Aaron Judge

RF New York Yankees

Age 35 R/R 6'7" / 282 lbs MLB HR +14% Svc 10.297 · Ctrl thru 2031

Overview

MLB40-MANExtFA 2032

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	32	MLBNYY	704	.322/.459/.701	58	10	197	9.9
2025	33	MLBNYY	679	.331/.461/.688	53	12	182	7.8
2026	34	MLBNYY	285	.241/.359/.511	18	5	129	1.2
2027PROJ	35	MLBNYY	361	.292/.395/.630	29	6	175	4.0
2028PROJ	36	MLBNYY	310	.279/.382/.600	24	2	164	2.4
2029PROJ	37	MLBNYY	250	.267/.370/.569	18	1	153	1.4

Last 3 seasons WAR 18.9 · Next 3 projected WAR 7.8Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2031Service10.297First FA2032NTC

2027Ext$40M2028Ext$40M2029Ext$40M2030Ext$40M2031Ext$40M

Skills · percentileStatcast 2024-2026

Barrel%90

xwOBA90

Avg EV90

Bat Spd90

Speed33

CompsJeff Bagwell (age 34) · Sammy Sosa (age 35) · José Bautista (age 35)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 179175vR 162

AVG/OBP/SLG.292 / .395 / .630

PA361

HR29

SB6

K%26

BB%13

BABIP325

ISO339

MLB%100%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$93M ctrl surplus

Tools · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

900.295

POWER

Barrel%

9025.0

Avg EV

9095.5

Bat Spd

9075.7

SPEED

Sprint

3326.7

Platoon Splits2024-2026 · 1497 PA

vs LHP

vs RHP

Edge

385

1112

—

wRC+

226

197

◀L

wOBA

502

460

◀L

ISO

440

341

◀◀L

BABIP

345

368

▶R

24.4%

24.2%

—

BB%

16.6%

13.9%

◀◀L

Contract CONFIRMED · hand-curated extension

Status FA

MLB Debut 2016

Service 10.297 yrs.days

Team Control Through 2031

First FA Year 2032

NTC

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$40M	+4.0	$44M	+$4M
2028	Ext	$40M	+2.4	$18M	-$18M
2029	Ext	$40M	+1.4	$10M	-$23M
2030	Ext	$40M	+0.6	$2M	-$27M
2031	Ext	beyond projection horizon · no WAR estimate
Totals		$160M		$73M	-$64M

Underwater contract
Projected production over the remaining contract is worth -$64M less than the salary owed. Most often this reflects an aging-curve fade that was visible at signing — the team paid a premium for the early years.

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)
2014	22	A+	Tampa Yankees	—	285	233	66	9	2	8	50	72	1	0	0	283	412	442	854	159	377	25	18	385	93	—	—	—	—	—	—
2014	22	A	Charleston RiverDogs	—	278	234	78	15	2	9	39	59	2	1	0	333	433	530	963	197	408	21	14	421	117	—	—	—	—	—	—
2014	22	INTL	Scottsdale Scorpions	—	106	90	25	5	0	4	13	22	2	0	0	278	381	467	848	189	323	21	12	375	140	—	—	—	—	—	—
2015	23	AAA	Scranton/Wilkes-Barre RailRiders	—	260	228	51	10	0	8	29	74	0	6	2	224	311	373	684	149	289	28	11	306	61	—	—	—	—	—	—
2015	23	AA	Trenton Thunder	—	280	250	71	16	3	12	24	70	3	1	0	284	354	516	870	232	345	25	9	377	94	—	—	—	—	—	—
2016	24	MLB	New York Yankees	—	95	84	15	2	0	4	9	42	1	0	1	179	266	345	611	167	282	44	9	274	68	-4	-0	+1	-5	+2	-0.6
2016	24	AAA	Scranton/Wilkes-Barre RailRiders	—	410	352	95	18	1	19	47	98	8	5	0	270	369	489	857	219	319	24	11	377	98	—	—	—	—	—	—
2017	25	MLB	New York Yankees	—	678	542	154	24	3	52	127	208	5	9	4	284	424	627	1.052	343	357	31	19	448	175	+61	+0	+6	-7	+15	7.6
2018	26	MLB	New York Yankees	—	498	413	115	22	0	27	76	152	4	6	3	278	396	528	923	249	368	31	15	402	151	+30	+0	+3	-5	+11	4.0
2019	27	MLB	New York Yankees	—	447	378	103	18	1	27	64	141	3	3	2	272	381	540	921	267	360	32	14	401	148	+26	-0	+4	-5	+10	3.5
2019	27	AAA	Scranton/Wilkes-Barre RailRiders	—	19	16	2	0	0	1	3	7	0	0	0	125	263	312	576	188	125	37	16	267	15	—	—	—	—	—	—
2020	28	MLB	New York Yankees	—	114	101	26	3	0	9	10	32	2	0	1	257	333	554	888	297	283	28	9	383	139	+5	-0	+1	-1	+2	0.8
2021	29	MLB	New York Yankees	—	633	550	158	24	0	39	75	158	3	6	1	287	376	544	919	256	332	25	12	399	149	+37	+1	-2	-7	+14	4.4
2022	30	MLB	New York Yankees	—	696	570	177	28	0	62	111	175	6	16	3	311	425	686	1.111	375	340	25	16	468	182	+68	+2	+2	+2	+15	9.2
2023	31	MLB	New York Yankees	—	458	367	98	16	0	37	88	130	0	3	1	267	409	613	1.022	346	300	28	19	436	165	+35	+0	-1	-5	+10	4.0
2024	32	MLB	New York Yankees	—	704	559	180	36	1	58	133	171	9	10	0	322	459	701	1.160	379	367	24	19	490	197	+82	+2	-5	+3	+15	9.9
2025	33	MLB	New York Yankees	—	679	541	179	30	2	53	124	160	7	12	5	331	461	688	1.149	357	376	24	18	484	182	+66	+0	+2	-7	+15	7.8
2026	34	MLB	New York Yankees	—	285	237	57	10	0	18	43	85	2	5	3	241	359	511	870	270	289	30	15	379	129	+10	-0	-1	-3	+6	1.2
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	5287	4342	1262	213	7	386	860	1454	42	70	24	291	412	610	1.022	319	345	28	16	437	182	+517	+4	+11	-41	+115	61.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	22	A+ MLE	Tampa Yankees	—	285	245	55	8	2	7	38	107	1	0	0	224	331	359	690	135	359	38	13	306	93	—	—	—	—	—	—
2014	22	A MLE	Charleston RiverDogs	—	278	249	70	11	2	8	24	81	2	1	0	281	349	438	787	157	370	29	9	341	117	—	—	—	—	—	—
2015	23	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	260	239	47	9	0	8	18	90	0	6	2	197	253	335	588	138	266	35	7	258	61	—	—	—	—	—	—
2015	23	AA MLE	Trenton Thunder	—	280	259	64	14	2	8	15	90	3	1	0	247	296	409	705	162	336	32	5	307	94	—	—	—	—	—	—
2016	24	MLB MLE	New York Yankees	—	95	84	15	2	0	4	9	42	1	0	1	179	266	345	611	167	282	44	9	269	68	-4	-0	+1	-5	+2	-0.6
2016	24	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	410	364	83	14	1	16	35	118	8	5	0	228	310	404	713	176	285	29	9	313	98	—	—	—	—	—	—
2017	25	MLB MLE	New York Yankees	—	678	553	151	24	3	49	116	208	5	9	4	273	404	593	997	320	357	31	17	428	175	+61	+0	+6	-7	+15	7.6
2018	26	MLB MLE	New York Yankees	—	498	416	113	22	0	25	73	152	4	6	3	272	385	505	890	233	368	31	15	391	151	+30	+0	+3	-5	+11	4.0
2019	27	MLB MLE	New York Yankees	—	447	383	101	18	1	25	60	141	3	3	2	264	368	512	879	248	360	32	13	388	148	+26	-0	+4	-5	+10	3.5
2019	27	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	19	17	2	0	0	1	2	8	0	0	0	118	211	294	505	176	111	42	11	191	15	—	—	—	—	—	—
2020	28	MLB MLE	New York Yankees	—	114	102	25	3	0	8	10	32	2	0	1	245	325	510	834	265	283	28	9	373	139	+5	-0	+1	-1	+2	0.8
2021	29	MLB MLE	New York Yankees	—	633	552	156	24	0	37	73	158	3	6	1	283	369	527	897	245	332	25	12	389	149	+37	+1	-2	-7	+14	4.4
2022	30	MLB MLE	New York Yankees	—	696	593	173	28	0	58	92	175	6	16	3	292	392	632	1.025	341	340	25	13	438	182	+68	+2	+2	+2	+15	9.2
2023	31	MLB MLE	New York Yankees	—	458	376	96	16	0	35	79	130	0	3	1	255	385	577	962	322	300	28	17	412	165	+35	+0	-1	-5	+10	4.0
2024	32	MLB MLE	New York Yankees	—	704	580	176	36	1	54	113	171	9	10	0	303	425	648	1.073	345	367	24	16	460	197	+82	+2	-5	+3	+15	9.9
2025	33	MLB MLE	New York Yankees	—	679	577	176	30	2	50	88	160	7	12	5	305	403	624	1.027	319	376	24	13	438	182	+66	+0	+2	-7	+15	7.8
2026	34	MLB MLE	New York Yankees	—	285	244	56	10	0	17	38	85	2	5	3	230	338	480	818	250	289	30	13	359	129	+10	-0	-1	-3	+6	1.2
2014	22	A+ MLE	3 teams	—	669	586	147	22	4	18	73	224	5	1	0	251	339	394	733	143	370	33	11	323	105	—	—	—	—	—	—
2014	22	A+ RAW	3 teams	—	669	557	169	29	4	21	102	153	5	1	0	303	416	483	899	180	381	23	15	398	105	—	—	—	—	—	—
2015	23	AA MLE	2 teams	—	540	497	111	23	2	16	34	180	3	7	2	223	277	374	651	151	309	33	6	283	78	—	—	—	—	—	—
2015	23	AA RAW	2 teams	—	540	478	122	26	3	20	53	144	3	7	2	255	333	448	781	192	319	27	10	343	78	—	—	—	—	—	—
2016	24	AAA MLE	2 teams	—	505	448	98	16	1	20	44	160	9	5	1	219	301	393	694	174	287	32	9	305	92	—	—	—	—	—	—
2016	24	AAA RAW	2 teams	—	505	436	110	20	1	23	56	140	9	5	1	252	349	461	810	209	314	28	11	358	92	—	—	—	—	—	—
2017	25	MLB MLE	New York Yankees	—	678	553	151	24	3	49	116	208	5	9	4	273	404	593	997	320	340	31	17	428	175	+61	+0	+6	-7	+15	7.6
2017	25	MLB RAW	New York Yankees	—	678	542	154	24	3	52	127	208	5	9	4	284	424	627	1.052	343	357	31	19	448	175	+61	+0	+6	-7	+15	7.6
2018	26	MLB MLE	New York Yankees	—	498	416	113	22	0	25	73	152	4	6	3	272	385	505	890	233	361	31	15	391	151	+30	+0	+3	-5	+11	4.0
2018	26	MLB RAW	New York Yankees	—	498	413	115	22	0	27	76	152	4	6	3	278	396	528	923	249	368	31	15	402	151	+30	+0	+3	-5	+11	4.0
2019	27	MLB MLE	2 teams	—	466	400	103	18	1	26	62	149	3	3	2	258	361	502	864	245	341	32	13	380	143	+24	-0	+4	-5	+10	3.4
2019	27	MLB RAW	2 teams	—	466	394	105	18	1	28	67	148	3	3	2	266	376	530	907	264	352	32	14	396	143	+24	-0	+4	-5	+10	3.4
2020	28	MLB MLE	New York Yankees	—	114	102	25	3	0	8	10	32	2	0	1	245	325	510	834	265	274	28	9	373	139	+5	-0	+1	-1	+2	0.8
2020	28	MLB RAW	New York Yankees	—	114	101	26	3	0	9	10	32	2	0	1	257	333	554	888	297	283	28	9	383	139	+5	-0	+1	-1	+2	0.8
2021	29	MLB MLE	New York Yankees	—	633	552	156	24	0	37	73	158	3	6	1	283	369	527	897	245	329	25	12	389	149	+37	+1	-2	-7	+14	4.4
2021	29	MLB RAW	New York Yankees	—	633	550	158	24	0	39	75	158	3	6	1	287	376	544	919	256	332	25	12	399	149	+37	+1	-2	-7	+14	4.4
2022	30	MLB MLE	New York Yankees	—	696	593	173	28	0	58	92	175	6	16	3	292	392	632	1.025	341	315	25	13	438	182	+68	+2	+2	+2	+15	9.2
2022	30	MLB RAW	New York Yankees	—	696	570	177	28	0	62	111	175	6	16	3	311	425	686	1.111	375	340	25	16	468	182	+68	+2	+2	+2	+15	9.2
2023	31	MLB MLE	New York Yankees	—	458	376	96	16	0	35	79	130	0	3	1	255	385	577	962	322	285	28	17	412	165	+35	+0	-1	-5	+10	4.0
2023	31	MLB RAW	New York Yankees	—	458	367	98	16	0	37	88	130	0	3	1	267	409	613	1.022	346	300	28	19	436	165	+35	+0	-1	-5	+10	4.0
2024	32	MLB MLE	New York Yankees	—	704	580	176	36	1	54	113	171	9	10	0	303	425	648	1.073	345	342	24	16	460	197	+82	+2	-5	+3	+15	9.9
2024	32	MLB RAW	New York Yankees	—	704	559	180	36	1	58	133	171	9	10	0	322	459	701	1.160	379	367	24	19	490	197	+82	+2	-5	+3	+15	9.9
2025	33	MLB MLE	New York Yankees	—	679	577	176	30	2	50	88	160	7	12	5	305	403	624	1.027	319	337	24	13	438	182	+66	+0	+2	-7	+15	7.8
2025	33	MLB RAW	New York Yankees	—	679	541	179	30	2	53	124	160	7	12	5	331	461	688	1.149	357	376	24	18	484	182	+66	+0	+2	-7	+15	7.8
2026	34	MLB MLE	New York Yankees	—	285	244	56	10	0	17	38	85	2	5	3	230	338	480	818	250	273	30	13	359	129	+10	-0	-1	-3	+6	1.2
2026	34	MLB RAW	New York Yankees	—	285	237	57	10	0	18	43	85	2	5	3	241	359	511	870	270	289	30	15	379	129	+10	-0	-1	-3	+6	1.2
2014	22	A+ MLE	3 teams	—	669	586	147	22	4	18	73	224	5	1	0	251	339	394	733	143	364	33	11	323	105	—	—	—	—	—	—
2015	23	AA MLE	2 teams	—	540	498	111	23	2	16	34	180	3	7	2	223	277	373	651	151	302	33	6	283	78	—	—	—	—	—	—
2016	24	AAA MLE	2 teams	—	505	447	98	16	1	20	44	160	9	5	1	219	301	394	695	174	284	32	9	305	92	—	—	—	—	—	—
2017	25	MLB MLE	New York Yankees	—	678	552	151	24	3	49	116	208	5	9	4	274	404	594	998	321	357	31	17	428	175	—	—	—	—	—	—
2018	26	MLB MLE	New York Yankees	—	498	418	113	22	0	25	73	152	4	6	3	270	385	502	888	232	368	31	15	391	151	—	—	—	—	—	—
2019	27	MLB MLE	2 teams	—	466	398	103	18	1	26	62	149	3	3	2	259	361	505	866	246	350	32	13	380	143	—	—	—	—	—	—
2020	28	MLB MLE	New York Yankees	—	114	101	25	3	0	8	10	32	2	0	1	248	325	515	839	267	283	28	9	373	139	—	—	—	—	—	—
2021	29	MLB MLE	New York Yankees	—	633	552	156	24	0	37	73	158	3	6	1	283	369	527	897	245	332	25	12	389	149	—	—	—	—	—	—
2022	30	MLB MLE	New York Yankees	—	696	593	173	28	0	58	92	175	6	16	3	292	392	632	1.025	341	340	25	13	438	182	—	—	—	—	—	—
2023	31	MLB MLE	New York Yankees	—	458	376	96	16	0	35	79	130	0	3	1	255	385	577	962	322	300	28	17	412	165	—	—	—	—	—	—
2024	32	MLB MLE	New York Yankees	—	704	576	176	36	1	54	113	171	9	10	0	306	425	653	1.077	347	367	24	16	460	197	—	—	—	—	—	—
2025	33	MLB MLE	New York Yankees	—	679	579	176	30	2	50	88	160	7	12	5	304	403	622	1.025	318	376	24	13	438	182	—	—	—	—	—	—
2026	34	MLB MLE	New York Yankees	—	285	243	56	10	0	17	38	85	2	5	3	230	338	481	820	251	289	30	13	359	129	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	32	MLB MLE	New York Yankees	—	704	576	176	36	1	54	113	171	9	10	0	306	425	653	1.077	347	367	24	16	460	197	—	—	—	—	—	—
2025	33	MLB MLE	New York Yankees	—	679	579	176	30	2	50	88	160	7	12	5	304	403	622	1.025	318	376	24	13	438	182	—	—	—	—	—	—
2026	34	MLB MLE	New York Yankees	—	285	243	56	10	0	17	38	85	2	5	3	230	338	481	820	251	289	30	13	359	129	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	35	MLB MLE	NYY	100%	451	383	110	19	1	34	61	117	4	8	2	287	390	608	998	321	323	26	14	427	175	+40	+1	+4	-5	+10	4.0
▸ 2027 — real world (MLB)
2027	35	MLB CTX	NYY	100%	361	307	90	15	1	29	48	94	3	6	2	292	395	630	1.025	338	325	26	13	437	175	+32	+0	+3	-4	+8	4.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	36	MLB MLE	NYY	100%	310	263	72	12	1	22	41	83	3	2	1	274	378	578	956	304	310	27	13	411	164	+24	+0	-4	-3	+7	2.4
2029	37	MLB MLE	NYY	100%	250	213	56	9	0	17	33	68	2	1	0	262	366	548	914	286	298	27	13	395	153	+16	+0	-5	-3	+5	1.4
2030	38	MLB MLE	NYY	100%	192	163	40	6	0	12	25	53	2	0	0	251	354	519	874	268	287	28	13	379	143	+10	+0	-6	-2	+4	0.6
2028	36	MLB CTX	NYY	100%	310	263	74	12	1	24	41	83	3	2	1	279	382	600	982	320	312	27	13	420	164	+24	+0	-4	-3	+7	2.4
2029	37	MLB CTX	NYY	100%	250	213	57	9	0	18	33	68	2	1	0	267	370	569	939	302	300	27	13	404	153	+16	+0	-5	-3	+5	1.4
2030	38	MLB CTX	NYY	100%	192	163	41	6	0	13	25	53	2	0	0	256	358	539	897	283	289	28	13	388	143	+10	+0	-6	-2	+4	0.6
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	6039	4981	1434	240	8	441	959	1658	49	73	25	288	407	605	1.012	317	340	27	16	434	151	+566	+5	-4	-49	+131	66.2
/ 162G	—	A+C		—	650	536	154	26	1	47	103	178	5	8	3	287	406	603	1.008	315	340	27	16	434	151	+61	+0	-0	-5	+14	7.1
Career	—	MLE		—	8038	6870	1837	314	16	491	1042	2282	68	92	29	267	369	532	901	265	324	28	13	391	151	+598	+5	-1	-53	+139	70.2
/ 162G	—	MLE		—	650	556	148	25	1	40	84	185	5	7	2	266	367	531	897	264	322	28	13	391	151	+61	+1	-0	-5	+14	7.1

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.

2019 AAAScranton/Wilkes-Barre RailRiders · 19 PAwOBA .261 → .191 (−70)K% 36.8% → 43.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	36.84%	÷1.007	×1.200	—	—	43.91%
BB% (unintentional) /PA	15.79%	÷1.066	×0.690	—	×1.003	10.25%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	11.11%	÷1.019	×0.930	—	×1.003	10.17%
Doubles /BIP	0.00%	÷1.009	×0.830	—	×1.003	0.00%
Triples /BIP	0.00%	÷0.938	×0.970	—	×1.003	0.00%
Home runs /BIP	11.11%	÷1.087	×0.840	—	×1.003	8.61%

Factors used: league row IL. Park (home-season share, regressed): HR 117, 1B 104, 2B 102, 3B 88, K 101, 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).

Result: wOBA .261 → .191; ISO .188 → .141; BABIP .125 → .111. 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 AAAScranton/Wilkes-Barre RailRiders · 410 PAwOBA .370 → .313 (−56)K% 23.9% → 28.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.90%	÷0.994	×1.200	—	—	28.85%
BB% (unintentional) /PA	11.46%	÷0.977	×0.690	—	×1.048	8.49%
HBP% /PA	1.95%	—	×0.940	—	×1.048	1.92%
Singles /BIP	22.44%	÷0.991	×0.930	×0.950	×1.048	20.98%
Doubles /BIP	7.09%	÷1.059	×0.830	×0.950	×1.048	5.53%
Triples /BIP	0.39%	÷0.900	×0.970	×0.950	×1.048	0.42%
Home runs /BIP	7.48%	÷0.996	×0.840	—	×1.048	6.61%

Factors used: league row IL. Park (home-season share, regressed): HR 99, 1B 98, 2B 112, 3B 80, K 99, BB 95 — 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 ×0.950.

Result: wOBA .370 → .313; ISO .219 → .185; BABIP .319 → .285. 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).

2015 AATrenton Thunder · 280 PAwOBA .369 → .307 (−62)K% 25.0% → 32.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷0.950	×1.220	—	—	32.10%
BB% (unintentional) /PA	8.21%	÷1.067	×0.700	—	×1.027	5.53%
HBP% /PA	1.07%	—	×0.850	—	×1.027	0.94%
Singles /BIP	22.22%	÷0.977	×0.970	×1.017	×1.027	23.05%
Doubles /BIP	8.89%	÷0.978	×0.860	×1.017	×1.027	8.16%
Triples /BIP	1.67%	÷1.150	×0.950	×1.017	×1.027	1.44%
Home runs /BIP	6.67%	÷1.153	×0.780	—	×1.027	4.63%

Factors used: league row EL. Park (home-season share, regressed): HR 131, 1B 95, 2B 96, 3B 130, K 90, BB 114 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.017.

Result: wOBA .369 → .307; ISO .232 → .172; BABIP .345 → .336. 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).

2015 AAAScranton/Wilkes-Barre RailRiders · 260 PAwOBA .302 → .258 (−44)K% 28.5% → 34.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.46%	÷0.991	×1.200	—	—	34.48%
BB% (unintentional) /PA	11.15%	÷1.139	×0.690	—	×1.050	7.09%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	21.43%	÷1.011	×0.930	×0.953	×1.050	19.74%
Doubles /BIP	6.49%	÷0.903	×0.830	×0.953	×1.050	5.98%
Triples /BIP	0.00%	÷1.150	×0.970	×0.953	×1.050	0.00%
Home runs /BIP	5.19%	÷0.878	×0.840	—	×1.050	5.22%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 102, 2B 81, 3B 130, K 98, BB 128 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.953.

Result: wOBA .302 → .258; ISO .149 → .144; BABIP .289 → .266. 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).

2014 A+Tampa Yankees · 285 PAwOBA .376 → .306 (−69)K% 25.3% → 37.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.26%	÷0.950	×1.420	—	—	37.74%
BB% (unintentional) /PA	17.19%	÷0.978	×0.750	—	×1.012	13.34%
HBP% /PA	0.35%	—	×0.930	—	×1.012	0.33%
Singles /BIP	29.19%	÷1.019	×0.920	×1.035	×1.012	27.63%
Doubles /BIP	5.59%	÷1.003	×0.960	×1.035	×1.012	5.61%
Triples /BIP	1.24%	÷0.900	×0.810	×1.035	×1.012	1.17%
Home runs /BIP	4.97%	÷0.882	×0.880	—	×1.012	5.02%

Factors used: league row FSL. Park (home-season share, regressed): HR 76, 1B 104, 2B 101, 3B 80, K 90, BB 96 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.035.

Result: wOBA .376 → .306; ISO .159 → .137; BABIP .377 → .359. 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).

2014 ACharleston RiverDogs · 278 PAwOBA .413 → .341 (−72)K% 21.2% → 29.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.22%	÷0.975	×1.340	—	—	29.17%
BB% (unintentional) /PA	13.67%	÷1.050	×0.660	—	—	8.59%
HBP% /PA	0.72%	—	×0.770	—	—	0.55%
Singles /BIP	29.71%	÷0.953	×0.920	×0.988	—	28.36%
Doubles /BIP	8.57%	÷1.073	×0.820	×0.988	—	6.47%
Triples /BIP	1.14%	÷0.991	×0.940	×0.988	—	1.07%
Home runs /BIP	5.14%	÷0.883	×0.820	—	—	4.77%

Factors used: league row SAL. Park (home-season share, regressed): HR 77, 1B 91, 2B 115, 3B 98, K 95, BB 110 — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.988.

Result: wOBA .413 → .341; ISO .197 → .168; BABIP .408 → .370. 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
#1Albert Pujolslast yr '22 MVPROYAS×3SS career totals — 22 seasons, 13,041 PA	19.6	13,041	703	117	296	374	544	-212	-86	94.3	76.9
/162	664	36	6	-10.8	-4.4	4.8	pk7: 60
#2Miguel Cabreralast yr '23 MVP×2ROYAS×12SS×7HOF career totals — 21 seasons, 11,796 PA	17.8	11,796	511	40	306	382	518	-133	-139	79.4	65.7
/162	664	29	2	-7.5	-7.8	4.5	pk7: 52
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 15 projected seasons	9.6	6,400	465	80	289	403	606	-75	+14	71.4	63.5
/162	664	48	8	-7.8	+1.4	7.4	pk7: 56
#3Mark McGwire'86-'01 * career totals — 16 seasons, 7,660 PA	11.5	7,660	583	12	256*	384*	595*	-136	-49	68.6	59.1
/162	664	51	1	-11.8	-4.2	5.9	pk7: 50
#4Dick Allen'63-'77 * career totals — 14 seasons, 7,314 PA	11.0	7,314	351	133	291*	382*	586*	-63	-28	63.8	55.1
/162	664	32	12	-5.7	-2.5	5.8	pk7: 46
#5Lance Berkman'99-'13 * AS×6SS career totals — 15 seasons, 7,813 PA	11.8	7,813	366	86	284*	393*	526*	-102	+3	62.4	53.0
/162	664	31	7	-8.7	+0.2	5.3	pk7: 44
#6Matt Hollidaylast yr '18 AS×7SS×4 career totals — 15 seasons, 7,981 PA	12.0	7,981	316	108	299	379	510	-89	-91	52.3	45.5
/162	664	26	9	-7.4	-7.5	4.4	pk7: 39

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
Aaron Judge (OGILVIE)	35	—	—	—	—	284/387/602	318	323	27	6	26%	13%	175	+4.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
★Jeff Bagwell 2002 · MLB	34	54→55	67→65	47→45	63	290/393/568	278	305	34	9	18%	14%	168	+6.3	279/378/513	234	305	29	8	18%	13%	151	+5.0	273/375/494	221	298	28	7	18%	13%	147	+5.4
●Sammy Sosa 2004 · MLB	35	49→57	73→80	41→40	54	280/360/572	292	297	43	2	23%	11%	158	+5.6	248/320/471	223	275	32	3	23%	9%	121	+2.9	239/307/452	212	268	30	0	23%	8%	113	+1.8
●José Bautista 2016 · MLB	35	47→52	65→70	47→45	66	260/372/513	253	256	33	7	16%	14%	148	+4.8	226/343/428	202	255	25	6	21%	14%	119	+2.7	209/331/386	177	248	21	5	24%	14%	107	+1.7
●Paul Goldschmidt 2023 · MLB	35	58→61	63→65	53→55	56	303/383/545	242	343	31	8	21%	11%	160	+5.7	269/339/456	187	324	23	9	23%	9%	124	+3.1	258/324/419	162	313	19	9	23%	8%	111	+2.2
★Manny Ramirez 2007 · MLB	35	54→64	70	39→30	60	295/386/578	283	307	38	2	18%	12%	168	+6.3	294/378/528	234	323	29	2	18%	11%	154	+5.3	294/377/519	226	324	28	1	18%	10%	153	+4.8
●Alex Rodriguez 2010 · MLB	35	53→59	67→70	52→55	59	289/384/549	260	304	35	17	18%	12%	161	+5.8	270/352/471	201	299	26	9	19%	10%	132	+3.6	265/346/449	184	298	23	8	19%	10%	126	+2.8
★Chipper Jones 2007 · MLB	35	55→65	64→65	50	63	292/384/543	250	302	30	7	15%	13%	159	+5.6	314/399/538	224	332	26	6	13%	13%	164	+6.0	308/401/515	207	326	24	5	13%	13%	160	+5.5
★Gary Sheffield 2005 · MLB	36	56→60	63→65	46→50	63	298/390/539	240	288	31	10	11%	12%	161	+5.8	282/368/492	210	281	28	12	12%	11%	143	+4.4	276/368/475	199	274	27	15	11%	11%	140	+3.4
★Luis Gonzalez 2003 · MLB	35	55→59	65	47→45	62	294/385/549	255	286	33	5	12%	12%	162	+5.8	278/365/495	217	283	24	5	12%	12%	142	+4.4	272/359/480	208	279	22	4	12%	11%	137	+4.1
●Jim Edmonds 2005 · MLB	35	52→59	72→70	44→45	60	285/386/592	307	322	39	6	24%	14%	171	+6.5	261/355/502	241	304	30	6	24%	12%	140	+4.2	251/343/461	211	291	26	4	23%	12%	127	+2.5
★Larry Walker 2002 · MLB	35	62→65	64→65	49→50	61	322/415/583	261	342	30	12	16%	12%	179	+7.1	307/404/547	240	333	26	9	15%	12%	167	+6.2	301/406/538	236	327	25	8	15%	13%	166	+4.9
●Ellis Burks 2001 · MLB	36	60→64	62→65	52→45	60	314/388/553	239	314	29	8	12%	11%	163	+5.9	289/363/523	234	309	30	6	17%	10%	148	+4.8	282/359/512	230	305	30	4	18%	10%	145	+3.4
★Moises Alou 2001 · MLB	35	61→65	64→65	42→45	58	326/389/575	249	315	33	5	10%	9%	169	+6.4	299/358/495	196	303	24	6	11%	8%	140	+4.2	291/365/506	214	290	27	4	11%	10%	145	+4.6
★Frank Thomas 2002 · MLB	34	54→59	66→70	39→30	62	293/382/554	260	293	33	3	14%	12%	162	+5.8	262/373/511	249	274	31	3	18%	14%	149	+4.9	257/382/517	260	266	33	1	18%	15%	154	+4.7
●Jeff Kent 2003 · MLB	35	59→64	60→65	45	54	305/369/537	233	321	27	7	15%	8%	153	+5.2	291/351/514	223	310	26	7	15%	8%	141	+4.3	286/352/508	222	302	26	6	15%	8%	142	+4.3
●John Vander Wal 2001 · MLB	35	55→57	62→60	51→50	62	287/386/531	243	321	29	14	20%	14%	157	+5.5	264/346/453	189	326	20	8	23%	11%	125	+3.2	257/338/437	180	325	18	5	25%	11%	120	+1.8
●David Justice 2001 · MLB	35	50→54	69→60	45→40	60	281/366/561	280	275	38	4	15%	12%	158	+5.5	258/348/451	193	278	24	5	16%	12%	126	+3.2	250/346/412	163	275	19	3	16%	13%	117	+2.0
★Jim Thome 2007 · MLB	36	48→52	67→80	42→30	63	263/376/528	264	293	36	2	24%	15%	153	+5.2	257/369/512	255	297	35	2	25%	15%	147	+4.8	249/364/500	252	287	35	0	26%	15%	144	+4.0
●Brandon Belt 2022 · MLB	34	50→60	67→65	44→50	57	272/368/539	268	308	35	5	24%	12%	153	+5.2	251/352/469	218	329	27	4	30%	13%	132	+3.6	235/348/431	195	325	24	1	32%	14%	123	+1.7
●Joey Votto 2018 · MLB	34	59→67	59→65	49→50	68	303/414/522	219	324	26	7	15%	15%	165	+6.1	272/382/438	166	312	17	4	17%	14%	135	+3.9	260/374/407	147	306	15	3	18%	15%	124	+2.5

Aaron Judge

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps