Chase Harlan

3B Ontario Tower Buzzers

Age 21 R/R 6'3" / 205 lbs A HR +8%BB -8% Svc 0.0 · Ctrl thru 2035

Overview

APROSPECTMiLBFA 2036

OGV OFP45OGV rank#117ETA2028MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2025	19	A/ROK2 orgs	300	.269/.360/.442	9	3	57	—	.195/.262/.305
2026	20	A+/A/INTL2 orgs	458	.295/.403/.509	17	2	116	—	.257/.344/.422
2027PROJMLE	21	MLBLAD	506	.231/.308/.380	14	7	94	0.4
2028PROJ43% MLB	22	MLBLAD	156	.233/.311/.397	5	2	101	0.3
2029PROJ61% MLB	23	MLBLAD	248	.238/.316/.411	9	4	106	0.8

Next 3 projected WAR 1.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2035Service0.0First FA2036

2027MiLB2028MiLB2029MiLB2030Pre-Arb$0.8M2031Pre-Arb$0.9M2032Pre-Arb$0.9M2033Arb-1$5M2034Arb-2$7M+1

Skills · percentileMiLB Statcast 2026 A+

Chase%76

Whiff%68

ISO50

K%50

wOBA38

wRC+38

Career WAR0.3 WAR median (P10 -0.5 / P90 31, comp-based) · star 12% · didn't stick 57%

CompsHeriberto Hernández (age 21) · Logan O'Hoppe (age 22) · Agustín Ramírez (age 22)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 210 proj PA

wRC+†94

AVG/OBP/SLG.229 / .306 / .376

PA210

HR6

K%23

BB%9

ISO149

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$46M ctrl surplus

Contract

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

Status MiLB

MLB Debut 2030

Service 0 yrs (est)

Team Control Through 2035

First FA Year 2036

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2030
2028	MiLB	still in minors · estimated debut 2030
2029	MiLB	still in minors · estimated debut 2030
2030	Pre-Arb	$0.8M	+1.1	$7M	+$6M
2031	Pre-Arb	$0.9M	+1.4	$8M	+$8M
2032	Pre-Arb	$0.9M	+1.4	$8M	+$7M
2033	Arb-1	$5M	+1.4	$7M	+$5M
2034	Arb-2	$7M	+1.2	$6M	+$2M
2035	Arb-3	$9M	+1.0	$4M	+$0.5M
Totals		$23M		$40M	+$29M

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)
2025	19	A	Rancho Cucamonga Quakes	—	123	104	25	3	0	3	18	32	1	2	1	240	358	356	713	115	319	26	15	330	60	—	—	—	—	—	—
2025	19	ROK	ACL Dodgers	—	177	156	45	13	1	6	18	35	0	1	1	288	362	500	862	212	331	20	10	373	55	—	—	—	—	—	—
2026	20	A+	Great Lakes Loons	—	130	113	27	5	0	4	13	31	3	1	0	239	333	389	723	150	291	24	10	325	69	—	—	—	—	—	—
2026	20	A	Ontario Tower Buzzers	—	266	219	72	17	3	10	38	51	6	0	0	329	439	571	1.010	242	388	19	14	438	131	—	—	—	—	—	—
2026	20	INTL	Glendale Desert Dogs	—	62	51	14	3	0	3	8	20	2	1	1	275	393	510	903	235	379	32	13	393	152	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2025	19	A MLE	Rancho Cucamonga Quakes	—	123	109	21	2	0	2	13	44	1	2	1	193	285	266	551	73	304	36	11	257	60	—	—	—	—	—	—
2025	19	ROK MLE	ACL Dodgers	—	177	163	32	8	1	4	11	51	0	1	1	196	247	331	578	135	245	29	6	249	55	—	—	—	—	—	—
2026	20	A+ MLE	Great Lakes Loons	—	130	116	24	4	0	3	10	39	3	1	0	207	287	319	606	112	275	30	8	270	69	—	—	—	—	—	—
2026	20	A MLE	Ontario Tower Buzzers	—	266	231	65	14	3	8	27	69	6	0	0	281	371	472	843	190	358	26	10	362	131	—	—	—	—	—	—
2025	19	ROK MLE	2 teams	—	300	271	53	10	1	6	25	95	1	3	2	196	266	306	572	111	272	32	8	252	57	—	—	—	—	—	—
2025	19	ROK RAW	2 teams	—	300	260	70	16	1	9	36	67	1	3	2	269	360	442	803	173	326	22	12	355	57	—	—	—	—	—	—
2026	20	A MLE	3 teams	—	458	400	103	22	3	13	43	126	11	2	1	258	346	425	771	167	340	28	9	332	111	—	—	—	—	—	—
2026	20	A RAW	3 teams	—	458	383	113	25	3	17	59	102	11	2	1	295	403	509	912	214	358	22	13	400	111	—	—	—	—	—	—
2025	19	ROK MLE	2 teams	—	300	271	53	10	1	6	25	95	1	3	2	196	266	306	572	111	269	32	8	252	57	—	—	—	—	—	—
2026	20	A MLE	3 teams	—	458	401	103	22	3	13	43	126	11	2	1	257	346	424	770	167	331	28	9	332	111	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2025	19	ROK MLE	2 teams	—	300	271	53	10	1	6	25	95	1	3	2	196	266	306	572	111	269	32	8	252	57	—	—	—	—	—	—
2026	20	A MLE	3 teams	—	458	401	103	22	3	13	43	126	11	2	1	257	346	424	770	167	331	28	9	332	111	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	21	MLB MLE	LAD	0%	506	451	103	20	2	14	43	118	7	7	2	231	308	380	688	149	279	23	8	308	94	-3	+1	-3	+2	+11	0.4
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	22	MLB MLE	LAD	43%	362	322	77	15	2	12	32	83	5	6	1	237	314	400	714	163	281	23	9	318	101	+1	+1	-2	+1	+8	0.9
2029	23	MLB MLE	LAD	61%	408	363	88	17	2	14	36	92	6	7	2	241	318	414	732	173	282	23	9	325	106	+3	+1	-2	+1	+9	1.2
2030	24	MLB MLE	LAD	66%	455	406	99	19	2	16	40	102	6	7	2	244	321	422	744	179	284	22	9	329	109	+5	+1	-1	+2	+10	1.6
2031	25	MLB MLE	LAD	69%	495	441	107	20	2	18	44	111	7	8	2	245	323	427	750	182	284	22	9	332	111	+6	+1	-1	+2	+11	1.9
2032	26	MLB MLE	LAD	70%	507	450	111	21	2	19	45	114	7	8	2	246	323	429	752	183	285	22	9	332	111	+7	+1	-1	+2	+11	2.0
2033	27	MLB MLE	LAD	69%	510	453	111	21	2	19	45	115	7	8	2	244	322	426	748	182	284	23	9	331	110	+6	+1	-1	+2	+11	2.0
2034	28	MLB MLE	LAD	68%	505	449	108	20	2	18	45	115	6	7	2	242	320	421	741	179	283	23	9	328	108	+5	+1	-1	+2	+11	1.7
2035	29	MLB MLE	LAD	67%	494	441	106	20	2	18	44	114	6	6	2	240	317	414	731	175	281	23	9	324	106	+3	+0	-2	+2	+11	1.4
2036	30	MLB MLE	LAD	66%	482	431	102	19	2	17	42	113	6	5	2	236	313	406	719	169	279	23	9	319	102	+1	+0	-3	+2	+10	1.1
2037	31	MLB MLE	LAD	65%	466	418	98	18	2	16	40	111	5	4	3	232	308	396	703	164	275	24	9	313	98	-1	-0	-3	+2	+10	0.7
2038	32	MLB MLE	LAD	65%	445	399	89	16	1	14	38	108	5	3	10	226	301	382	683	156	271	24	9	305	93	-4	-3	-4	+2	+10	-0.0
2039	33	MLB MLE	LAD	65%	408	367	80	14	1	12	34	101	4	2	38	219	293	366	659	147	266	25	8	295	86	-7	-15	-5	+1	+9	-1.6
2028	22	MLB CTX	LAD	43%	156	139	33	6	1	5	14	36	2	2	1	233	311	397	708	164	274	23	9	315	101	+0	+0	-1	+1	+3	0.3
2029	23	MLB CTX	LAD	61%	248	221	53	10	1	9	22	56	3	4	1	238	316	411	727	173	276	23	9	322	106	+2	+0	-1	+1	+5	0.8
2030	24	MLB CTX	LAD	66%	301	267	64	12	1	11	27	68	4	5	1	241	318	420	738	179	278	23	9	327	109	+3	+1	-1	+1	+7	1.1
2031	25	MLB CTX	LAD	69%	340	302	73	13	1	13	30	76	5	6	1	242	320	425	745	183	278	22	9	330	111	+4	+1	-0	+1	+7	1.4
2032	26	MLB CTX	LAD	70%	354	315	76	14	1	14	31	79	5	6	1	243	320	427	747	184	278	22	9	330	111	+5	+1	-0	+1	+8	1.4
2033	27	MLB CTX	LAD	69%	352	313	76	14	1	14	31	79	5	5	1	241	319	424	743	183	278	22	9	329	110	+4	+1	-0	+1	+8	1.4
2034	28	MLB CTX	LAD	68%	346	308	73	13	1	13	31	79	4	5	1	239	317	419	736	180	277	23	9	326	108	+3	+1	-1	+1	+7	1.2
2035	29	MLB CTX	LAD	67%	330	294	69	12	1	12	29	76	4	4	1	237	314	412	727	176	275	23	9	322	106	+2	+0	-1	+1	+7	1.0
2036	30	MLB CTX	LAD	66%	317	282	67	12	1	12	28	74	4	4	1	234	310	404	715	171	273	23	9	317	102	+1	+0	-2	+1	+7	0.8
2037	31	MLB CTX	LAD	65%	303	271	63	11	1	11	26	72	3	3	2	229	305	394	699	165	270	24	9	311	98	-1	-0	-2	+1	+7	0.5
2038	32	MLB CTX	LAD	65%	288	258	58	10	1	10	25	70	3	2	6	224	299	380	679	157	265	24	9	303	93	-3	-2	-3	+1	+6	0.0
2039	33	MLB CTX	LAD	65%	263	236	52	9	1	8	22	65	3	1	25	217	291	364	655	148	260	25	8	294	86	-4	-10	-3	+1	+6	-1.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3598	3206	757	136	12	132	316	830	45	47	42	236	313	410	723	173	276	23	9	320	102	+17	-7	-16	+13	+78	8.6
/ 162G	—	A+C		—	650	579	137	25	2	24	57	150	8	8	8	237	314	411	725	174	276	23	9	320	102	+3	-1	-3	+2	+14	1.6
Career	—	MLE		—	6505	5798	1375	260	27	218	571	1549	85	79	72	237	315	404	719	167	285	24	9	319	102	+24	-13	-27	+21	+125	13.2
/ 162G	—	MLE		—	650	579	138	26	3	22	57	155	8	8	7	238	315	408	722	169	286	24	9	319	102	+3	-1	-3	+2	+14	1.5

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 AOntario Tower Buzzers · 266 PAwOBA .430 → .362 (−68)K% 19.2% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.17%	÷1.000	×1.360	—	—	26.08%
BB% (unintentional) /PA	14.29%	÷1.000	×0.690	—	×1.030	10.15%
HBP% /PA	2.26%	—	×0.780	—	×1.030	1.81%
Singles /BIP	25.00%	÷1.000	×0.920	×1.015	×1.030	24.04%
Doubles /BIP	10.12%	÷1.000	×0.830	×1.015	×1.030	8.78%
Triples /BIP	1.79%	÷1.000	×0.910	×1.015	×1.030	1.70%
Home runs /BIP	5.95%	÷1.000	×0.800	—	×1.030	4.90%

Factors used: level-wide A 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 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.015.

Result: wOBA .430 → .362; ISO .242 → .202; BABIP .388 → .358. 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).

2026 A+Great Lakes Loons · 130 PAwOBA .320 → .270 (−49)K% 23.8% → 30.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.85%	÷1.000	×1.270	—	—	30.28%
BB% (unintentional) /PA	10.00%	÷1.000	×0.710	—	×1.042	7.40%
HBP% /PA	2.31%	—	×0.790	—	×1.042	1.90%
Singles /BIP	21.95%	÷1.000	×0.920	×1.022	×1.042	21.51%
Doubles /BIP	6.10%	÷1.000	×0.810	×1.022	×1.042	5.26%
Triples /BIP	0.00%	÷1.000	×0.850	×1.022	×1.042	0.00%
Home runs /BIP	4.88%	÷1.000	×0.800	—	×1.042	4.07%

Factors used: league row Midwest League. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×1.022.

Result: wOBA .320 → .270; ISO .150 → .121; BABIP .291 → .275. 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 ROKACL Dodgers · 177 PAwOBA .369 → .249 (−120)K% 19.8% → 28.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.77%	÷0.993	×1.440	—	—	28.68%
BB% (unintentional) /PA	10.17%	÷0.997	×0.620	—	×1.008	6.37%
HBP% /PA	0.00%	—	×0.720	—	×1.008	0.00%
Singles /BIP	20.66%	÷0.996	×0.820	×0.982	×1.008	16.83%
Doubles /BIP	10.74%	÷1.102	×0.720	×0.982	×1.008	6.95%
Triples /BIP	0.83%	÷1.060	×0.720	×0.982	×1.008	0.56%
Home runs /BIP	4.96%	÷1.187	×0.780	—	×1.008	3.28%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 137, 1B 99, 2B 120, 3B 112, K 99, BB 99 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.982.

Result: wOBA .369 → .249; ISO .212 → .132; BABIP .331 → .245. 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 ARancho Cucamonga Quakes · 123 PAwOBA .322 → .257 (−65)K% 26.0% → 35.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.02%	÷0.987	×1.360	—	—	35.84%
BB% (unintentional) /PA	14.63%	÷0.981	×0.690	—	×1.045	10.76%
HBP% /PA	0.81%	—	×0.780	—	×1.045	0.66%
Singles /BIP	26.39%	÷1.004	×0.920	×1.025	×1.045	25.90%
Doubles /BIP	4.17%	÷1.054	×0.830	×1.025	×1.045	3.51%
Triples /BIP	0.00%	÷1.150	×0.910	×1.025	×1.045	0.00%
Home runs /BIP	4.17%	÷1.055	×0.800	—	×1.045	3.30%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 111, 1B 101, 2B 111, 3B 130, K 97, BB 96 — 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 ×1.025.

Result: wOBA .322 → .257; ISO .115 → .084; BABIP .319 → .304. 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
#1Steve Buechele'85-'95 * career totals — 11 seasons, 4,790 PA	7.2	4,790	137	17	242*	314*	413*	+16	+18	15.7	16.1
/162	664	19	2	+2.2	+2.5	2.2	pk7: 16
#2Scott Brosius'91-'01 * career totals — 11 seasons, 4,356 PA	6.6	4,356	141	57	245*	309*	410*	+6	+18	14.1	15.1
/162	664	21	9	+1.0	+2.8	2.1	pk7: 16
#3Jeimer Candelariolast yr '25 career totals — 9 seasons, 3,576 PA	5.4	3,576	110	19	237	316	412	+8	-5	12.7	13.0
/162	664	20	4	+1.6	-0.9	2.4	pk7: 13
#4Jim Lefebvre'65-'72 * career totals — 8 seasons, 3,417 PA	5.1	3,417	74	8	250*	327*	411*	+11	-10	13.0	13.0
/162	664	14	2	+2.1	-2.0	2.5	pk7: 13
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 9 projected seasons	5.7	3,808	132	50	239	312	410	+14	-12	12.7	11.4
/162	664	23	9	+2.4	-2.1	2.2	pk7: 10
#5Maikel 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
#6Trevor 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

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
Chase Harlan (OGILVIE)	21	—	—	—	—	229/306/376	148	279	6	3	23%	9%	94	+0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Heriberto Hernández 2021 · A	21	45→48	49→60	46→50	47	220/300/377	156	305	15	6	31%	9%	92	+0.7	206/285/353	147	323	17	6	38%	9%	81	-0.1	222/305/421	199	281	26	11	30%	10%	104	+1.3
●Logan O'Hoppe 2022 · AAA	22	44→48	48→55	46→45	43	226/277/363	137	270	17	7	24%	6%	80	-0.2	240/312/419	179	282	24	6	24%	8%	106	+1.8	242/317/431	188	286	27	4	25%	8%	110	+1.4
✕Agustín Ramírez 2024 · AA	22	44→48	48→55	48→55	47	226/286/366	140	275	16	10	24%	8%	84	+0.1	237/299/402	165	282	19	17	22%	7%	97	+1.1	236/301/405	169	279	19	20	22%	7%	97	+1.1
●Andy Pages 2021 · A	20	43→53	46→60	46→50	46	215/300/346	131	277	14	9	26%	8%	85	+0.2	217/306/408	191	287	24	6	32%	9%	102	+1.5	269/326/453	184	315	23	10	22%	6%	121	+2.8
●Sean Rodríguez 2006 · A	21	44→51	46→60	49→50	53	217/301/350	133	262	13	15	22%	10%	86	+0.3	235/307/404	169	301	19	11	27%	8%	101	+1.4	244/318/452	208	301	26	12	27%	7%	113	+1.7
✕Miguel Amaya 2021 · A	22	43	46→50	48→40	47	217/290/349	133	270	14	4	25%	8%	82	-0.0	222/315/352	130	303	13	6	29%	9%	92	+0.7	216/325/362	146	296	16	3	30%	10%	98	+0.3
●Josmil Pinto 2010 · A	21	44→54	48→50	47→40	44	225/277/373	147	267	16	3	22%	6%	82	-0.0	217/263/349	132	268	14	2	24%	5%	71	-0.8	257/325/415	158	308	17	0	21%	8%	106	+1.5
●Gary Sánchez 2014 · AA	21	45→53	48→65	47→45	41	228/279/370	142	291	16	6	28%	6%	82	+0.0	248/299/402	154	302	19	6	24%	6%	97	+1.1	245/318/474	229	271	32	4	23%	8%	121	+2.3
●Derek Norris 2010 · A	21	45→55	52→55	45→50	49	228/310/392	164	299	20	5	30%	10%	99	+1.3	209/309/374	165	282	20	9	31%	12%	95	+1.0	257/333/410	152	314	16	5	22%	9%	112	+1.6
✕Max Stassi 2013 · A	22	43→45	48→55	44→40	40	219/279/357	139	300	16	5	32%	6%	79	-0.2	222/269/363	141	295	16	3	30%	5%	76	-0.4	216/302/377	161	281	21	0	29%	10%	94	+0.4
✕Renato Núñez 2015 · A	21	42→52	51→60	47→30	37	220/264/374	155	282	20	3	30%	4%	78	-0.3	216/261/384	168	263	23	3	27%	5%	79	-0.2	246/311/421	175	298	23	1	25%	7%	106	+1.3
●Travis d'Arnaud 2010 · A	21	44→54	45→60	45	43	219/265/344	126	254	12	6	20%	5%	71	-0.8	245/290/396	151	309	16	5	25%	5%	92	+0.7	260/318/455	195	291	26	1	20%	7%	117	+1.4
✕Bryan Ramos 2023 · AA	21	42	50	46→50	43	220/278/368	148	268	19	5	26%	6%	82	-0.0	212/275/345	133	268	16	8	27%	7%	76	-0.4	196/266/318	122	249	15	10	27%	7%	63	-1.0
●Jordan Diaz 2022 · A	21	49→59	49→55	42→30	44	249/294/398	149	296	16	5	22%	6%	93	+0.8	268/308/425	157	313	19	2	20%	5%	105	+1.7	274/316/435	161	317	20	0	20%	5%	108	+1.5
✕Kevin Cornelius 2016 · A	23	44	48→65	49→40	46	225/291/366	141	295	16	6	29%	8%	85	+0.2	218/276/375	157	324	19	3	36%	7%	82	-0.0	201/257/372	171	295	21	0	38%	7%	72	-0.2
●Todd Frazier 2008 · A	22	46→52	46→60	47→50	46	229/290/362	133	268	13	6	20%	6%	84	+0.2	235/289/383	148	296	15	8	25%	6%	88	+0.5	245/310/456	211	270	30	14	22%	8%	114	+2.6
●Sal Stewart 2024 · A	20	49→53	43→55	48→50	55	236/321/346	110	286	11	10	21%	11%	92	+0.7	249/321/397	148	298	16	12	21%	9%	104	+1.6	255/323/425	170	297	21	13	21%	8%	109	+1.8
●Vinnie Catricala 2010 · A	21	45→55	45→55	51→45	43	227/276/353	127	269	13	7	21%	5%	77	-0.3	248/303/396	148	306	15	7	23%	6%	97	+1.1	248/304/397	149	302	15	7	23%	6%	96	+0.9
✕Aaron Luna 2009 · A	22	42→46	51→50	51→45	45	211/318/370	159	292	18	7	32%	9%	99	+1.2	219/326/372	153	274	16	7	25%	8%	101	+1.4	219/329/369	150	272	17	7	24%	9%	99	+0.8
●Zach Neto 2023 · AA	22	51→48	46→60	49→55	42	249/311/386	137	314	13	12	25%	6%	97	+1.1	248/318/428	180	302	21	19	24%	6%	111	+2.1	246/319/446	200	307	24	25	27%	7%	116	+2.6

Chase Harlan

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps