Zyhir Hope

RF Erie SeaWolves

Age 22 L/L 5'10" / 193 lbs AA HR -8% Svc 0.0 · Ctrl thru 2033

Overview

AAPROSPECTMiLBFA 2034

OGV OFP45OGV rank#79ETA2028MLB%12%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	A/ROK/INTL3 orgs	375	.272/.385/.473	14	11	98	—	.222/.331/.359
2025	20	AA/A+LAD	544	.266/.377/.428	13	27	80	—	.216/.303/.337
2026	21	AA/INTL2 orgs	630	.282/.376/.493	30	26	110	—	.257/.320/.433
2027PROJ12% MLB	22	MLBDET	25	.226/.300/.377	1	1	94	0.0
2028PROJ54% MLB	23	MLBDET	271	.232/.306/.397	10	8	101	0.5
2029PROJ65% MLB	24	MLBDET	351	.236/.310/.409	13	10	106	0.9

Next 3 projected WAR 1.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2033Service0.0First FA2034

2027MiLB2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Arb-1$4M2032Arb-2$7M2033Arb-3$9M

Skills · percentileMiLB Statcast 2026 AA

ISO86

wOBA85

wRC+83

Z-Con%57

Speed56

Whiff%54

Career WAR0.5 WAR median (P10 -0.9 / P90 23, comp-based) · star 8% · didn't stick 62%

CompsBo Naylor (age 23) · Jarred Kelenic (age 22) · Colby Rasmus (age 22)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†94

AVG/OBP/SLG.226 / .300 / .377

PA25

HR1

K%28

BB%8

BABIP295

ISO174

MLB%12%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$25M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.5	$2M	+$1M
2029	Pre-Arb	$0.8M	+0.9	$3M	+$2M
2030	Pre-Arb	$0.8M	+1.1	$7M	+$6M
2031	Arb-1	$4M	+1.2	$7M	+$4M
2032	Arb-2	$7M	+1.1	$6M	+$2M
2033	Arb-3	$9M	+1.0	$5M	+$0.3M
Totals		$22M		$30M	+$17M

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. 2027 = full-season projection (no games played yet). 2028+ 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)
2023	18	ROK	ACL Cubs	—	43	35	10	0	0	3	8	13	0	3	1	286	419	543	961	257	368	30	19	422	78	—	—	—	—	—	—
2024	19	A	Rancho Cucamonga Quakes	—	248	202	58	14	0	9	37	60	7	8	2	287	411	490	901	203	368	24	15	401	95	—	—	—	—	—	—
2024	19	ROK	ACL Dodgers	—	24	19	6	2	0	0	4	2	1	1	0	316	458	421	879	105	353	8	17	405	86	—	—	—	—	—	—
2024	19	INTL	Glendale Desert Dogs	—	103	92	21	3	1	5	8	25	2	2	1	228	304	446	750	217	254	24	8	328	108	—	—	—	—	—	—
2025	20	AA	Tulsa Drillers	—	20	19	6	2	0	0	1	4	0	1	0	316	350	421	771	105	400	20	5	344	86	—	—	—	—	—	—
2025	20	A+	Great Lakes Loons	—	524	439	116	27	3	13	78	139	3	26	6	264	378	428	806	164	355	27	15	361	80	—	—	—	—	—	—
2026	21	AA	Erie SeaWolves	—	564	491	141	20	2	29	62	141	4	26	6	287	372	513	885	226	341	25	11	385	109	—	—	—	—	—	—
2026	21	INTL	Scottsdale Scorpions	—	66	51	12	0	0	1	13	16	2	0	0	235	409	294	703	59	324	24	20	342	118	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2023	18	ROK MLE	ACL Cubs	—	43	38	7	0	0	2	5	19	0	3	1	184	279	342	621	158	299	44	12	284	78	—	—	—	—	—	—
2024	19	A MLE	Rancho Cucamonga Quakes	—	248	213	47	12	0	6	28	85	7	8	2	221	331	362	692	141	331	34	11	309	95	—	—	—	—	—	—
2024	19	ROK MLE	ACL Dodgers	—	24	21	5	2	0	0	2	3	1	1	0	238	333	333	667	95	277	12	8	295	86	—	—	—	—	—	—
2025	20	AA MLE	Tulsa Drillers	—	20	19	6	2	0	0	1	5	0	1	0	316	350	421	771	105	382	25	5	295	86	—	—	—	—	—	—
2025	20	A+ MLE	Great Lakes Loons	—	524	462	98	22	2	10	56	180	3	26	6	212	301	333	635	121	318	34	11	286	80	—	—	—	—	—	—
2026	21	AA MLE	Erie SeaWolves	—	564	510	131	17	2	23	43	172	4	26	6	257	320	433	753	176	328	30	8	329	109	—	—	—	—	—	—
2023	18	ROK MLE	ACL Cubs	—	43	38	7	0	0	2	5	19	0	3	1	184	279	342	621	158	294	44	12	284	78	—	—	—	—	—	—
2023	18	ROK RAW	ACL Cubs	—	43	35	10	0	0	3	8	13	0	3	1	286	419	543	961	257	368	30	19	422	78	—	—	—	—	—	—
2024	19	A MLE	3 teams	—	375	322	72	18	0	9	42	121	10	11	3	224	332	363	695	140	326	32	11	308	94	—	—	—	—	—	—
2024	19	A RAW	3 teams	—	375	313	85	19	1	14	49	87	10	11	3	272	385	473	858	201	333	23	13	381	94	—	—	—	—	—	—
2025	20	A+ MLE	2 teams	—	544	482	104	24	2	10	56	185	3	27	6	216	301	336	637	120	324	34	10	286	80	—	—	—	—	—	—
2025	20	A+ RAW	2 teams	—	544	458	122	29	3	13	79	143	3	27	6	266	377	428	805	162	357	26	15	361	80	—	—	—	—	—	—
2026	21	AA MLE	2 teams	—	630	568	146	19	2	26	49	192	6	26	6	257	323	435	757	178	336	30	8	329	109	—	—	—	—	—	—
2026	21	AA RAW	2 teams	—	630	542	153	20	2	30	75	157	6	26	6	282	376	493	868	210	340	25	12	380	109	—	—	—	—	—	—
2023	18	ROK MLE	ACL Cubs	—	43	38	7	0	0	2	5	19	0	3	1	184	279	342	621	158	299	44	12	284	78	—	—	—	—	—	—
2024	19	A MLE	3 teams	—	375	320	72	18	0	9	42	121	10	11	3	225	332	366	697	141	326	32	11	308	94	—	—	—	—	—	—
2025	20	A+ MLE	2 teams	—	544	480	104	24	2	10	56	185	3	27	6	217	301	338	639	121	320	34	10	286	80	—	—	—	—	—	—
2026	21	AA MLE	2 teams	—	630	570	146	19	2	26	49	192	6	26	6	256	323	433	756	177	328	30	8	329	109	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	A MLE	3 teams	—	375	320	72	18	0	9	42	121	10	11	3	225	332	366	697	141	326	32	11	308	94	—	—	—	—	—	—
2025	20	A+ MLE	2 teams	—	544	480	104	24	2	10	56	185	3	27	6	217	301	338	639	121	320	34	10	286	80	—	—	—	—	—	—
2026	21	AA MLE	2 teams	—	630	570	146	19	2	26	49	192	6	26	6	256	323	433	756	177	328	30	8	329	109	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	DET	12%	648	582	134	23	2	21	57	190	4	19	4	231	304	387	691	157	300	29	9	308	94	-4	+2	+1	-7	+14	0.6
▸ 2027 — real world (MLB)
2027	22	MLB CTX	DET	12%	25	23	5	1	0	1	2	7	0	1	0	226	300	377	677	151	295	28	8	302	94	-0	+0	+0	-0	+1	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	DET	54%	505	452	107	18	2	18	45	144	3	15	3	237	310	407	718	171	301	29	9	318	101	+1	+2	+1	-5	+11	1.0
2029	24	MLB MLE	DET	65%	537	480	116	20	2	21	48	150	4	15	3	241	315	420	735	180	302	28	9	325	106	+4	+2	+1	-6	+12	1.3
2030	25	MLB MLE	DET	70%	560	500	122	21	2	23	51	155	4	15	4	243	317	427	744	185	302	28	9	329	109	+6	+1	+2	-6	+12	1.5
2031	26	MLB MLE	DET	72%	578	517	126	21	2	24	52	158	4	15	4	244	318	430	748	187	301	27	9	330	110	+7	+1	+2	-6	+13	1.6
2032	27	MLB MLE	DET	71%	582	520	126	22	2	23	53	159	4	15	3	243	317	427	744	184	300	27	9	329	108	+6	+2	+2	-6	+13	1.6
2033	28	MLB MLE	DET	71%	576	515	124	21	2	23	52	158	4	13	3	241	315	422	737	181	299	27	9	326	107	+5	+1	+1	-6	+12	1.4
2034	29	MLB MLE	DET	69%	562	503	120	20	2	22	50	156	4	10	3	239	313	416	729	177	298	28	9	322	104	+3	+1	+0	-6	+12	1.0
2035	30	MLB MLE	DET	68%	550	493	117	20	2	21	49	154	3	8	3	236	309	409	718	173	296	28	9	318	101	+1	+0	-1	-6	+12	0.7
2036	31	MLB MLE	DET	68%	533	478	111	19	2	19	47	152	3	5	2	232	304	399	704	167	294	29	9	312	98	-2	+0	-1	-6	+12	0.3
2037	32	MLB MLE	DET	67%	511	459	104	17	1	18	44	148	3	3	3	227	299	387	685	160	290	29	9	305	93	-5	-1	-2	-5	+11	-0.2
2038	33	MLB MLE	DET	67%	475	430	94	15	1	16	40	140	2	4	4	221	291	372	663	151	285	29	8	296	86	-8	-1	-3	-5	+10	-0.6
2028	23	MLB CTX	DET	54%	271	243	57	10	1	10	24	77	2	8	2	232	306	397	703	165	296	28	9	312	101	+0	+1	+1	-3	+6	0.5
2029	24	MLB CTX	DET	65%	351	315	74	13	1	13	31	98	2	10	2	236	310	409	719	173	296	28	9	319	106	+3	+1	+1	-4	+8	0.9
2030	25	MLB CTX	DET	70%	392	351	83	14	1	15	35	108	3	11	2	238	313	416	728	178	296	28	9	322	109	+4	+1	+1	-4	+8	1.1
2031	26	MLB CTX	DET	72%	416	372	89	15	2	16	38	114	3	11	3	239	314	419	732	180	296	27	9	324	110	+5	+1	+1	-4	+9	1.2
2032	27	MLB CTX	DET	71%	414	371	89	15	2	16	37	113	3	10	2	238	313	415	728	177	295	27	9	322	108	+4	+1	+1	-4	+9	1.1
2033	28	MLB CTX	DET	71%	408	365	86	15	1	15	37	112	3	9	2	236	311	411	722	175	294	27	9	320	107	+3	+1	+1	-4	+9	1.0
2034	29	MLB CTX	DET	69%	388	347	81	14	1	14	35	108	3	7	2	234	308	405	713	171	293	28	9	316	104	+2	+1	+0	-4	+8	0.7
2035	30	MLB CTX	DET	68%	375	337	78	13	1	14	33	105	2	6	2	231	305	398	703	166	291	28	9	312	101	+1	+0	-0	-4	+8	0.5
2036	31	MLB CTX	DET	68%	361	324	74	12	1	13	32	103	2	4	2	227	300	389	689	161	289	29	9	307	98	-1	+0	-1	-4	+8	0.2
2037	32	MLB CTX	DET	67%	344	309	69	11	1	12	30	99	2	2	2	222	295	377	671	154	285	29	9	299	93	-3	-0	-1	-4	+7	-0.1
2038	33	MLB CTX	DET	67%	319	288	62	10	1	10	27	94	1	2	3	216	287	362	649	146	280	29	8	290	86	-5	-1	-2	-3	+7	-0.5
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4039	3622	842	142	13	148	359	1131	26	80	24	232	306	401	708	169	294	28	9	314	101	+13	+6	+1	-43	+88	6.6
/ 162G	—	A+C		—	650	583	136	23	2	24	58	182	4	13	4	233	307	403	710	170	295	28	9	314	101	+2	+1	+0	-7	+14	1.1
Career	—	MLE		—	7771	6946	1639	282	25	282	701	2252	58	191	52	236	311	406	717	170	305	29	9	317	101	+16	+10	+2	-66	+134	9.9
/ 162G	—	MLE		—	650	581	138	24	2	24	59	188	5	16	4	238	314	410	723	172	306	29	9	317	101	+2	+1	+0	-7	+14	1.0

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2026 AAErie SeaWolves · 564 PAwOBA .377 → .329 (−49)K% 25.0% → 30.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.000	×1.220	—	—	30.50%
BB% (unintentional) /PA	10.46%	÷1.000	×0.700	—	×1.050	7.69%
HBP% /PA	0.71%	—	×0.850	—	×1.050	0.63%
Singles /BIP	25.71%	÷1.000	×0.970	×0.979	×1.050	25.65%
Doubles /BIP	5.71%	÷1.000	×0.860	×0.979	×1.050	5.05%
Triples /BIP	0.57%	÷1.000	×0.950	×0.979	×1.050	0.56%
Home runs /BIP	8.29%	÷1.000	×0.780	—	×1.050	6.79%

Factors used: league row EL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.979.

Result: wOBA .377 → .329; ISO .226 → .186; BABIP .341 → .328. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 A+Great Lakes Loons · 524 PAwOBA .354 → .286 (−68)K% 26.5% → 34.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.53%	÷0.980	×1.270	—	—	34.37%
BB% (unintentional) /PA	14.69%	÷1.023	×0.710	—	×1.042	10.63%
HBP% /PA	0.57%	—	×0.790	—	×1.042	0.47%
Singles /BIP	24.33%	÷1.000	×0.920	×0.960	×1.042	22.40%
Doubles /BIP	9.00%	÷0.927	×0.810	×0.960	×1.042	7.87%
Triples /BIP	1.00%	÷1.150	×0.850	×0.960	×1.042	0.74%
Home runs /BIP	4.33%	÷0.992	×0.800	—	×1.042	3.64%

Factors used: league row Midwest League. Park (home-season share, regressed): HR 98, 1B 100, 2B 85, 3B 130, K 96, BB 105 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.960.

Result: wOBA .354 → .286; ISO .164 → .132; BABIP .355 → .318. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2025 AATulsa Drillers · 20 PAwOBA .335 → .295 (−40)K% 20.0% → 24.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷0.984	×1.220	—	—	24.81%
BB% (unintentional) /PA	5.00%	÷1.061	×0.700	—	×1.050	3.46%
HBP% /PA	0.00%	—	×0.870	—	×1.050	0.00%
Singles /BIP	26.67%	÷0.968	×0.920	—	×1.050	26.61%
Doubles /BIP	13.33%	÷1.014	×0.840	—	×1.050	11.59%
Triples /BIP	0.00%	÷1.137	×0.940	—	×1.050	0.00%
Home runs /BIP	0.00%	÷0.957	×0.800	—	×1.050	0.00%

Factors used: league row TL. Park (home-season share, regressed): HR 91, 1B 94, 2B 103, 3B 127, K 97, BB 112 — applied at half strength. Age: age 20 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (4.8 yr younger than average).

Result: wOBA .335 → .295; ISO .105 → .088; BABIP .400 → .382. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2024 ARancho Cucamonga Quakes · 248 PAwOBA .391 → .309 (−82)K% 24.2% → 34.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.19%	÷0.964	×1.360	—	—	34.13%
BB% (unintentional) /PA	14.92%	÷0.943	×0.690	—	×1.045	11.41%
HBP% /PA	2.82%	—	×0.780	—	×1.045	2.30%
Singles /BIP	24.65%	÷1.072	×0.920	×1.019	×1.045	22.52%
Doubles /BIP	9.86%	÷0.973	×0.830	×1.019	×1.045	8.95%
Triples /BIP	0.00%	÷0.973	×0.910	×1.019	×1.045	0.00%
Home runs /BIP	6.34%	÷1.072	×0.800	—	×1.045	4.94%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 114, 1B 114, 2B 95, 3B 95, K 93, BB 89 — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.019.

Result: wOBA .391 → .309; ISO .203 → .152; BABIP .368 → .331. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2024 ROKACL Dodgers · 24 PAwOBA .395 → .295 (−101)K% 8.3% → 12.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.33%	÷0.984	×1.440	—	—	12.19%
BB% (unintentional) /PA	16.67%	÷1.070	×0.620	—	×1.008	9.73%
HBP% /PA	4.17%	—	×0.720	—	×1.008	3.02%
Singles /BIP	23.53%	÷1.011	×0.820	—	×1.008	19.22%
Doubles /BIP	11.76%	÷1.010	×0.720	—	×1.008	8.45%
Triples /BIP	0.00%	÷0.967	×0.720	—	×1.008	0.00%
Home runs /BIP	0.00%	÷0.942	×0.780	—	×1.008	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 88, 1B 102, 2B 102, 3B 93, K 97, BB 114 — applied at half strength. Age: age 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average).

Result: wOBA .395 → .295; ISO .105 → .080; BABIP .353 → .277. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

2023 ROKACL Cubs · 43 PAwOBA .411 → .284 (−128)K% 30.2% → 43.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.23%	÷1.000	×1.440	—	—	43.53%
BB% (unintentional) /PA	18.60%	÷1.000	×0.620	—	×1.022	11.79%
HBP% /PA	0.00%	—	×0.720	—	×1.022	0.00%
Singles /BIP	31.82%	÷1.000	×0.820	—	×1.022	26.68%
Doubles /BIP	0.00%	÷1.000	×0.720	—	×1.022	0.00%
Triples /BIP	0.00%	÷1.000	×0.720	—	×1.022	0.00%
Home runs /BIP	13.64%	÷1.000	×0.780	—	×1.022	10.88%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average).

Result: wOBA .411 → .284; ISO .257 → .179; BABIP .368 → .299. Both wOBAs use the same linear weights, so the change is the translation alone. The MLE line is not regressed to the mean — regression happens later, when seasons are blended into a projection (how).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Ron Gant'87-'03 * career totals — 15 seasons, 7,320 PA	11.0	7,320	321	243	249*	328*	478*	-50	-5	30.8	27.6
/162	664	29	22	-4.6	-0.5	2.8	pk7: 24
#2Chris Taylorlast yr '25 career totals — 12 seasons, 3,909 PA	5.9	3,909	110	91	248	327	419	-9	+4	15.9	16.4
/162	664	19	15	-1.6	+0.6	2.7	pk7: 17
#3Tony Armas'76-'89 * career totals — 13 seasons, 5,502 PA	8.3	5,502	251	18	248*	287*	477*	-31	+20	17.5	16.3
/162	664	30	2	-3.7	+2.4	2.1	pk7: 15
#4Eric Byrneslast yr '09 career totals — 8 seasons, 3,440 PA	5.2	3,440	106	125	260	321	441	-21	+3	14.9	15.2
/162	664	20	24	-4.1	+0.6	2.9	pk7: 16
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 8 projected seasons	6.1	4,065	155	81	238	308	414	+10	+6	14.5	13.0
/162	664	25	13	+1.6	+0.9	2.4	pk7: 12
#5Mike Davis'80-'89 * career totals — 9 seasons, 3,298 PA	5.0	3,298	91	134	256*	313*	432*	-31	+13	11.4	12.4
/162	664	18	27	-6.2	+2.5	2.3	pk7: 13
#6Chas McCormicklast yr '25 career totals — 5 seasons, 1,567 PA	2.4	1,567	56	37	247	321	413	+2	+14	7.3	7.3
/162	664	24	16	+0.8	+6.0	3.1	pk7: 7

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
Zyhir Hope (OGILVIE)	22	—	—	—	—	228/301/384	155	300	7	6	29%	9%	94	+0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Bo Naylor 2023 · AAA	23	42→46	50→55	54→50	49	211/301/366	155	290	17	16	32%	10%	90	+0.6	217/302/391	174	272	21	10	27%	10%	96	+1.0	206/293/384	178	246	22	6	26%	10%	92	+0.5
✕Jarred Kelenic 2021 · AA	22	45→54	54→60	53→50	43	235/291/415	180	301	21	14	29%	7%	97	+1.1	229/294/412	183	290	21	13	27%	8%	97	+1.1	230/297/414	184	294	20	15	28%	8%	99	+1.1
●Colby Rasmus 2009 · AAA	22	44→54	51→65	53→50	49	227/299/386	159	271	18	17	24%	8%	93	+0.8	243/308/415	172	291	20	10	23%	8%	103	+1.5	243/309/466	223	315	29	3	32%	8%	116	+1.9
●Oneil Cruz 2022 · AAA	23	50→57	54→60	57→60	41	254/303/442	188	332	22	21	30%	6%	107	+1.9	239/302/430	191	317	23	20	30%	8%	104	+1.6	242/319/436	194	325	25	34	32%	10%	113	+2.0
●Chris Young 2006 · AA	22	46→48	56→60	55	47	238/309/441	203	302	22	23	28%	9%	110	+2.1	236/301/437	201	274	23	20	23%	8%	106	+1.8	238/319/427	189	288	21	17	24%	10%	111	+2.3
✕Daulton Varsho 2019 · A	23	47→50	47→60	55→50	42	235/292/365	130	303	15	18	27%	6%	86	+0.3	241/303/411	170	281	19	17	21%	7%	101	+1.4	227/293/421	194	258	25	15	23%	8%	100	+1.1
●Matt McLain 2023 · AA	23	41→51	50→55	59→55	48	209/297/370	161	292	17	24	33%	10%	89	+0.5	248/327/426	178	332	20	21	29%	9%	113	+2.3	229/312/388	159	300	18	22	28%	9%	98	+1.1
●Brian Goodwin 2013 · AA	22	47→52	46→60	48→50	49	233/308/370	136	299	14	13	26%	9%	93	+0.8	220/293/335	115	302	9	13	28%	9%	79	-0.2	243/307/436	194	312	22	11	28%	8%	108	+1.1
✕Graham Pauley 2024 · AA	23	50→52	52→55	53→50	48	253/317/427	174	298	20	14	22%	8%	109	+2.0	220/288/373	153	268	17	10	24%	8%	86	+0.3	202/274/352	149	245	16	9	24%	8%	75	-0.3
●Derek Fisher 2017 · AAA	23	46→52	49→55	55	46	225/299/371	146	316	17	20	32%	9%	90	+0.6	234/306/405	171	327	21	18	33%	9%	100	+1.3	231/307/412	181	317	23	18	33%	9%	100	+1.0
✕Everson Pereira 2023 · AA	22	47→49	52→55	54→50	39	232/288/405	173	334	20	16	36%	7%	93	+0.8	228/292/381	153	338	18	15	35%	7%	90	+0.6	220/292/370	150	322	19	15	35%	8%	84	+0.1
●Jazz Chisholm Jr. 2020 · AA	22	39→49	53→60	54→60	38	203/265/376	173	304	22	14	39%	7%	79	-0.2	231/293/420	189	313	23	20	32%	7%	99	+1.2	247/318/446	199	301	28	36	27%	9%	115	+2.1
✕Matt Shaw 2024 · AA	22	52→48	49→55	59→55	41	261/297/413	152	307	16	22	21%	4%	98	+1.2	244/315/408	164	287	19	23	21%	8%	104	+1.6	237/316/404	167	275	19	23	21%	9%	102	+1.1
✕Austin Wells 2023 · AA	24	43→44	52→55	57→50	48	221/305/386	165	294	19	14	30%	10%	96	+1.0	218/292/386	168	268	20	8	26%	9%	91	+0.7	211/285/386	175	250	21	5	25%	8%	89	+0.4
★Pete Crow-Armstrong 2023 · A	21	52→53	48→65	55→60	41	255/308/405	150	338	15	21	28%	6%	100	+1.3	236/288/405	169	305	18	31	28%	6%	94	+0.9	247/308/475	228	288	29	35	25%	7%	118	+2.8
✕Kirk Nieuwenhuis 2010 · AA	22	50→51	48→60	51→50	43	241/307/393	152	335	13	11	30%	7%	97	+1.1	246/301/395	149	342	13	10	30%	7%	95	+1.0	221/299/412	191	304	20	11	32%	9%	99	+0.7
✕Brett Jackson 2012 · AAA	23	48→53	49→55	55	45	234/306/391	157	333	16	19	33%	9%	97	+1.1	195/269/331	136	331	13	17	41%	8%	70	-0.9	170/248/295	125	306	12	17	45%	8%	52	-1.5
★Gunnar Henderson 2023 · MLB	22	51→56	50→60	56→55	49	244/328/411	167	344	17	15	32%	10%	109	+2.0	260/336/467	207	319	24	16	25%	10%	125	+3.2	263/338/474	211	310	25	18	23%	9%	129	+3.8
✕Anthony Volpe 2023 · AAA	22	44→50	53→55	60→55	49	227/311/414	187	277	19	29	25%	9%	104	+1.6	222/287/376	154	278	16	24	25%	8%	86	+0.3	226/286/365	138	282	13	24	24%	7%	83	+0.1
✕Ryan Kalish 2011 · MLB	23	51→53	48→50	57→55	49	254/316/397	143	308	15	23	22%	8%	101	+1.4	234/291/348	114	301	11	21	25%	7%	81	-0.1	217/264/312	94	293	8	20	27%	6%	59	-0.9

Zyhir Hope

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps