Jose Contreras — OGILVIE

Jose ContrerasOF Charleston RiverDogs

Age 21 R/R 6'1" / 200 lbs A Svc 0.0 · Ctrl thru 2036 peak 0.8 · 2031

wRC+†67

AVG/OBP/SLG.205 / .275 / .324

PA98

HR2

K%30

BB%8

MLB%0%

Scouting · now → future

HIT

25↗30

PWR

32↗37

SPD

48↗53

EYE

41↗46

trajectory · 10 yrs

0.8peak

2032

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	+0.8	$4M	+$3M
2032	Ext / FA-deal	$0.9M	+0.8	$4M	+$3M
2033	Ext / FA-deal	$1.0M	+0.6	$3M	+$2M
2034	Ext / FA-deal	$1M	+0.5	$3M	+$2M
2035	Ext / FA-deal	$1M	+0.3	$2M	+$0.6M
2036	Ext / FA-deal	$0.6M	+0.1	$0.5M	-$0.1M
Totals		$5M		$15M	+$10M

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
2022	17	ROK	DSL Rays	211	190	29	4	2	1	14	95	4	3	3	.153	.226	.211	.436	.058	.289	45	7	.192	5	-23	-1	+0	-1	+6	-1.9
2023	18	ROK	DSL Tampa Bay	103	94	9	2	1	2	6	50	2	2	3	.096	.167	.202	.369	.106	.163	49	6	.164	-16	-14	-1	+0	-1	+3	-1.2
2024	19	ROK	FCL Rays	187	167	27	7	1	1	11	60	7	6	4	.162	.243	.234	.477	.072	.243	32	6	.220	27	-16	-0	+0	-1	+5	-1.2
2025	20	A	2 teams	93	86	16	3	0	1	4	37	2	3	1	.186	.239	.256	.495	.070	.312	40	4	.213	21	-8	+0	+0	-1	+3	-0.6
▸ 2026 Season
2026	21	MLB	TB	98	89	18	3	1	2	8	30	1	2	0	.202	.276	.326	.601	.124	.283	31	8	.273	67	-4	+0	+0	-1	+3	-0.1
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	22	MLB 11%	TB	198	178	38	7	1	5	16	57	2	4	1	.213	.286	.348	.634	.135	.284	29	8	.286	77	-5	+0	+0	-1	+6	-0.0
2028	23	MLB 28%	TB	311	277	61	11	2	8	27	87	4	6	2	.220	.299	.361	.660	.141	.285	28	9	.294	84	-6	+0	+0	-2	+9	0.2
2029	24	MLB 45%	TB	392	349	78	14	2	11	35	108	5	8	2	.223	.303	.370	.673	.146	.286	28	9	.300	88	-5	+1	+0	-2	+11	0.4
2030	25	MLB 60%	TB	438	390	87	16	2	12	40	119	5	9	2	.223	.303	.367	.670	.144	.287	27	9	.304	91	-5	+1	+0	-3	+12	0.6
2031	26	MLB 85%	TB	466	414	93	17	3	13	43	127	6	10	2	.225	.307	.374	.681	.150	.287	27	9	.306	92	-4	+1	+0	-3	+13	0.8
2032	27	MLB	TB	478	424	96	17	3	14	45	130	6	10	2	.226	.309	.380	.689	.153	.287	27	9	.306	92	-4	+1	+0	-3	+14	0.8
2033	28	MLB	TB	481	427	96	17	3	14	45	132	6	9	2	.225	.308	.377	.685	.152	.287	27	9	.305	91	-5	+1	-1	-3	+14	0.6
2034	29	MLB	TB	476	422	93	17	2	13	45	132	6	9	1	.220	.304	.363	.667	.142	.286	28	9	.302	90	-6	+1	-1	-3	+13	0.5
2035	30	MLB	TB	468	416	91	17	2	13	44	131	5	8	1	.219	.301	.363	.664	.144	.285	28	9	.299	87	-7	+1	-2	-3	+13	0.3
2036	31	MLB	TB	456	405	87	16	2	12	43	130	5	7	0	.215	.298	.353	.651	.138	.283	29	9	.295	84	-8	+1	-3	-3	+13	0.1
2037	32	MLB	TB	439	390	83	15	2	11	41	127	5	7	0	.213	.296	.346	.642	.133	.282	29	9	.291	81	-10	+1	-4	-3	+12	-0.2
2038	33	MLB	TB	410	365	76	14	2	10	38	122	4	6	0	.208	.290	.340	.630	.132	.280	30	9	.285	77	-11	+1	-4	-2	+12	-0.5
2039	34	MLB	TB	366	325	66	12	2	8	34	112	4	5	0	.203	.287	.326	.613	.123	.278	31	9	.279	72	-12	+1	-5	-2	+10	-0.8
▸ Career Totals (MLE all levels + projections)
Career	—			6071	5408	1144	209	33	151	539	1786	79	114	26	.212	.292	.346	.639	.135	.284	29	9	.287	78	-150	+12	-20	-36	+172	-2.2
/ 162G	—			650	579	122	22	4	16	58	191	8	12	3	.211	.291	.345	.637	.135	.283	29	9	.287	78	-16	+1	-2	-4	+18	-0.3

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
2022	17	ROK	DSL Rays	211	179	41	7	2	2	25	64	4	3	3	.229	.337	.324	.661	.095	.336	30	12	.303	90	-2	-1	—	—	+6	0.3
2023	18	ROK	DSL Tampa Bay	103	87	15	5	1	3	13	35	2	2	3	.172	.294	.356	.650	.184	.240	34	13	.294	83	-2	-1	—	—	+3	0.0
2024	19	ROK	FCL Rays	187	160	40	10	3	2	18	40	7	6	4	.250	.351	.388	.739	.138	.319	21	10	.332	113	+3	-0	—	—	+5	0.8
2025	20	A	Charleston RiverDogs	54	49	11	1	0	0	4	17	0	1	0	.224	.283	.245	.528	.020	.344	31	7	.243	44	-3	+0	—	—	+2	-0.2
2025	20	ROK	FCL Rays	39	35	10	3	0	1	2	9	2	2	1	.286	.359	.457	.816	.171	.360	23	5	.365	137	+2	+0	—	—	+1	0.3

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 Contreras (OGILVIE)	21	25→30	32→37	48→53	46	.205/.275/.324	.119	.283	2	2	30%	8%	67	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Iverson Leonardo 2023 · A	21	37	44→50	49→50	40	.188/.259/.305	.117	.281	12	9	36%	7%	55	-1.4	.194/.278/.291	.097	.346	7	8	42%	9%	59	-1.1	.146/.273/.221	.075	.359	3	4	52%	12%	39	-0.5
✕Luis Hidalgo 2017 · A	21	39	43→45	46→45	44	.196/.254/.303	.107	.234	12	12	22%	6%	52	-1.6	.223/.274/.346	.123	.264	13	9	21%	5%	71	-0.3	.259/.302/.380	.121	.288	12	8	14%	4%	89	+0.4
✕Anderson Gomes 2007 · A	22	41→38	43→45	47→50	39	.205/.252/.313	.108	.275	10	9	29%	5%	53	-1.5	.220/.270/.333	.113	.292	11	7	27%	6%	66	-0.6	.223/.275/.335	.112	.290	12	5	26%	6%	67	-0.2
✕Jose Meza 2023 · A	20	41→35	41→45	47→50	40	.199/.265/.295	.096	.286	9	10	32%	6%	55	-1.4	.204/.294/.305	.101	.301	9	8	32%	10%	70	-0.3	.186/.292/.283	.097	.277	9	10	33%	11%	63	-0.5
✕Rudy van Heydoorn 2010 · A	21	33	41→45	41→50	41	.168/.252/.259	.091	.262	9	8	37%	8%	41	-2.3	.197/.275/.307	.110	.307	11	5	36%	9%	63	-0.9	.204/.303/.338	.134	.292	14	2	32%	11%	83	+0.2
✕Stanley Martinez 2018 · A	21	41	40→45	49→50	46	.200/.273/.294	.093	.261	7	8	25%	7%	58	-1.2	.224/.288/.327	.103	.314	9	7	30%	7%	72	-0.2	.220/.280/.293	.072	.342	5	3	34%	6%	56	-0.4
✕Carlos Dominguez 2021 · A	21	43→27	42→45	51→50	36	.201/.283/.313	.112	.310	9	12	35%	5%	68	-0.5	.173/.247/.300	.127	.331	15	12	50%	5%	50	-1.8	.134/.213/.254	.119	.278	17	13	54%	6%	21	-1.6
✕Misael Urbina 2023 · A	21	38→30	41→45	49→50	45	.187/.256/.291	.104	.256	8	12	29%	8%	50	-1.8	.177/.255/.265	.088	.259	6	9	31%	9%	43	-2.2	.164/.251/.245	.081	.237	5	8	30%	9%	33	-1.7
✕Johan Mieses 2016 · A	21	41→32	45→55	53→50	39	.208/.253/.334	.126	.273	12	15	28%	5%	59	-1.1	.188/.236/.349	.161	.267	20	5	37%	5%	56	-1.3	.194/.269/.375	.181	.237	26	7	31%	7%	74	-0.0
✕Jorge Alcantara 2013 · A	21	43	41→45	50	43	.204/.273/.304	.100	.299	8	11	32%	8%	59	-1.1	.191/.262/.285	.094	.292	6	14	34%	8%	50	-1.7	.147/.226/.244	.097	.221	6	25	34%	8%	24	-0.9
✕Imbewer Alvarez 2007 · A	21	42	39→40	45→55	37	.199/.254/.291	.092	.307	6	8	35%	6%	48	-1.9	.213/.277/.298	.085	.301	6	15	29%	7%	60	-1.0	.216/.288/.295	.079	.292	7	22	26%	7%	60	-0.3
✕Sean Coyle 2013 · A	21	37→36	45→50	54→50	38	.192/.253/.319	.127	.271	12	13	33%	6%	56	-1.3	.204/.262/.355	.151	.295	18	14	36%	6%	69	-0.4	.197/.258/.362	.165	.284	22	15	38%	7%	67	-0.3
✕Zack Larson 2015 · A	21	46→37	39→45	52→50	41	.221/.275/.306	.085	.293	6	11	26%	5%	61	-1.0	.196/.253/.258	.062	.265	2	11	25%	6%	39	-2.5	.171/.232/.215	.044	.233	0	12	25%	6%	19	-2.9
✕Payton Henry 2018 · A	21	40→31	41→45	46→30	38	.191/.255/.294	.102	.304	8	4	38%	7%	50	-1.7	.187/.253/.289	.102	.316	10	2	41%	6%	48	-1.9	.246/.293/.382	.135	.322	19	1	29%	4%	83	+0.2
✕Cole Roederer 2021 · A	21	38→33	43→45	51→50	43	.192/.259/.300	.108	.274	11	13	33%	8%	53	-1.5	.205/.268/.319	.114	.301	12	12	34%	7%	62	-0.9	.179/.252/.298	.118	.265	14	11	36%	8%	49	-1.0
✕Tyler Kolodny 2010 · A	22	40→34	44→45	49→50	40	.200/.267/.320	.119	.267	12	8	29%	6%	63	-0.9	.206/.277/.341	.135	.271	14	9	29%	6%	72	-0.2	.206/.284/.354	.148	.258	17	10	26%	5%	76	+0.0
✕Kyle Nevin 2023 · A	21	42→40	40→45	52→50	39	.201/.254/.299	.098	.279	6	10	29%	5%	50	-1.8	.218/.276/.321	.103	.329	9	10	34%	7%	65	-0.7	.213/.274/.311	.098	.326	9	12	35%	7%	59	-0.6
✕Alexander Campos 2022 · A	22	43	42→40	46→45	48	.209/.289/.317	.108	.281	9	6	28%	9%	70	-0.3	.221/.304/.311	.090	.312	8	6	29%	9%	75	-0.0	.236/.329/.308	.072	.330	7	6	28%	11%	83	+0.2
✕Allan Cerda 2021 · A	21	44→24	42→55	47→45	42	.213/.292/.320	.108	.301	10	6	31%	7%	73	-0.1	.189/.282/.362	.173	.292	20	5	40%	9%	80	+0.4	.158/.266/.332	.174	.243	22	5	42%	10%	64	-0.5
✕Jose Medina 2008 · A	21	42	44→45	45→50	46	.210/.285/.326	.117	.274	12	9	27%	8%	71	-0.3	.205/.283/.322	.117	.286	11	8	30%	8%	69	-0.4	.181/.269/.305	.124	.250	11	4	30%	6%	59	-0.2

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)