Javier Roman — OGILVIE

Javier RomanC FCL Twins

Age 23 R/R 6'0" / 155 lbs ROK Svc 0.0 · Ctrl thru 2037

2026 FULL-SEASON PROJECTIONpark-neutral Marcel · 77 proj PA

wRC+†59

AVG/OBP/SLG.202 / .266 / .291

PA7

HR0

K%30

BB%7

ISO90

MLB%0%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$5M ctrl surplus

Tools · Contract

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

Status MiLB

MLB Debut 2032

Service 0 yrs (est)

Team Control Through 2037

First FA Year 2038

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2032
2027	MiLB	still in minors · estimated debut 2032
2028	MiLB	still in minors · estimated debut 2032
2029	MiLB	still in minors · estimated debut 2032
2030	MiLB	still in minors · estimated debut 2032
2031	MiLB	still in minors · estimated debut 2032
2032	Pre-Arb	$0.9M	+0.1	$0.3M	+$0.0M (cut)
2033	Pre-Arb	$1.0M	—	—	—
2034	Ext	beyond projection horizon · no WAR estimate
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
2037	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$0.3M	+$0.0M

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. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve. Catcher framing: only 2026 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run below FG-DC by 1-3 WAR.

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)
2022	19	ROK	DSL Twins	—	67	55	6	0	0	0	6	21	4	1	1	109	246	109	355		171	31	9	187	13	-7	-0	—	—	+1	-0.6
2023	20	ROK	DSL Twins	—	115	99	28	7	0	2	14	20	1	0	1	283	377	414	791	131	333	17	12	355	127	+4	-0	—	—	+2	0.6
2024	21	ROK	FCL Twins	—	105	96	29	6	1	0	7	21	2	0	0	302	362	385	747	83	387	20	7	339	115	+2	+0	—	—	+2	0.4
2025	22	A	Fort Myers Mighty Mussels	—	29	22	1	0	0	0	7	12	0	0	0	45	276	45	321		100	41	24	200	21	-3	+0	—	—	+1	-0.2
2025	22	ROK	FCL Twins	—	32	28	6	1	0	2	4	14	0	0	0	214	312	464	777	250	333	44	12	342	118	+1	+0	—	—	+1	0.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2022	19	ROK MLE	DSL Twins	—	67	58	5	0	0	0	3	31	4	1	1	86	185	86	271		149	46	4	128	-27	-10	-0	—	—	+1	-0.9
2023	20	ROK MLE	DSL Twins	—	115	104	21	5	0	2	9	29	1	0	1	202	272	308	580	106	248	25	8	245	52	-7	-0	—	—	+2	-0.5
2024	21	ROK MLE	FCL Twins	—	105	99	21	4	1	0	4	31	2	0	0	212	257	273	530	61	311	30	4	235	45	-7	+0	—	—	+2	-0.5
2025	22	A MLE	Fort Myers Mighty Mussels	—	29	24	1	0	0	0	5	17	0	0	0	42	207	42	249		89	59	17	137	-21	-4	+0	—	—	+1	-0.4
2025	22	ROK MLE	FCL Twins	—	32	29	3	0	0	1	3	20	0	0	0	103	188	207	394	103	251	62	9	181	9	-3	+0	—	—	+1	-0.3
2022	19	ROK MLE	DSL Twins	—	67	58	5	0	0	0	3	31	4	1	1	86	185	86	271		179	46	4	128	-27	—	—	—	—	—	—
2022	19	ROK RAW	DSL Twins	—	67	55	6	0	0	0	6	21	4	1	1	109	246	109	355		171	31	9	187	-27	—	—	—	—	—	—
2023	20	ROK MLE	DSL Twins	—	115	104	21	5	0	2	9	29	1	0	1	202	272	308	580	106	257	25	8	245	52	—	—	—	—	—	—
2023	20	ROK RAW	DSL Twins	—	115	99	28	7	0	2	14	20	1	0	1	283	377	414	791	131	333	17	12	355	52	—	—	—	—	—	—
2024	21	ROK MLE	FCL Twins	—	105	99	21	4	1	0	4	31	2	0	0	212	257	273	530	61	309	30	4	235	45	—	—	—	—	—	—
2024	21	ROK RAW	FCL Twins	—	105	96	29	6	1	0	7	21	2	0	0	302	362	385	747	83	387	20	7	339	45	—	—	—	—	—	—
2025	22	ROK MLE	2 teams	—	61	53	3	0	0	1	8	37	0	0	0	57	180	113	294	57	133	61	13	160	-5	—	—	—	—	—	—
2025	22	ROK RAW	2 teams	—	61	50	7	1	0	2	11	26	0	0	0	140	295	280	575	140	227	43	18	274	-5	—	—	—	—	—	—
2022	19	ROK MLE	DSL Twins	—	67	60	5	0	0	0	3	31	4	1	1	83	185	83	268		149	46	4	128	-27	—	—	—	—	—	—
2023	20	ROK MLE	DSL Twins	—	115	104	21	5	0	2	9	29	1	0	1	202	272	308	580	106	248	25	8	245	52	—	—	—	—	—	—
2024	21	ROK MLE	FCL Twins	—	105	98	21	4	1	0	4	31	2	0	0	214	257	276	533	61	311	30	4	235	45	—	—	—	—	—	—
2025	22	ROK MLE	2 teams	—	61	53	3	0	0	1	8	37	0	0	0	57	180	113	294	57	174	61	13	160	-5	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2023	20	ROK MLE	DSL Twins	—	115	104	21	5	0	2	9	29	1	0	1	202	272	308	580	106	248	25	8	245	52	—	—	—	—	—	—
2024	21	ROK MLE	FCL Twins	—	105	98	21	4	1	0	4	31	2	0	0	214	257	276	533	61	311	30	4	235	45	—	—	—	—	—	—
2025	22	ROK MLE	2 teams	—	61	53	3	0	0	1	8	37	0	0	0	57	180	113	294	57	174	61	13	160	-5	—	—	—	—	—	—
▸ 2026 season
2026	23	MLB MLE	MIN	0%	7	6	1	0	0	0	1	2	0	0	0	167	286	167	452		287	29	14	256	59	-0	+0	+0	+0	+0	0.0
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	24	MLB MLE	MIN	30%	167	151	32	6	1	3	12	49	2	2	1	212	279	325	603	113	289	29	7	267	67	-7	+0	+0	+3	+4	-0.0
2028	25	MLB MLE	MIN	44%	266	242	52	9	2	5	20	77	2	3	1	215	280	331	611	116	289	29	8	274	71	-9	+0	+0	+5	+6	0.2
2029	26	MLB MLE	MIN	51%	336	305	66	12	2	7	25	96	3	3	1	216	282	338	620	121	290	29	7	278	74	-10	+0	+0	+6	+7	0.3
2030	27	MLB MLE	MIN	52%	372	336	72	13	2	7	29	106	4	4	1	214	285	327	612	113	289	28	8	279	75	-11	+0	+0	+7	+8	0.4
2031	28	MLB MLE	MIN	53%	394	356	77	14	2	8	31	113	4	4	1	216	286	334	621	118	289	29	8	278	75	-12	+0	-1	+7	+9	0.3
2032	29	MLB MLE	MIN	53%	400	362	77	14	2	8	31	115	4	4	1	213	282	329	611	116	288	29	8	277	73	-13	+0	-1	+7	+9	0.2
2033	30	MLB MLE	MIN	56%	402	363	77	14	2	8	32	117	4	3	1	212	283	328	611	116	287	29	8	274	71	-14	+0	-2	+7	+9	0.0
2027	24	MLB CTX	MIN	30%	50	46	10	2	0	1	4	15	0	1	0	217	280	326	606	109	289	30	8	260	67	-2	+0	+0	+1	+1	0.0
2028	25	MLB CTX	MIN	44%	117	106	23	4	1	2	9	34	1	1	0	217	284	330	615	113	290	29	8	267	71	-4	+0	+0	+2	+3	0.1
2029	26	MLB CTX	MIN	51%	170	153	33	6	1	3	13	49	2	2	1	216	286	327	613	111	290	29	8	272	74	-5	+0	+0	+3	+4	0.2
2030	27	MLB CTX	MIN	52%	195	176	38	7	1	4	15	56	2	2	1	216	285	335	620	119	290	29	8	273	75	-6	+0	+0	+3	+4	0.2
2031	28	MLB CTX	MIN	53%	210	190	41	8	1	4	16	60	2	2	1	216	284	332	615	116	289	29	8	272	75	-6	+0	-0	+4	+5	0.2
2032	29	MLB CTX	MIN	53%	210	190	40	7	1	4	16	60	2	2	1	211	279	321	600	111	288	29	8	270	73	-7	+0	-1	+4	+5	0.1
2033	30	MLB CTX	MIN	56%	227	205	43	8	1	4	18	66	2	2	1	210	280	317	597	107	287	29	8	267	71	-8	+0	-1	+4	+5	0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1179	1066	228	42	6	22	91	340	11	12	5	214	283	326	609	113	290	29	8	270	67	-38	+0	-2	+21	+26	0.7
/ 162G	—	A+C		—	650	588	125	23	3	12	50	187	6	7	3	213	281	323	604	111	288	29	8	270	67	-21	+0	-1	+12	+14	0.4
Career	—	MLE		—	2692	2435	504	91	14	49	205	803	30	24	9	207	277	316	593	109	285	30	8	267	67	-75	+2	-4	+42	+51	1.5
/ 162G	—	MLE		—	650	588	122	22	3	12	49	194	7	6	2	207	276	316	592	109	286	30	8	267	67	-21	+0	-1	+12	+14	0.4

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Sandy Leónlast yr '22 career totals — 9 seasons, 1,648 PA	2.5	1,648	31	1	209	276	313	+29	+56	6.4	6.7
/162	664	12	0	+11.9	+22.4	2.6	pk7: 7
#2Ronny Cedenolast yr '13 career totals — 9 seasons, 2,783 PA	4.2	2,783	40	39	246	289	354	+28	+19	5.5	5.6
/162	664	10	9	+6.7	+4.5	1.3	pk7: 6
#3Adam Engellast yr '22 career totals — 6 seasons, 1,540 PA	2.3	1,540	30	47	225	280	350	+4	+33	4.1	4.1
/162	664	13	20	+1.8	+14.4	1.8	pk7: 4
#4Guillermo Heredialast yr '22 career totals — 6 seasons, 1,530 PA	2.3	1,530	25	6	231	311	345	+3	+17	3.5	3.5
/162	664	11	3	+1.2	+7.6	1.5	pk7: 3
#5Ryan Goinslast yr '19 career totals — 7 seasons, 1,680 PA	2.5	1,680	22	6	230	279	335	+9	+21	2.0	2.0
/162	664	9	2	+3.7	+8.5	0.8	pk7: 2
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 4 projected seasons	1.9	1,257	24	12	215	280	329	+22	+16	1.6	1.6
/162	664	12	6	+11.9	+8.5	0.9	pk7: 2
#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
Javier Roman (OGILVIE)	23	—	—	—	—	202/266/291	90	287	1	1	30%	7%	59	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Martin Cervenka 2016 · A	23	38→48	37→45	47→40	39	185/228/255	70	254	4	4	29%	5%	35	-3.4	217/262/314	97	295	9	3	28%	6%	61	-1.5	221/267/330	109	291	11	1	27%	6%	66	-0.8
✕Steven Baron 2014 · A	23	35	40→45	53→50	34	179/213/275	95	257	7	9	33%	4%	34	-3.5	216/264/299	83	296	5	9	27%	6%	59	-1.7	237/293/310	73	315	4	8	24%	7%	69	-0.4
✕Nick Quintana 2021 · A	23	39→40	39→45	49→45	36	186/240/271	86	298	6	9	38%	6%	44	-2.8	182/266/288	106	256	11	5	31%	9%	59	-1.6	164/257/264	101	226	11	3	30%	10%	49	-1.3
✕Dylan Neuse 2023 · A	24	36	39→40	49→50	44	177/255/257	79	269	8	14	35%	9%	48	-2.5	207/287/299	92	295	7	12	29%	9%	69	-0.9	212/301/305	93	294	5	13	27%	10%	75	-0.3
✕Claudio Finol 2023 · AA	23	38	37→40	50→45	40	186/240/263	77	257	4	8	28%	6%	42	-2.9	207/267/299	92	292	8	10	30%	7%	61	-1.5	192/260/271	78	271	9	12	31%	7%	51	-0.6
✕Raul Siri 2018 · A	23	39	38→40	51→50	42	192/251/271	80	265	6	11	29%	7%	49	-2.4	199/265/283	84	347	5	9	41%	7%	57	-1.8	146/235/232	85	299	4	14	47%	8%	34	-0.6
✕Andy Yerzy 2021 · A	23	35	38→50	49→40	35	174/226/251	77	275	5	7	37%	5%	34	-3.5	188/272/333	145	263	18	6	34%	9%	72	-0.7	166/252/300	134	233	18	4	36%	9%	55	-1.0
✕Daniel Berg 2008 · A	23	37	39→40	45→40	39	180/245/262	82	274	6	4	35%	6%	45	-2.7	203/273/290	87	311	6	4	34%	7%	61	-1.5	202/279/286	84	310	6	2	34%	7%	60	-0.7
✕Arturo De Freitas 2023 · A	22	35	39→45	45→40	34	174/222/255	81	277	7	4	39%	5%	34	-3.5	184/241/265	81	306	8	5	40%	6%	44	-2.8	141/191/216	75	260	9	0	47%	5%	11	-1.0
✕Jack Winkler 2022 · A	23	40→41	38→40	48→55	40	194/249/274	80	270	4	10	28%	6%	48	-2.5	206/268/296	90	274	7	14	26%	6%	61	-1.5	192/259/279	87	258	7	18	27%	6%	51	-1.6
✕Joe Napoli 2006 · A	23	39→43	37→50	44→45	41	190/245/267	76	267	4	4	29%	6%	45	-2.7	208/266/312	104	303	8	6	32%	5%	63	-1.3	211/274/343	132	288	12	7	30%	4%	72	-0.5
✕Zane Gurwitz 2019 · A	24	41	39→45	48→45	39	199/243/290	92	268	6	7	28%	5%	49	-2.4	205/261/308	103	296	9	6	32%	6%	61	-1.5	197/258/298	101	284	11	4	33%	7%	55	-1.3
✕Brian Ruggiano 2009 · A	23	40→43	38→45	54→55	38	190/244/275	85	291	5	10	35%	6%	47	-2.6	214/268/322	108	306	8	14	31%	6%	66	-1.1	216/270/330	114	301	9	15	30%	5%	67	-0.7
✕Shane Carlson 2010 · A	23	41	35→45	48→45	37	196/245/259	63	287	3	9	31%	5%	42	-2.9	222/261/311	89	277	6	8	21%	4%	61	-1.5	235/265/330	95	278	6	6	17%	3%	65	-0.6
✕Chris Hess 2018 · A	23	39→34	37→45	48→30	39	187/246/269	82	279	3	5	32%	6%	46	-2.6	191/250/294	103	282	9	4	34%	5%	54	-2.0	178/238/288	110	257	11	1	34%	4%	47	-2.0
✕J.C. Millan 2018 · A	22	40	37→40	45→30	36	194/235/270	76	278	4	8	31%	4%	41	-3.0	218/265/312	94	270	8	6	22%	6%	63	-1.4	223/270/312	90	261	9	4	18%	6%	61	-0.6
✕Javier Castillo 2006 · A	22	39→49	38→45	47→45	37	191/238/267	76	273	5	6	31%	5%	42	-2.9	226/271/334	108	298	8	7	26%	5%	70	-0.9	243/287/361	118	312	9	6	24%	5%	80	-0.1
✕Bobby Wernes 2017 · A	23	40	35→45	46→40	45	191/247/249	59	252	2	6	24%	7%	41	-3.0	213/270/306	93	274	6	6	23%	6%	63	-1.4	218/284/324	106	265	7	3	19%	7%	70	-0.4
✕Francisco Contreras 2015 · A	23	40	38→40	45	41	196/251/275	79	270	6	8	29%	6%	49	-2.4	190/235/267	77	277	4	6	31%	5%	40	-3.0	153/185/214	60	222	0	2	30%	3%	7	-1.9
✕Chris Mariscal 2016 · A	23	42→50	36→40	42→45	38	193/252/258	64	308	4	6	36%	6%	46	-2.6	226/284/313	87	334	6	6	32%	7%	70	-0.9	233/293/322	89	333	7	5	30%	7%	73	-0.5

Career Stats + Projections

Career Comps

Career Path Comps