Jack Penney — OGILVIE

Jack PenneySS FCL Tigers

Age 23 L/R 5'11" / 190 lbs ROK HR -8% Svc 0.0 · Ctrl thru 2037

2026 ROS PROJECTION20 act + 11 ros · stats below = ROS only

showingROS

wRC+†70

AVG/OBP/SLG.100 / .182 / .100

PA11

HR0

K%27

BB%9

BABIP257

ISO101

MLB%0%

Value2026 · WAR

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

Tools · ContractCON 45 / POW 43

Toolsscout grade

CONTACT45

scouting grade only

POWER43

scouting grade only

EYE60

scouting grade only

SPEED49

scouting grade only

DEFENSE45

scouting grade only

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	Pre-Arb	$1.0M	—	—	—
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		$-0.2M	+$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
▸ Career — actual stats, one row per stint (as recorded, no adjustments)
2024	21	A	Lakeland Flying Tigers	—	60	51	13	3	2	0	9	18	0	2	1	255	367	392	759	137	394	30	15	343	119	+1	+0	—	—	+1	0.3
2025	22	A+	West Michigan Whitecaps	—	306	252	66	11	1	5	46	62	5	6	2	262	386	373	759	111	324	20	15	347	121	+8	+0	—	—	+7	1.5
2025	22	A	Lakeland Flying Tigers	—	43	33	4	0	0	0	7	13	3	0	0	121	326	121	447		200	30	16	249	55	-2	+0	—	—	+1	-0.1
2025	22	INTL	Scottsdale Scorpions	—	73	54	15	1	0	1	15	20	3	2	0	278	458	352	810	74	412	27	21	381	144	+4	+0	—	—	+2	0.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	21	A MLE	Lakeland Flying Tigers	—	60	54	10	2	1	0	6	25	0	2	1	185	267	259	526	74	337	42	10	241	49	-4	+0	—	—	+1	-0.2
2025	22	A+ MLE	West Michigan Whitecaps	—	306	269	57	9	1	5	29	87	5	6	2	212	300	309	609	97	286	28	9	274	72	-10	+0	—	—	+7	-0.3
2025	22	A MLE	Lakeland Flying Tigers	—	43	34	3	0	0	0	6	18	3	0	0	88	279	88	367		175	42	14	194	17	-4	+0	—	—	+1	-0.3
2024	21	A MLE	Lakeland Flying Tigers	—	60	54	10	2	1	0	6	25	0	2	1	185	267	259	526	74	345	42	10	241	49	—	—	—	—	—	—
2024	21	A RAW	Lakeland Flying Tigers	—	60	51	13	3	2	0	9	18	0	2	1	255	367	392	759	137	394	30	15	343	49	—	—	—	—	—	—
2025	22	A+ MLE	3 teams	—	422	365	72	11	1	6	42	128	11	8	2	197	299	282	581	85	281	30	10	264	65	—	—	—	—	—	—
2025	22	A+ RAW	3 teams	—	422	339	85	12	1	6	68	95	11	8	2	251	392	345	737	94	326	23	16	343	65	—	—	—	—	—	—
2024	21	A MLE	Lakeland Flying Tigers	—	60	54	10	2	1	0	6	25	0	2	1	185	267	259	526	74	337	42	10	241	49	—	—	—	—	—	—
2025	22	A+ MLE	3 teams	—	422	366	72	11	1	6	42	128	11	8	2	197	299	281	580	85	272	30	10	264	65	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2024	21	A MLE	Lakeland Flying Tigers	—	60	54	10	2	1	0	6	25	0	2	1	185	267	259	526	74	337	42	10	241	49	—	—	—	—	—	—
2025	22	A+ MLE	3 teams	—	422	366	72	11	1	6	42	128	11	8	2	197	299	281	580	85	272	30	10	264	65	—	—	—	—	—	—
YTD	23	ROK MLE	DET	—	20	19	4	1	0	1	1	3	0	0	1	211	250	421	671	211	200	15	5	317	101	+0	-0	+0	+0	+0	0.0
▸ 2026 season
YTD	23	ROK RAW	DET	—	20	18	6	2	0	1	2	2	0	0	1	333	400	611	1.011	278	333	10	10	438	101	—	—	—	—	—	—
ROS	23	ROK MLE	DET	0%	11	10	1	0	0	0	1	3	0	0	0	100	182	100	282		261	27	9	271	70	-0	+0	-0	+0	+0	-0.0
TOT	23	ROK MLE	DET	—	31	29	5	1	0	1	2	6	0	0	1	172	226	310	536	138	182	19	6	301	90	-0	-0	-0	+0	+1	0.0
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	24	MLB MLE	DET	30%	375	330	69	13	2	7	37	96	5	6	2	209	298	324	623	115	265	26	10	280	75	-11	+0	-1	+4	+8	0.0
2028	25	MLB MLE	DET	44%	424	374	78	15	2	8	41	107	6	7	2	209	297	324	620	115	268	25	10	285	79	-11	+1	-2	+5	+9	0.2
2029	26	MLB MLE	DET	51%	454	401	84	16	2	9	44	114	6	7	2	209	297	327	624	117	269	25	10	287	81	-11	+1	-2	+5	+10	0.3
2030	27	MLB MLE	DET	52%	466	411	87	16	2	10	46	117	6	8	2	212	300	333	634	122	269	25	10	288	81	-10	+1	-2	+5	+10	0.4
2031	28	MLB MLE	DET	53%	470	415	87	16	2	10	46	119	6	7	2	210	298	330	628	120	269	25	10	288	81	-11	+1	-2	+5	+10	0.3
2032	29	MLB MLE	DET	53%	465	410	85	16	2	9	46	119	6	7	2	207	297	322	618	115	268	26	10	286	80	-11	+1	-3	+5	+10	0.1
2033	30	MLB MLE	DET	52%	458	403	83	15	2	9	46	118	6	6	2	206	297	320	617	114	267	26	10	283	78	-12	+0	-4	+5	+10	-0.1
2034	31	MLB MLE	DET	56%	446	393	80	15	2	8	44	116	6	5	1	204	293	313	606	109	265	26	10	279	75	-13	+1	-4	+5	+10	-0.3
2027	24	MLB CTX	DET	30%	113	99	21	4	1	2	11	29	2	2	1	212	304	333	637	121	261	26	10	265	75	-3	+0	-0	+1	+2	-0.0
2028	25	MLB CTX	DET	44%	187	164	34	6	1	4	18	47	3	3	1	207	297	329	627	122	263	25	10	270	79	-5	+0	-1	+2	+4	0.1
2029	26	MLB CTX	DET	51%	230	203	43	8	1	5	22	58	3	4	1	212	298	335	633	123	264	25	10	273	81	-5	+0	-1	+2	+5	0.2
2030	27	MLB CTX	DET	52%	244	215	44	8	1	5	24	61	3	4	1	205	293	321	614	116	265	25	10	274	81	-5	+0	-1	+3	+5	0.2
2031	28	MLB CTX	DET	53%	250	220	45	8	1	5	25	63	3	4	1	205	294	318	613	114	264	25	10	273	81	-6	+0	-1	+3	+5	0.2
2032	29	MLB CTX	DET	53%	244	215	44	8	1	5	24	62	3	4	1	205	293	321	614	116	264	25	10	272	80	-6	+0	-2	+3	+5	0.1
2033	30	MLB CTX	DET	52%	239	210	43	8	1	4	24	62	3	3	1	205	295	310	605	105	263	26	10	269	78	-6	+0	-2	+3	+5	-0.0
2034	31	MLB CTX	DET	56%	250	220	45	8	1	5	25	65	3	3	1	205	294	318	613	114	261	26	10	266	75	-7	+0	-2	+3	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1757	1546	319	58	8	35	173	447	23	27	8	206	296	322	618	116	265	25	10	271	77	-44	+2	-10	+19	+38	0.5
/ 162G	—	A+C		—	650	572	118	21	3	13	64	165	9	10	3	206	297	322	618	115	264	25	10	271	77	-16	+1	-4	+7	+14	0.2
Career	—	MLE		—	4051	3566	736	135	18	76	399	1062	58	63	18	206	297	318	615	112	270	26	10	282	77	-90	+5	-20	+38	+77	1.0
/ 162G	—	MLE		—	650	572	118	22	3	12	64	170	9	10	3	206	296	318	614	112	270	26	10	282	77	-16	+1	-4	+7	+14	0.2

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Gordon 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
#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
#3Chris Owingslast yr '22 career totals — 9 seasons, 2,420 PA	3.6	2,420	35	78	239	286	365	+13	-0	3.7	4.5
/162	664	10	21	+3.6	-0.1	1.0	pk7: 5
#4Daniel Descalsolast yr '19 career totals — 9 seasons, 2,856 PA	4.3	2,856	48	25	235	320	363	+16	-36	3.5	4.0
/162	664	11	6	+3.8	-8.3	0.8	pk7: 4
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	3.1	2,078	40	31	209	295	324	+22	-10	2.6	2.5
/162	664	13	10	+7.1	-3.2	0.8	pk7: 2
#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
Jack Penney (OGILVIE)	23	45	35→43	45→49	60	197/287/297	100	261	5	5	26%	10%	70	-0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Sherman Johnson 2013 · A	23	46→50	40→45	52→50	54	216/306/311	95	287	6	9	25%	11%	78	-0.3	222/300/333	111	283	8	12	23%	10%	81	-0.1	213/294/328	115	264	9	14	22%	10%	75	-0.5
✕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
✕Chris Meyers 2022 · A	23	40→45	41→50	51→40	45	197/267/298	101	259	8	11	26%	7%	61	-1.5	220/278/357	137	292	15	6	29%	6%	79	-0.2	222/283/366	144	287	17	3	28%	6%	80	-0.1
✕Hoy Park 2019 · A	23	46→49	39→45	55	51	217/298/301	85	285	6	17	25%	9%	74	-0.6	228/306/324	96	300	7	16	24%	9%	81	-0.1	215/302/326	111	288	12	18	27%	10%	79	-0.2
✕Mitchell Tolman 2018 · A	24	46→47	41→45	45→50	50	221/293/316	94	273	9	9	22%	8%	74	-0.5	212/284/301	89	300	7	10	29%	8%	68	-1.0	217/287/331	114	285	10	8	26%	7%	73	-0.4
✕Pratt Maynard 2014 · A	24	45	41→45	45	50	216/283/311	95	265	8	6	22%	8%	70	-0.9	226/285/337	111	294	8	6	24%	8%	76	-0.4	235/286/363	128	311	6	0	25%	7%	82	-0.0
✕Blake Tekotte 2010 · A	23	43→47	43→50	50→55	47	213/273/320	107	259	10	15	22%	7%	68	-1.0	221/282/366	145	287	16	21	27%	7%	82	+0.0	214/275/365	151	282	17	23	29%	7%	76	-0.4
✕Kobe Kato 2023 · A	24	47	42→40	46→55	54	224/310/326	102	281	9	10	22%	10%	84	+0.1	215/295/302	87	300	5	22	27%	9%	72	-0.7	198/286/279	81	284	5	29	29%	10%	61	-0.5
✕Nolan Fontana 2014 · A	23	45→43	40	52→50	59	208/323/305	98	291	7	14	28%	14%	85	+0.2	207/302/294	87	304	4	9	29%	12%	74	-0.6	184/288/307	123	253	11	12	29%	12%	71	-0.3
✕Conner Crumbliss 2010 · A	23	49	40→45	50	50	230/314/332	102	296	6	10	23%	9%	86	+0.3	225/328/316	91	285	6	14	21%	13%	88	+0.5	221/330/313	92	278	6	16	20%	13%	87	+0.4
✕Irving Lopez 2018 · A	23	46→50	42→45	47→40	46	224/289/330	106	262	10	7	19%	6%	77	-0.3	226/289/333	107	278	9	3	21%	6%	77	-0.3	210/280/304	94	269	8	4	23%	7%	65	-0.6
✕Casey Turgeon 2016 · A	23	45	37→40	50→45	53	210/297/285	75	261	4	9	20%	10%	70	-0.9	208/293/302	94	266	7	7	23%	10%	72	-0.7	199/289/298	99	252	9	5	23%	10%	68	-0.5
✕Mike Gerber 2015 · A	23	50→51	41→50	51→45	47	240/297/343	103	299	8	10	22%	7%	82	-0.0	232/281/363	131	313	12	9	28%	6%	80	-0.1	230/281/363	133	315	12	8	29%	6%	79	-0.2
✕Jeisson Rosario 2023 · AA	23	45→49	42→45	47→50	49	215/293/323	108	288	9	12	27%	9%	76	-0.4	209/293/310	101	310	9	12	32%	10%	74	-0.6	195/287/283	88	301	8	12	34%	11%	63	-0.8
✕Chris Herrmann 2012 · AA	24	46→49	41→50	49→50	52	221/297/320	99	274	7	7	21%	9%	77	-0.3	225/282/326	101	284	8	5	23%	7%	72	-0.7	214/305/376	161	274	20	8	28%	11%	91	+0.3
✕Johnny Monell 2009 · A	23	47→44	43→50	48→45	47	229/298/348	120	287	10	10	23%	8%	84	+0.1	229/286/362	133	289	13	6	24%	7%	82	+0.0	226/287/350	124	285	13	8	24%	7%	78	-0.1
✕Ryne Malone 2007 · A	22	47	40→45	48→50	49	225/294/330	105	288	6	10	23%	8%	78	-0.3	214/278/310	96	271	7	6	22%	7%	68	-1.0	197/264/276	80	244	5	1	20%	7%	53	-1.0
✕Peter Maris 2018 · A	24	48→50	40→45	46→50	50	232/288/320	89	270	7	9	17%	7%	73	-0.6	221/282/348	127	276	12	9	23%	7%	78	-0.3	213/273/360	147	272	16	7	27%	7%	75	-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
✕Collin Burns 2023 · A	23	49	40→45	49→55	43	237/289/330	93	299	7	13	23%	6%	76	-0.4	205/263/286	81	279	6	17	27%	6%	56	-1.9	181/241/246	65	252	4	21	28%	6%	37	-1.5

Career Stats + Projections

Career Comps

Career Path Comps