	363	685	115	311	22	9	314	98	-1	+0	-1	+5	+10	1.3
2021	23	MLB RAW	2 teams	—	455	403	100	16	4	8	47	98	3	4	1	248	331	367	698	119	308	22	10	316	98	-1	+0	-1	+5	+10	1.3
2022	24	MLB MLE	Los Angeles Dodgers	—	471	421	119	21	8	6	47	95	0	7	2	283	355	413	768	131	350	20	10	345	120	+11	+1	+1	+2	+10	2.6
2022	24	MLB RAW	Los Angeles Dodgers	—	471	421	116	20	7	6	47	95	0	7	2	276	348	399	747	124	341	20	10	334	120	+11	+1	+1	+2	+10	2.6
2024	26	MLB MLE	Los Angeles Dodgers	—	487	439	112	25	2	10	44	110	2	5	2	255	326	390	715	134	318	23	9	323	105	+3	+0	-3	+2	+11	1.3
2024	26	MLB RAW	Los Angeles Dodgers	—	487	439	110	24	2	10	44	110	2	5	2	251	322	383	704	132	312	23	9	316	105	+3	+0	-3	+2	+11	1.3
2025	27	MLB MLE	Cincinnati Reds	—	503	446	120	28	2	5	56	114	0	1	0	269	351	374	725	105	351	23	11	326	107	+4	+0	-8	-5	+11	0.2
2025	27	MLB RAW	Cincinnati Reds	—	503	446	120	28	2	5	56	114	0	1	0	269	351	374	725	105	351	23	11	329	107	+4	+0	-8	-5	+11	0.2
2026	28	AAA MLE	Durham Bulls	—	119	102	21	4	0	1	17	35	0	2	2	206	319	275	594	69	303	29	14	265	65	—	—	—	—	—	—
2026	28	AAA RAW	Durham Bulls	—	119	94	21	4	0	1	25	29	0	2	2	223	387	298	684	74	312	24	21	329	65	—	—	—	—	—	—
2016	18	ROK MLE	Ogden Raptors	—	253	233	50	9	3	0	17	73	1	2	0	215	270	279	549	64	312	29	7	249	55	—	—	—	—	—	—
2017	19	A MLE	Great Lakes Loons	—	501	455	101	12	7	6	38	121	3	27	10	222	288	319	607	97	280	24	8	267	67	—	—	—	—	—	—
2018	20	A+ MLE	2 teams	—	524	479	125	20	5	12	38	121	2	13	9	261	316	399	715	138	322	23	7	314	99	—	—	—	—	—	—
2019	21	AA MLE	3 teams	—	605	550	153	24	8	23	50	154	0	12	6	278	338	476	814	198	341	25	8	352	125	—	—	—	—	—	—
2020	22	MLB MLE	Los Angeles Dodgers	—	69	63	11	2	0	3	6	19	0	1	0	175	246	349	596	175	195	28	9	269	68	—	—	—	—	—	—
2021	23	MLB MLE	2 teams	—	455	407	101	16	5	7	42	101	3	4	1	248	322	364	686	115	309	22	9	314	98	—	—	—	—	—	—
2022	24	MLB MLE	Los Angeles Dodgers	—	471	421	119	21	8	6	47	95	0	7	2	283	355	413	768	131	341	20	10	345	120	—	—	—	—	—	—
2024	26	MLB MLE	Los Angeles Dodgers	—	487	438	112	25	2	10	44	110	2	5	2	256	326	390	716	135	312	23	9	323	105	—	—	—	—	—	—
2025	27	MLB MLE	Cincinnati Reds	—	503	442	120	28	2	5	56	114	0	1	0	271	351	378	728	106	351	23	11	326	107	—	—	—	—	—	—
2026	28	AAA MLE	Durham Bulls	—	119	101	21	4	0	1	17	35	0	2	2	208	319	277	597	69	292	29	14	265	65	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	26	MLB MLE	Los Angeles Dodgers	—	487	438	112	25	2	10	44	110	2	5	2	256	326	390	716	135	312	23	9	323	105	—	—	—	—	—	—
2025	27	MLB MLE	Cincinnati Reds	—	503	442	120	28	2	5	56	114	0	1	0	271	351	378	728	106	351	23	11	326	107	—	—	—	—	—	—
2026	28	AAA MLE	Durham Bulls	—	119	101	21	4	0	1	17	35	0	2	2	208	319	277	597	69	292	29	14	265	65	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	29	MLB MLE	TB	45%	301	263	65	14	1	4	34	70	1	3	1	249	335	360	695	111	321	23	11	315	99	-0	+0	-2	+1	+7	0.1
▸ 2027 — real world (MLB)
2027	29	MLB CTX	TB	45%	56	50	13	3	0	1	6	13	0	1	0	251	337	360	697	109	324	23	11	316	99	-0	+0	-0	+0	+1	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	30	MLB MLE	TB	100%	237	209	51	11	1	3	26	56	0	1	0	245	331	351	682	106	318	24	11	309	95	-1	+0	-3	+1	+5	0.2
2028	30	MLB CTX	TB	100%	237	209	52	11	1	3	26	56	0	1	0	247	333	351	684	104	321	24	11	310	95	-1	+0	-3	+1	+5	0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2230	1988	508	101	17	36	227	501	5	21	5	256	333	378	711	122	323	22	10	320	98	+8	+2	-12	+6	+48	5.3
/ 162G	—	A+C		—	650	579	147	29	5	10	66	146	1	6	1	254	331	373	704	119	322	22	10	320	98	+2	+1	-4	+2	+14	1.6
Career	—	MLE		—	4349	3917	991	178	41	78	395	1028	11	76	32	253	323	379	702	126	322	24	9	314	98	+8	+2	-13	+7	+51	5.6
/ 162G	—	MLE		—	650	585	149	27	6	12	59	154	2	11	5	255	325	383	708	128	325	24	9	314	98	+2	+1	-4	+2	+14	1.5

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 AAADurham Bulls · 119 PAwOBA .322 → .265 (−57)K% 24.4% → 29.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.37%	÷1.000	×1.200	—	—	29.24%
BB% (unintentional) /PA	21.01%	÷1.000	×0.690	—	×0.982	14.23%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	24.62%	÷1.000	×0.930	×1.049	×0.982	23.58%
Doubles /BIP	6.15%	÷1.000	×0.830	×1.049	×0.982	5.26%
Triples /BIP	0.00%	÷1.000	×0.970	×1.049	×0.982	0.00%
Home runs /BIP	1.54%	÷1.000	×0.700	—	×0.982	1.06%

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 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 ×1.049.

Result: wOBA .322 → .265; ISO .074 → .060; BABIP .312 → .292. 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 · 74 PAwOBA .317 → .296 (−21)K% 20.3% → 24.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.27%	÷0.994	×1.200	—	—	24.46%
BB% (unintentional) /PA	8.11%	÷1.015	×0.690	—	×1.048	5.78%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	26.42%	÷0.958	×0.930	×1.050	×1.048	28.22%
Doubles /BIP	7.55%	÷0.941	×0.830	×1.050	×1.048	7.33%
Triples /BIP	0.00%	÷0.900	×0.920	×1.050	×1.048	0.00%
Home runs /BIP	1.89%	÷1.016	×0.700	—	×1.048	1.36%

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 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 ×1.050.

Result: wOBA .317 → .296; ISO .103 → .087; BABIP .346 → .360. 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 AATulsa Drillers · 291 PAwOBA .384 → .330 (−54)K% 20.6% → 26.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.62%	÷0.954	×1.220	—	—	26.38%
BB% (unintentional) /PA	9.28%	÷1.063	×0.700	—	×1.042	6.37%
HBP% /PA	0.00%	—	×0.870	—	×1.042	0.00%
Singles /BIP	28.64%	÷0.997	×0.920	×0.950	×1.042	26.15%
Doubles /BIP	3.52%	÷1.048	×0.840	×0.950	×1.042	2.79%
Triples /BIP	2.01%	÷0.925	×0.940	×0.950	×1.042	2.02%
Home runs /BIP	6.53%	÷0.909	×0.800	—	×1.042	5.99%

Factors used: league row TL. Park (home-season share, regressed): HR 82, 1B 99, 2B 110, 3B 85, K 91, BB 113 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .384 → .330; ISO .208 → .187; BABIP .358 → .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).

2019 AAAOklahoma City Dodgers · 232 PAwOBA .497 → .391 (−107)K% 18.1% → 23.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.10%	÷1.014	×1.290	—	—	23.03%
BB% (unintentional) /PA	14.22%	÷0.993	×0.710	—	×1.050	10.68%
HBP% /PA	0.00%	—	×0.980	—	×1.050	0.00%
Singles /BIP	27.39%	÷1.048	×0.900	×0.950	×1.050	23.47%
Doubles /BIP	11.46%	÷1.012	×0.810	×0.950	×1.050	9.15%
Triples /BIP	2.55%	÷1.045	×0.810	×0.950	×1.050	1.97%
Home runs /BIP	8.28%	÷1.073	×0.780	—	×1.050	6.32%

Factors used: league row PCL. Park (home-season share, regressed): HR 115, 1B 110, 2B 102, 3B 109, K 103, BB 99 — 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 ×0.950.

Result: wOBA .497 → .391; ISO .327 → .248; BABIP .451 → .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).

2018 A+Rancho Cucamonga Quakes · 404 PAwOBA .393 → .307 (−86)K% 16.8% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.83%	÷0.957	×1.340	—	—	23.57%
BB% (unintentional) /PA	10.64%	÷1.066	×0.710	—	×1.027	7.28%
HBP% /PA	0.25%	—	×0.790	—	×1.027	0.20%
Singles /BIP	25.86%	÷1.025	×0.910	×0.969	×1.027	22.85%
Doubles /BIP	7.93%	÷1.076	×0.820	×0.969	×1.027	6.01%
Triples /BIP	2.41%	÷1.150	×0.760	×0.969	×1.027	1.59%
Home runs /BIP	3.79%	÷1.058	×0.920	—	×1.027	3.39%

Factors used: league row CAL. Park (home-season share, regressed): HR 112, 1B 105, 2B 115, 3B 130, K 91, BB 113 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.969.

Result: wOBA .393 → .307; ISO .196 → .151; BABIP .374 → .313. 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 AATulsa Drillers · 120 PAwOBA .386 → .338 (−48)K% 16.7% → 21.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.67%	÷0.964	×1.220	—	—	21.10%
BB% (unintentional) /PA	10.00%	÷1.033	×0.700	—	×1.050	7.11%
HBP% /PA	0.83%	—	×0.870	—	×1.050	0.76%
Singles /BIP	29.41%	÷0.987	×0.920	×0.989	×1.050	28.48%
Doubles /BIP	4.71%	÷0.991	×0.840	×0.989	×1.050	4.14%
Triples /BIP	1.18%	÷0.907	×0.940	×0.989	×1.050	1.27%
Home runs /BIP	4.71%	÷1.147	×0.800	—	×1.050	3.45%

Factors used: league row TL. Park (home-season share, regressed): HR 129, 1B 97, 2B 98, 3B 81, K 93, BB 107 — 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 ×0.989.

Result: wOBA .386 → .338; ISO .171 → .138; BABIP .370 → .351. 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 AGreat Lakes Loons · 501 PAwOBA .308 → .267 (−40)K% 17.6% → 24.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.56%	÷0.990	×1.360	—	—	24.13%
BB% (unintentional) /PA	11.18%	÷1.048	×0.690	—	×1.030	7.58%
HBP% /PA	0.60%	—	×0.780	—	×1.030	0.48%
Singles /BIP	22.25%	÷0.965	×0.920	×1.019	×1.030	22.26%
Doubles /BIP	4.05%	÷1.013	×0.830	×1.019	×1.030	3.48%
Triples /BIP	2.31%	÷1.013	×0.910	×1.019	×1.030	2.18%
Home runs /BIP	2.02%	÷0.970	×0.800	—	×1.030	1.72%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 94, 1B 93, 2B 103, 3B 103, K 98, BB 110 — 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 ×1.019.

Result: wOBA .308 → .267; ISO .118 → .102; BABIP .288 → .280. 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 ROKOgden Raptors · 253 PAwOBA .343 → .249 (−93)K% 20.2% → 29.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.16%	÷1.000	×1.440	—	—	29.03%
BB% (unintentional) /PA	11.07%	÷1.000	×0.610	—	×1.008	6.80%
HBP% /PA	0.40%	—	×0.720	—	×1.008	0.29%
Singles /BIP	27.91%	÷1.000	×0.820	×1.025	×1.008	23.64%
Doubles /BIP	7.56%	÷1.000	×0.720	×1.025	×1.008	5.62%
Triples /BIP	2.91%	÷1.000	×0.720	×1.025	×1.008	2.16%
Home runs /BIP	0.00%	÷1.000	×0.750	—	×1.008	0.00%

Factors used: league row PIO. 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.025.

Result: wOBA .343 → .249; ISO .103 → .072; BABIP .382 → .312. 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
#1Vance Law'80-'91 * career totals — 11 seasons, 4,298 PA	6.5	4,298	71	34	253*	327*	401*	+13	-17	10.0	11.5
/162	664	11	5	+2.0	-2.6	1.5	pk7: 13
#2Logan Forsythelast yr '19 career totals — 9 seasons, 3,502 PA	5.3	3,502	70	42	246	327	370	+5	-11	8.6	9.2
/162	664	13	8	+0.9	-2.2	1.6	pk7: 10
#3Lonnie Chisenhalllast yr '18 career totals — 8 seasons, 2,360 PA	3.6	2,360	64	20	268	320	427	-3	-9	8.0	7.9
/162	664	18	6	-0.8	-2.6	2.3	pk7: 8
#4Brock Holtlast yr '21 career totals — 10 seasons, 2,661 PA	4.0	2,661	25	41	262	332	362	+5	+3	7.4	7.8
/162	664	6	10	+1.2	+0.6	1.9	pk7: 8
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 7 projected seasons	3.5	2,293	37	22	257	332	380	+5	-9	7.3	7.3
/162	664	11	6	+1.4	-2.7	2.1	pk7: 7
#5Chris Brown'84-'89 * career totals — 6 seasons, 1,690 PA	2.5	1,690	38	21	267*	331*	418*	+6	-16	5.4	5.4
/162	664	15	8	+2.4	-6.4	2.1	pk7: 5
#6Chris Stynes'95-'04 * career totals — 9 seasons, 2,573 PA	3.9	2,573	51	49	264*	321*	387*	+1	-10	3.7	4.5
/162	664	13	13	+0.2	-2.5	1.0	pk7: 5

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
Gavin Lux (OGILVIE)	29	50	40	55	60	247/332/357	110	321	2	1	23%	11%	99	+0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Greg Garcia 2019 · MLB	29	50→55	41→40	46→50	55	240/332/333	94	294	8	7	20%	11%	94	+0.9	239/336/347	108	306	8	6	22%	12%	98	+1.2	249/364/356	107	326	6	0	22%	14%	111	+1.3
✕Nick Martini 2019 · MLB	29	53→58	40→50	51→45	52	249/327/349	99	317	7	7	22%	10%	95	+0.9	244/327/354	110	312	10	5	23%	10%	96	+1.0	229/316/358	129	286	13	1	23%	9%	91	+0.5
✕Andrew Knapp 2021 · MLB	29	49→56	45	49→40	53	233/330/364	132	320	12	5	28%	12%	100	+1.3	202/273/323	121	282	13	4	31%	8%	69	-0.9	205/271/323	118	275	12	2	29%	7%	66	-0.7
✕Vimael Machín 2023 · MLB	29	51→54	41→45	46→50	52	242/309/346	104	287	7	3	18%	8%	87	+0.4	231/290/339	108	277	10	8	19%	7%	78	-0.3	229/280/342	113	271	12	10	20%	6%	73	-0.4
✕Luis Guillorme 2024 · MLB	29	52→62	39→40	45	56	244/324/332	88	288	6	4	17%	10%	90	+0.6	219/302/300	81	278	5	8	21%	10%	74	-0.5	204/293/256	52	267	2	8	22%	11%	60	-0.6
✕Mitch Maier 2011 · MLB	29	53→56	42→50	49→50	53	253/319/361	108	296	8	9	17%	9%	94	+0.9	239/317/356	117	305	10	9	23%	10%	93	+0.8	230/317/338	108	308	10	9	26%	11%	87	+0.1
✕Eric Filia 2021 · AAA	29	52→60	41→40	48→45	54	246/316/348	102	276	7	6	14%	8%	90	+0.6	239/315/353	114	287	10	12	19%	9%	91	+0.7	243/331/336	93	287	7	11	16%	11%	92	+0.2
✕Taylor Kohlwey 2023 · AAA	29	51→57	41→45	48→50	48	244/309/345	101	307	8	10	22%	8%	87	+0.4	232/308/343	111	293	9	12	22%	9%	86	+0.3	238/325/354	116	293	9	15	20%	10%	94	+0.8
✕Eric Campbell 2016 · MLB	29	53→56	44→45	49→50	55	257/344/380	123	311	11	14	20%	10%	109	+2.0	240/324/350	110	296	10	12	21%	9%	94	+0.9	228/312/340	112	280	10	9	21%	9%	86	+0.2
✕Josh Rojas 2023 · MLB	29	52→53	45→50	53→55	54	253/329/379	126	310	12	18	22%	10%	102	+1.5	234/304/344	110	294	10	16	22%	9%	85	+0.2	220/289/316	97	278	9	15	23%	9%	74	-0.4
✕Xavier Paul 2014 · MLB	29	52→61	47→50	48→55	48	257/316/400	143	312	14	13	22%	7%	102	+1.5	211/266/337	126	278	15	6	29%	6%	70	-0.9	172/219/274	102	240	13	1	33%	5%	36	-2.0
✕Donovan Walton 2023 · MLB	29	47→55	47→50	48→45	48	235/295/383	149	262	13	8	17%	6%	91	+0.7	233/292/345	112	267	11	7	17%	7%	81	-0.1	241/312/357	116	269	13	5	16%	8%	91	+0.5
✕Larry Bigbie 2007 · MLB	29	49→56	45→50	45→50	48	241/307/359	119	309	12	8	25%	9%	89	+0.5	243/301/363	120	307	10	9	23%	8%	88	+0.4	259/309/375	117	323	7	9	21%	7%	91	+0.4
✕Jeff Fiorentino 2011 · MLB	28	51→54	44→50	51→50	50	251/310/376	125	299	11	15	20%	8%	94	+0.9	223/289/346	123	269	12	10	21%	8%	80	-0.2	212/283/335	123	253	12	8	20%	8%	74	-0.4
✕Cory Sullivan 2009 · MLB	29	52→60	41→45	50	44	247/293/354	108	304	6	13	21%	6%	82	+0.0	234/292/323	89	277	6	11	17%	8%	75	-0.5	233/298/305	73	266	4	10	13%	8%	71	-0.4
✕Mark Teahen 2011 · MLB	29	54→59	45→55	44→50	48	262/321/395	133	321	12	7	22%	8%	103	+1.5	226/286/324	98	299	8	7	25%	8%	73	-0.6	205/262/279	74	281	5	5	27%	7%	52	-1.0
✕Carlos Asuaje 2021 · MLB	29	44→54	43→45	46→45	49	215/287/328	113	262	10	6	22%	8%	76	-0.4	227/292/328	101	269	7	12	17%	7%	77	-0.3	228/293/308	80	269	3	12	15%	7%	69	-0.5
✕Brock Holt 2017 · MLB	29	55→65	42→45	51→50	51	261/325/370	110	313	8	10	19%	8%	98	+1.2	246/324/356	110	302	10	8	20%	9%	95	+1.0	262/344/371	109	329	8	7	21%	10%	107	+0.8
✕Carlos Alvarez 2017 · AAA	29	52	39→45	45	51	248/318/332	85	300	6	7	19%	8%	87	+0.4	229/297/313	84	287	5	10	21%	7%	75	-0.5	205/274/275	70	258	2	12	20%	6%	56	-0.8
●Daniel Nava 2012 · MLB	29	49→59	44→50	47→45	50	238/313/363	125	292	11	8	22%	8%	93	+0.8	253/336/379	126	305	12	6	20%	9%	105	+1.7	260/347/379	119	313	11	4	19%	9%	110	+1.7

Gavin Lux

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps