Miguel Andujar

LF San Diego Padres

Age 32 R/R 6'0" / 211 lbs MLB HR +5% Svc 7.308 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	29	AAA/INTL2 orgs	51	.245/.275/.408	1	0	64	—	.333/.368/.500
2024	29	MLBOakland Athle…	319	.285/.321/.377	4	3	99	-0.3
2025	30	MLBCIN	341	.318/.354/.470	10	1	127	1.5
2026	31	AAASD	38	.306/.324/.444	0	0	75	—	.250/.270/.361
2026	31	MLBSD	254	.259/.303/.423	5	2	105	0.8
2027PROJ	32	MLBSD	225	.258/.297/.398	4	2	98	0.1
2028PROJ	33	MLBSD	197	.250/.288/.380	4	1	89	-0.5

Last 3 seasons WAR 2.0 · Next 2 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service7.308First FA2028Options2

2027Ext / FA-deal$1M

Skills · percentileStatcast 2024-2026

Bat Spd48

Speed47

xwOBA38

Avg EV28

Barrel%17

CompsAdonis García (age 32) · Mike Kinkade (age 33) · Andy Phillips (age 32)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 10398vR 84

AVG/OBP/SLG.258 / .297 / .398

PA225

HR4

K%16

BB%4

BABIP290

ISO132

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

600.260

POWER

Barrel%

173.9

Avg EV

2887.4

Bat Spd

4871.1

SPEED

Sprint

4727.4

Platoon Splits2024-2026 · 704 PA

vs LHP

vs RHP

Edge

154

550

—

wRC+

178

◀◀L

wOBA

431

309

◀◀L

ISO

164

112

◀◀L

BABIP

445

311

◀◀L

14.3%

14.2%

—

BB%

4.5%

4.2%

◀L

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

Status FA

MLB Debut 2018

Service 7.308 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	+0.1	$0.4M	-$0.6M
Totals		$1M		$0.4M	-$0.6M

Options · projected decision
2027	MUTUAL OPT	$1.0M / $0.0M buyout	DECLINE
2028	MUTUAL OPT	$8.0M / $2.5M buyout	DECLINE

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)
2012	17	ROK	GCL Yankees	—	191	177	41	9	0	1	13	37	1	1	3	232	288	299	587	68	288	19	7	270	16	—	—	—	—	—	—
2013	18	ROK	GCL Yankees2	—	144	133	43	11	0	4	7	21	3	4	1	323	371	496	867	173	358	15	5	381	77	—	—	—	—	—	—
2014	19	A	Charleston RiverDogs	—	527	484	129	25	4	10	35	83	3	5	1	267	320	397	717	130	302	16	7	318	74	—	—	—	—	—	—
2015	20	A+	Tampa Yankees	—	520	485	118	24	5	8	29	90	3	12	1	243	290	363	653	120	282	17	6	291	52	—	—	—	—	—	—
2016	21	AA	Trenton Thunder	—	319	282	75	16	2	2	21	42	7	2	1	266	332	358	690	92	296	13	7	306	84	—	—	—	—	—	—
2016	21	A+	Tampa Yankees	—	251	230	65	10	2	10	18	30	3	1	3	283	343	474	817	191	289	12	7	361	102	—	—	—	—	—	—
2016	21	INTL	Scottsdale Scorpions	—	77	67	19	2	2	0	9	11	0	0	1	284	368	373	742	90	333	14	12	333	112	—	—	—	—	—	—
2017	22	AAA	Scranton/Wilkes-Barre RailRiders	—	250	227	72	13	1	9	17	33	2	3	0	317	370	502	872	185	333	13	7	379	115	—	—	—	—	—	—
2017	22	AA	Trenton Thunder	—	272	253	79	23	1	7	12	38	2	2	3	312	348	494	842	182	338	14	4	364	120	—	—	—	—	—	—
2017	22	INTL	Gigantes del Cibao	—	70	65	12	0	0	1	4	9	1	0	1	185	243	231	474	46	200	13	6	222	37	—	—	—	—	—	—
2018	23	MLB	New York Yankees	—	606	573	170	47	2	27	25	97	4	2	1	297	331	527	858	230	316	16	4	372	133	+24	+0	-4	+2	+13	3.6
2019	24	MLB	New York Yankees	—	49	47	6	0	0	0	1	11	0	0	0	128	146	128	273		162	22	2	125	-29	-8	+0	-2	+0	+1	-0.8
2020	25	MLB	New York Yankees	—	65	62	15	2	1	1	3	9	0	0	0	242	277	355	632	113	269	14	5	282	76	-2	+0	-3	-1	+1	-0.5
2020	25	INTL	Toros del Este	—	42	40	12	4	0	0	2	4	0	1	0	300	333	400	733	100	333	10	5	328	108	—	—	—	—	—	—
2021	26	MLB	New York Yankees	—	162	154	39	2	0	6	7	28	0	0	1	253	286	383	669	130	273	17	4	296	83	-3	-0	-2	-3	+4	-0.5
2021	26	AAA	Scranton/Wilkes-Barre RailRiders	—	63	54	18	1	0	5	7	6	0	0	0	333	410	630	1.039	296	289	10	11	435	128	—	—	—	—	—	—
2021	26	INTL	Toros del Este	—	33	31	5	0	0	0	1	6	0	0	0	161	188	161	349		192	18	3	158	-7	—	—	—	—	—	—
2022	27	MLB	Pittsburgh Pirates	—	140	132	31	5	1	1	5	27	0	4	1	235	263	311	573	76	280	19	4	252	57	-7	+0	+1	-6	+3	-0.9
2022	27	AAA	Scranton/Wilkes-Barre RailRiders	—	297	277	79	17	0	13	17	35	2	5	0	285	331	487	818	202	287	12	6	359	79	—	—	—	—	—	—
2022	27	INTL	Toros del Este	—	92	85	21	3	0	2	7	15	0	1	0	247	304	353	657	106	279	16	8	298	88	—	—	—	—	—	—
2023	28	MLB	Pittsburgh Pirates	—	90	84	21	7	0	4	6	13	0	2	0	250	300	476	776	226	254	14	7	339	118	+2	+0	-1	-7	+2	-0.4
2023	28	AAA	Indianapolis Indians	—	465	414	140	30	2	16	47	55	1	5	3	338	407	536	943	198	358	12	10	413	103	—	—	—	—	—	—
2023	28	INTL	Tigres del Licey	—	131	121	37	2	2	2	7	9	1	1	0	306	349	405	754	99	312	7	5	333	112	—	—	—	—	—	—
2024	29	MLB	Oakland Athletics	—	319	302	86	14	1	4	13	42	3	3	2	285	321	377	698	93	319	13	4	313	99	-0	-0	-5	-4	+7	-0.3
2024	29	AAA	Las Vegas Aviators	—	19	18	7	4	0	0	1	2	0	0	0	389	421	611	1.032	222	438	11	5	450	124	—	—	—	—	—	—
2024	29	INTL	Tigres del Licey	—	32	31	5	1	0	1	1	6	0	0	0	161	188	290	478	129	167	19	3	212	29	—	—	—	—	—	—
2025	30	MLB	Cincinnati Reds	—	341	321	102	17	1	10	17	49	1	1	0	318	354	470	824	153	348	14	5	363	127	+11	+0	-5	+1	+7	1.5
2025	30	AAA	Las Vegas Aviators	—	18	18	4	0	1	0	0	3	0	0	0	222	222	333	556	111	267	17	0	241	22	—	—	—	—	—	—
2026	31	MLB	San Diego Padres	—	254	239	62	20	2	5	11	38	4	2	2	259	303	423	726	163	291	15	4	321	105	+1	-0	+0	+1	+6	0.8
2026	31	AAA	El Paso Chihuahuas	—	38	36	11	5	0	0	1	4	0	0	0	306	324	444	769	139	333	11	3	330	75	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2026	1914	532	114	8	58	88	314	12	14	7	278	314	437	751	159	305	15	4	330	110	+23	+0	-20	-16	+44	3.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	17	ROK MLE	GCL Yankees	—	191	182	31	6	0	1	8	53	1	1	3	170	209	220	429	49	237	28	4	192	16	—	—	—	—	—	—
2013	18	ROK MLE	GCL Yankees2	—	144	136	34	8	0	3	4	30	3	4	1	250	287	375	662	125	288	21	3	282	77	—	—	—	—	—	—
2014	19	A MLE	Charleston RiverDogs	—	527	497	122	20	4	9	22	114	3	5	1	245	282	356	638	111	296	22	4	277	74	—	—	—	—	—	—
2015	20	A+ MLE	Tampa Yankees	—	520	492	101	21	3	8	22	126	3	12	1	205	244	309	553	104	258	24	4	245	52	—	—	—	—	—	—
2016	21	AA MLE	Trenton Thunder	—	319	288	77	15	2	2	15	51	7	2	1	267	319	354	674	87	294	16	5	292	84	—	—	—	—	—	—
2016	21	A+ MLE	Tampa Yankees	—	251	234	60	10	2	10	14	43	3	1	3	256	307	444	751	188	275	17	6	319	102	—	—	—	—	—	—
2017	22	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	250	234	69	12	1	6	10	40	2	3	0	295	329	432	761	137	326	16	4	338	115	—	—	—	—	—	—
2017	22	AA MLE	Trenton Thunder	—	272	256	79	23	1	6	9	46	2	2	3	309	337	477	814	168	340	17	3	346	120	—	—	—	—	—	—
2018	23	MLB MLE	New York Yankees	—	606	575	169	48	2	25	23	97	4	2	1	294	326	515	840	221	316	16	4	365	133	+24	+0	-4	+2	+13	3.6
2019	24	MLB MLE	New York Yankees	—	49	47	6	0	0	0	1	11	0	0	0	128	146	128	273		162	22	2	125	-29	-8	+0	-2	+0	+1	-0.8
2020	25	MLB MLE	New York Yankees	—	65	62	15	2	1	1	3	9	0	0	0	242	277	355	632	113	269	14	5	280	76	-2	+0	-3	-1	+1	-0.5
2021	26	MLB MLE	New York Yankees	—	162	154	39	2	0	6	7	28	0	0	1	253	286	383	669	130	273	17	4	292	83	-3	-0	-2	-3	+4	-0.5
2021	26	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	63	56	16	1	0	3	5	7	0	0	0	286	344	464	809	179	261	11	8	357	128	—	—	—	—	—	—
2022	27	MLB MLE	Pittsburgh Pirates	—	140	132	31	5	1	1	5	27	0	4	1	235	263	311	573	76	280	19	4	252	57	-7	+0	+1	-6	+3	-0.9
2022	27	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	297	284	69	15	0	9	10	42	2	5	0	243	274	391	664	148	252	14	3	285	79	—	—	—	—	—	—
2023	28	MLB MLE	Pittsburgh Pirates	—	90	84	21	7	0	4	6	13	0	2	0	250	300	476	776	226	254	14	7	343	118	+2	+0	-1	-7	+2	-0.4
2023	28	AAA MLE	Indianapolis Indians	—	465	433	120	24	2	10	28	68	1	5	3	277	323	411	734	134	304	15	6	321	103	—	—	—	—	—	—
2024	29	MLB MLE	Oakland Athletics	—	319	302	86	14	1	4	13	42	3	3	2	285	321	377	698	93	319	13	4	315	99	-0	-0	-5	-4	+7	-0.3
2024	29	AAA MLE	Las Vegas Aviators	—	19	18	6	3	0	0	1	2	0	0	0	333	368	500	868	167	363	11	5	351	124	—	—	—	—	—	—
2025	30	MLB MLE	Cincinnati Reds	—	341	322	101	17	1	9	16	49	1	1	0	314	348	457	805	143	348	14	5	356	127	+11	+0	-5	+1	+7	1.5
2025	30	AAA MLE	Las Vegas Aviators	—	18	18	3	0	1	0	0	4	0	0	0	167	167	278	444	111	235	22	0	201	22	—	—	—	—	—	—
2026	31	MLB MLE	San Diego Padres	—	254	241	63	21	2	5	9	38	4	2	2	261	299	427	727	166	291	15	4	323	105	+1	-0	+0	+1	+6	0.8
2026	31	AAA MLE	El Paso Chihuahuas	—	38	36	9	4	0	0	1	5	0	0	0	250	270	361	631	111	284	13	3	279	75	—	—	—	—	—	—
2012	17	ROK MLE	GCL Yankees	—	191	182	31	6	0	1	8	53	1	1	3	170	209	220	429	49	234	28	4	192	16	—	—	—	—	—	—
2012	17	ROK RAW	GCL Yankees	—	191	177	41	9	0	1	13	37	1	1	3	232	288	299	587	68	288	19	7	270	16	—	—	—	—	—	—
2013	18	ROK MLE	GCL Yankees2	—	144	136	34	8	0	3	4	30	3	4	1	250	287	375	662	125	298	21	3	282	77	—	—	—	—	—	—
2013	18	ROK RAW	GCL Yankees2	—	144	133	43	11	0	4	7	21	3	4	1	323	371	496	867	173	358	15	5	381	77	—	—	—	—	—	—
2014	19	A MLE	Charleston RiverDogs	—	527	497	122	20	4	9	22	114	3	5	1	245	282	356	638	111	300	22	4	277	74	—	—	—	—	—	—
2014	19	A RAW	Charleston RiverDogs	—	527	484	129	25	4	10	35	83	3	5	1	267	320	397	717	130	302	16	7	318	74	—	—	—	—	—	—
2015	20	A+ MLE	Tampa Yankees	—	520	492	101	21	3	8	22	126	3	12	1	205	244	309	553	104	258	24	4	245	52	—	—	—	—	—	—
2015	20	A+ RAW	Tampa Yankees	—	520	485	118	24	5	8	29	90	3	12	1	243	290	363	653	120	282	17	6	291	52	—	—	—	—	—	—
2016	21	AA MLE	3 teams	—	647	595	155	29	4	13	32	107	10	3	5	261	309	388	697	128	293	17	5	304	92	—	—	—	—	—	—
2016	21	AA RAW	3 teams	—	647	579	159	28	6	12	48	83	10	3	5	275	341	406	747	131	298	13	7	330	92	—	—	—	—	—	—
2017	22	AA MLE	3 teams	—	592	556	169	40	2	14	22	97	5	5	4	304	336	459	795	155	341	16	4	342	118	—	—	—	—	—	—
2017	22	AA RAW	3 teams	—	592	545	163	36	2	17	33	80	5	5	4	299	345	466	811	167	319	14	6	353	118	—	—	—	—	—	—
2018	23	MLB MLE	New York Yankees	—	606	575	169	48	2	25	23	97	4	2	1	294	326	515	840	221	315	16	4	365	133	+24	+0	-4	+2	+13	3.6
2018	23	MLB RAW	New York Yankees	—	606	573	170	47	2	27	25	97	4	2	1	297	331	527	858	230	316	16	4	372	133	+24	+0	-4	+2	+13	3.6
2019	24	MLB MLE	New York Yankees	—	49	47	6	0	0	0	1	11	0	0	0	128	146	128	273		162	22	2	125	-29	-8	+0	-2	+0	+1	-0.8
2019	24	MLB RAW	New York Yankees	—	49	47	6	0	0	0	1	11	0	0	0	128	146	128	273		162	22	2	125	-29	-8	+0	-2	+0	+1	-0.8
2020	25	MLB MLE	2 teams	—	107	102	25	3	2	2	5	15	0	1	0	245	280	373	653	127	271	14	5	280	76	-3	+0	-3	-1	+2	-0.5
2020	25	MLB RAW	2 teams	—	107	102	27	6	1	1	5	13	0	1	0	265	299	373	672	108	295	12	5	300	76	-3	+0	-3	-1	+2	-0.5
2021	26	MLB MLE	3 teams	—	258	240	62	3	0	10	14	40	0	0	1	258	299	396	695	137	268	16	5	310	96	-1	-0	-2	-3	+6	-0.1
2021	26	MLB RAW	3 teams	—	258	239	62	3	0	11	15	40	0	0	1	259	303	410	713	151	266	16	6	313	96	-1	-0	-2	-3	+6	-0.1
2022	27	AAA MLE	3 teams	—	529	504	119	23	1	12	19	83	2	10	1	236	267	357	624	121	259	16	4	275	72	—	—	—	—	—	—
2022	27	AAA RAW	3 teams	—	529	494	131	25	1	16	29	77	2	10	1	265	309	417	726	152	284	15	5	320	72	—	—	—	—	—	—
2023	28	AAA MLE	3 teams	—	686	637	174	38	2	18	42	101	2	8	3	273	320	424	744	151	298	15	6	325	106	—	—	—	—	—	—
2023	28	AAA RAW	3 teams	—	686	619	198	39	4	22	60	77	2	8	3	320	382	502	884	183	335	11	9	388	106	—	—	—	—	—	—
2024	29	MLB MLE	3 teams	—	370	351	101	18	1	5	15	49	3	3	2	288	322	387	710	100	322	13	4	317	101	+0	-0	-5	-4	+8	-0.1
2024	29	MLB RAW	3 teams	—	370	351	98	19	1	5	15	50	3	3	2	279	314	382	696	103	313	14	4	311	101	+0	-0	-5	-4	+8	-0.1
2025	30	MLB MLE	2 teams	—	359	340	104	17	2	9	16	53	1	1	0	306	339	447	786	141	339	15	4	348	122	+9	+0	-5	+1	+8	1.4
2025	30	MLB RAW	2 teams	—	359	339	106	17	2	10	17	52	1	1	0	313	347	463	810	150	344	14	5	357	122	+9	+0	-5	+1	+8	1.4
2026	31	MLB MLE	2 teams	—	292	277	73	25	2	5	10	43	4	2	2	264	299	422	721	159	296	15	3	317	101	+0	-0	+0	+1	+6	0.7
2026	31	MLB RAW	2 teams	—	292	275	73	25	2	5	12	42	4	2	2	265	306	425	731	160	297	14	4	322	101	+0	-0	+0	+1	+6	0.7
2012	17	ROK MLE	GCL Yankees	—	191	180	31	6	0	1	8	53	1	1	3	172	209	222	432	50	237	28	4	192	16	—	—	—	—	—	—
2013	18	ROK MLE	GCL Yankees2	—	144	136	34	8	0	3	4	30	3	4	1	250	287	375	662	125	288	21	3	282	77	—	—	—	—	—	—
2014	19	A MLE	Charleston RiverDogs	—	527	497	122	20	4	9	22	114	3	5	1	245	282	356	638	111	296	22	4	277	74	—	—	—	—	—	—
2015	20	A+ MLE	Tampa Yankees	—	520	490	101	21	3	8	22	126	3	12	1	206	244	310	554	104	258	24	4	245	52	—	—	—	—	—	—
2016	21	AA MLE	3 teams	—	647	600	155	29	4	13	32	107	10	3	5	258	309	385	694	127	286	17	5	304	92	—	—	—	—	—	—
2017	22	AA MLE	3 teams	—	592	560	169	40	2	14	22	97	5	5	4	302	336	455	792	154	333	16	4	342	118	—	—	—	—	—	—
2018	23	MLB MLE	New York Yankees	—	606	574	169	48	2	25	23	97	4	2	1	294	326	516	841	221	316	16	4	365	133	—	—	—	—	—	—
2019	24	MLB MLE	New York Yankees	—	49	48	6	0	0	0	1	11	0	0	0	125	146	125	271		162	22	2	125	-29	—	—	—	—	—	—
2020	25	MLB MLE	2 teams	—	107	101	25	3	2	2	5	15	0	1	0	248	280	376	657	129	269	14	5	280	76	—	—	—	—	—	—
2021	26	MLB MLE	3 teams	—	258	242	62	3	0	10	14	40	0	0	1	256	299	393	692	136	269	16	5	310	96	—	—	—	—	—	—
2022	27	AAA MLE	3 teams	—	529	503	119	23	1	12	19	83	2	10	1	237	267	358	625	121	261	16	4	275	72	—	—	—	—	—	—
2023	28	AAA MLE	3 teams	—	686	637	174	38	2	18	42	101	2	8	3	273	320	424	744	151	296	15	6	325	106	—	—	—	—	—	—
2024	29	MLB MLE	3 teams	—	370	349	101	18	1	5	15	49	3	3	2	289	322	390	712	100	322	13	4	317	101	—	—	—	—	—	—
2025	30	MLB MLE	2 teams	—	359	339	104	17	2	9	16	53	1	1	0	307	339	448	787	142	343	15	4	348	122	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	292	276	73	25	2	5	10	43	4	2	2	264	299	424	723	159	290	15	3	317	101	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	3 teams	—	370	349	101	18	1	5	15	49	3	3	2	289	322	390	712	100	322	13	4	317	101	—	—	—	—	—	—
2025	30	MLB MLE	2 teams	—	359	339	104	17	2	9	16	53	1	1	0	307	339	448	787	142	343	15	4	348	122	—	—	—	—	—	—
2026	31	MLB MLE	2 teams	—	292	276	73	25	2	5	10	43	4	2	2	264	299	424	723	159	290	15	3	317	101	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	SD	100%	336	315	84	22	2	7	14	54	4	3	1	264	303	407	710	143	297	16	4	313	98	-1	+0	-1	-4	+7	0.1
▸ 2027 — real world (MLB)
2027	32	MLB CTX	SD	100%	225	212	54	14	1	4	9	36	2	2	1	258	297	398	696	140	290	16	4	307	98	-1	+0	-1	-2	+5	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	SD	100%	197	185	47	12	1	3	8	33	2	1	0	255	292	388	680	133	290	17	4	300	89	-2	+0	-5	-2	+4	-0.5
2028	33	MLB CTX	SD	100%	197	185	46	11	1	4	8	33	2	1	0	250	288	380	667	130	283	17	4	295	89	-2	+0	-5	-2	+4	-0.5
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2223	2099	578	125	9	62	96	347	14	15	7	275	311	432	744	157	303	16	4	327	92	+21	+0	-25	-18	+48	2.6
/ 162G	—	A+C		—	650	614	170	37	3	18	28	101	4	4	2	277	313	435	748	158	305	16	4	327	92	+6	+0	-7	-5	+14	0.8
Career	—	MLE		—	6299	5928	1548	326	27	141	272	1088	45	60	26	261	299	397	695	135	296	17	4	305	92	+20	+0	-26	-21	+53	2.7
/ 162G	—	MLE		—	650	612	161	34	3	15	28	112	5	6	3	263	301	402	703	139	298	17	4	305	92	+5	+0	-7	-6	+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.

2026 AAAEl Paso Chihuahuas · 38 PAwOBA .330 → .279 (−51)K% 10.5% → 12.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.53%	÷1.000	×1.200	—	—	12.63%
BB% (unintentional) /PA	2.63%	÷1.000	×0.690	—	×0.962	1.75%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	18.75%	÷1.000	×0.930	—	×0.962	16.77%
Doubles /BIP	15.62%	÷1.000	×0.830	—	×0.962	12.48%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.962	0.00%
Home runs /BIP	0.00%	÷1.000	×0.700	—	×0.962	0.00%

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 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average).

Result: wOBA .330 → .279; ISO .139 → .113; BABIP .333 → .284. 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 AAALas Vegas Aviators · 18 PAwOBA .234 → .201 (−33)K% 16.7% → 19.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.67%	÷1.027	×1.200	—	—	19.48%
BB% (unintentional) /PA	0.00%	÷0.970	×0.690	—	×0.972	0.00%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	20.00%	÷1.052	×0.930	—	×0.972	17.18%
Doubles /BIP	0.00%	÷0.988	×0.830	—	×0.972	0.00%
Triples /BIP	6.67%	÷1.000	×0.970	—	×0.972	6.29%
Home runs /BIP	0.00%	÷1.183	×0.700	—	×0.972	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 137, 1B 110, 2B 98, 3B 100, K 105, BB 94 — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average).

Result: wOBA .234 → .201; ISO .111 → .101; BABIP .267 → .235. 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 AAALas Vegas Aviators · 19 PAwOBA .437 → .351 (−86)K% 10.5% → 12.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.53%	÷1.022	×1.200	—	—	12.36%
BB% (unintentional) /PA	5.26%	÷0.952	×0.690	—	×0.982	3.75%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	18.75%	÷0.974	×0.930	—	×0.982	17.58%
Doubles /BIP	25.00%	÷1.088	×0.830	—	×0.982	18.73%
Triples /BIP	0.00%	÷1.150	×0.970	—	×0.982	0.00%
Home runs /BIP	0.00%	÷1.001	×0.700	—	×0.982	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 100, 1B 95, 2B 118, 3B 130, K 104, BB 90 — 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).

Result: wOBA .437 → .351; ISO .222 → .166; BABIP .438 → .363. 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 AAAIndianapolis Indians · 465 PAwOBA .402 → .321 (−81)K% 11.8% → 14.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.83%	÷0.967	×1.200	—	—	14.68%
BB% (unintentional) /PA	9.46%	÷1.056	×0.690	—	×0.992	6.14%
HBP% /PA	0.22%	—	×0.940	—	×0.992	0.20%
Singles /BIP	25.63%	÷1.004	×0.930	×0.967	×0.992	22.79%
Doubles /BIP	8.36%	÷1.013	×0.830	×0.967	×0.992	6.57%
Triples /BIP	0.56%	÷1.150	×0.970	×0.967	×0.992	0.45%
Home runs /BIP	4.46%	÷1.095	×0.700	—	×0.992	2.83%

Factors used: league row International League. Park (home-season share, regressed): HR 119, 1B 101, 2B 103, 3B 130, K 93, BB 111 — 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 ×0.967.

Result: wOBA .402 → .321; ISO .198 → .142; BABIP .358 → .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).

2022 AAAScranton/Wilkes-Barre RailRiders · 297 PAwOBA .349 → .285 (−63)K% 11.8% → 14.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.78%	÷1.001	×1.200	—	—	14.12%
BB% (unintentional) /PA	5.39%	÷1.066	×0.690	—	×1.003	3.50%
HBP% /PA	0.67%	—	×0.940	—	×1.003	0.63%
Singles /BIP	20.25%	÷1.047	×0.930	×1.018	×1.003	18.36%
Doubles /BIP	7.02%	÷0.988	×0.830	×1.018	×1.003	6.02%
Triples /BIP	0.00%	÷1.000	×0.970	×1.018	×1.003	0.00%
Home runs /BIP	5.37%	÷1.006	×0.700	—	×1.003	3.75%

Factors used: league row International League. Park (home-season share, regressed): HR 101, 1B 109, 2B 98, 3B 100, K 100, BB 113 — 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 ×1.018.

Result: wOBA .349 → .285; ISO .202 → .151; BABIP .287 → .252. 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 AAAScranton/Wilkes-Barre RailRiders · 63 PAwOBA .437 → .357 (−80)K% 9.5% → 11.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.52%	÷0.993	×1.200	—	—	11.51%
BB% (unintentional) /PA	11.11%	÷0.973	×0.690	—	×1.018	8.02%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	25.00%	÷0.974	×0.930	×0.972	×1.018	23.61%
Doubles /BIP	2.08%	÷0.915	×0.830	×0.972	×1.018	1.87%
Triples /BIP	0.00%	÷1.150	×0.920	×0.972	×1.018	0.00%
Home runs /BIP	10.42%	÷1.149	×0.700	—	×1.018	6.46%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 130, 1B 95, 2B 83, 3B 130, K 99, BB 95 — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.972.

Result: wOBA .437 → .357; ISO .296 → .200; BABIP .289 → .261. 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 AATrenton Thunder · 272 PAwOBA .360 → .346 (−14)K% 14.0% → 16.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.97%	÷1.007	×1.220	—	—	16.93%
BB% (unintentional) /PA	4.41%	÷0.979	×0.700	—	×1.042	3.29%
HBP% /PA	0.74%	—	×0.850	—	×1.042	0.65%
Singles /BIP	22.33%	÷1.020	×0.970	×1.035	×1.042	22.89%
Doubles /BIP	10.70%	÷0.936	×0.860	×1.035	×1.042	10.59%
Triples /BIP	0.47%	÷1.150	×0.950	×1.035	×1.042	0.41%
Home runs /BIP	3.26%	÷0.960	×0.780	—	×1.042	2.76%

Factors used: league row EL. Park (home-season share, regressed): HR 92, 1B 104, 2B 87, 3B 130, K 101, BB 96 — 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 ×1.035.

Result: wOBA .360 → .346; ISO .182 → .168; BABIP .338 → .340. 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 AAAScranton/Wilkes-Barre RailRiders · 250 PAwOBA .373 → .338 (−35)K% 13.2% → 15.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.20%	÷0.995	×1.200	—	—	15.92%
BB% (unintentional) /PA	6.40%	÷1.105	×0.690	—	×1.050	4.20%
HBP% /PA	0.80%	—	×0.940	—	×1.050	0.79%
Singles /BIP	25.26%	÷0.980	×0.930	×1.013	×1.050	25.50%
Doubles /BIP	6.70%	÷0.951	×0.830	×1.013	×1.050	6.22%
Triples /BIP	0.52%	÷1.150	×0.970	×1.013	×1.050	0.46%
Home runs /BIP	4.64%	÷1.247	×0.840	—	×1.050	3.28%

Factors used: league row IL. Park (home-season share, regressed): HR 149, 1B 96, 2B 90, 3B 130, K 99, BB 121 — 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 ×1.013.

Result: wOBA .373 → .338; ISO .185 → .148; BABIP .333 → .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).

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
#1Reed Johnsonlast yr '14 career totals — 12 seasons, 3,968 PA	6.0	3,968	65	41	280	336	406	-30	-16	10.5	11.0
/162	664	11	7	-5.1	-2.6	1.8	pk7: 11
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 10 projected seasons	3.6	2,399	66	17	280	312	439	-26	-19	6.3	6.6
/162	664	18	5	-7.1	-5.3	1.7	pk7: 7
#2Ryan Raburnlast yr '17 career totals — 11 seasons, 2,703 PA	4.1	2,703	93	15	255	318	439	-20	-40	5.0	6.6
/162	664	23	4	-4.9	-9.9	1.2	pk7: 8
#3Matt Diazlast yr '12 career totals — 8 seasons, 1,999 PA	3.0	1,999	44	33	294	341	432	-21	-19	5.8	6.3
/162	664	15	11	-7.1	-6.2	1.9	pk7: 7
#4Mark Carreon'87-'96 * career totals — 8 seasons, 2,190 PA	3.3	2,190	69	12	270*	321*	452*	-26	-18	4.6	5.0
/162	664	21	4	-7.8	-5.5	1.4	pk7: 5
#5Dwight Smith'89-'96 * career totals — 8 seasons, 1,987 PA	3.0	1,987	46	42	270*	330*	442*	-16	-2	4.5	4.9
/162	664	15	14	-5.4	-0.5	1.5	pk7: 5
#6Terry Whitfield'74-'86 * career totals — 7 seasons, 2,106 PA	3.2	2,106	33	18	274*	327*	421*	-21	-6	4.2	4.4
/162	664	10	6	-6.6	-1.8	1.3	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
Miguel Andujar (OGILVIE)	32	—	—	—	—	262/300/404	142	297	4	2	16%	4%	98	+0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Adonis García 2017 · MLB	32	53→54	48→50	45→50	42	264/295/401	137	294	16	6	17%	3%	95	+0.9	240/282/366	126	271	15	11	17%	4%	82	-0.0	207/253/301	95	236	12	15	18%	4%	56	-0.7
✕Mike Kinkade 2006 · MLB	33	47→57	48→45	44→45	44	237/310/384	147	270	15	8	18%	5%	97	+1.1	255/319/378	123	298	11	8	18%	5%	99	+1.3	276/337/388	112	320	9	7	16%	4%	105	+1.0
✕Andy Phillips 2009 · MLB	32	51→55	48→55	44→40	49	255/308/393	138	283	15	5	16%	7%	97	+1.1	247/296/376	129	278	15	7	17%	6%	89	+0.5	255/291/361	106	285	12	2	15%	4%	82	-0.0
✕Rolando Acosta 2015 · AAA	32	53→60	44→50	43→45	46	257/308/370	113	295	12	8	17%	5%	93	+0.8	224/284/317	93	261	9	7	17%	6%	72	-0.7	208/270/282	74	242	7	4	17%	5%	56	-0.9
✕Danny Bautista 2004 · MLB	32	56→58	46→50	48→45	48	275/324/410	135	307	13	9	15%	6%	107	+1.9	271/320/396	125	297	12	8	13%	6%	103	+1.5	283/328/396	114	306	11	6	11%	6%	106	+1.7
✕Santiago Gonzalez 2015 · AAA	32	48→58	46→50	46→55	42	236/268/364	128	253	13	7	14%	3%	76	-0.4	227/269/323	96	255	8	10	14%	4%	67	-1.1	226/267/298	72	258	4	9	14%	4%	57	-0.6
✕Joey Meneses 2024 · MLB	32	53→56	49→55	46→40	44	265/309/414	149	315	17	2	22%	6%	103	+1.5	234/283/353	119	275	12	3	19%	6%	79	-0.2	224/273/331	107	259	10	1	18%	5%	69	-0.8
✕Angel Berroa 2009 · MLB	32	47→56	44→50	44→50	44	231/276/344	113	261	11	5	17%	5%	74	-0.5	220/263/332	112	256	11	7	18%	4%	67	-1.1	244/286/384	140	291	15	5	21%	4%	86	+0.2
✕Raul Gonzalez 2006 · MLB	32	49→58	47→45	43→50	50	246/298/386	140	272	14	7	16%	7%	92	+0.7	246/298/357	111	281	10	6	16%	7%	85	+0.2	268/327/373	105	306	10	12	15%	7%	97	+0.5
✕Jesse Gutierrez 2010 · AAA	32	51→55	47→55	43→30	46	253/306/388	135	283	15	3	17%	6%	96	+1.0	259/314/425	166	280	20	3	16%	6%	107	+1.9	260/316/434	173	275	22	0	15%	6%	108	+1.1
✕Abraham Valencia 2011 · AAA	31	51→50	46→45	44→45	44	251/307/380	129	279	14	7	16%	5%	95	+0.9	235/291/363	128	269	15	5	19%	5%	85	+0.2	232/291/340	108	275	13	2	20%	4%	76	-0.2
✕Kevan Smith 2020 · MLB	32	53→54	44→50	49→40	48	259/314/378	119	292	12	5	16%	6%	97	+1.1	229/296/348	119	289	11	7	23%	8%	83	+0.1	162/217/192	30	235	0	0	29%	7%	17	-0.8
✕Jose Iglesias 2022 · MLB	32	56→64	45	45→50	44	277/313/404	127	306	12	6	14%	4%	101	+1.4	273/312/386	113	311	9	6	15%	4%	97	+1.1	284/321/388	105	325	8	5	15%	4%	101	+0.8
✕Corban Joseph 2021 · MLB	32	52→57	46→50	48→45	48	255/302/392	137	279	13	5	14%	6%	95	+1.0	238/293/359	121	276	11	8	17%	7%	84	+0.1	242/295/335	94	271	7	0	13%	7%	77	-0.1
✕Matt McBride 2017 · MLB	32	45→52	46→55	45→40	44	224/269/357	133	259	13	5	20%	5%	75	-0.5	205/258/364	159	238	19	4	23%	6%	73	-0.6	181/236/353	172	199	22	1	23%	5%	61	-0.6
✕Andy Ibáñez 2024 · MLB	31	50→56	49→50	48→45	48	249/302/400	151	280	16	6	18%	7%	97	+1.1	238/292/365	127	281	13	8	20%	6%	85	+0.2	228/279/331	103	270	11	8	19%	5%	72	-0.4
✕Mike Cervenak 2009 · AAA	32	51→58	44→45	44→40	39	249/274/364	115	281	11	5	16%	2%	78	-0.3	240/271/349	109	267	10	4	14%	3%	74	-0.6	256/299/370	115	282	13	3	14%	5%	87	+0.3
✕Jorge Luis Valle 2007 · AAA	32	57→64	46→45	40	43	279/314/412	133	307	13	3	14%	4%	104	+1.6	261/292/363	102	298	7	4	15%	3%	84	+0.1	260/285/341	82	301	3	2	14%	2%	76	-0.2
✕Matt Hague 2017 · MLB	31	55→62	44→45	46→45	49	270/328/391	121	307	12	6	16%	7%	105	+1.7	237/298/332	95	275	9	7	16%	7%	80	-0.2	232/295/314	82	268	7	5	16%	8%	73	-0.4
✕Michael A. Taylor 2023 · MLB	32	50→54	46→55	46→60	45	248/305/370	122	314	15	10	25%	7%	91	+0.7	222/280/376	154	300	20	16	31%	7%	84	+0.1	201/260/365	164	275	21	20	34%	7%	75	-0.3

Miguel Andujar

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps