Jake McCutcheon — OGILVIE

Jake McCutcheonRF Jupiter Hammerheads

Age 22 L/R 6'0" / 195 lbs A HR -10%H -3% Svc 0.0 · Ctrl thru 2036

2026 ROS PROJECTION333 act + 9 ros · stats below = ROS only

showingROS

wRC+†65

AVG/OBP/SLG.125 / .222 / .125

PA9

HR0

K%33

BB%11

BABIP249

ISO116

MLB%0%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$3M ctrl surplus

Tools · ContractCON 26 / POW 44

Toolsscout grade

CONTACT26

scouting grade only

POWER44

scouting grade only

EYE64

scouting grade only

SPEED55

scouting grade only

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	$0.2M	—	—	—
2035	Ext	beyond projection horizon · no WAR estimate
2036	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-6M	+$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	22	A MLE	MIA	—	333	286	45	8	1	6	36	122	6	10	3	157	265	255	520	98	239	37	11	239	48	-21	+1	+0	-4	+7	-1.6
▸ 2026 season
YTD	22	A RAW	MIA	—	262	207	45	8	1	7	45	67	5	5	2	217	370	367	737	150	275	26	17	335	48	—	—	—	—	—	—
YTD	22	A+ RAW	MIA	—	71	67	10	1	1	0	3	20	1	5	1	149	197	194	391	45	213	28	4	183	48	—	—	—	—	—	—
ROS	22	A MLE	MIA	0%	9	8	1	0	0	0	1	3	0	0	0	125	222	125	347		256	33	11	264	65	-0	+0	+0	-0	+0	-0.0
TOT	22	A MLE	MIA	—	342	294	46	8	1	6	37	125	6	10	3	156	264	252	516	95	238	37	11	240	49	-21	+1	+0	-4	+7	-1.7
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	23	MLB MLE	MIA	34%	454	398	76	14	2	9	47	137	6	8	2	191	286	304	590	113	262	30	10	273	71	-16	+1	+0	-5	+10	-1.0
2028	24	MLB MLE	MIA	46%	490	430	85	15	3	11	50	144	7	9	2	198	292	323	615	126	266	29	10	279	75	-15	+1	+0	-5	+11	-0.8
2029	25	MLB MLE	MIA	52%	529	463	93	17	3	12	54	153	7	9	3	201	294	328	622	127	267	29	10	282	77	-14	+1	+0	-6	+11	-0.8
2030	26	MLB MLE	MIA	54%	571	500	100	18	3	13	58	165	8	10	3	200	293	326	619	126	268	29	10	284	78	-15	+1	+0	-6	+12	-0.8
2031	27	MLB MLE	MIA	54%	617	540	108	20	3	14	64	178	8	11	3	200	294	326	620	126	268	29	10	284	78	-16	+1	+0	-7	+13	-0.8
2032	28	MLB MLE	MIA	54%	619	542	108	20	3	14	64	180	8	11	3	199	293	325	618	125	267	29	10	283	78	-16	+1	-1	-7	+13	-1.0
2033	29	MLB MLE	MIA	53%	613	536	106	19	3	14	64	179	8	10	3	198	293	323	616	125	266	29	10	281	76	-17	+1	-1	-7	+13	-1.1
2034	30	MLB MLE	MIA	52%	604	528	104	19	3	13	63	178	8	9	2	197	292	318	610	121	264	29	10	278	74	-18	+1	-2	-6	+13	-1.3
2027	23	MLB CTX	MIA	34%	156	137	25	4	1	3	16	47	2	3	1	182	277	292	569	109	255	30	10	257	71	-5	+0	+0	-2	+3	-0.4
2028	24	MLB CTX	MIA	46%	226	198	38	7	1	5	23	67	3	4	1	192	286	313	599	121	258	30	10	263	75	-7	+0	+0	-2	+5	-0.4
2029	25	MLB CTX	MIA	52%	273	239	46	8	1	6	28	79	4	5	1	192	288	310	597	117	260	29	10	266	77	-7	+1	+0	-3	+6	-0.4
2030	26	MLB CTX	MIA	54%	310	271	53	9	2	7	32	89	4	6	2	196	290	321	611	125	260	29	10	267	78	-8	+0	+0	-3	+7	-0.4
2031	27	MLB CTX	MIA	54%	335	293	57	10	2	7	35	97	4	6	2	195	289	314	603	119	260	29	10	267	78	-9	+0	+0	-4	+7	-0.5
2032	28	MLB CTX	MIA	54%	336	294	57	10	2	7	35	98	4	6	2	194	288	313	601	119	259	29	10	266	78	-9	+0	-0	-4	+7	-0.5
2033	29	MLB CTX	MIA	53%	325	284	56	10	2	7	34	95	4	5	1	197	292	320	612	123	258	29	10	265	76	-9	+1	-1	-3	+7	-0.6
2034	30	MLB CTX	MIA	52%	317	277	53	9	1	7	33	93	4	5	1	191	287	307	593	116	257	29	10	262	74	-10	+1	-1	-3	+7	-0.7
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2278	1993	385	67	12	49	236	665	29	40	11	193	288	313	600	119	260	29	10	265	76	-64	+4	-2	-24	+49	-3.8
/ 162G	—	A+C		—	650	569	109	19	3	14	67	190	8	11	3	192	286	309	595	118	257	29	10	265	76	-18	+1	-1	-7	+14	-1.1
Career	—	MLE		—	4506	3945	781	142	23	100	465	1317	60	77	21	198	292	322	614	124	267	29	10	281	76	-128	+7	-4	-48	+98	-7.7
/ 162G	—	MLE		—	650	569	111	20	3	14	67	190	9	11	3	195	290	315	605	120	264	29	10	281	76	-18	+1	-1	-7	+14	-1.1

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Danny Espinosalast yr '17 career totals — 8 seasons, 3,267 PA	4.9	3,267	98	64	221	297	378	+16	+36	11.0	11.4
/162	664	20	13	+3.2	+7.3	2.2	pk7: 12
#2Gordon Beckhamlast yr '19 career totals — 10 seasons, 3,764 PA	5.7	3,764	80	34	237	301	368	+13	+19	8.2	8.4
/162	664	14	6	+2.4	+3.4	1.4	pk7: 9
#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
#4Dustin Ackleylast yr '16 career totals — 6 seasons, 2,347 PA	3.5	2,347	46	31	241	304	367	-5	+7	3.8	3.8
/162	664	13	9	-1.3	+1.9	1.1	pk7: 4
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	3.9	2,598	57	44	200	291	324	+5	+5	1.3	1.3
/162	664	15	11	+1.2	+1.3	0.3	pk7: 1
#5Nick Senzellast yr '24 career totals — 6 seasons, 1,633 PA	2.5	1,633	40	33	232	299	363	+6	-14	0.9	0.9
/162	664	16	13	+2.4	-5.8	0.4	pk7: 1
#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
Jake McCutcheon (OGILVIE)	22	21→26	39→44	50→55	64	181/279/288	107	256	6	7	31%	10%	65	-0.7	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Darrien Miller 2023 · A	22	38→41	47→45	50→45	48	196/307/325	129	265	16	7	30%	10%	84	+0.2	187/296/284	97	258	8	5	29%	10%	71	-0.8	175/316/278	103	239	9	4	27%	12%	76	-0.2
✕Brian Holberton 2014 · A	22	42	45	47→30	51	208/291/330	122	251	13	6	22%	9%	78	-0.3	213/275/319	106	250	9	3	18%	7%	68	-1.0	210/270/316	106	241	9	1	16%	7%	64	-0.6
✕Christopher Familia 2023 · A	23	40	46→55	47→45	45	203/281/331	128	258	14	8	26%	8%	74	-0.5	219/278/387	168	291	21	4	31%	6%	86	+0.3	217/271/408	191	280	27	0	32%	5%	84	+0.1
✕Jacob Wetzel 2023 · A	23	39→34	44→45	49→50	45	195/276/305	110	270	12	10	31%	8%	67	-1.1	191/265/303	112	284	10	13	34%	8%	61	-1.5	178/252/295	117	273	8	16	35%	8%	53	-1.1
✕Zack Short 2018 · A	23	42→39	45→50	48→45	53	208/299/335	127	266	12	11	25%	10%	82	+0.0	198/288/331	133	281	13	8	31%	10%	77	-0.3	175/276/313	138	241	16	6	32%	11%	66	-0.7
✕Daury Arias 2023 · A	21	39→38	44→40	46→45	50	197/285/309	112	247	11	8	24%	9%	71	-0.8	183/263/266	83	270	7	9	32%	9%	53	-2.1	162/246/233	72	244	6	9	33%	9%	36	-1.7
✕Drew Robinson 2014 · A	22	43→42	43→55	49→50	46	207/288/323	116	304	10	8	33%	9%	75	-0.5	192/266/331	139	282	14	11	35%	9%	69	-0.9	208/288/362	155	321	16	12	38%	10%	81	-0.0
✕Anthony Seigler 2023 · A	24	41→39	42→45	46→55	56	196/304/308	112	272	9	11	28%	13%	78	-0.3	197/295/308	111	251	10	20	24%	12%	75	-0.5	219/309/345	126	268	10	25	21%	11%	85	+0.2
✕Jace Jung 2023 · A	22	44→42	39→50	50→40	50	208/292/300	92	296	6	7	29%	10%	71	-0.8	215/300/370	155	288	18	4	30%	10%	90	+0.6	208/298/364	156	272	18	3	29%	11%	86	+0.3
✕Johnny Monell 2008 · A	22	43→44	44→50	44→45	48	213/288/328	115	279	11	8	27%	9%	76	-0.4	232/294/362	130	290	12	8	23%	7%	85	+0.2	226/287/350	124	285	13	8	24%	7%	78	-0.1
✕Jose Brizuela 2016 · A	23	42→39	44→50	50→45	45	207/273/328	121	277	11	7	28%	8%	70	-0.8	210/268/335	125	296	14	5	32%	7%	70	-0.9	191/245/320	130	262	17	1	34%	6%	56	-0.8
✕Eddinson Paulino 2023 · A	21	43→40	46→45	56→50	44	213/280/360	147	287	12	14	29%	8%	80	-0.2	202/260/324	122	280	11	15	30%	6%	64	-1.3	187/244/301	115	257	12	15	31%	6%	50	-1.5
✕Daniel Vellojin 2022 · A	22	45	43→45	45	56	216/315/332	116	282	9	7	25%	12%	87	+0.4	187/274/291	104	267	10	5	31%	10%	63	-1.4	154/237/226	72	219	7	4	31%	9%	32	-1.3
✕Trey Sweeney 2022 · A	22	43	50	53→55	45	220/289/382	163	296	17	9	31%	8%	88	+0.5	208/282/344	136	276	15	19	28%	8%	78	-0.3	213/282/342	129	276	14	17	27%	8%	75	-0.4
✕Isan Díaz 2018 · A	22	39→41	46→55	45	42	198/268/329	131	290	14	8	35%	8%	69	-0.9	208/276/351	143	291	16	8	32%	8%	77	-0.3	206/286/370	164	268	21	5	30%	9%	80	-0.1
✕Alexander Ovalles 2023 · AA	22	43→42	46→50	46→50	45	217/283/344	127	282	13	8	27%	8%	78	-0.3	214/280/320	106	310	10	11	32%	8%	71	-0.8	175/252/223	48	291	3	15	38%	9%	35	-0.7
✕Alexander Campos 2022 · A	22	42	42→40	46→45	48	206/291/311	105	278	9	6	28%	9%	73	-0.6	220/302/308	88	316	7	6	30%	9%	76	-0.4	234/327/306	73	330	7	6	28%	11%	84	+0.1
✕Charles Mack 2022 · A	22	42	44→45	51→40	49	201/293/315	114	311	12	5	36%	12%	75	-0.5	179/244/282	103	315	10	6	43%	8%	49	-2.4	122/180/219	97	214	10	0	47%	6%	8	-1.9
✕Carlos Soto 2022 · A	23	40	45	45→30	48	200/279/321	122	272	12	3	30%	9%	71	-0.8	196/272/310	114	293	10	5	34%	9%	66	-1.1	142/232/239	97	223	7	0	37%	10%	34	-1.0
✕Dillon Paulson 2019 · A	22	41→36	47→50	50→30	48	207/281/353	146	266	14	4	27%	9%	79	-0.2	206/284/335	129	302	13	4	33%	10%	76	-0.4	192/276/319	127	274	13	2	32%	10%	68	-0.6

Career Stats + Projections

Career Comps

Career Path Comps