Amed Rosario

3B New York Yankees

Age 31 R/R 6'1" / 227 lbs MLB HR +14% Svc 9.360 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	28	MLBCIN	346	.280/.307/.380	3	13	92	-0.5
2025	29	MLBNYY	191	.276/.311/.436	6	1	107	0.1
2026	30	MLBNYY	244	.238/.282/.405	10	3	86	0.0
2027PROJ	31	MLBNYY	171	.275/.315/.432	5	7	106	0.4
2028PROJ	32	MLBNYY	159	.267/.307/.416	5	4	99	-0.1

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

ContractESTIMATED

Control thru2027Service9.360First FA2028

2027Ext / FA-deal$4M

Skills · percentileStatcast 2024-2026

Speed79

Bat Spd77

Avg EV48

xwOBA46

Barrel%39

Form.285/.318/.412 · rolling true talent (60d window) · proj .273/.311/.425

CompsEduardo Núñez (age 31) · Jonathan Villar (age 31) · Jon Berti (age 31)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 109106vR 95

AVG/OBP/SLG.275 / .315 / .432

PA171

HR5

SB7

K%21

BB%5

BABIP322

ISO150

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Recent Form · Splits · Contract

ToolsStatcast %ile · 2024-2026

CONTACT

xAVG

590.259

POWER

Barrel%

396.8

Avg EV

4889.0

Bat Spd

7774.2

SPEED

Sprint

7928.6

Recent Formrolling true talent ⓘ

K%17%▲▲10% over 41 PA (60d) · proj 21%

BB%4%▼2% over 41 PA (60d) · proj 5%

ISO.126▼.025 over 40 AB (60d) · proj .151

HR/BB3.1%▼0.0% over 36 BBE (60d) · proj 4.1%

BABIP.322·.333 over 36 BIP (60d) · proj .322

SLASH.285/.318/.412·proj .273/.311/.425

Platoon Splits2024-2026 · 595 PA

vs LHP

vs RHP

Edge

277

318

—

wRC+

117

◀◀L

wOBA

341

294

◀L

ISO

171

109

◀◀L

BABIP

322

327

—

15.2%

22.3%

◀◀L

BB%

4.0%

2.8%

◀◀L

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

Status FA

MLB Debut 2017

Service 9.360 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$4M	+0.5	$2M	-$2M
Totals		$4M		$2M	-$2M

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)
2013	17	ROK	Kingsport Mets	—	226	212	51	8	4	3	11	43	1	2	6	241	281	358	640	118	286	19	5	283	33	—	—	—	—	—	—
2014	18	A	Savannah Sand Gnats	—	31	30	4	0	1	1	1	11	0	0	0	133	161	300	461	167	167	35	3	200	-11	—	—	—	—	—	—
2015	19	A+	St. Lucie Mets	—	417	385	99	20	5	0	23	73	5	12	4	257	308	335	643	78	316	18	6	289	53	—	—	—	—	—	—
2016	20	AA	Binghamton Mets	—	237	214	73	14	5	2	19	51	1	6	2	341	397	481	879	140	433	22	8	385	124	—	—	—	—	—	—
2016	20	A+	St. Lucie Mets	—	290	265	82	10	8	3	21	36	1	13	6	309	362	442	804	132	345	12	7	354	100	—	—	—	—	—	—
2017	21	MLB	New York Mets	—	170	165	41	4	4	4	3	49	2	7	3	248	271	394	665	145	330	29	2	293	89	-2	+0	-3	+6	+4	0.5
2017	21	AAA	Las Vegas 51s	—	425	393	129	19	7	7	23	67	4	19	6	328	371	466	837	137	377	16	5	367	99	—	—	—	—	—	—
2018	22	MLB	New York Mets	—	592	554	142	26	8	9	29	119	3	24	11	256	297	381	678	125	310	20	5	299	91	-6	+0	-10	+6	+13	0.3
2019	23	MLB	New York Mets	—	655	616	177	30	7	15	31	124	3	19	10	287	325	432	756	144	338	19	5	333	116	+12	-0	-6	+7	+14	2.8
2020	24	MLB	New York Mets	—	147	143	36	3	1	4	4	34	0	0	1	252	272	371	643	119	305	23	3	285	84	-3	-0	+2	+2	+3	0.4
2021	25	MLB	Cleveland Indians	—	588	550	155	25	6	11	31	120	3	13	0	282	324	409	733	127	340	20	5	324	107	+5	+3	-0	+6	+13	2.7
2022	26	MLB	Cleveland Guardians	—	670	637	180	26	9	11	25	111	4	18	4	283	314	403	717	121	326	17	4	317	103	+2	+2	-2	+7	+15	2.4
2023	27	MLB	Los Angeles Dodgers	—	545	510	134	25	8	6	29	99	3	15	2	263	306	378	685	116	314	18	5	304	99	-1	+2	-8	+6	+12	1.2
2024	28	MLB	Cincinnati Reds	—	346	332	93	18	3	3	9	73	4	13	5	280	307	380	687	99	350	21	3	306	92	-3	+1	-6	-4	+7	-0.5
2025	29	MLB	New York Yankees	—	191	181	50	11	0	6	7	31	2	1	0	276	311	436	747	160	303	16	4	329	107	+1	+0	-5	+1	+4	0.1
2026	30	MLB	New York Yankees	—	244	227	54	6	1	10	14	57	0	3	1	238	282	405	687	167	270	23	6	301	86	-4	+0	-2	+1	+5	0.0
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4148	3915	1062	174	47	79	182	817	24	113	37	271	308	400	708	129	323	20	4	313	98	-10	+8	-40	+38	+90	8.7
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	17	ROK MLE	Kingsport Mets	—	226	216	41	6	3	2	7	61	1	2	6	190	219	273	492	83	249	27	3	217	33	—	—	—	—	—	—
2014	18	A MLE	Savannah Sand Gnats	—	31	30	4	0	1	1	1	14	0	0	0	133	161	300	461	167	164	45	3	152	-11	—	—	—	—	—	—
2015	19	A+ MLE	St. Lucie Mets	—	417	390	87	18	4	0	18	105	5	12	4	223	266	290	556	67	300	25	4	246	53	—	—	—	—	—	—
2016	20	AA MLE	Binghamton Mets	—	237	220	71	12	5	2	13	59	1	6	2	323	363	450	813	127	417	25	5	351	124	—	—	—	—	—	—
2016	20	A+ MLE	St. Lucie Mets	—	290	271	78	10	7	3	15	53	1	13	6	288	328	410	737	122	337	18	5	316	100	—	—	—	—	—	—
2017	21	MLB MLE	New York Mets	—	170	165	42	4	4	4	3	49	2	7	3	255	276	400	676	145	330	29	2	300	89	-2	+0	-3	+6	+4	0.5
2017	21	AAA MLE	Las Vegas 51s	—	425	399	117	16	5	5	17	91	4	19	6	293	329	396	725	103	359	21	4	315	99	—	—	—	—	—	—
2018	22	MLB MLE	New York Mets	—	592	558	147	28	8	9	25	119	3	24	11	263	299	391	689	127	310	20	4	303	91	-6	+0	-10	+6	+13	0.3
2019	23	MLB MLE	New York Mets	—	655	618	182	32	7	15	29	124	3	19	10	294	329	442	771	147	338	19	4	339	116	+12	-0	-6	+7	+14	2.8
2020	24	MLB MLE	New York Mets	—	147	143	37	3	1	4	4	34	0	0	1	259	279	378	657	119	305	23	3	292	84	-3	-0	+2	+2	+3	0.4
2021	25	MLB MLE	Cleveland Indians	—	588	550	156	25	7	11	31	120	3	13	0	284	325	415	740	131	340	20	5	326	107	+5	+3	-0	+6	+13	2.7
2022	26	MLB MLE	Cleveland Guardians	—	670	637	182	26	11	11	25	111	4	18	4	286	317	413	730	127	326	17	4	320	103	+2	+2	-2	+7	+15	2.4
2023	27	MLB MLE	Los Angeles Dodgers	—	545	510	138	26	10	6	29	99	3	15	2	271	314	396	710	125	314	18	5	315	99	-1	+2	-8	+6	+12	1.2
2024	28	MLB MLE	Cincinnati Reds	—	346	332	93	18	3	3	9	73	4	13	5	280	307	380	687	99	350	21	3	304	92	-3	+1	-6	-4	+7	-0.5
2025	29	MLB MLE	New York Yankees	—	191	181	50	11	0	6	7	31	2	1	0	276	311	436	747	160	303	16	4	326	107	+1	+0	-5	+1	+4	0.1
2026	30	MLB MLE	New York Yankees	—	244	227	53	6	1	9	14	57	0	3	1	233	278	388	666	154	270	23	6	296	86	-4	+0	-2	+1	+5	0.0
2013	17	ROK MLE	Kingsport Mets	—	226	216	41	6	3	2	7	61	1	2	6	190	219	273	492	83	252	27	3	217	33	—	—	—	—	—	—
2013	17	ROK RAW	Kingsport Mets	—	226	212	51	8	4	3	11	43	1	2	6	241	281	358	640	118	286	19	5	283	33	—	—	—	—	—	—
2014	18	A MLE	Savannah Sand Gnats	—	31	30	4	0	1	1	1	14	0	0	0	133	161	300	461	167	200	45	3	152	-11	—	—	—	—	—	—
2014	18	A RAW	Savannah Sand Gnats	—	31	30	4	0	1	1	1	11	0	0	0	133	161	300	461	167	167	35	3	200	-11	—	—	—	—	—	—
2015	19	A+ MLE	St. Lucie Mets	—	417	390	87	18	4	0	18	105	5	12	4	223	266	290	556	67	304	25	4	246	53	—	—	—	—	—	—
2015	19	A+ RAW	St. Lucie Mets	—	417	385	99	20	5	0	23	73	5	12	4	257	308	335	643	78	316	18	6	289	53	—	—	—	—	—	—
2016	20	A+ MLE	2 teams	—	527	492	148	22	12	4	27	112	2	19	8	301	340	419	758	118	377	21	5	332	111	—	—	—	—	—	—
2016	20	A+ RAW	2 teams	—	527	479	155	24	13	5	40	87	2	19	8	324	378	459	837	136	382	17	8	368	111	—	—	—	—	—	—
2017	21	AAA MLE	2 teams	—	595	564	159	20	9	9	20	140	6	26	9	282	314	397	711	115	357	24	3	311	96	—	—	—	—	—	—
2017	21	AAA RAW	2 teams	—	595	558	170	23	11	11	26	116	6	26	9	305	342	444	787	140	365	19	4	346	96	—	—	—	—	—	—
2018	22	MLB MLE	New York Mets	—	592	558	147	28	8	9	25	119	3	24	11	263	299	391	689	127	319	20	4	303	91	-6	+0	-10	+6	+13	0.3
2018	22	MLB RAW	New York Mets	—	592	554	142	26	8	9	29	119	3	24	11	256	297	381	678	125	310	20	5	299	91	-6	+0	-10	+6	+13	0.3
2019	23	MLB MLE	New York Mets	—	655	618	182	32	7	15	29	124	3	19	10	294	329	442	771	147	346	19	4	339	116	+12	-0	-6	+7	+14	2.8
2019	23	MLB RAW	New York Mets	—	655	616	177	30	7	15	31	124	3	19	10	287	325	432	756	144	338	19	5	333	116	+12	-0	-6	+7	+14	2.8
2020	24	MLB MLE	New York Mets	—	147	143	37	3	1	4	4	34	0	0	1	259	279	378	657	119	314	23	3	292	84	-3	-0	+2	+2	+3	0.4
2020	24	MLB RAW	New York Mets	—	147	143	36	3	1	4	4	34	0	0	1	252	272	371	643	119	305	23	3	285	84	-3	-0	+2	+2	+3	0.4
2021	25	MLB MLE	Cleveland Indians	—	588	550	156	25	7	11	31	120	3	13	0	284	325	415	740	131	343	20	5	326	107	+5	+3	-0	+6	+13	2.7
2021	25	MLB RAW	Cleveland Indians	—	588	550	155	25	6	11	31	120	3	13	0	282	324	409	733	127	340	20	5	324	107	+5	+3	-0	+6	+13	2.7
2022	26	MLB MLE	Cleveland Guardians	—	670	637	182	26	11	11	25	111	4	18	4	286	317	413	730	127	329	17	4	320	103	+2	+2	-2	+7	+15	2.4
2022	26	MLB RAW	Cleveland Guardians	—	670	637	180	26	9	11	25	111	4	18	4	283	314	403	717	121	326	17	4	317	103	+2	+2	-2	+7	+15	2.4
2023	27	MLB MLE	Los Angeles Dodgers	—	545	510	138	26	10	6	29	99	3	15	2	271	314	396	710	125	324	18	5	315	99	-1	+2	-8	+6	+12	1.2
2023	27	MLB RAW	Los Angeles Dodgers	—	545	510	134	25	8	6	29	99	3	15	2	263	306	378	685	116	314	18	5	304	99	-1	+2	-8	+6	+12	1.2
2024	28	MLB MLE	Cincinnati Reds	—	346	332	93	18	3	3	9	73	4	13	5	280	307	380	687	99	350	21	3	304	92	-3	+1	-6	-4	+7	-0.5
2024	28	MLB RAW	Cincinnati Reds	—	346	332	93	18	3	3	9	73	4	13	5	280	307	380	687	99	350	21	3	306	92	-3	+1	-6	-4	+7	-0.5
2025	29	MLB MLE	New York Yankees	—	191	181	50	11	0	6	7	31	2	1	0	276	311	436	747	160	303	16	4	326	107	+1	+0	-5	+1	+4	0.1
2025	29	MLB RAW	New York Yankees	—	191	181	50	11	0	6	7	31	2	1	0	276	311	436	747	160	303	16	4	329	107	+1	+0	-5	+1	+4	0.1
2026	30	MLB MLE	New York Yankees	—	244	227	53	6	1	9	14	57	0	3	1	233	278	388	666	154	268	23	6	296	86	-4	+0	-2	+1	+5	0.0
2026	30	MLB RAW	New York Yankees	—	244	227	54	6	1	10	14	57	0	3	1	238	282	405	687	167	270	23	6	301	86	-4	+0	-2	+1	+5	0.0
2013	17	ROK MLE	Kingsport Mets	—	226	216	41	6	3	2	7	61	1	2	6	190	219	273	492	83	249	27	3	217	33	—	—	—	—	—	—
2014	18	A MLE	Savannah Sand Gnats	—	31	30	4	0	1	1	1	14	0	0	0	133	161	300	461	167	164	45	3	152	-11	—	—	—	—	—	—
2015	19	A+ MLE	St. Lucie Mets	—	417	391	87	18	4	0	18	105	5	12	4	223	266	289	555	66	300	25	4	246	53	—	—	—	—	—	—
2016	20	A+ MLE	2 teams	—	527	493	148	22	12	4	27	112	2	19	8	300	340	418	758	118	373	21	5	332	111	—	—	—	—	—	—
2017	21	AAA MLE	2 teams	—	595	564	159	20	9	9	20	140	6	26	9	282	314	397	711	115	351	24	3	311	96	—	—	—	—	—	—
2018	22	MLB MLE	New York Mets	—	592	559	147	28	8	9	25	119	3	24	11	263	299	390	689	127	310	20	4	303	91	—	—	—	—	—	—
2019	23	MLB MLE	New York Mets	—	655	618	182	32	7	15	29	124	3	19	10	294	329	442	771	147	338	19	4	339	116	—	—	—	—	—	—
2020	24	MLB MLE	New York Mets	—	147	142	37	3	1	4	4	34	0	0	1	261	279	380	659	120	305	23	3	292	84	—	—	—	—	—	—
2021	25	MLB MLE	Cleveland Indians	—	588	549	156	25	7	11	31	120	3	13	0	284	325	415	741	131	340	20	5	326	107	—	—	—	—	—	—
2022	26	MLB MLE	Cleveland Guardians	—	670	636	182	26	11	11	25	111	4	18	4	286	317	414	730	127	326	17	4	320	103	—	—	—	—	—	—
2023	27	MLB MLE	Los Angeles Dodgers	—	545	508	138	26	10	6	29	99	3	15	2	272	314	398	711	126	314	18	5	315	99	—	—	—	—	—	—
2024	28	MLB MLE	Cincinnati Reds	—	346	330	93	18	3	3	9	73	4	13	5	282	307	382	689	100	350	21	3	304	92	—	—	—	—	—	—
2025	29	MLB MLE	New York Yankees	—	191	180	50	11	0	6	7	31	2	1	0	278	311	439	749	161	303	16	4	326	107	—	—	—	—	—	—
2026	30	MLB MLE	New York Yankees	—	244	228	53	6	1	9	14	57	0	3	1	232	278	386	664	154	270	23	6	296	86	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	28	MLB MLE	Cincinnati Reds	—	346	330	93	18	3	3	9	73	4	13	5	282	307	382	689	100	350	21	3	304	92	—	—	—	—	—	—
2025	29	MLB MLE	New York Yankees	—	191	180	50	11	0	6	7	31	2	1	0	278	311	439	749	161	303	16	4	326	107	—	—	—	—	—	—
2026	30	MLB MLE	New York Yankees	—	244	228	53	6	1	9	14	57	0	3	1	232	278	386	664	154	270	23	6	296	86	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	31	MLB MLE	NYY	100%	276	259	71	12	1	8	13	58	2	11	2	274	314	425	739	151	322	21	5	325	106	+2	+1	-4	+1	+6	0.5
▸ 2027 — real world (MLB)
2027	31	MLB CTX	NYY	100%	171	160	44	7	1	5	8	36	1	7	1	275	315	432	748	157	322	21	5	329	106	+1	+1	-2	+1	+4	0.4
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	32	MLB MLE	NYY	100%	159	149	40	6	1	5	8	34	1	4	1	266	305	409	714	143	315	21	5	315	99	-0	+0	-6	+1	+3	-0.1
2028	32	MLB CTX	NYY	100%	159	149	40	6	1	5	8	34	1	4	1	267	307	416	723	149	315	21	5	318	99	-0	+0	-6	+1	+3	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4307	4064	1102	180	48	84	190	851	25	117	38	271	308	401	709	130	323	20	4	313	95	-10	+8	-46	+39	+93	8.6
/ 162G	—	A+C		—	650	613	166	27	7	13	29	128	4	18	6	271	308	401	709	131	322	20	4	313	95	-2	+1	-7	+6	+14	1.3
Career	—	MLE		—	6104	5757	1561	254	79	100	262	1270	38	176	63	271	307	395	702	124	330	21	4	309	95	-9	+9	-48	+40	+97	9.0
/ 162G	—	MLE		—	650	613	166	27	8	11	28	135	4	19	7	271	307	395	702	124	329	21	4	309	95	-1	+1	-7	+6	+14	1.3

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.

2017 AAALas Vegas 51s · 425 PAwOBA .362 → .315 (−47)K% 15.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.76%	÷0.948	×1.290	—	—	21.45%
BB% (unintentional) /PA	5.41%	÷1.015	×0.710	—	×1.050	3.97%
HBP% /PA	0.94%	—	×0.980	—	×1.050	0.97%
Singles /BIP	29.45%	÷0.994	×0.900	×1.038	×1.050	29.07%
Doubles /BIP	5.83%	÷0.998	×0.810	×1.038	×1.050	5.16%
Triples /BIP	2.15%	÷1.111	×0.810	×1.038	×1.050	1.71%
Home runs /BIP	2.15%	÷1.209	×0.780	—	×1.050	1.45%

Factors used: league row PCL. Park (home-season share, regressed): HR 142, 1B 99, 2B 100, 3B 122, K 90, BB 103 — 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 ×1.038.

Result: wOBA .362 → .315; ISO .137 → .103; 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).

2016 A+St. Lucie Mets · 290 PAwOBA .347 → .316 (−31)K% 12.4% → 18.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.41%	÷0.959	×1.420	—	—	18.39%
BB% (unintentional) /PA	6.90%	÷1.032	×0.750	—	×1.027	5.15%
HBP% /PA	0.34%	—	×0.930	—	×1.027	0.33%
Singles /BIP	26.64%	÷0.994	×0.920	×1.031	×1.027	26.11%
Doubles /BIP	4.37%	÷0.956	×0.960	×1.031	×1.027	4.64%
Triples /BIP	3.49%	÷1.017	×0.810	×1.031	×1.027	2.95%
Home runs /BIP	1.31%	÷0.943	×0.880	—	×1.027	1.25%

Factors used: league row FSL. Park (home-season share, regressed): HR 89, 1B 99, 2B 91, 3B 103, K 92, BB 106 — 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 ×1.031.

Result: wOBA .347 → .316; ISO .132 → .119; BABIP .345 → .337. 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 AABinghamton Mets · 237 PAwOBA .377 → .351 (−26)K% 21.5% → 24.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.52%	÷1.062	×1.220	—	—	24.72%
BB% (unintentional) /PA	7.17%	÷0.996	×0.700	—	×1.050	5.30%
HBP% /PA	0.42%	—	×0.850	—	×1.050	0.38%
Singles /BIP	31.90%	÷1.034	×0.970	×1.004	×1.050	31.54%
Doubles /BIP	8.59%	÷1.070	×0.860	×1.004	×1.050	7.28%
Triples /BIP	3.07%	÷0.956	×0.950	×1.004	×1.050	3.22%
Home runs /BIP	1.23%	÷1.085	×0.780	—	×1.050	0.93%

Factors used: league row EL. Park (home-season share, regressed): HR 117, 1B 107, 2B 114, 3B 91, K 112, BB 99 — 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 ×1.004.

Result: wOBA .377 → .351; ISO .140 → .127; BABIP .433 → .417. 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+St. Lucie Mets · 417 PAwOBA .282 → .246 (−36)K% 17.5% → 25.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.51%	÷0.992	×1.420	—	—	25.06%
BB% (unintentional) /PA	5.52%	÷1.023	×0.750	—	×1.042	4.21%
HBP% /PA	1.20%	—	×0.930	—	×1.042	1.16%
Singles /BIP	23.72%	÷1.049	×0.920	×1.030	×1.042	22.32%
Doubles /BIP	6.41%	÷1.055	×0.960	×1.030	×1.042	6.26%
Triples /BIP	1.60%	÷0.900	×0.810	×1.030	×1.042	1.55%
Home runs /BIP	0.00%	÷1.269	×0.880	—	×1.042	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 154, 1B 110, 2B 111, 3B 80, K 98, BB 105 — 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 ×1.030.

Result: wOBA .282 → .246; ISO .078 → .071; BABIP .316 → .300. 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 ASavannah Sand Gnats · 31 PAwOBA .194 → .152 (−42)K% 35.5% → 46.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	35.48%	÷1.018	×1.340	—	—	46.71%
BB% (unintentional) /PA	3.23%	÷1.053	×0.660	—	×1.045	2.11%
HBP% /PA	0.00%	—	×0.770	—	×1.045	0.00%
Singles /BIP	10.53%	÷1.017	×0.920	—	×1.045	9.95%
Doubles /BIP	0.00%	÷0.984	×0.820	—	×1.045	0.00%
Triples /BIP	5.26%	÷0.908	×0.940	—	×1.045	5.70%
Home runs /BIP	5.26%	÷0.987	×0.820	—	×1.045	4.57%

Factors used: league row SAL. Park (home-season share, regressed): HR 97, 1B 103, 2B 97, 3B 82, K 104, BB 111 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average).

Result: wOBA .194 → .152; ISO .167 → .133; BABIP .167 → .164. 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).

2013 ROKKingsport Mets · 226 PAwOBA .278 → .217 (−61)K% 19.0% → 27.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.03%	÷1.000	×1.420	—	—	27.02%
BB% (unintentional) /PA	4.87%	÷1.000	×0.640	—	×1.022	3.19%
HBP% /PA	0.44%	—	×0.740	—	×1.022	0.33%
Singles /BIP	21.30%	÷1.000	×0.840	×1.050	×1.022	19.21%
Doubles /BIP	4.73%	÷1.000	×0.740	×1.050	×1.022	3.76%
Triples /BIP	2.37%	÷1.000	×0.740	×1.050	×1.022	1.88%
Home runs /BIP	1.78%	÷1.000	×0.800	—	×1.022	1.45%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .278 → .217; ISO .118 → .088; BABIP .286 → .249. 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
#1Felipe Lopezlast yr '11 career totals — 11 seasons, 4,864 PA	7.3	4,864	90	124	264	333	391	+31	-19	17.7	18.1
/162	664	12	17	+4.2	-2.6	2.4	pk7: 19
#2Josh Harrisonlast yr '23 career totals — 13 seasons, 4,347 PA	6.5	4,347	73	91	270	316	396	+14	+16	15.1	15.4
/162	664	11	14	+2.2	+2.4	2.3	pk7: 16
#3Todd Walker'96-'07 * career totals — 12 seasons, 5,055 PA	7.6	5,055	107	66	277*	335*	420*	+6	-24	13.7	13.9
/162	664	14	9	+0.9	-3.1	1.8	pk7: 14
#4Adam Kennedy'99-'12 * career totals — 14 seasons, 6,054 PA	9.1	6,054	80	179	263*	319*	375*	+11	+3	13.1	13.2
/162	664	9	20	+1.2	+0.4	1.4	pk7: 13
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 12 projected seasons	6.7	4,478	89	124	273	306	404	+16	-33	13.4	12.4
/162	664	13	18	+2.4	-4.9	2.0	pk7: 11
#5Mariano Duncan'85-'97 * career totals — 12 seasons, 4,998 PA	7.5	4,998	87	174	260*	295*	402*	+25	-15	9.1	9.4
/162	664	12	23	+3.3	-2.0	1.2	pk7: 10
#6Eduardo Núñezlast yr '19 career totals — 10 seasons, 3,006 PA	4.5	3,006	58	141	276	310	404	+19	-34	7.7	7.9
/162	664	13	31	+4.3	-7.6	1.7	pk7: 8

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
Amed Rosario (OGILVIE)	31	—	—	—	—	271/311/421	150	322	5	7	21%	5%	106	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Eduardo Núñez 2018 · MLB	31	58→65	49→50	56→60	46	290/324/436	147	311	16	30	13%	4%	114	+2.3	254/285/378	124	279	13	15	14%	4%	85	+0.2	242/267/351	108	267	11	10	14%	3%	72	-0.4
✕Jonathan Villar 2022 · MLB	31	51→60	50	53→65	48	254/321/408	154	319	18	24	26%	9%	106	+1.8	236/291/375	139	303	15	19	26%	7%	87	+0.4	222/266/342	120	290	10	25	26%	6%	68	-0.6
✕Jon Berti 2021 · MLB	31	55→62	45	58→60	53	264/350/394	130	333	12	30	23%	10%	114	+2.3	248/330/363	115	316	10	31	22%	10%	99	+1.3	268/335/372	103	335	9	39	21%	8%	103	+0.8
✕Cameron Maybin 2018 · MLB	31	52→60	45→50	57→55	54	252/327/377	125	300	12	30	20%	10%	101	+1.4	251/328/385	134	316	13	20	23%	10%	103	+1.6	255/333/386	131	328	12	16	24%	10%	106	+0.8
✕Hernán Pérez 2022 · MLB	31	47→57	48→50	52→55	43	238/285/377	138	300	16	15	26%	6%	86	+0.3	218/264/334	116	278	13	20	26%	5%	68	-1.0	201/245/310	110	254	13	20	26%	5%	54	-1.0
✕Elvis Andrus 2020 · MLB	31	54→61	44→50	53→60	47	264/308/386	122	295	12	20	15%	6%	96	+1.0	245/295/359	114	277	11	17	15%	6%	84	+0.2	245/297/358	113	280	10	17	16%	6%	86	+0.2
✕Will Venable 2014 · MLB	31	52→55	53→55	61→60	45	262/312/449	187	310	19	26	22%	6%	112	+2.2	234/292/362	128	293	13	18	24%	7%	84	+0.2	215/277/310	95	275	9	16	24%	7%	66	-0.7
✕Justin Greene 2017 · AAA	31	56→62	42→50	56→60	45	268/318/380	111	336	9	29	22%	6%	97	+1.1	271/321/387	116	343	12	38	23%	6%	101	+1.4	283/332/392	109	359	12	49	23%	6%	102	+0.7
✕Ian Desmond 2017 · MLB	31	52→62	51→60	51→55	44	259/312/416	157	326	19	16	26%	7%	105	+1.7	247/306/396	149	306	17	17	24%	7%	98	+1.2	235/298/390	155	287	18	15	24%	7%	95	+0.8
✕Darnell McDonald 2011 · MLB	32	51→55	49→55	56→55	44	252/299/413	161	309	15	15	23%	6%	99	+1.2	224/285/362	138	271	14	10	22%	7%	82	+0.0	198/263/310	112	238	12	9	21%	7%	61	-0.7
✕Jose Castillo 2012 · AAA	31	55→57	45→50	51→50	48	271/308/395	124	285	12	17	10%	5%	98	+1.2	268/295/393	125	288	15	12	13%	4%	93	+0.8	267/292/387	120	289	14	10	13%	3%	89	+0.4
✕Alejandro De Aza 2014 · MLB	30	55→61	46→50	52→55	48	267/326/405	137	320	13	21	20%	7%	107	+1.8	249/314/389	140	311	12	15	23%	8%	99	+1.2	242/311/378	136	306	11	14	23%	8%	96	+0.7
✕Masataka Yoshida 2024 · MLB	31	55→57	49→50	54→45	49	273/324/427	154	296	16	9	14%	6%	112	+2.2	266/327/402	136	288	14	7	13%	7%	107	+1.8	263/330/387	123	283	13	5	12%	7%	106	+0.9
✕Whit Merrifield 2020 · MLB	31	61→63	49→55	56→60	48	299/347/457	159	339	14	24	16%	6%	126	+3.2	279/325/420	141	314	13	24	15%	6%	109	+2.0	266/312/394	128	296	12	27	14%	6%	100	+1.1
✕Mike Aviles 2012 · MLB	31	52→61	47→50	53→55	45	259/291/395	137	280	14	19	14%	4%	91	+0.7	244/278/369	125	263	14	16	13%	4%	80	-0.1	238/271/349	111	256	12	16	13%	4%	74	-0.4
✕Drew Stubbs 2015 · MLB	30	50→57	48→50	57→60	44	245/305/392	146	336	16	24	30%	8%	97	+1.1	222/297/354	132	325	14	22	33%	9%	85	+0.2	197/281/304	107	299	11	23	35%	10%	66	-0.5
✕Wynton Bernard 2023 · MLB	32	49→59	46→45	62→60	44	242/286/382	140	287	13	30	21%	5%	86	+0.3	236/282/346	110	292	9	33	22%	6%	77	-0.3	231/279/323	91	291	7	39	22%	5%	66	-0.8
✕Jason Bartlett 2011 · MLB	31	57→65	43→45	53→55	52	273/337/393	120	314	8	20	16%	8%	108	+1.9	238/307/326	88	287	5	17	18%	8%	82	-0.0	245/310/308	63	293	2	22	16%	8%	78	-0.3
●Josh Harrison 2018 · MLB	31	55→63	46→55	51→55	44	271/321/407	136	305	13	15	16%	4%	106	+1.8	242/297/370	128	276	14	10	17%	5%	88	+0.5	257/320/371	113	296	10	6	16%	5%	98	+0.7
✕Rafael Ortega 2022 · MLB	31	49→55	53→55	48→55	49	253/317/425	172	297	21	17	22%	8%	109	+2.0	228/312/354	126	278	13	20	22%	11%	91	+0.7	210/304/322	112	258	11	24	22%	12%	80	-0.1

Amed Rosario

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps