Jorge Mateo

SS Tampa Bay Rays

Age 32 R/R 6'0" / 200 lbs MLB HR -6%H +4% Svc 7.000 · 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	MLBBAL	208	.229/.271/.401	5	13	78	0.2
2025	30	AAA/INTL2 orgs	179	.256/.331/.350	2	11	85	—	.289/.319/.400
2025	30	MLBBAL	83	.177/.217/.266	1	15	32	-0.5
2026	31	MLBTB	221	.203/.247/.314	5	19	56	-0.1
2027PROJ	32	MLBTB	142	.218/.265/.342	3	12	69	0.1
2028PROJ	33	MLBTB	123	.211/.257/.327	3	8	62	-0.5

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

ContractESTIMATED

Control thru2027Service7.000First FA2028Options2

2027Ext / FA-deal$1M

Skills · percentileStatcast 2024-2026

Speed90

Bat Spd70

Barrel%31

Avg EV26

xwOBA12

Form.192/.229/.291 ▼▼ rolling true talent (60d window) · proj .216/.261/.343

CompsDairon Blanco (age 30) · Darren Ford (age 30) · Trent Durrington (age 31)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 7369vR 58

AVG/OBP/SLG.218 / .265 / .342

PA142

HR3

SB12

K%27

BB%6

BABIP280

ISO114

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · ContractCON 40 / POW 40

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT40

xAVG

100.215

POWER40

Barrel%

315.7

Avg EV

2687.3

Bat Spd

7073.5

EYE40

scouting grade only

SPEED60

Sprint

9030.2

Recent Formrolling true talent ⓘ

K%34%▼▼40% over 60 PA (60d) · proj 27%

BB%4%▼2% over 60 PA (60d) · proj 5%

ISO.099▼.018 over 57 AB (60d) · proj .127

HR/BB2.8%▼0.0% over 33 BBE (60d) · proj 3.6%

BABIP.274·.212 over 33 BIP (60d) · proj .277

SLASH.192/.229/.291▼▼proj .216/.261/.343

Platoon Splits2024-2025 · 291 PA

vs LHP

vs RHP

Edge

129

162

—

wRC+

◀◀L

wOBA

305

238

◀◀L

ISO

181

122

◀◀L

BABIP

318

237

◀◀L

27.1%

26.5%

—

BB%

3.9%

5.6%

▶▶R

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

Status FA

MLB Debut 2020

Service 7.000 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	CLUB OPT	$1.0M / $0.0M buyout	DECLINE
2028	CLUB OPT	$5.5M / $0.0M 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	DSL Yankees 2	—	69	55	14	2	1	1	12	11	0	4	1	255	388	382	770	127	295	16	17	343	42	—	—	—	—	—	—
2013	18	ROK	DSL Yankees 1	—	299	258	74	9	6	7	34	52	5	49	10	287	380	450	830	163	333	17	11	369	43	—	—	—	—	—	—
2014	19	ROK	GCL Yankees1	—	65	58	16	5	1	0	7	17	0	11	1	276	354	397	750	121	390	26	11	338	36	—	—	—	—	—	—
2015	20	A+	Tampa Yankees	—	91	84	27	5	3	0	7	18	0	11	2	321	374	452	826	131	409	20	8	366	83	—	—	—	—	—	—
2015	20	A	Charleston RiverDogs	—	409	365	98	18	8	2	36	80	3	71	15	268	339	378	717	110	338	20	9	320	59	—	—	—	—	—	—
2016	21	A+	Tampa Yankees	—	507	464	118	16	9	8	33	108	3	36	15	254	308	379	687	125	312	21	7	304	51	—	—	—	—	—	—
2016	21	INTL	Toros del Este	—	46	42	7	1	1	0	3	10	1	5	1	167	239	238	477	71	219	22	7	223	37	—	—	—	—	—	—
2017	22	AA	Midland RockHounds	—	287	257	76	14	10	8	24	65	2	24	10	296	360	521	882	226	364	23	8	379	93	—	—	—	—	—	—
2017	22	A+	Tampa Yankees	—	297	275	66	16	8	4	16	79	3	28	3	240	289	400	689	160	321	27	5	301	32	—	—	—	—	—	—
2017	22	INTL	Toros del Este	—	124	115	25	3	2	3	4	30	3	10	0	217	262	357	619	139	265	24	3	272	70	—	—	—	—	—	—
2018	23	AAA	Nashville Sounds	—	510	470	108	17	16	3	29	139	5	25	10	230	282	353	635	123	316	27	6	280	38	—	—	—	—	—	—
2018	23	INTL	Toros del Este	—	71	59	10	2	1	0	10	13	1	2	2	169	300	237	537	68	217	18	14	257	60	—	—	—	—	—	—
2019	24	AAA	Las Vegas Aviators	—	566	532	154	29	14	19	29	145	4	24	11	289	331	504	835	214	366	26	5	364	66	—	—	—	—	—	—
2019	24	INTL	Dominican Republic	—	172	151	31	4	1	0	19	37	0	6	1	205	294	245	539	40	267	22	11	253	57	—	—	—	—	—	—
2020	25	MLB	San Diego Padres	—	28	26	4	3	0	0	1	11	0	1	0	154	185	269	454	115	267	39	4	195	25	-3	+0	+0	-1	+1	-0.3
2020	25	INTL	Toros del Este	—	75	68	21	3	1	2	6	15	1	4	2	309	373	471	844	162	373	20	8	375	140	—	—	—	—	—	—
2021	26	MLB	Baltimore Orioles	—	209	194	48	11	1	4	9	55	4	10	3	247	295	376	671	129	324	26	4	298	85	-4	+1	-1	+2	+5	0.3
2022	27	MLB	Baltimore Orioles	—	533	494	109	25	7	13	27	147	5	35	9	221	267	379	646	158	286	28	5	283	75	-16	+3	+12	+6	+12	1.7
2023	28	MLB	Baltimore Orioles	—	350	318	69	14	2	7	22	82	1	32	5	217	269	340	609	123	267	23	6	267	64	-15	+4	+1	+4	+8	0.2
2023	28	INTL	Toros del Este	—	44	40	14	1	1	0	1	7	1	0	0	350	381	425	806	75	400	16	2	345	120	—	—	—	—	—	—
2024	29	MLB	Baltimore Orioles	—	208	192	44	14	2	5	10	48	1	13	2	229	271	401	672	172	275	23	5	289	78	-5	+2	+0	+1	+5	0.2
2025	30	MLB	Baltimore Orioles	—	83	79	14	4	0	1	4	30	0	15	2	177	217	266	483	89	271	36	5	219	32	-7	+2	-4	+1	+2	-0.5
2025	30	AAA	Norfolk Tides	—	47	44	14	2	0	1	3	7	0	2	0	318	362	432	794	114	361	15	6	355	84	—	—	—	—	—	—
2025	30	INTL	Estrellas Orientales	—	132	116	27	3	2	1	13	28	2	9	1	233	321	319	640	86	299	21	10	293	85	—	—	—	—	—	—
2026	31	MLB	Tampa Bay Rays	—	221	207	42	8	0	5	11	69	1	19	4	203	247	314	561	111	276	31	5	250	56	-12	+2	+2	+2	+5	-0.1
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1632	1510	330	79	12	35	84	442	12	125	25	219	265	356	621	138	283	27	5	273	71	-56	+15	+10	+15	+35	2.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	17	ROK MLE	DSL Yankees 2	—	69	58	10	1	1	1	9	13	0	4	1	172	284	276	559	103	188	19	13	231	42	—	—	—	—	—	—
2013	18	ROK MLE	DSL Yankees 1	—	299	268	47	5	4	3	24	63	5	49	10	175	256	257	513	82	213	21	8	232	43	—	—	—	—	—	—
2014	19	ROK MLE	GCL Yankees1	—	65	61	11	3	1	0	4	25	0	11	1	180	231	262	493	82	308	38	6	222	36	—	—	—	—	—	—
2015	20	A+ MLE	Tampa Yankees	—	91	86	22	4	2	0	5	25	0	11	2	256	297	349	646	93	371	27	5	291	83	—	—	—	—	—	—
2015	20	A MLE	Charleston RiverDogs	—	409	379	86	15	7	2	22	111	3	71	15	227	275	319	594	92	306	27	5	256	59	—	—	—	—	—	—
2016	21	A+ MLE	Tampa Yankees	—	507	473	96	14	6	8	24	155	3	36	15	203	246	309	555	106	277	31	5	243	51	—	—	—	—	—	—
2017	22	AA MLE	Midland RockHounds	—	287	263	61	11	9	7	18	84	2	24	10	232	286	422	708	190	306	29	6	306	93	—	—	—	—	—	—
2017	22	A+ MLE	Tampa Yankees	—	297	279	48	13	5	3	12	118	3	28	3	172	214	287	501	115	275	40	4	216	32	—	—	—	—	—	—
2018	23	AAA MLE	Nashville Sounds	—	510	478	90	14	11	2	21	170	5	25	10	188	230	276	506	88	280	33	4	225	38	—	—	—	—	—	—
2019	24	AAA MLE	Las Vegas Aviators	—	566	540	118	22	9	13	21	189	4	24	11	219	253	365	618	146	309	33	4	266	66	—	—	—	—	—	—
2020	25	MLB MLE	San Diego Padres	—	28	26	4	3	0	0	1	11	0	1	0	154	185	269	454	115	267	39	4	205	25	-3	+0	+0	-1	+1	-0.3
2021	26	MLB MLE	Baltimore Orioles	—	209	194	48	11	1	4	9	55	4	10	3	247	295	376	671	129	324	26	4	294	85	-4	+1	-1	+2	+5	0.3
2022	27	MLB MLE	Baltimore Orioles	—	533	496	107	24	7	13	27	147	5	35	9	216	263	371	634	155	286	28	5	279	75	-16	+3	+12	+6	+12	1.7
2023	28	MLB MLE	Baltimore Orioles	—	350	319	68	13	2	7	22	82	1	32	5	213	266	332	598	119	267	23	6	263	64	-15	+4	+1	+4	+8	0.2
2024	29	MLB MLE	Baltimore Orioles	—	208	192	43	13	2	5	10	48	1	13	2	224	266	391	657	167	275	23	5	283	78	-5	+2	+0	+1	+5	0.2
2025	30	MLB MLE	Baltimore Orioles	—	83	79	14	4	0	1	4	30	0	15	2	177	217	266	483	89	271	36	5	215	32	-7	+2	-4	+1	+2	-0.5
2025	30	AAA MLE	Norfolk Tides	—	47	45	13	2	0	1	2	9	0	2	0	289	319	400	719	111	331	19	4	292	84	—	—	—	—	—	—
2026	31	MLB MLE	Tampa Bay Rays	—	221	207	41	8	0	5	11	69	1	19	4	198	242	309	551	111	276	31	5	250	56	-12	+2	+2	+2	+5	-0.1
2012	17	ROK MLE	DSL Yankees 2	—	69	58	10	1	1	1	9	13	0	4	1	172	284	276	559	103	200	19	13	231	42	—	—	—	—	—	—
2012	17	ROK RAW	DSL Yankees 2	—	69	55	14	2	1	1	12	11	0	4	1	255	388	382	770	127	295	16	17	343	42	—	—	—	—	—	—
2013	18	ROK MLE	DSL Yankees 1	—	299	268	47	5	4	3	24	63	5	49	10	175	256	257	513	82	216	21	8	232	43	—	—	—	—	—	—
2013	18	ROK RAW	DSL Yankees 1	—	299	258	74	9	6	7	34	52	5	49	10	287	380	450	830	163	333	17	11	369	43	—	—	—	—	—	—
2014	19	ROK MLE	GCL Yankees1	—	65	61	11	3	1	0	4	25	0	11	1	180	231	262	493	82	306	38	6	222	36	—	—	—	—	—	—
2014	19	ROK RAW	GCL Yankees1	—	65	58	16	5	1	0	7	17	0	11	1	276	354	397	750	121	390	26	11	338	36	—	—	—	—	—	—
2015	20	A MLE	2 teams	—	500	464	108	19	9	2	28	136	3	82	17	233	281	325	606	93	324	27	6	262	64	—	—	—	—	—	—
2015	20	A RAW	2 teams	—	500	449	125	23	11	2	43	98	3	82	17	278	345	392	737	114	351	20	9	328	64	—	—	—	—	—	—
2016	21	A+ MLE	2 teams	—	553	515	106	16	7	8	27	169	4	41	16	206	251	311	562	105	287	31	5	243	51	—	—	—	—	—	—
2016	21	A+ RAW	2 teams	—	553	506	125	17	10	8	36	118	4	41	16	247	302	368	670	121	305	21	7	297	51	—	—	—	—	—	—
2017	22	A+ MLE	3 teams	—	708	655	133	29	17	13	36	246	8	62	13	203	253	359	612	156	299	35	5	260	62	—	—	—	—	—	—
2017	22	A+ RAW	3 teams	—	708	647	167	33	20	15	44	174	8	62	13	258	313	440	754	182	328	25	6	328	62	—	—	—	—	—	—
2018	23	AAA MLE	2 teams	—	581	544	103	16	12	3	24	193	6	27	12	189	232	279	511	90	284	33	4	225	38	—	—	—	—	—	—
2018	23	AAA RAW	2 teams	—	581	529	118	19	17	3	39	152	6	27	12	223	284	340	624	117	304	26	7	277	38	—	—	—	—	—	—
2019	24	AAA MLE	2 teams	—	738	704	153	29	12	16	27	246	4	30	12	217	250	361	611	143	308	33	4	266	66	—	—	—	—	—	—
2019	24	AAA RAW	2 teams	—	738	683	185	33	15	19	48	182	4	30	12	271	322	447	769	176	342	25	7	338	66	—	—	—	—	—	—
2020	25	INTL MLE	2 teams	—	103	97	16	12	0	0	4	40	1	5	2	165	206	289	495	124	281	39	4	205	25	—	—	—	—	—	—
2020	25	INTL RAW	2 teams	—	103	94	25	6	1	2	7	26	1	5	2	266	324	415	738	149	348	25	7	326	25	—	—	—	—	—	—
2021	26	MLB MLE	Baltimore Orioles	—	209	194	48	11	1	4	9	55	4	10	3	247	295	376	671	129	324	26	4	294	85	-4	+1	-1	+2	+5	0.3
2021	26	MLB RAW	Baltimore Orioles	—	209	194	48	11	1	4	9	55	4	10	3	247	295	376	671	129	324	26	4	298	85	-4	+1	-1	+2	+5	0.3
2022	27	MLB MLE	Baltimore Orioles	—	533	496	107	24	7	13	27	147	5	35	9	216	263	371	634	155	278	28	5	279	75	-16	+3	+12	+6	+12	1.7
2022	27	MLB RAW	Baltimore Orioles	—	533	494	109	25	7	13	27	147	5	35	9	221	267	379	646	158	286	28	5	283	75	-16	+3	+12	+6	+12	1.7
2023	28	MLB MLE	2 teams	—	394	357	76	15	2	8	25	92	2	32	5	213	268	333	602	120	260	23	6	263	64	-17	+4	+1	+4	+9	0.1
2023	28	MLB RAW	2 teams	—	394	358	83	15	3	7	23	89	2	32	5	232	281	349	630	117	285	23	6	276	64	-17	+4	+1	+4	+9	0.1
2024	29	MLB MLE	Baltimore Orioles	—	208	192	43	13	2	5	10	48	1	13	2	224	266	391	657	167	268	23	5	283	78	-5	+2	+0	+1	+5	0.2
2024	29	MLB RAW	Baltimore Orioles	—	208	192	44	14	2	5	10	48	1	13	2	229	271	401	672	172	275	23	5	289	78	-5	+2	+0	+1	+5	0.2
2025	30	INTL MLE	3 teams	—	262	247	53	11	0	3	12	78	2	26	3	215	257	296	552	81	301	30	5	243	51	—	—	—	—	—	—
2025	30	INTL RAW	3 teams	—	262	239	55	9	2	3	20	65	2	26	3	230	295	322	617	92	304	25	8	281	51	—	—	—	—	—	—
2026	31	MLB MLE	Tampa Bay Rays	—	221	207	41	8	0	5	11	69	1	19	4	198	242	309	551	111	269	31	5	250	56	-12	+2	+2	+2	+5	-0.1
2026	31	MLB RAW	Tampa Bay Rays	—	221	207	42	8	0	5	11	69	1	19	4	203	247	314	561	111	276	31	5	250	56	-12	+2	+2	+2	+5	-0.1
2012	17	ROK MLE	DSL Yankees 2	—	69	60	10	1	1	1	9	13	0	4	1	167	284	267	550	100	188	19	13	231	42	—	—	—	—	—	—
2013	18	ROK MLE	DSL Yankees 1	—	299	268	47	5	4	3	24	63	5	49	10	175	256	257	513	82	213	21	8	232	43	—	—	—	—	—	—
2014	19	ROK MLE	GCL Yankees1	—	65	61	11	3	1	0	4	25	0	11	1	180	231	262	493	82	308	38	6	222	36	—	—	—	—	—	—
2015	20	A MLE	2 teams	—	500	465	108	19	9	2	28	136	3	82	17	232	281	325	606	92	318	27	6	262	64	—	—	—	—	—	—
2016	21	A+ MLE	2 teams	—	553	517	106	16	7	8	27	169	4	41	16	205	251	309	560	104	277	31	5	243	51	—	—	—	—	—	—
2017	22	A+ MLE	3 teams	—	708	658	133	29	17	13	36	246	8	62	13	202	253	357	610	155	290	35	5	260	62	—	—	—	—	—	—
2018	23	AAA MLE	2 teams	—	581	546	103	16	12	3	24	193	6	27	12	189	232	278	510	90	280	33	4	225	38	—	—	—	—	—	—
2019	24	AAA MLE	2 teams	—	738	701	153	29	12	16	27	246	4	30	12	218	250	362	613	144	309	33	4	266	66	—	—	—	—	—	—
2020	25	INTL MLE	2 teams	—	103	97	16	12	0	0	4	40	1	5	2	165	206	289	495	124	267	39	4	205	25	—	—	—	—	—	—
2021	26	MLB MLE	Baltimore Orioles	—	209	194	48	11	1	4	9	55	4	10	3	247	295	376	671	129	324	26	4	294	85	—	—	—	—	—	—
2022	27	MLB MLE	Baltimore Orioles	—	533	496	107	24	7	13	27	147	5	35	9	216	263	371	634	155	286	28	5	279	75	—	—	—	—	—	—
2023	28	MLB MLE	2 teams	—	394	364	76	15	2	8	25	92	2	32	5	209	268	327	595	118	267	23	6	263	64	—	—	—	—	—	—
2024	29	MLB MLE	Baltimore Orioles	—	208	195	43	13	2	5	10	48	1	13	2	221	266	385	651	164	275	23	5	283	78	—	—	—	—	—	—
2025	30	INTL MLE	3 teams	—	262	246	53	11	0	3	12	78	2	26	3	215	257	297	553	81	293	30	5	243	51	—	—	—	—	—	—
2026	31	MLB MLE	Tampa Bay Rays	—	221	207	41	8	0	5	11	69	1	19	4	198	242	309	551	111	276	31	5	250	56	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	29	MLB MLE	Baltimore Orioles	—	208	195	43	13	2	5	10	48	1	13	2	221	266	385	651	164	275	23	5	283	78	—	—	—	—	—	—
2025	30	INTL MLE	3 teams	—	262	246	53	11	0	3	12	78	2	26	3	215	257	297	553	81	293	30	5	243	51	—	—	—	—	—	—
2026	31	MLB MLE	Tampa Bay Rays	—	221	207	41	8	0	5	11	69	1	19	4	198	242	309	551	111	276	31	5	250	56	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	32	MLB MLE	TB	100%	229	213	47	9	1	6	13	63	1	20	3	216	263	344	607	127	277	28	6	270	69	-8	+3	-0	+2	+5	0.1
▸ 2027 — real world (MLB)
2027	32	MLB CTX	TB	100%	142	132	28	6	0	3	8	39	1	12	2	218	265	342	607	124	280	27	6	270	69	-5	+2	-0	+2	+3	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	33	MLB MLE	TB	100%	123	114	24	5	0	3	7	35	1	8	1	209	255	328	583	118	271	28	6	260	62	-6	+1	-4	+1	+3	-0.5
2028	33	MLB CTX	TB	100%	123	114	25	5	0	3	7	35	1	8	1	211	257	327	584	116	274	28	6	260	62	-6	+1	-4	+1	+3	-0.5
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1755	1624	355	84	12	38	91	477	13	133	26	219	265	355	620	137	283	27	5	272	59	-62	+16	+6	+16	+38	1.5
/ 162G	—	A+C		—	650	601	131	31	4	14	34	177	5	49	10	218	265	353	618	135	283	27	5	272	59	-23	+6	+2	+6	+14	0.6
Career	—	MLE		—	5708	5305	1107	223	75	90	292	1694	48	466	113	209	256	330	586	121	286	30	5	256	59	-67	+18	+6	+18	+41	1.6
/ 162G	—	MLE		—	650	604	126	25	9	10	33	193	5	53	13	209	255	329	585	121	286	30	5	256	59	-23	+6	+2	+6	+14	0.6

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 AAANorfolk Tides · 47 PAwOBA .346 → .292 (−54)K% 14.9% → 18.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.89%	÷0.967	×1.200	—	—	18.48%
BB% (unintentional) /PA	6.38%	÷1.063	×0.690	—	×0.972	4.03%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	29.73%	÷0.959	×0.930	—	×0.972	28.01%
Doubles /BIP	5.41%	÷0.978	×0.830	—	×0.972	4.46%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.972	0.00%
Home runs /BIP	2.70%	÷0.945	×0.700	—	×0.972	1.95%

Factors used: league row International League. Park (home-season share, regressed): HR 89, 1B 92, 2B 96, 3B 80, K 93, BB 113 — 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 .346 → .292; ISO .114 → .085; BABIP .361 → .331. 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 AAALas Vegas Aviators · 566 PAwOBA .353 → .266 (−87)K% 25.6% → 33.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.62%	÷0.990	×1.290	—	—	33.37%
BB% (unintentional) /PA	4.95%	÷0.985	×0.710	—	×1.048	3.74%
HBP% /PA	0.71%	—	×0.980	—	×1.048	0.73%
Singles /BIP	23.77%	÷1.018	×0.900	×0.950	×1.048	20.92%
Doubles /BIP	7.49%	÷0.951	×0.810	×0.950	×1.048	6.35%
Triples /BIP	3.62%	÷1.102	×0.810	×0.950	×1.048	2.65%
Home runs /BIP	4.91%	÷1.119	×0.780	—	×1.048	3.59%

Factors used: league row PCL. Park (home-season share, regressed): HR 124, 1B 104, 2B 90, 3B 120, K 98, BB 97 — 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 .353 → .266; ISO .214 → .148; BABIP .366 → .309. 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 AAANashville Sounds · 510 PAwOBA .274 → .225 (−49)K% 27.3% → 33.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.25%	÷1.055	×1.290	—	—	33.31%
BB% (unintentional) /PA	5.49%	÷0.966	×0.710	—	×1.050	4.24%
HBP% /PA	0.98%	—	×0.980	—	×1.050	1.01%
Singles /BIP	21.75%	÷0.986	×0.900	×0.967	×1.050	20.17%
Doubles /BIP	5.14%	÷0.937	×0.810	×0.967	×1.050	4.51%
Triples /BIP	4.83%	÷1.150	×0.810	×0.967	×1.050	3.46%
Home runs /BIP	0.91%	÷0.988	×0.780	—	×1.050	0.75%

Factors used: league row PCL. Park (home-season share, regressed): HR 98, 1B 97, 2B 87, 3B 130, K 111, BB 93 — 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 ×0.967.

Result: wOBA .274 → .225; ISO .123 → .091; BABIP .316 → .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).

2017 A+Tampa Yankees · 297 PAwOBA .294 → .216 (−78)K% 26.6% → 39.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.60%	÷0.949	×1.420	—	—	39.81%
BB% (unintentional) /PA	5.39%	÷1.007	×0.750	—	×1.012	4.06%
HBP% /PA	1.01%	—	×0.930	—	×1.012	0.95%
Singles /BIP	19.39%	÷1.071	×0.920	×0.967	×1.012	16.30%
Doubles /BIP	8.16%	÷0.995	×0.960	×0.967	×1.012	7.71%
Triples /BIP	4.08%	÷1.031	×0.810	×0.967	×1.012	3.14%
Home runs /BIP	2.04%	÷0.949	×0.880	—	×1.012	1.92%

Factors used: league row FSL. Park (home-season share, regressed): HR 90, 1B 114, 2B 99, 3B 106, K 90, BB 101 — 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 ×0.967.

Result: wOBA .294 → .216; ISO .160 → .118; BABIP .321 → .275. 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 AAMidland RockHounds · 287 PAwOBA .373 → .306 (−67)K% 22.6% → 29.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.65%	÷0.939	×1.220	—	—	29.44%
BB% (unintentional) /PA	8.36%	÷0.990	×0.700	—	×1.042	6.16%
HBP% /PA	0.70%	—	×0.870	—	×1.042	0.63%
Singles /BIP	22.92%	÷1.142	×0.920	×0.965	×1.042	18.57%
Doubles /BIP	7.29%	÷0.987	×0.840	×0.965	×1.042	6.24%
Triples /BIP	5.21%	÷0.977	×0.940	×0.965	×1.042	5.04%
Home runs /BIP	4.17%	÷0.862	×0.800	—	×1.042	4.03%

Factors used: league row TL. Park (home-season share, regressed): HR 72, 1B 128, 2B 97, 3B 95, K 88, BB 98 — 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 ×0.965.

Result: wOBA .373 → .306; ISO .226 → .202; BABIP .364 → .306. 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 A+Tampa Yankees · 507 PAwOBA .297 → .243 (−54)K% 21.3% → 30.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.30%	÷0.988	×1.420	—	—	30.60%
BB% (unintentional) /PA	6.31%	÷1.021	×0.750	—	×1.027	4.76%
HBP% /PA	0.59%	—	×0.930	—	×1.027	0.57%
Singles /BIP	23.88%	÷1.022	×0.920	×0.953	×1.027	21.03%
Doubles /BIP	4.49%	÷0.953	×0.960	×0.953	×1.027	4.43%
Triples /BIP	2.53%	÷1.032	×0.810	×0.953	×1.027	1.94%
Home runs /BIP	2.25%	÷0.862	×0.880	—	×1.027	2.36%

Factors used: league row FSL. Park (home-season share, regressed): HR 72, 1B 104, 2B 91, 3B 106, K 98, BB 104 — 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 ×0.953.

Result: wOBA .297 → .243; ISO .125 → .108; BABIP .312 → .277. 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 ACharleston RiverDogs · 409 PAwOBA .312 → .256 (−55)K% 19.6% → 27.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.56%	÷0.968	×1.340	—	—	27.07%
BB% (unintentional) /PA	8.56%	÷1.054	×0.660	—	×1.030	5.52%
HBP% /PA	0.73%	—	×0.770	—	×1.030	0.58%
Singles /BIP	24.56%	÷1.031	×0.920	×0.997	×1.030	22.51%
Doubles /BIP	6.32%	÷0.989	×0.820	×0.997	×1.030	5.38%
Triples /BIP	2.81%	÷1.041	×0.940	×0.997	×1.030	2.60%
Home runs /BIP	0.70%	÷0.937	×0.820	—	×1.030	0.63%

Factors used: league row SAL. Park (home-season share, regressed): HR 87, 1B 106, 2B 98, 3B 108, K 94, BB 111 — 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 ×0.997.

Result: wOBA .312 → .256; ISO .110 → .093; BABIP .338 → .306. 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 A+Tampa Yankees · 91 PAwOBA .357 → .291 (−66)K% 19.8% → 27.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.78%	÷1.016	×1.420	—	—	27.64%
BB% (unintentional) /PA	7.69%	÷1.015	×0.750	—	×1.042	5.92%
HBP% /PA	0.00%	—	×0.930	—	×1.042	0.00%
Singles /BIP	28.79%	÷1.046	×0.920	×1.004	×1.042	26.50%
Doubles /BIP	7.58%	÷1.044	×0.960	×1.004	×1.042	7.29%
Triples /BIP	4.55%	÷1.150	×0.810	×1.004	×1.042	3.35%
Home runs /BIP	0.00%	÷0.832	×0.880	—	×1.042	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 66, 1B 109, 2B 109, 3B 130, K 103, BB 103 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.004.

Result: wOBA .357 → .291; ISO .131 → .101; BABIP .409 → .371. 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
#1Chris Owingslast yr '22 career totals — 9 seasons, 2,420 PA	3.6	2,420	35	78	239	286	365	+13	-0	3.7	4.5
/162	664	10	21	+3.6	-0.1	1.0	pk7: 5
#2Alexi Casillalast yr '13 career totals — 7 seasons, 1,883 PA	2.8	1,883	12	80	248	302	332	+8	+3	2.7	2.7
/162	664	4	28	+2.8	+0.9	1.0	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 8 projected seasons	2.8	1,869	41	144	218	262	354	+20	+18	2.5	2.5
/162	664	15	51	+7.1	+6.4	0.9	pk7: 3
#3Enzo Hernandez'71-'78 * career totals — 6 seasons, 2,612 PA	3.9	2,612	2	129	222*	281*	294*	+28	+4	1.6	1.9
/162	664	1	33	+7.0	+1.0	0.4	pk7: 2
#4Pete Mackanin'73-'81 * career totals — 6 seasons, 1,686 PA	2.5	1,686	30	27	222*	261*	370*	+6	+23	0.6	1.6
/162	664	12	11	+2.4	+8.9	0.2	pk7: 3
#5Al Weis'62-'71 * career totals — 8 seasons, 1,763 PA	2.7	1,763	7	55	223*	283*	300*	+10	+9	-0.2	1.3
/162	664	3	21	+3.8	+3.5	-0.1	pk7: 3
#6Alexi Amaristalast yr '17 career totals — 7 seasons, 1,901 PA	2.9	1,901	21	39	231	275	323	+14	-6	-1.1	-1.1
/162	664	7	14	+4.9	-2.1	-0.4	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
Jorge Mateo (OGILVIE)	32	40	40	60	40	214/261/341	126	277	3	12	27%	5%	69	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Dairon Blanco 2023 · AAA	30	48→50	46→45	62→70	41	237/290/363	127	308	14	42	27%	6%	84	+0.2	249/310/375	126	320	13	71	25%	6%	95	+0.9	246/312/366	120	313	12	95	24%	6%	91	+0.3
✕Darren Ford 2016 · AAA	30	45→53	41→45	57→65	43	218/270/309	91	280	9	39	25%	6%	64	-1.3	218/270/298	80	283	6	24	24%	6%	61	-1.5	212/261/258	46	279	1	23	23%	6%	45	-1.9
✕Trent Durrington 2007 · MLB	31	47→43	38→40	59→60	43	223/275/304	81	286	6	35	24%	6%	64	-1.3	217/277/301	84	279	6	26	23%	7%	65	-1.2	201/270/253	52	258	2	33	21%	7%	49	-0.9
✕Greg Allen 2024 · MLB	31	48→57	43→45	64→65	46	227/323/344	117	300	10	43	26%	8%	94	+0.9	215/293/329	114	285	9	28	27%	6%	79	-0.2	202/278/307	105	272	7	27	27%	5%	66	-0.4
✕Billy Hamilton 2022 · MLB	31	43→53	42→40	61→70	41	212/261/324	112	292	8	32	30%	6%	63	-1.3	189/248/283	94	290	8	32	35%	7%	50	-2.3	129/196/167	38	216	1	52	38%	7%	2	-1.2
✕Jarrod Dyson 2016 · MLB	31	52→57	40→45	73→70	49	245/305/346	101	293	6	58	18%	7%	85	+0.2	247/313/348	101	283	6	44	14%	8%	88	+0.5	240/310/329	89	273	5	47	13%	8%	84	+0.1
✕Wynton Bernard 2024 · MLB	33	49→59	43→45	60	45	240/290/359	119	294	10	32	22%	6%	82	+0.0	232/277/340	108	287	10	30	22%	5%	74	-0.6	225/254/312	87	273	7	44	20%	3%	54	-0.9
✕Gilberto Mejia 2015 · AAA	32	54→58	39→40	63→65	46	255/308/347	92	311	5	41	19%	6%	86	+0.3	247/296/336	89	297	4	35	17%	5%	79	-0.2	247/296/330	83	295	3	37	16%	5%	75	-0.3
✕Christian Zazueta 2017 · AAA	32	47→54	44→45	58→60	37	236/258/352	117	277	12	29	20%	2%	69	-0.9	224/250/319	95	264	9	27	19%	2%	58	-1.7	220/244/297	77	255	7	27	17%	2%	47	-1.5
✕Todd Donovan 2009 · AAA	30	49→52	36→40	61→65	48	232/291/301	69	291	3	38	21%	7%	70	-0.9	224/300/306	82	289	5	31	22%	10%	75	-0.5	214/305/285	71	275	3	38	21%	11%	71	-0.6
✕Matt Lipka 2022 · AAA	30	50→52	44→45	58→60	39	239/287/355	116	329	11	31	30%	5%	81	-0.1	222/281/328	106	323	9	34	32%	7%	72	-0.7	188/256/263	75	291	4	59	34%	8%	45	-1.0
✕Rajai Davis 2014 · MLB	33	52→62	43→50	67→70	45	251/301/371	120	301	10	56	20%	6%	90	+0.6	264/312/405	141	311	12	41	19%	6%	101	+1.4	264/312/409	145	311	13	43	19%	6%	103	+1.2
✕Jon Berti 2023 · MLB	33	50→60	42→45	62→60	55	237/326/347	110	304	8	39	23%	11%	94	+0.9	263/324/370	107	324	10	29	21%	8%	98	+1.2	276/329/367	91	337	9	30	20%	6%	100	+0.5
✕Craig Gentry 2015 · MLB	31	55	37→40	62→60	49	256/323/331	75	307	4	36	17%	7%	88	+0.5	218/277/292	74	274	6	25	21%	7%	63	-1.4	218/282/291	73	279	4	29	22%	7%	64	-0.4
✕Justin Christian 2012 · MLB	32	51→54	43→45	62→65	48	245/296/359	115	273	9	33	14%	6%	85	+0.2	237/287/343	106	266	8	22	14%	6%	78	-0.3	231/281/333	102	259	7	17	14%	5%	71	-0.6
✕Freddy Guzman 2013 · AAA	32	50→60	42→45	74→70	50	241/295/353	112	281	7	60	17%	7%	83	+0.1	257/308/356	99	309	8	61	18%	7%	88	+0.5	252/307/325	73	310	4	63	19%	7%	78	-0.2
✕Esix Snead 2006 · AAA	30	46	37→30	63→65	50	217/292/290	73	265	4	44	19%	8%	68	-1.0	218/284/303	85	265	7	33	19%	8%	68	-1.0	199/258/236	37	236	3	46	16%	7%	41	-0.8
✕Andrew Velazquez 2024 · MLB	30	41→51	44→50	60	41	204/263/320	116	294	12	34	34%	7%	64	-1.3	203/249/300	97	306	10	31	35%	6%	54	-2.0	199/241/282	83	298	9	34	35%	5%	44	-1.7
✕Tyler Graham 2014 · AAA	30	47→54	39→40	60→65	45	225/290/311	86	287	6	33	23%	6%	72	-0.7	228/274/303	75	282	6	28	21%	5%	63	-1.3	230/270/276	46	284	3	38	19%	4%	52	-1.6
✕Jason Bourgeois 2012 · MLB	30	57→58	38→45	63→65	48	270/309/352	82	300	5	44	12%	5%	87	+0.4	242/284/318	76	270	5	27	12%	5%	70	-0.8	241/275/316	76	274	5	14	14%	4%	64	-0.7

Jorge Mateo

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps