Jose Ramos — OGILVIE

Jose RamosSS San Jose Giants

Age 23 R/R 5'11" / 143 lbs A BB -3% Svc 0.0 · Ctrl thru 2036 peak 0.8 · 2030

wRC+†60

AVG/OBP/SLG.192 / .281 / .287

PA207

HR3

SB7

K%32

BB%9

MLB%0%

Scouting · now → future

HIT

34↗39

PWR

34↗39

SPD

60↗65

EYE

59↗64

trajectory · 10 yrs

0.8peak

2030

Contract

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

Status MiLB

MLB Debut 2031

Service 0 yrs (est)

Team Control Through 2036

First FA Year 2037

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2031
2027	MiLB	still in minors · estimated debut 2031
2028	MiLB	still in minors · estimated debut 2031
2029	MiLB	still in minors · estimated debut 2031
2030	MiLB	still in minors · estimated debut 2031
2031	Arb-3	$0.9M	+0.7	$3M	+$2M
2032	Ext / FA-deal	$0.9M	+0.6	$3M	+$2M
2033	Ext / FA-deal	$1.0M	+0.4	$2M	+$1M
2034	Ext / FA-deal	$0.4M	+0.2	$1M	+$0.6M
2035	Ext / FA-deal	$0.4M	—	—	—
2036	Ext / FA-deal	$0.6M	—	—	—
Totals		$4M		$6M	+$2M

Career Projections (MLE)

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	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
2021	18	ROK	DSL Giants Black	110	104	18	2	3	2	5	33	1	6	3	.173	.218	.308	.526	.135	.232	30	5	.227	32	-8	+0	+0	+1	+3	-0.4
2022	19	ROK	DSL Giants Orange	181	158	30	7	1	2	18	40	3	22	1	.190	.285	.285	.570	.095	.239	22	10	.261	58	-9	+4	+0	+2	+5	0.3
2023	20	A	2 teams	398	354	57	13	4	2	26	135	13	33	5	.161	.244	.237	.482	.076	.249	34	7	.214	22	-35	+5	+0	+4	+11	-1.5
2024	21	ROK	ACL Giants	177	152	34	6	2	1	20	48	2	13	2	.224	.322	.309	.631	.086	.314	27	11	.272	66	-7	+2	+0	+2	+5	0.2
2025	22	A	2 teams	221	192	33	4	1	3	24	72	4	20	3	.172	.277	.250	.527	.078	.254	33	11	.237	40	-15	+3	+0	+2	+6	-0.4
▸ 2026 Season
2026	23	MLB	SF	207	182	36	7	1	3	19	65	4	7	1	.198	.288	.297	.585	.099	.281	31	9	.264	60	-9	+1	+0	+2	+6	-0.0
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	24	MLB 10%	SF	263	232	47	9	2	4	25	80	4	9	2	.203	.291	.310	.602	.108	.283	30	10	.276	69	-9	+1	+0	+3	+7	0.2
2028	25	MLB 25%	SF	337	297	61	11	2	6	32	100	5	11	2	.205	.293	.316	.610	.111	.285	30	9	.283	75	-9	+1	+0	+4	+10	0.5
2029	26	MLB 42%	SF	387	340	71	13	2	8	38	113	6	12	2	.209	.299	.329	.629	.121	.286	29	10	.287	78	-10	+2	+0	+4	+11	0.7
2030	27	MLB 58%	SF	411	362	75	14	2	8	40	120	6	12	2	.207	.297	.323	.620	.116	.286	29	10	.288	79	-10	+2	+0	+4	+12	0.8
2031	28	MLB 68%	SF	423	371	77	14	2	9	42	124	7	12	2	.208	.300	.329	.629	.121	.286	29	10	.287	78	-11	+2	-1	+5	+12	0.7
2032	29	MLB 77%	SF	423	371	76	14	2	8	42	125	7	11	1	.205	.298	.318	.616	.113	.285	30	10	.285	76	-11	+2	-1	+5	+12	0.6
2033	30	MLB 84%	SF	420	369	75	14	2	8	42	126	6	11	1	.203	.295	.317	.612	.114	.283	30	10	.282	74	-12	+2	-2	+4	+12	0.4
2034	31	MLB 91%	SF	409	359	71	13	2	7	41	124	6	9	0	.198	.291	.304	.594	.106	.282	30	10	.278	71	-13	+2	-3	+4	+12	0.2
2035	32	MLB	SF	393	345	68	12	2	7	39	122	6	8	0	.197	.290	.304	.594	.107	.280	31	10	.274	68	-14	+2	-4	+4	+11	-0.1
2036	33	MLB	SF	365	321	62	11	2	6	36	115	5	7	0	.193	.285	.296	.580	.103	.278	32	10	.268	64	-15	+1	-4	+4	+10	-0.4
2037	34	MLB	SF	321	281	54	10	2	5	32	104	5	6	0	.192	.286	.295	.582	.103	.276	32	10	.262	59	-15	+1	-5	+3	+9	-0.6
▸ Career Totals (MLE all levels + projections)
Career	—			5446	4790	945	174	34	89	521	1646	90	209	27	.197	.288	.304	.592	.106	.277	30	10	.271	65	-213	+31	-20	+58	+154	1.1
/ 162G	—			650	572	113	21	4	11	62	196	11	25	3	.198	.289	.306	.595	.108	.276	30	10	.271	65	-25	+4	-2	+7	+18	0.1

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

Year	Age	Lvl	Team	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
2021	18	ROK	DSL Giants Black	110	98	24	3	4	3	11	24	1	6	3	.245	.327	.449	.776	.204	.296	22	10	.342	120	+2	+0	—	—	+3	0.6
2022	19	ROK	DSL Giants Orange	181	147	40	11	1	3	29	28	3	22	1	.272	.402	.422	.824	.150	.316	15	16	.370	142	+9	+4	—	—	+5	1.8
2023	20	A	San Jose Giants	368	318	67	16	5	2	35	87	11	29	4	.211	.310	.311	.622	.101	.280	24	10	.286	77	-10	+4	—	—	+10	0.5
2023	20	ROK	ACL Giants Black	30	25	4	1	0	0	2	9	2	4	1	.160	.276	.200	.476	.040	.235	30	7	.229	33	-2	+0	—	—	+1	-0.1
2024	21	ROK	ACL Giants	177	138	39	7	2	1	34	33	2	13	2	.283	.431	.384	.815	.101	.358	19	19	.371	142	+8	+2	—	—	+5	1.6
2025	22	A+	Eugene Emeralds	91	73	19	2	0	1	14	24	3	6	3	.260	.400	.329	.729	.068	.367	26	15	.342	120	+2	+0	—	—	+3	0.5
2025	22	A	San Jose Giants	130	107	22	4	1	3	22	29	1	14	0	.206	.346	.346	.692	.140	.253	22	17	.321	104	+1	+3	—	—	+4	0.7

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
Jose Ramos (OGILVIE)	23	34→39	34→39	60→65	64	.192/.281/.287	.095	.281	3	7	32%	9%	60	-0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Cooper Bowman 2023 · A	23	39→42	43→45	58→60	44	.194/.275/.303	.109	.285	11	30	34%	8%	61	-1.0	.204/.277/.322	.118	.283	12	35	30%	8%	67	-0.5	.200/.273/.320	.120	.271	12	40	29%	8%	62	-0.6
✕Clay Fuller 2010 · A	23	44→46	42→45	56→55	46	.208/.289/.317	.109	.297	9	20	31%	9%	70	-0.3	.210/.272/.325	.115	.292	12	17	31%	7%	65	-0.7	.206/.260/.324	.118	.278	15	16	31%	5%	56	-0.8
✕Ronaldo Urdaneta 2022 · A	23	43	41→40	57→60	40	.203/.269/.298	.096	.321	9	24	38%	7%	56	-1.3	.188/.271/.269	.081	.305	6	20	37%	9%	51	-1.7	.098/.228/.122	.024	.176	0	28	38%	12%	-2	-1.2
✕Braulio Vasquez 2022 · A	23	40	40	54→65	40	.192/.269/.282	.090	.299	8	28	36%	7%	53	-1.5	.216/.284/.315	.099	.302	7	27	29%	7%	67	-0.5	.225/.290/.320	.095	.304	4	32	25%	7%	66	-0.3
✕Hayden Cantrelle 2022 · AA	23	35	41→45	54→55	54	.169/.297/.268	.099	.266	8	23	35%	14%	64	-0.8	.189/.306/.297	.108	.297	8	20	34%	13%	74	-0.1	.191/.310/.302	.111	.299	9	21	34%	12%	74	-0.0
✕Adam Engel 2015 · A	23	45→48	40→50	57→60	39	.215/.266/.310	.095	.290	7	24	28%	5%	58	-1.2	.203/.259/.302	.099	.292	7	30	31%	6%	53	-1.5	.227/.287/.366	.138	.305	13	23	28%	5%	79	+0.1
✕Jacob Young 2022 · A	23	43→53	38→40	57→60	43	.206/.257/.288	.083	.264	5	20	24%	6%	48	-1.9	.238/.299/.313	.075	.302	4	31	21%	6%	72	-0.2	.248/.310/.323	.074	.311	3	36	20%	6%	76	+0.1
✕Max Ferguson 2023 · A	23	37→34	39→40	63→60	51	.177/.278/.266	.090	.267	7	31	33%	12%	53	-1.5	.181/.264/.273	.092	.273	8	29	34%	10%	49	-1.8	.174/.253/.257	.083	.252	9	32	32%	9%	37	-1.8
✕Samad Taylor 2021 · A	23	37→47	41→50	53→65	44	.181/.257/.285	.104	.262	8	23	32%	8%	49	-1.8	.226/.297/.368	.142	.326	16	33	33%	8%	87	+0.8	.236/.312/.377	.141	.324	16	46	30%	9%	94	+0.8
✕Jared Oliva 2019 · A	23	46	42→50	55→65	43	.222/.290/.334	.112	.306	9	23	29%	7%	75	-0.0	.220/.280/.317	.097	.306	8	25	29%	6%	66	-0.6	.224/.292/.359	.135	.282	14	55	25%	7%	78	+0.1
✕Corey Joyce 2022 · AA	23	41	39→45	53→50	39	.193/.262/.274	.080	.300	7	13	36%	7%	48	-1.9	.208/.307/.328	.120	.294	12	12	31%	10%	82	+0.5	.212/.315/.318	.105	.301	9	14	29%	10%	80	+0.2
✕Wes Rogers 2017 · A	23	45→51	39→40	61→65	44	.217/.276/.302	.085	.284	6	31	25%	7%	60	-1.0	.216/.269/.304	.088	.297	6	33	27%	6%	57	-1.2	.206/.258/.289	.083	.292	6	34	30%	6%	47	-1.3
✕Hoy Park 2019 · A	23	44→50	39→45	56→55	49	.210/.288/.294	.085	.276	6	17	25%	9%	63	-0.8	.228/.306/.323	.095	.301	7	16	25%	9%	79	+0.3	.219/.306/.338	.119	.290	13	18	27%	10%	79	+0.2
✕Jon Matthews 2014 · A	23	41	37→40	58→60	41	.196/.260/.271	.075	.276	4	25	29%	6%	46	-2.0	.231/.298/.298	.067	.313	3	17	25%	7%	68	-0.5	.242/.313/.293	.051	.324	2	16	24%	8%	70	-0.1
✕Justin Dean 2021 · A	24	45→47	41→45	57→65	43	.217/.284/.321	.104	.304	8	22	30%	7%	69	-0.4	.201/.276/.308	.107	.320	10	27	37%	7%	63	-0.8	.208/.288/.296	.088	.322	8	47	35%	9%	62	-0.6
✕Todd Hankins 2014 · A	23	39→48	39→40	58→55	41	.190/.257/.277	.087	.284	7	26	34%	7%	46	-2.0	.202/.254/.295	.093	.297	7	22	33%	6%	49	-1.8	.200/.246/.281	.080	.295	7	22	33%	5%	38	-1.6
✕Cade Gotta 2015 · A	23	42→51	39→45	54→55	46	.198/.272/.289	.091	.280	5	15	29%	8%	56	-1.3	.217/.267/.318	.101	.286	7	21	25%	6%	60	-1.0	.241/.300/.342	.101	.308	6	36	22%	8%	78	+0.1
✕Kenny Wilson 2013 · A	23	43→50	36→40	58→60	44	.199/.275/.267	.068	.284	3	29	29%	7%	52	-1.6	.220/.279/.306	.086	.306	5	27	28%	6%	63	-0.9	.199/.267/.293	.094	.305	8	22	35%	7%	52	-0.6
✕Darin Mastroianni 2009 · A	23	43→53	38→40	59→60	42	.205/.259/.283	.078	.276	5	21	27%	6%	48	-1.9	.248/.313/.322	.074	.318	3	35	21%	8%	80	+0.4	.258/.326/.333	.075	.324	2	38	19%	9%	85	+0.6
✕Levi Michael 2014 · A	23	42→52	37→45	55	49	.197/.274/.273	.076	.263	4	12	25%	9%	53	-1.5	.221/.289/.307	.086	.294	5	16	25%	7%	67	-0.5	.227/.293/.340	.113	.317	11	11	30%	5%	75	-0.0

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)