Maikol Orozco

SS FCL Tigers

Age 21 R/R 5'11" / 175 lbs ROK HR -8% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#2381ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	18	ROKDSL Tigers 1	187	.301/.452/.411	2	13	63	—	.192/.323/.256
2025	19	ROKDET	132	.226/.364/.377	2	2	42	—	.152/.264/.259
2026	20	ROKDET	167	.315/.398/.418	2	1	53	—	.211/.277/.263
2027PROJMLE	21	MLBDET	277	.194/.265/.280	3	4	55	-0.1
2028PROJ34% MLB	22	MLBDET	46	.196/.267/.289	1	1	61	-0.0
2029PROJ48% MLB	23	MLBDET	104	.200/.272/.300	2	2	65	-0.1

Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2038Service0.0First FA2039

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032MiLB2033Pre-Arb$0.9M2034Pre-Arb$1.0M+4

Skills · percentileMiLB Statcast 2026 Rk

wRC+68

wOBA57

ISO42

Z-Con%34

K%33

Speed27

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsSteven Baron (age 21) · Chris Roller (age 21) · Ricardo Hurtado (age 21)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 86 proj PA

wRC+†55

AVG/OBP/SLG.192 / .262 / .278

PA86

HR1

K%28

BB%7

ISO87

MLB%0%

Value2027 · WAR

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

Tools · ContractCON 25 / POW 40

Toolsscout grade

CONTACT25

scouting grade only

POWER40

scouting grade only

EYE50

scouting grade only

SPEED49

scouting grade only

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

Status MiLB

MLB Debut 2033

Service 0 yrs (est)

Team Control Through 2038

First FA Year 2039

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2033
2028	MiLB	still in minors · estimated debut 2033
2029	MiLB	still in minors · estimated debut 2033
2030	MiLB	still in minors · estimated debut 2033
2031	MiLB	still in minors · estimated debut 2033
2032	MiLB	still in minors · estimated debut 2033
2033	Pre-Arb	$0.9M	—	—	—
2034	Pre-Arb	$1.0M	—	—	—
2035	Pre-Arb	$1.0M	—	—	—
2036	Ext	beyond projection horizon · no WAR estimate
2037	Ext	beyond projection horizon · no WAR estimate
2038	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.7M	+$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. 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	17	ROK	DSL Tigers 1	—	167	133	34	4	1	2	23	29	8	9	3	256	396	346	742	90	305	17	14	343	42	—	—	—	—	—	—
2024	18	ROK	DSL Tigers 1	—	187	146	44	8	1	2	31	32	9	13	8	301	452	411	863	110	372	17	17	397	63	—	—	—	—	—	—
2025	19	ROK	FCL Tigers	—	132	106	24	6	2	2	17	37	6	2	1	226	364	377	742	151	314	28	13	334	42	—	—	—	—	—	—
2026	20	ROK	FCL Tigers	—	167	146	46	5	2	2	15	42	5	1	2	315	398	418	815	103	427	25	9	368	53	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2023	17	ROK MLE	DSL Tigers 1	—	167	140	23	3	1	1	16	36	8	9	3	164	287	221	508	57	192	22	10	231	42	—	—	—	—	—	—
2024	18	ROK MLE	DSL Tigers 1	—	187	156	30	5	1	1	21	39	9	13	8	192	323	256	579	64	240	21	11	262	63	—	—	—	—	—	—
2025	19	ROK MLE	FCL Tigers	—	132	112	17	4	1	2	11	53	6	2	1	152	264	259	522	107	238	40	8	230	42	—	—	—	—	—	—
2026	20	ROK MLE	FCL Tigers	—	167	152	32	3	1	1	9	60	5	1	2	211	277	263	540	53	332	36	5	247	53	—	—	—	—	—	—
2023	17	ROK MLE	DSL Tigers 1	—	167	140	23	3	1	1	16	36	8	9	3	164	287	221	508	57	208	22	10	231	42	—	—	—	—	—	—
2023	17	ROK RAW	DSL Tigers 1	—	167	133	34	4	1	2	23	29	8	9	3	256	396	346	742	90	305	17	14	343	42	—	—	—	—	—	—
2024	18	ROK MLE	DSL Tigers 1	—	187	156	30	5	1	1	21	39	9	13	8	192	323	256	579	64	248	21	11	262	63	—	—	—	—	—	—
2024	18	ROK RAW	DSL Tigers 1	—	187	146	44	8	1	2	31	32	9	13	8	301	452	411	863	110	372	17	17	397	63	—	—	—	—	—	—
2025	19	ROK MLE	FCL Tigers	—	132	112	17	4	1	2	11	53	6	2	1	152	264	259	522	107	250	40	8	230	42	—	—	—	—	—	—
2025	19	ROK RAW	FCL Tigers	—	132	106	24	6	2	2	17	37	6	2	1	226	364	377	742	151	314	28	13	334	42	—	—	—	—	—	—
2026	20	ROK MLE	FCL Tigers	—	167	152	32	3	1	1	9	60	5	1	2	211	277	263	540	53	337	36	5	247	53	—	—	—	—	—	—
2026	20	ROK RAW	FCL Tigers	—	167	146	46	5	2	2	15	42	5	1	2	315	398	418	815	103	427	25	9	368	53	—	—	—	—	—	—
2023	17	ROK MLE	DSL Tigers 1	—	167	141	23	3	1	1	16	36	8	9	3	163	287	220	506	57	192	22	10	231	42	—	—	—	—	—	—
2024	18	ROK MLE	DSL Tigers 1	—	187	155	30	5	1	1	21	39	9	13	8	194	323	258	581	65	240	21	11	262	63	—	—	—	—	—	—
2025	19	ROK MLE	FCL Tigers	—	132	114	17	4	1	2	11	53	6	2	1	149	264	254	518	105	238	40	8	230	42	—	—	—	—	—	—
2026	20	ROK MLE	FCL Tigers	—	167	151	32	3	1	1	9	60	5	1	2	212	277	265	542	53	332	36	5	247	53	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	18	ROK MLE	DSL Tigers 1	—	187	155	30	5	1	1	21	39	9	13	8	194	323	258	581	65	240	21	11	262	63	—	—	—	—	—	—
2025	19	ROK MLE	FCL Tigers	—	132	114	17	4	1	2	11	53	6	2	1	149	264	254	518	105	238	40	8	230	42	—	—	—	—	—	—
2026	20	ROK MLE	FCL Tigers	—	167	151	32	3	1	1	9	60	5	1	2	212	277	265	542	53	332	36	5	247	53	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	21	MLB MLE	DET	0%	277	251	48	8	2	3	20	77	4	4	1	194	265	280	545	87	263	28	7	250	55	-15	+0	+0	+3	+6	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	22	MLB MLE	DET	34%	134	121	24	4	1	2	10	37	2	2	1	199	270	295	566	97	266	28	7	258	61	-6	+0	+0	+1	+3	-0.2
2029	23	MLB MLE	DET	48%	215	194	40	7	1	4	16	58	3	4	1	203	275	307	582	104	268	27	7	265	65	-9	+0	+0	+2	+5	-0.2
2030	24	MLB MLE	DET	53%	298	269	56	10	2	5	22	80	5	5	2	207	278	316	594	109	270	27	7	270	69	-11	+0	+0	+3	+6	-0.1
2031	25	MLB MLE	DET	55%	355	320	67	12	2	7	27	94	5	6	2	209	281	322	603	113	271	26	8	273	71	-12	+0	+0	+4	+8	-0.0
2032	26	MLB MLE	DET	56%	387	349	74	13	2	8	29	102	6	7	2	211	283	327	609	116	272	26	7	276	73	-13	+1	+0	+4	+8	0.1
2033	27	MLB MLE	DET	55%	401	361	75	13	2	8	31	106	6	7	2	210	282	324	606	114	272	26	8	274	72	-13	+1	+0	+4	+9	0.0
2034	28	MLB MLE	DET	55%	404	364	76	13	2	8	31	108	6	6	2	208	280	320	600	112	271	27	8	272	70	-14	+0	-1	+4	+9	-0.2
2035	29	MLB MLE	DET	53%	398	359	74	13	2	7	30	107	6	6	2	206	277	314	591	108	270	27	8	268	68	-15	+0	-1	+4	+9	-0.3
2028	22	MLB CTX	DET	34%	46	42	8	1	0	1	3	13	1	1	0	196	267	289	556	94	261	28	7	254	61	-2	+0	+0	+0	+1	-0.0
2029	23	MLB CTX	DET	48%	104	93	19	3	1	2	8	28	2	2	1	200	272	300	572	101	264	27	8	261	65	-4	+0	+0	+1	+2	-0.1
2030	24	MLB CTX	DET	53%	157	142	29	5	1	3	12	42	2	3	1	203	275	309	584	106	266	27	8	266	69	-6	+0	+0	+2	+3	-0.1
2031	25	MLB CTX	DET	55%	194	174	36	6	1	4	15	51	3	3	1	205	278	315	593	110	267	26	8	269	71	-7	+0	+0	+2	+4	-0.0
2032	26	MLB CTX	DET	56%	215	194	40	7	1	4	16	57	3	4	1	207	280	319	599	112	268	27	7	271	73	-7	+0	+0	+2	+5	0.0
2033	27	MLB CTX	DET	55%	221	199	40	7	1	4	17	58	3	4	1	206	279	317	595	111	267	26	8	270	72	-7	+0	+0	+2	+5	0.0
2034	28	MLB CTX	DET	55%	221	199	40	7	1	4	17	59	3	3	1	205	277	312	589	108	266	27	8	268	70	-8	+0	-0	+2	+5	-0.1
2035	29	MLB CTX	DET	53%	212	191	39	7	1	4	16	57	3	3	1	202	274	307	581	104	265	27	8	264	68	-8	+0	-1	+2	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1370	1234	251	43	7	26	104	365	20	23	7	203	276	313	589	109	265	27	8	267	66	-49	+2	-1	+15	+30	-0.4
/ 162G	—	A+C		—	650	585	118	20	3	12	49	173	9	11	3	202	273	308	581	106	263	27	8	267	66	-23	+1	-1	+7	+14	-0.2
Career	—	MLE		—	3331	2976	604	103	19	55	259	904	68	69	28	203	282	306	588	103	269	27	8	265	66	-99	+3	-2	+29	+58	-1.1
/ 162G	—	MLE		—	650	581	118	20	4	11	51	176	13	13	5	203	282	308	590	105	269	27	8	265	66	-24	+1	-1	+7	+14	-0.3

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 ROKFCL Tigers · 167 PAwOBA .361 → .247 (−114)K% 25.1% → 36.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.15%	÷1.000	×1.440	—	—	36.22%
BB% (unintentional) /PA	8.98%	÷1.000	×0.620	—	×0.985	5.49%
HBP% /PA	2.99%	—	×0.720	—	×0.985	2.12%
Singles /BIP	35.58%	÷1.000	×0.820	×0.987	×0.985	28.35%
Doubles /BIP	4.81%	÷1.000	×0.720	×0.987	×0.985	3.36%
Triples /BIP	1.92%	÷1.000	×0.720	×0.987	×0.985	1.35%
Home runs /BIP	1.92%	÷1.000	×0.780	—	×0.985	1.48%

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 21 vs a level average of 19.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.987.

Result: wOBA .361 → .247; ISO .103 → .067; BABIP .427 → .332. 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 ROKFCL Tigers · 132 PAwOBA .333 → .230 (−103)K% 28.0% → 40.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.03%	÷1.001	×1.440	—	—	40.32%
BB% (unintentional) /PA	12.88%	÷0.996	×0.620	—	×0.995	7.98%
HBP% /PA	4.55%	—	×0.720	—	×0.995	3.26%
Singles /BIP	20.29%	÷0.974	×0.820	×0.950	×0.995	16.15%
Doubles /BIP	8.70%	÷0.992	×0.720	×0.950	×0.995	5.97%
Triples /BIP	2.90%	÷0.900	×0.720	×0.950	×0.995	2.19%
Home runs /BIP	2.90%	÷0.880	×0.780	—	×0.995	2.56%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 76, 1B 95, 2B 98, 3B 80, K 100, BB 99 — applied at half strength. Age: age 20 vs a level average of 19.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .333 → .230; ISO .151 → .109; BABIP .314 → .238. 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 DSLDSL Tigers 1 · 187 PAwOBA .390 → .262 (−127)K% 17.1% → 20.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.11%	÷1.002	×1.220	—	—	20.84%
BB% (unintentional) /PA	16.58%	÷1.009	×0.700	—	×0.995	11.45%
HBP% /PA	4.81%	—	×0.700	—	×0.995	3.35%
Singles /BIP	28.95%	÷1.014	×0.680	×0.993	×0.995	19.18%
Doubles /BIP	7.02%	÷0.958	×0.600	×0.993	×0.995	4.34%
Triples /BIP	0.88%	÷1.150	×0.600	×0.993	×0.995	0.45%
Home runs /BIP	1.75%	÷1.105	×0.470	—	×0.995	0.74%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 121, 1B 103, 2B 92, 3B 130, K 100, BB 102 — applied at half strength. Age: age 19 vs a level average of 18.5 → −0.5% on BB/HBP/hit rates (0.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.

Result: wOBA .390 → .262; ISO .110 → .062; BABIP .372 → .240. 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 DSLDSL Tigers 1 · 167 PAwOBA .341 → .231 (−110)K% 17.4% → 21.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.37%	÷0.995	×1.220	—	—	21.28%
BB% (unintentional) /PA	13.77%	÷1.009	×0.700	—	×1.008	9.62%
HBP% /PA	4.79%	—	×0.700	—	×1.008	3.38%
Singles /BIP	25.96%	÷1.058	×0.680	×0.975	×1.008	16.40%
Doubles /BIP	3.85%	÷0.901	×0.600	×0.975	×1.008	2.52%
Triples /BIP	0.96%	÷0.900	×0.600	×0.975	×1.008	0.63%
Home runs /BIP	1.92%	÷0.862	×0.470	—	×1.008	1.06%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 72, 1B 112, 2B 80, 3B 80, K 99, BB 102 — applied at half strength. Age: age 18 vs a level average of 18.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.975.

Result: wOBA .341 → .231; ISO .090 → .057; BABIP .305 → .192. 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).

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1Adam Rosaleslast yr '17 career totals — 9 seasons, 1,756 PA	2.6	1,756	47	16	227	293	367	+6	+8	3.0	3.5
/162	664	18	6	+2.4	+3.0	1.1	pk7: 4
#2Tim Bogar'93-'01 * career totals — 8 seasons, 1,710 PA	2.6	1,710	24	13	217*	284*	324*	+11	+37	2.1	2.9
/162	664	9	5	+4.2	+14.4	0.8	pk7: 4
#3Ryan Goinslast yr '19 career totals — 7 seasons, 1,680 PA	2.5	1,680	22	6	230	279	335	+9	+21	2.0	2.0
/162	664	9	2	+3.7	+8.5	0.8	pk7: 2
#4Benji Gil'93-'03 * career totals — 7 seasons, 1,767 PA	2.7	1,767	32	24	227*	272*	349*	+10	+30	0.6	1.0
/162	664	12	9	+3.8	+11.3	0.2	pk7: 1
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	2.2	1,457	26	24	208	277	318	+16	+15	0.4	0.5
/162	664	12	11	+7.1	+6.8	0.2	pk7: 1
#5David Howard'91-'99 * career totals — 8 seasons, 1,795 PA	2.7	1,795	11	23	220*	280*	301*	+10	+23	-1.6	-0.8
/162	664	4	9	+3.7	+8.5	-0.6	pk7: -0
#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
Maikol Orozco (OGILVIE)	21	20→25	35→40	44→49	50	192/262/278	86	263	1	1	28%	7%	55	-0.3	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Steven Baron 2012 · A	21	34	39→45	45→50	36	174/218/258	84	255	7	7	34%	5%	32	-3.6	190/226/284	94	268	6	9	30%	4%	41	-3.0	236/292/311	74	314	4	8	24%	7%	69	-0.4
✕Chris Roller 2018 · A	21	37	37→45	53→55	45	177/253/254	77	242	4	12	27%	8%	46	-2.6	204/272/316	112	294	8	11	31%	7%	67	-1.1	189/255/293	104	275	7	15	32%	6%	54	-1.0
✕Ricardo Hurtado 2024 · A	21	39→29	40→45	48→45	46	187/286/283	96	259	7	6	28%	8%	67	-1.1	184/278/286	102	279	10	4	35%	9%	63	-1.3	163/265/259	96	246	11	3	35%	10%	51	-1.2
✕Misael Urbina 2023 · A	21	38→32	41→40	49→50	45	190/258/293	104	259	8	12	29%	8%	57	-1.8	179/258/267	88	262	6	9	31%	9%	51	-2.3	166/253/247	81	240	5	8	30%	10%	42	-1.7
✕Jose D. Hernandez 2024 · A	21	38	39→45	47→45	49	183/269/272	89	233	6	8	23%	8%	57	-1.8	203/275/318	115	275	11	8	29%	7%	69	-0.9	170/260/288	119	235	15	5	33%	11%	53	-0.7
✕Sammy Hernandez 2024 · A	20	37	43→40	51→50	40	188/254/301	113	262	11	5	31%	6%	57	-1.8	203/291/298	95	270	8	9	26%	9%	71	-0.8	201/300/298	97	262	9	13	24%	10%	72	-0.4
✕Gilberto Vizcarra 2019 · A	20	34	37→45	47→40	47	164/238/229	66	203	5	3	22%	7%	35	-3.4	205/261/282	77	259	5	4	22%	6%	55	-2.0	227/269/318	92	274	7	1	19%	4%	65	-0.4
✕Ismael Alcantara 2019 · A	20	36→30	38→45	50	43	177/250/254	77	257	5	13	32%	7%	45	-2.7	207/272/309	102	322	8	15	36%	7%	65	-1.2	191/253/307	116	283	12	16	35%	6%	55	-0.9
✕Aaron McKeithan 2022 · A	22	41	38→40	49→40	40	195/262/275	80	276	6	7	30%	6%	54	-2.0	219/293/300	81	280	8	4	23%	7%	72	-0.7	211/298/265	54	265	5	1	21%	8%	64	-0.3
✕Victor Duarte 2022 · A	21	38	38→30	48→45	42	185/249/264	79	253	5	7	28%	6%	47	-2.6	199/274/279	80	289	6	6	31%	7%	59	-1.6	182/251/245	63	250	5	11	28%	7%	41	-0.8
✕Kyle Nevin 2023 · A	21	41→40	40	52→50	39	199/251/297	98	277	6	10	29%	5%	54	-2.0	219/276/320	101	333	8	10	34%	7%	69	-0.9	214/275/310	96	327	9	12	35%	7%	64	-0.8
✕Imbewer Alvarez 2007 · A	21	39	38→40	45→55	39	187/243/268	81	270	4	8	31%	6%	45	-2.7	194/262/265	71	270	4	15	28%	7%	51	-2.2	186/265/247	62	244	4	22	24%	8%	47	-0.7
✕Rudy van Heydoorn 2010 · A	21	31	39→40	40→50	43	157/245/233	76	238	7	8	35%	8%	39	-3.1	186/267/280	94	282	8	5	34%	9%	57	-1.8	172/284/270	98	232	9	2	27%	12%	64	-0.5
✕Juan Mora 2021 · A	21	40	39→45	53→55	52	192/277/280	88	229	6	14	19%	8%	61	-1.5	221/287/329	108	296	9	10	27%	6%	75	-0.5	218/275/319	102	286	9	8	26%	5%	67	-0.5
✕Abrahan Gutierrez 2021 · A	21	45→41	39→45	46→40	43	217/266/297	81	277	7	6	24%	6%	59	-1.6	224/295/328	104	296	9	4	26%	8%	78	-0.3	216/291/318	102	282	9	2	25%	8%	72	-0.4
✕Nelson Medina 2022 · A	21	38	38→45	53→50	51	181/272/260	79	252	4	15	28%	10%	55	-2.0	185/255/278	93	317	6	13	40%	8%	52	-2.2	140/198/215	76	278	6	16	49%	6%	14	-1.7
✕Pablo Aliendo 2021 · A	20	38	36→50	50→45	44	181/261/246	65	268	3	13	31%	8%	47	-2.5	202/271/300	98	303	9	5	34%	6%	63	-1.3	206/275/350	144	296	17	5	34%	7%	73	-0.3
✕Jason Lopez 2018 · A	20	39	37→50	47→45	46	188/260/261	73	250	5	9	26%	8%	50	-2.3	207/250/323	116	289	11	6	31%	5%	60	-1.6	192/240/305	113	271	11	8	32%	6%	50	-1.0
✕Jose Cordoba 2023 · A	20	37	41→40	44→55	40	185/250/278	93	262	9	9	32%	6%	50	-2.3	205/259/296	91	278	6	11	27%	6%	57	-1.8	203/257/294	91	267	4	15	24%	5%	53	-0.9
✕Allan Cerda 2021 · A	21	43→25	40→55	47→45	44	206/283/296	90	283	7	7	28%	7%	67	-1.1	185/280/351	166	286	19	5	39%	9%	80	-0.2	159/268/326	167	242	20	5	41%	10%	67	-0.7

Maikol Orozco

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps