Player 822153 — OGILVIE

Player 8221531B Rancho Cucamonga Quakes

Age — —/— A K +5%HR +4% Svc 0.0 · Ctrl thru 2036

2026 ROS PROJECTION187 act + 27 ros · stats below = ROS only

showingROS

wRC+†89

AVG/OBP/SLG.167 / .259 / .208

PA27

HR0

K%30

BB%7

BABIP302

ISO42

MLB%0%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$4M ctrl surplus

Tools · Contract

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	Pre-Arb	$0.9M	—	—	—
2032	Pre-Arb	$0.9M	—	—	—
2033	Pre-Arb	$1.0M	—	—	—
2034	Arb-1	$1M	—	—	—
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$0.0M	+$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.

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
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
YTD	—	A MLE	LAA	—	187	155	36	8	3	3	20	55	10	15	1	232	357	381	737	148	333	29	11	328	108	+2	+3	+0	-3	+4	0.5
▸ 2026 season
YTD	—	ROK RAW	LAA	—	75	56	20	4	2	1	11	15	6	3	1	357	507	554	1.060	196	452	20	15	457	108	—	—	—	—	—	—
YTD	—	A RAW	LAA	—	112	90	25	7	2	3	18	25	4	12	0	278	420	500	920	222	355	22	16	408	108	—	—	—	—	—	—
ROS	—	A MLE	LAA	0%	27	24	4	1	0	0	2	8	1	1	0	167	259	208	468	42	303	30	7	300	89	-0	+0	+0	-0	+1	-0.0
TOT	—	A MLE	LAA	—	214	179	40	9	3	3	22	63	11	16	1	223	344	358	702	134	322	29	10	324	106	+1	+3	+0	-4	+5	0.5
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	25	MLB MLE	LAA	0%	345	303	68	13	4	7	31	97	8	14	2	224	313	363	676	139	300	28	9	302	90	-4	+2	+0	-6	+7	-0.1
2028	25	MLB MLE	LAA	0%	428	377	85	17	4	9	38	119	10	17	2	225	313	363	676	138	300	28	9	304	92	-4	+3	+0	-8	+9	0.0
2029	25	MLB MLE	LAA	0%	483	426	97	19	5	11	43	133	11	19	3	228	315	373	688	146	299	28	9	306	94	-4	+3	+0	-9	+10	0.1
2030	25	MLB MLE	LAA	0%	522	459	105	21	5	12	47	143	11	21	3	229	315	375	690	146	299	27	9	308	94	-3	+3	+0	-9	+11	0.2
2031	25	MLB MLE	LAA	0%	549	483	110	22	5	13	49	150	12	22	3	228	314	375	689	147	298	27	9	309	95	-3	+3	+0	-10	+12	0.2
2032	25	MLB MLE	LAA	0%	568	499	113	22	5	14	51	155	13	23	3	226	314	375	689	148	298	27	9	309	96	-3	+3	+0	-10	+12	0.3
2033	25	MLB MLE	LAA	0%	582	512	116	23	5	14	52	159	13	23	3	227	314	373	687	146	298	27	9	310	96	-3	+3	+0	-10	+13	0.3
2034	25	MLB MLE	LAA	0%	593	522	119	23	6	15	53	162	13	24	3	228	315	381	696	153	298	27	9	311	96	-2	+4	+0	-11	+13	0.3
2027	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	300	—	—	284	90	—	—	+0	-0	—	—
2028	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	299	—	—	288	92	—	—	+0	-0	—	—
2029	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	298	—	—	290	94	—	—	+0	-0	—	—
2030	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	298	—	—	292	94	—	—	+0	-0	—	—
2031	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	298	—	—	293	95	—	—	+0	-0	—	—
2032	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	297	—	—	293	96	—	—	+0	-0	—	—
2033	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	297	—	—	294	96	—	—	+0	-0	—	—
2034	25	MLB CTX	LAA	0%	0	0	0	0	0	0	0	0	0	0	0	—	—	—	—	—	297	—	—	295	96	—	—	+0	-0	—	—
▸ Career Totals
Career	—	MLE		—	4097	3605	817	161	39	95	366	1126	92	164	22	227	314	372	686	145	300	27	9	308	94	-27	+24	+0	-73	+89	1.3
/ 162G	—	MLE		—	650	572	130	26	6	15	58	179	15	26	3	227	315	372	687	145	302	28	9	308	94	-4	+4	+0	-12	+14	0.2

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Kole Calhounlast yr '23 career totals — 11 seasons, 4,963 PA	7.5	4,963	179	33	242	316	418	-54	-33	8.3	9.6
/162	664	24	4	-7.3	-4.4	1.1	pk7: 11
#2Manuel Margotlast yr '24 career totals — 8 seasons, 3,154 PA	4.8	3,154	56	94	254	307	380	-5	+27	8.4	8.8
/162	664	12	20	-1.1	+5.6	1.8	pk7: 9
#3Will Venablelast yr '15 career totals — 8 seasons, 3,127 PA	4.7	3,127	81	135	251	317	406	-20	-4	8.9	8.7
/162	664	17	29	-4.2	-0.8	1.9	pk7: 9
#4Desmond Jenningslast yr '16 career totals — 6 seasons, 2,327 PA	3.5	2,327	55	93	245	323	394	-9	+10	8.1	8.1
/162	664	16	27	-2.5	+2.7	2.3	pk7: 8
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 9 projected seasons	6.6	4,390	99	174	226	309	370	-49	+0	7.0	6.8
/162	664	15	26	-7.5	+0.0	1.1	pk7: 7
#5Michael Saunderslast yr '17 career totals — 8 seasons, 2,711 PA	4.1	2,711	81	55	233	305	399	-12	-13	4.1	4.5
/162	664	20	13	-2.9	-3.2	1.0	pk7: 5
#6Gregory Polancolast yr '21 career totals — 8 seasons, 3,220 PA	4.8	3,220	96	98	241	309	409	-34	-28	3.8	4.4
/162	664	20	20	-7.1	-5.8	0.8	pk7: 5

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
Player 822153 (OGILVIE)	25	—	—	—	—	217/310/344	127	303	5	16	29%	9%	89	+0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jonathan Davis 2017 · A	25	42→52	46→45	55	45	207/293/340	133	287	12	21	30%	8%	81	-0.1	221/300/334	113	289	9	19	25%	8%	82	-0.0	221/304/328	106	311	9	22	29%	9%	79	-0.1
✕Dylan Moore 2017 · A	24	44→48	44→50	54→65	47	216/295/339	123	274	11	23	24%	8%	81	-0.1	209/275/329	120	265	11	18	25%	7%	71	-0.8	207/330/379	172	285	16	41	30%	12%	101	+0.7
●Rafael Lantigua 2022 · A	24	45→55	45	53→55	45	223/287/353	130	295	13	20	28%	8%	81	-0.1	247/317/352	105	324	8	18	24%	9%	91	+0.7	251/326/344	93	326	6	18	23%	9%	90	+0.5
✕Mario Lisson 2008 · A	24	47→49	42→50	52→55	43	226/287/335	108	297	9	19	26%	6%	76	-0.4	206/252/317	111	266	11	17	26%	5%	59	-1.6	230/303/360	129	300	15	8	27%	8%	88	+0.3
✕Phillip Ervin 2017 · AA	25	42→51	44→50	55	48	207/286/327	120	254	12	25	23%	8%	76	-0.4	228/295/356	128	288	12	22	24%	7%	84	+0.2	235/299/371	136	298	13	21	24%	7%	86	+0.3
✕Kyle Datres 2022 · A	26	40→42	47→50	54→55	46	201/285/337	136	272	14	18	30%	9%	78	-0.3	212/290/348	136	290	16	23	31%	8%	82	-0.0	203/285/337	134	276	17	26	31%	8%	75	-0.3
✕Justin Dean 2021 · A	24	47→49	42→45	58→65	44	222/293/331	108	316	8	23	30%	8%	78	-0.3	203/281/302	99	319	8	27	36%	8%	68	-1.0	212/292/295	83	324	7	47	34%	9%	67	-0.7
✕Scott Heineman 2017 · A	24	48→55	45	51→50	43	234/300/367	133	315	12	17	28%	7%	89	+0.5	244/302/363	119	329	11	14	27%	6%	88	+0.5	250/311/378	128	324	14	16	26%	6%	92	+0.4
✕Allen Córdoba 2021 · A	25	47→52	40→45	53→55	40	228/277/321	93	297	7	20	25%	5%	70	-0.9	229/299/337	108	283	9	16	21%	6%	82	+0.0	227/303/337	110	275	9	18	20%	6%	82	+0.0
✕Alex Castellanos 2011 · A	24	44→51	45→55	52→50	36	213/265/346	134	307	11	15	33%	5%	72	-0.7	229/289/391	162	307	17	15	30%	6%	91	+0.6	223/288/391	168	294	19	17	30%	6%	88	+0.4
✕Niko Goodrum 2017 · AA	25	43→53	41→55	56→55	43	208/270/312	104	295	8	21	31%	7%	65	-1.2	229/283/372	143	310	14	14	29%	7%	84	+0.1	240/314/421	180	324	18	16	30%	9%	104	+1.0
✕Kyle Petty 2016 · A	25	45→50	42→50	53→50	39	221/265/325	104	304	10	11	30%	5%	65	-1.2	233/292/345	112	331	11	9	31%	7%	80	-0.1	238/302/353	114	340	11	8	31%	7%	84	+0.1
✕Daniel Carbonell 2015 · A	24	50→53	45→50	55	42	247/292/377	130	307	13	18	24%	5%	88	+0.4	212/250/306	94	281	8	15	27%	4%	56	-1.9	243/288/376	132	309	13	21	25%	5%	84	+0.1
✕Nate Eaton 2022 · A	25	40→50	40→45	55→60	43	197/264/288	91	273	7	19	29%	7%	57	-1.8	216/270/336	120	285	13	28	28%	6%	71	-0.8	213/270/337	124	278	12	27	27%	6%	68	-0.7
✕Keon Broxton 2015 · AA	25	45→50	47→55	54→60	39	221/274/361	141	315	15	16	34%	6%	78	-0.3	228/296/382	154	343	15	32	35%	8%	91	+0.6	224/300/388	164	339	17	38	36%	9%	92	+0.6
✕Eli Iorg 2008 · A	25	45→50	47→50	59→55	37	226/266/369	143	303	14	24	30%	4%	76	-0.4	229/264/344	115	313	10	17	29%	4%	69	-0.9	240/270/352	112	320	10	19	28%	3%	70	-0.7
✕Anthony Seratelli 2008 · A	25	46→48	46→45	56→55	46	229/291/363	134	291	12	19	25%	8%	84	+0.2	206/263/302	96	297	8	17	31%	7%	59	-1.6	230/302/348	119	296	13	20	25%	9%	84	+0.1
✕Corey Julks 2019 · A	23	46→51	43→50	52→55	43	221/279/335	114	304	10	18	30%	7%	74	-0.6	214/275/320	106	297	9	13	29%	7%	69	-0.9	226/286/381	155	284	18	21	27%	7%	84	+0.1
✕John Shelby 2011 · AA	25	43→52	46→55	54→55	39	216/256/351	134	278	12	20	27%	5%	68	-1.0	217/254/357	140	279	15	11	27%	4%	69	-0.9	210/241/362	153	258	17	7	26%	3%	63	-1.0
✕Brett Harris 2022 · A	24	44→52	44→45	49→50	43	218/288/335	117	294	12	11	29%	7%	78	-0.3	241/313/376	135	292	15	10	22%	8%	96	+1.0	238/318/367	129	288	14	9	21%	8%	93	+0.6

Career Stats + Projections

Career Comps

Career Path Comps