Parks Harber — OGILVIE

Parks Harber3B Richmond Flying Squirrels

Age 24 R/R 6'3" / 217 lbs AA HR -15%H -3% Svc 0.0 · Ctrl thru 2032

2026 ROS PROJECTION518 act + 9 ros · stats below = ROS only

showingROS

wRC+†95

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

PA9

HR0

K%33

BB%11

BABIP311

ISO163

MLB%2%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$20M ctrl surplus

Tools · ContractCON 47 / POW 55

Toolsscout grade

CONTACT47

scouting grade only

POWER55

scouting grade only

EYE52

scouting grade only

SPEED35

scouting grade only

DEFENSE40

scouting grade only

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

Status MiLB

MLB Debut 2027

Service 0 yrs (est)

Team Control Through 2032

First FA Year 2033

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2027
2027	Pre-Arb	$0.8M	+0.5	$2M	+$1M
2028	Pre-Arb	$0.8M	+0.9	$3M	+$2M
2029	Pre-Arb	$0.8M	+0.9	$3M	+$2M
2030	Arb-1	$3M	+0.9	$3M	+$0.6M
2031	Arb-2	$5M	+0.8	$2M	+$0.0M (cut)
2032	Arb-3	$6M	+0.6	$2M	+$0.0M (cut)
Totals		$6M		$14M	+$6M

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	22	A	Tampa Tarpons	—	95	78	21	7	2	1	15	24	1	4	0	269	394	449	842	179	370	25	16	373	139	+4	+1	—	—	+2	0.7
2025	23	A+	Eugene Emeralds	—	260	222	73	17	1	10	32	57	4	2	1	329	422	550	972	221	401	22	12	424	173	+23	+0	—	—	+6	2.9
2025	23	A	Tampa Tarpons	—	83	69	21	4	2	3	12	22	2	4	1	304	422	551	972	246	409	27	14	425	174	+7	+0	—	—	+2	1.0
2025	23	INTL	Scottsdale Scorpions	—	76	60	23	9	0	3	14	20	2	1	0	383	513	683	1.196	300	541	26	18	513	233	+12	+0	—	—	+2	1.4
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	22	A MLE	Tampa Tarpons	—	95	82	16	6	1	1	11	36	1	4	0	195	298	329	627	134	315	38	12	276	73	-3	+1	—	—	+2	-0.0
2025	23	A+ MLE	Eugene Emeralds	—	260	233	59	12	1	8	21	75	4	2	1	253	326	416	742	163	327	29	8	321	103	+1	+0	—	—	+6	0.7
2025	23	A MLE	Tampa Tarpons	—	83	72	17	3	2	3	9	31	2	4	1	236	337	458	796	222	349	37	11	326	107	+1	+0	—	—	+2	0.3
2024	22	A MLE	Tampa Tarpons	—	95	82	16	6	1	1	11	36	1	4	0	195	298	329	627	134	326	38	12	276	73	—	—	—	—	—	—
2024	22	A RAW	Tampa Tarpons	—	95	78	21	7	2	1	15	24	1	4	0	269	394	449	842	179	370	25	16	373	73	—	—	—	—	—	—
2025	23	A+ MLE	3 teams	—	419	372	92	19	3	13	37	129	8	7	2	247	329	419	748	172	341	31	9	322	104	—	—	—	—	—	—
2025	23	A+ RAW	3 teams	—	419	351	117	30	3	16	58	99	8	7	2	333	439	573	1.011	239	424	24	14	440	104	—	—	—	—	—	—
2024	22	A MLE	Tampa Tarpons	—	95	83	16	6	1	1	11	36	1	4	0	193	298	325	623	133	315	38	12	276	73	—	—	—	—	—	—
2025	23	A+ MLE	3 teams	—	419	371	92	19	3	13	37	129	8	7	2	248	329	420	749	173	332	31	9	322	104	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2024	22	A MLE	Tampa Tarpons	—	95	83	16	6	1	1	11	36	1	4	0	193	298	325	623	133	315	38	12	276	73	—	—	—	—	—	—
2025	23	A+ MLE	3 teams	—	419	371	92	19	3	13	37	129	8	7	2	248	329	420	749	173	332	31	9	322	104	—	—	—	—	—	—
YTD	24	AA MLE	SF	—	518	462	102	24	1	13	44	159	5	4	3	221	295	361	657	141	300	31	8	287	81	-12	-0	+0	+2	+11	0.1
▸ 2026 season
YTD	24	AA RAW	SF	—	298	257	73	20	1	12	35	73	2	2	2	284	374	510	884	226	347	24	12	384	81	—	—	—	—	—	—
YTD	24	AAA RAW	SF	—	220	186	47	9	0	5	28	54	3	2	1	253	359	382	741	129	323	25	13	334	81	—	—	—	—	—	—
ROS	24	AA MLE	SF	2%	9	8	1	0	0	0	1	3	0	0	0	125	222	125	347		317	33	11	309	95	-0	+0	-0	+0	+0	0.0
TOT	24	AA MLE	SF	—	527	470	103	24	1	13	45	162	5	4	3	219	294	357	652	138	298	31	9	288	81	-12	-0	-0	+2	+11	0.1
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	25	MLB MLE	SF	43%	547	488	116	26	2	16	48	160	6	5	2	238	314	398	711	160	315	29	9	316	100	+0	+0	-3	+2	+12	1.2
2028	26	MLB MLE	SF	62%	562	501	120	26	2	18	50	161	6	5	2	240	316	407	723	168	313	29	9	320	103	+2	+0	-3	+2	+12	1.4
2029	27	MLB MLE	SF	69%	567	505	121	26	2	18	51	161	6	5	2	240	317	406	723	166	311	28	9	320	103	+2	+0	-3	+2	+12	1.4
2030	28	MLB MLE	SF	72%	566	504	121	26	2	18	51	161	6	5	2	240	317	407	724	167	310	28	9	319	102	+1	+0	-4	+2	+12	1.3
2031	29	MLB MLE	SF	72%	561	499	118	25	2	17	51	160	6	4	2	236	315	397	712	160	309	29	9	317	101	+1	+0	-4	+2	+12	1.1
2032	30	MLB MLE	SF	72%	554	493	116	25	2	17	50	160	6	4	2	235	313	398	711	162	308	29	9	314	99	-1	+0	-5	+2	+12	0.8
2033	31	MLB MLE	SF	72%	546	486	113	24	2	16	50	159	5	3	2	233	311	389	699	156	305	29	9	310	96	-3	-0	-6	+2	+12	0.6
2034	32	MLB MLE	SF	72%	537	478	109	23	2	15	49	159	5	3	1	228	306	379	685	151	301	30	9	304	92	-5	+0	-6	+2	+12	0.2
2035	33	MLB MLE	SF	72%	355	317	70	14	1	10	32	107	3	1	1	221	298	366	664	145	296	30	9	297	87	-6	-0	-6	+1	+8	-0.3
2027	25	MLB CTX	SF	43%	236	211	49	11	1	6	21	69	2	2	1	232	308	379	687	147	308	29	9	301	100	+0	+0	-1	+1	+5	0.5
2028	26	MLB CTX	SF	62%	351	313	73	16	1	10	31	101	4	3	1	233	310	387	697	153	306	29	9	304	103	+1	+0	-2	+1	+8	0.9
2029	27	MLB CTX	SF	69%	390	348	81	17	2	11	35	111	4	3	2	233	310	388	698	155	305	28	9	304	103	+1	-0	-2	+1	+8	0.9
2030	28	MLB CTX	SF	72%	409	365	85	18	2	12	37	116	4	3	2	233	310	392	702	159	304	28	9	303	102	+1	-0	-3	+1	+9	0.9
2031	29	MLB CTX	SF	72%	404	360	82	18	1	11	37	115	4	3	2	228	307	375	682	147	303	28	9	302	101	+0	-0	-3	+1	+9	0.8
2032	30	MLB CTX	SF	72%	399	356	80	17	1	11	36	115	4	3	1	225	303	371	674	146	301	29	9	299	99	-1	+0	-4	+1	+9	0.6
2033	31	MLB CTX	SF	72%	393	350	79	17	1	11	36	115	4	2	1	226	305	374	679	149	299	29	9	295	96	-2	+0	-4	+1	+9	0.4
2034	32	MLB CTX	SF	72%	386	344	76	16	1	10	35	114	4	2	1	221	300	360	661	140	295	30	9	289	92	-4	+0	-4	+1	+8	0.2
2035	33	MLB CTX	SF	72%	255	228	49	10	1	6	23	77	2	1	0	215	292	346	639	132	290	30	9	282	87	-4	+0	-4	+1	+6	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3223	2875	654	140	11	88	291	933	32	22	11	227	306	376	681	148	303	29	9	298	99	-6	+0	-27	+12	+70	4.9
/ 162G	—	A+C		—	650	580	132	28	2	18	59	188	6	4	2	228	305	376	681	148	302	29	9	298	99	-1	+0	-5	+2	+14	1.0
Career	—	MLE		—	5318	4733	1113	240	21	159	481	1556	58	46	18	235	313	396	709	160	313	29	9	314	99	-8	+1	-39	+17	+104	7.6
/ 162G	—	MLE		—	650	578	136	29	3	19	59	190	7	6	2	235	314	394	708	159	314	29	9	314	99	-1	+0	-5	+2	+14	1.0

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Colby Rasmuslast yr '17 career totals — 9 seasons, 4,070 PA	6.1	4,070	165	35	242	311	438	-0	+8	16.7	16.2
/162	664	27	6	-0.0	+1.3	2.7	pk7: 16
#2Pedro Álvarezlast yr '18 career totals — 8 seasons, 3,287 PA	5.0	3,287	161	15	235	309	447	+1	-40	10.0	10.2
/162	664	33	3	+0.2	-8.0	2.0	pk7: 10
#3Maikel Francolast yr '22 career totals — 9 seasons, 3,573 PA	5.4	3,573	130	5	244	293	414	+13	-5	9.3	9.6
/162	664	24	1	+2.4	-1.0	1.7	pk7: 10
#4Yangervis Solartelast yr '19 career totals — 6 seasons, 2,645 PA	4.0	2,645	75	6	258	315	408	+9	+3	9.4	9.4
/162	664	19	2	+2.4	+0.7	2.4	pk7: 9
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	4.9	3,230	96	23	235	309	394	+12	-24	9.2	8.7
/162	664	20	5	+2.4	-4.9	1.9	pk7: 8
#5Trevor Plouffelast yr '17 career totals — 7 seasons, 3,178 PA	4.8	3,178	103	12	243	306	411	+14	-18	8.4	8.4
/162	664	22	3	+2.8	-3.8	1.8	pk7: 8
#6Tim Beckhamlast yr '19 career totals — 5 seasons, 1,743 PA	2.6	1,743	63	13	248	301	431	+19	-13	6.1	6.1
/162	664	24	5	+7.1	-4.8	2.3	pk7: 6

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
Parks Harber (OGILVIE)	24	47	55	35	52	231/306/380	149	317	8	3	30%	9%	95	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Josh Jung 2022 · AAA	24	52→59	52→60	45	43	261/315/432	172	323	20	6	25%	6%	110	+2.1	247/294/431	184	322	24	6	30%	5%	102	+1.5	259/309/396	137	316	16	5	23%	6%	96	+0.7
✕Michael McKenry 2009 · A	24	42→48	52→55	38→40	47	222/296/395	173	274	20	4	27%	8%	95	+0.9	221/284/354	133	278	14	3	25%	8%	80	-0.1	251/325/430	179	297	23	2	23%	9%	110	+0.8
✕Tanner Nishioka 2019 · A	24	53	48→50	45	42	259/315/407	148	337	15	6	27%	6%	104	+1.6	217/274/325	108	316	10	7	33%	4%	70	-0.9	187/244/273	86	284	9	5	36%	3%	47	-1.0
✕Jarrod Saltalamacchia 2009 · MLB	24	50→55	48→60	40	49	245/317/388	143	317	15	3	26%	9%	100	+1.3	230/293/386	156	305	18	3	29%	8%	91	+0.7	239/302/451	213	309	26	2	30%	8%	107	+1.3
✕Zach Lutz 2011 · AAA	25	47→48	51→55	39→30	47	238/310/398	161	301	19	3	27%	8%	100	+1.3	238/308/383	145	328	16	2	30%	8%	96	+1.0	233/311/364	131	319	13	0	29%	9%	91	+0.4
✕Josmil Pinto 2014 · MLB	25	52→58	49→50	40	48	260/318/412	152	311	16	2	22%	8%	106	+1.8	236/298/375	139	290	15	2	23%	8%	90	+0.6	219/281/352	132	271	15	0	24%	7%	76	-0.3
●Domingo Santana 2017 · MLB	24	51→56	52→60	40→50	47	244/324/410	166	352	20	6	34%	10%	108	+1.9	255/339/438	183	364	22	10	33%	11%	120	+2.8	255/339/438	184	364	23	10	33%	11%	117	+2.2
✕Joe Gaetti 2006 · A	24	51→52	55	43→45	42	252/318/444	192	351	21	6	33%	8%	114	+2.3	232/293/396	164	323	18	6	32%	7%	93	+0.8	220/281/382	162	306	19	5	33%	6%	83	+0.0
✕Kyle Parker 2014 · AA	24	48→51	51→55	42→45	44	246/303/407	161	305	20	4	26%	7%	99	+1.3	225/269/348	123	302	13	6	29%	5%	72	-0.7	213/256/323	110	291	11	5	30%	5%	59	-1.1
✕Max Ramirez 2009 · MLB	24	52	52→50	44→40	50	259/340/429	171	333	20	3	27%	10%	118	+2.7	224/296/345	121	306	13	3	29%	8%	83	+0.1	247/320/382	135	288	14	2	19%	9%	98	+0.7
●Tyler Flowers 2009 · A	23	49→55	49→50	41→40	50	242/318/395	153	311	15	5	26%	10%	102	+1.5	228/316/382	154	319	16	4	31%	10%	99	+1.3	260/361/411	151	335	17	0	25%	10%	120	+1.5
●Willy Adames 2021 · MLB	25	51→53	52→60	44→50	46	254/318/423	169	335	20	7	29%	8%	109	+2.0	246/317/449	203	310	25	7	28%	9%	115	+2.4	238/319/443	205	285	27	12	26%	10%	111	+2.2
✕James Darnell 2011 · AA	24	50→52	48→55	45→40	52	250/321/399	150	293	15	5	20%	9%	104	+1.6	240/305/402	162	280	19	5	21%	8%	99	+1.3	240/310/422	182	269	23	3	20%	8%	105	+1.0
✕Tyler Gentry 2023 · AA	24	52→55	51→50	46→50	46	253/332/415	162	342	20	9	30%	9%	112	+2.2	218/291/347	129	305	14	10	31%	8%	82	-0.0	197/271/316	119	278	12	10	32%	8%	64	-1.0
✕Travis d'Arnaud 2013 · AAA	24	50→53	52→60	45	39	256/298/424	168	319	19	5	26%	5%	101	+1.4	252/312/423	171	291	18	3	20%	8%	106	+1.8	261/320/456	195	292	26	1	20%	7%	114	+1.2
✕Kenny Holmberg 2007 · A	24	46→47	48→50	41→40	49	231/300/373	142	280	16	5	23%	8%	91	+0.6	219/301/321	102	275	10	4	23%	9%	80	-0.2	211/302/300	89	264	9	2	22%	10%	74	-0.4
✕Jordan Czarniecki 2006 · AA	25	50→51	46→50	40→50	49	247/315/384	136	301	13	8	22%	8%	98	+1.2	245/306/376	131	297	12	14	21%	7%	93	+0.8	245/307/375	130	292	11	16	19%	7%	90	+0.5
✕Sergio Pedroza 2008 · A	24	45→47	56→60	38→45	45	231/313/427	196	301	23	3	30%	8%	109	+2.0	225/294/350	125	305	12	11	29%	7%	83	+0.1	219/289/315	97	284	9	12	25%	8%	71	-0.3
●Jhonny Peralta 2007 · MLB	25	54→64	50→55	37→40	51	266/335/430	164	327	17	2	23%	9%	116	+2.5	266/330/427	161	321	18	3	22%	8%	114	+2.3	279/344/442	163	323	18	2	19%	8%	119	+2.6
●Khalil Greene 2004 · MLB	24	47→54	51→60	45	45	237/300/403	166	294	18	8	26%	7%	97	+1.1	257/325/430	173	294	18	6	18%	8%	113	+2.3	255/324/430	175	290	18	6	18%	8%	107	+1.5

Career Stats + Projections

Career Comps

Career Path Comps