Luis Aguilera

SS FCL Tigers

Age 20 L/R 5'11" / 145 lbs ROK HR -8% Svc 0.0 · Ctrl thru 2035

Overview

ROKPROSPECTMiLBFA 2036

OGV OFP35OGV rank#1349ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL Tigers 2	108	.292/.417/.348	1	5	57	—	.202/.306/.223
2025	18	ROKDSL Tigers 2	95	.253/.333/.337	0	5	32	—	.174/.237/.221
2026	19	ROKDET	118	.276/.356/.324	0	4	45	—	.211/.271/.239
2027PROJMLE	20	MLBDET	228	.224/.287/.303	2	4	68	0.0
2028PROJ34% MLB	21	MLBDET	40	.224/.288/.310	0	1	73	-0.0
2029PROJ48% MLB	22	MLBDET	99	.227/.292/.320	1	2	76	0.0

Next 3 projected WAR -0.0Projected 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$2M2034Arb-2$3M+1

Skills · percentileMiLB Statcast 2026 Rk

K%91

Z-Con%83

Whiff%79

Speed66

wRC+34

wOBA25

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 97%

CompsMatt Cerda (age 20) · Alberto Rodriguez (age 20) · Jean Carlos Sio (age 20)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 62 proj PA

wRC+†68

AVG/OBP/SLG.222 / .284 / .300

PA62

HR1

K%23

BB%7

ISO78

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$2M 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	+0.1	$0.3M	+$0.0M (cut)
2031	Pre-Arb	$0.9M	+0.2	$0.6M	+$0.0M
2032	Pre-Arb	$0.9M	+0.4	$1M	+$0.6M
2033	Arb-1	$2M	+0.4	$1M	+$0.0M (cut)
2034	Arb-2	$3M	+0.4	$0.9M	+$0.0M (cut)
2035	Arb-3	$4M	+0.3	$0.7M	+$0.0M (cut)
Totals		$2M		$5M	+$0.6M

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. 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)
2024	17	ROK	DSL Tigers 2	—	108	89	26	0	1	1	18	15	1	5	3	292	417	348	765	56	342	14	17	358	57	—	—	—	—	—	—
2025	18	ROK	DSL Tigers 2	—	95	83	21	3	2	0	10	10	0	5	2	253	333	337	671	84	280	11	11	300	32	—	—	—	—	—	—
2026	19	ROK	FCL Tigers	—	118	105	29	1	2	0	11	14	2	4	1	276	356	324	680	48	319	12	9	315	45	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Tigers 2	—	108	94	19	0	1	0	13	19	1	5	3	202	306	223	529	21	247	18	12	253	57	—	—	—	—	—	—
2025	18	ROK MLE	DSL Tigers 2	—	95	86	15	2	1	0	7	12	0	5	2	174	237	221	457	47	198	13	7	216	32	—	—	—	—	—	—
2026	19	ROK MLE	FCL Tigers	—	118	109	23	1	1	0	7	20	2	4	1	211	271	239	510	28	263	17	6	235	45	—	—	—	—	—	—
2024	17	ROK MLE	DSL Tigers 2	—	108	94	19	0	1	0	13	19	1	5	3	202	306	223	529	21	253	18	12	253	57	—	—	—	—	—	—
2024	17	ROK RAW	DSL Tigers 2	—	108	89	26	0	1	1	18	15	1	5	3	292	417	348	765	56	342	14	17	358	57	—	—	—	—	—	—
2025	18	ROK MLE	DSL Tigers 2	—	95	86	15	2	1	0	7	12	0	5	2	174	237	221	457	47	197	13	7	216	32	—	—	—	—	—	—
2025	18	ROK RAW	DSL Tigers 2	—	95	83	21	3	2	0	10	10	0	5	2	253	333	337	671	84	280	11	11	300	32	—	—	—	—	—	—
2026	19	ROK MLE	FCL Tigers	—	118	109	23	1	1	0	7	20	2	4	1	211	271	239	510	28	258	17	6	235	45	—	—	—	—	—	—
2026	19	ROK RAW	FCL Tigers	—	118	105	29	1	2	0	11	14	2	4	1	276	356	324	680	48	319	12	9	315	45	—	—	—	—	—	—
2024	17	ROK MLE	DSL Tigers 2	—	108	93	19	0	1	0	13	19	1	5	3	204	306	226	531	22	247	18	12	253	57	—	—	—	—	—	—
2025	18	ROK MLE	DSL Tigers 2	—	95	88	15	2	1	0	7	12	0	5	2	170	237	216	452	45	198	13	7	216	32	—	—	—	—	—	—
2026	19	ROK MLE	FCL Tigers	—	118	108	23	1	1	0	7	20	2	4	1	213	271	241	512	28	263	17	6	235	45	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Tigers 2	—	108	93	19	0	1	0	13	19	1	5	3	204	306	226	531	22	247	18	12	253	57	—	—	—	—	—	—
2025	18	ROK MLE	DSL Tigers 2	—	95	88	15	2	1	0	7	12	0	5	2	170	237	216	452	45	198	13	7	216	32	—	—	—	—	—	—
2026	19	ROK MLE	FCL Tigers	—	118	108	23	1	1	0	7	20	2	4	1	213	271	241	512	28	263	17	6	235	45	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	DET	0%	228	208	47	6	2	2	16	53	2	4	1	224	287	303	589	78	290	23	7	268	68	-9	+0	-1	+2	+5	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	DET	34%	115	105	23	3	1	1	8	27	1	2	1	228	292	316	607	88	291	23	7	275	73	-4	+0	-1	+1	+2	-0.1
2029	22	MLB MLE	DET	48%	205	186	44	6	2	3	15	47	2	4	1	231	295	327	622	96	292	23	7	281	76	-6	+0	-1	+2	+4	0.0
2030	23	MLB MLE	DET	54%	300	272	65	9	3	5	22	69	3	6	2	233	298	335	633	102	293	23	7	286	80	-7	+0	-1	+3	+6	0.2
2031	24	MLB MLE	DET	55%	374	339	79	11	3	6	28	85	4	8	2	235	300	342	643	107	293	23	7	290	82	-8	+1	-1	+4	+8	0.5
2032	25	MLB MLE	DET	56%	417	378	90	13	4	7	32	95	4	9	2	236	302	347	649	111	293	23	8	292	84	-8	+1	+0	+4	+9	0.7
2033	26	MLB MLE	DET	56%	440	400	94	13	4	8	33	100	4	9	3	236	302	348	650	112	293	23	8	292	84	-8	+1	+0	+5	+10	0.7
2034	27	MLB MLE	DET	55%	450	409	97	14	4	8	34	103	4	9	3	235	301	345	646	110	293	23	8	291	83	-9	+1	+0	+5	+10	0.6
2035	28	MLB MLE	DET	55%	450	409	95	13	4	8	34	104	4	9	3	233	299	341	640	107	292	23	8	288	81	-10	+1	-1	+5	+10	0.5
2036	29	MLB MLE	DET	53%	443	403	93	13	4	7	33	104	4	8	3	231	296	335	632	104	291	23	7	285	79	-11	+0	-1	+5	+10	0.2
2037	30	MLB MLE	DET	57%	432	393	89	12	3	7	32	103	4	7	3	229	293	328	621	99	290	24	7	281	76	-12	+0	-2	+5	+9	-0.0
2028	21	MLB CTX	DET	34%	40	37	7	1	0	0	3	9	0	1	0	224	288	310	598	85	286	22	8	272	73	-1	+0	-0	+0	+1	-0.0
2029	22	MLB CTX	DET	48%	99	91	21	3	1	1	7	23	1	2	1	227	292	320	612	93	287	23	7	277	76	-3	+0	-0	+1	+2	0.0
2030	23	MLB CTX	DET	54%	163	148	34	5	1	2	12	37	2	3	1	230	295	329	623	99	288	23	7	282	80	-4	+0	-0	+2	+4	0.1
2031	24	MLB CTX	DET	55%	207	187	43	6	2	3	16	47	2	4	1	231	297	335	632	104	289	23	8	285	82	-4	+0	-0	+2	+4	0.2
2032	25	MLB CTX	DET	56%	233	211	49	7	2	4	18	53	2	5	1	232	298	340	638	108	289	23	8	288	84	-4	+1	+0	+2	+5	0.4
2033	26	MLB CTX	DET	56%	247	224	51	7	2	4	19	56	2	5	1	232	298	340	639	108	289	23	8	288	84	-5	+1	+0	+3	+5	0.4
2034	27	MLB CTX	DET	55%	249	226	52	7	2	4	19	57	2	5	1	231	297	338	635	107	288	23	8	287	83	-5	+1	+0	+3	+5	0.4
2035	28	MLB CTX	DET	55%	247	224	51	7	2	4	19	57	2	5	1	230	296	334	629	104	288	23	8	284	81	-5	+1	-0	+3	+5	0.3
2036	29	MLB CTX	DET	53%	237	215	50	7	2	4	18	55	2	4	1	228	293	328	621	101	287	23	8	281	79	-6	+0	-1	+3	+5	0.1
2037	30	MLB CTX	DET	57%	247	225	51	7	2	4	18	59	2	4	2	225	290	321	611	96	285	24	7	277	76	-7	+0	-1	+3	+5	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1969	1788	409	57	16	30	149	453	17	38	10	229	294	329	623	100	289	23	8	283	78	-45	+4	-4	+21	+43	1.9
/ 162G	—	A+C		—	650	590	135	19	5	10	49	150	6	13	3	229	295	329	623	100	289	23	8	283	78	-15	+1	-1	+7	+14	0.6
Career	—	MLE		—	4009	3640	840	112	36	61	302	903	38	86	29	231	296	332	628	101	289	23	8	283	78	-86	+5	-7	+40	+80	3.2
/ 162G	—	MLE		—	650	590	136	18	6	10	49	146	6	14	5	231	296	332	628	102	288	22	8	283	78	-15	+1	-1	+7	+14	0.6

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 · 118 PAwOBA .308 → .235 (−72)K% 11.9% → 17.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.86%	÷1.000	×1.440	—	—	17.08%
BB% (unintentional) /PA	9.32%	÷1.000	×0.620	—	×1.008	5.82%
HBP% /PA	1.69%	—	×0.720	—	×1.008	1.23%
Singles /BIP	28.57%	÷1.000	×0.820	×1.012	×1.008	23.88%
Doubles /BIP	1.10%	÷1.000	×0.720	×1.012	×1.008	0.81%
Triples /BIP	2.20%	÷1.000	×0.720	×1.012	×1.008	1.61%
Home runs /BIP	0.00%	÷1.000	×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): no park row on file (treated as neutral) — 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 ×1.012.

Result: wOBA .308 → .235; ISO .048 → .034; BABIP .319 → .263. 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 DSLDSL Tigers 2 · 95 PAwOBA .295 → .216 (−80)K% 10.5% → 13.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.53%	÷0.991	×1.220	—	—	12.96%
BB% (unintentional) /PA	9.47%	÷0.974	×0.700	—	×1.008	6.86%
HBP% /PA	0.00%	—	×0.700	—	×1.008	0.00%
Singles /BIP	21.92%	÷0.994	×0.680	×1.039	×1.008	15.69%
Doubles /BIP	4.11%	÷0.962	×0.600	×1.039	×1.008	2.68%
Triples /BIP	2.74%	÷0.900	×0.600	×1.039	×1.008	1.91%
Home runs /BIP	0.00%	÷1.048	×0.470	—	×1.008	0.00%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 110, 1B 99, 2B 92, 3B 80, K 98, BB 95 — 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 ×1.039.

Result: wOBA .295 → .216; ISO .084 → .060; BABIP .280 → .198. 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 2 · 108 PAwOBA .350 → .253 (−97)K% 13.9% → 17.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.89%	÷0.986	×1.220	—	—	17.18%
BB% (unintentional) /PA	16.67%	÷0.973	×0.700	—	×1.022	12.26%
HBP% /PA	0.93%	—	×0.700	—	×1.022	0.66%
Singles /BIP	32.43%	÷0.995	×0.680	×1.050	×1.022	23.81%
Doubles /BIP	0.00%	÷0.951	×0.600	×1.050	×1.022	0.00%
Triples /BIP	1.35%	÷1.135	×0.600	×1.050	×1.022	0.77%
Home runs /BIP	1.35%	÷0.995	×0.470	—	×1.022	0.65%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 99, 1B 99, 2B 90, 3B 127, K 97, BB 95 — applied at half strength. Age: age 17 vs a level average of 18.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .350 → .253; ISO .056 → .030; BABIP .342 → .247. 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
#1Ronny 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
#2Chris 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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	3.1	2,031	33	41	234	296	340	+22	+0	3.5	3.3
/162	664	11	13	+7.1	+0.0	1.1	pk7: 3
#3Carlos Sanchez'14-'22 * career totals — 6 seasons, 2,503 PA	3.8	2,503	32	30	248*	305*	353*	+8	+0	2.1	2.6
/162	664	8	8	+2.0	+0.0	0.6	pk7: 3
#4Luis Rivera'86-'98 * career totals — 8 seasons, 2,453 PA	3.7	2,453	28	20	232*	291*	357*	+24	+5	1.2	2.3
/162	664	8	5	+6.4	+1.4	0.3	pk7: 3
#5Frank Duffy'70-'79 * career totals — 7 seasons, 2,924 PA	4.4	2,924	26	49	234*	283*	348*	+30	-2	0.9	2.1
/162	664	6	11	+6.7	-0.5	0.2	pk7: 3
#6Eddie Leon'68-'74 * career totals — 6 seasons, 2,092 PA	3.2	2,092	24	7	239*	296*	345*	+15	+4	0.1	0.1
/162	664	8	2	+4.7	+1.4	0.0	pk7: 0

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
Luis Aguilera (OGILVIE)	20	—	—	—	—	222/284/300	78	290	1	1	23%	7%	68	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Matt Cerda 2010 · A	20	43→53	38→40	50→40	46	207/264/285	78	263	6	6	23%	7%	56	-1.9	239/314/318	79	300	3	4	19%	10%	82	+0.0	241/325/315	74	303	3	4	19%	11%	84	+0.1
✕Alberto Rodriguez 2021 · A	20	42→52	38→50	52→50	44	203/259/282	79	268	5	14	25%	7%	53	-2.1	228/290/353	125	327	10	8	31%	7%	82	-0.0	228/292/360	132	326	11	7	31%	7%	81	-0.1
✕Jean Carlos Sio 2024 · A	20	41→51	36→45	51→50	51	192/268/258	66	238	4	13	20%	9%	52	-2.2	221/300/315	94	287	8	11	24%	8%	78	-0.3	224/303/331	107	289	11	12	25%	8%	79	-0.2
✕Eliezer Álvarez 2014 · A	19	36→46	37→45	50→55	46	176/242/253	76	228	4	12	24%	7%	41	-3.0	231/280/336	105	295	5	13	22%	6%	74	-0.6	254/307/364	110	341	6	19	26%	6%	88	+0.3
✕Gilberto Celestino 2019 · A	20	43→53	38→45	52→55	42	209/257/289	80	280	6	12	27%	6%	54	-2.0	226/281/328	102	291	8	8	24%	7%	72	-0.7	239/317/316	76	309	5	10	22%	9%	81	-0.0
✕Luis Barrera 2016 · A	20	40→50	36→45	50	43	190/245/252	62	259	3	6	27%	6%	41	-3.0	220/260/308	88	302	5	11	27%	5%	59	-1.7	248/293/357	110	319	5	17	23%	6%	80	-0.1
✕Marco Hernández 2013 · A	20	43→53	38→45	48→50	41	208/245/290	82	263	5	10	23%	4%	49	-2.4	227/255/309	82	299	5	12	25%	3%	57	-1.8	274/300/384	110	350	8	6	24%	3%	89	+0.3
✕Thomas Milone 2015 · A	20	41→46	36→45	51→55	38	195/248/268	73	295	3	10	33%	6%	46	-2.6	200/255/265	65	287	3	13	29%	6%	48	-2.5	237/293/355	117	331	8	17	29%	6%	79	-0.1
✕Juan Villavicencio 2024 · A	19	36→44	38→50	51→55	47	174/251/254	80	234	5	13	26%	8%	45	-2.7	189/262/280	91	279	7	14	32%	8%	55	-1.9	193/266/307	113	285	10	20	34%	8%	61	-0.6
✕Luis Valenzuela 2014 · A	20	40	37→45	53→45	47	191/248/264	73	236	4	9	20%	7%	45	-2.7	228/257/313	85	294	5	8	23%	4%	59	-1.7	263/285/365	102	319	5	7	19%	2%	78	-0.1
✕José Tena 2021 · A	20	45→55	36→45	50→55	38	213/250/285	72	290	3	9	27%	4%	50	-2.3	233/274/354	121	341	11	9	33%	5%	76	-0.4	252/310/371	119	358	10	21	31%	7%	90	+0.5
✕Rosell Herrera 2013 · A	20	40→50	37→45	48→55	42	193/245/268	75	263	5	9	28%	6%	45	-2.7	238/286/328	90	316	8	10	26%	6%	74	-0.6	253/308/344	91	321	4	24	21%	7%	84	+0.1
✕Yoyner Fajardo 2019 · A	20	46→56	37→40	57→60	51	211/279/293	82	248	2	14	16%	8%	63	-1.3	227/286/295	68	281	2	19	19%	6%	67	-1.1	260/318/350	90	329	5	34	21%	7%	87	+0.2
✕Adan Velazquez 2010 · A	20	41→51	40→45	53→50	45	197/263/292	95	245	6	11	22%	6%	58	-1.7	203/256/288	85	282	5	10	28%	5%	54	-2.0	254/293/350	97	308	8	4	20%	4%	79	-0.1
✕Brainer Bonaci 2022 · A	20	40→46	38→45	53→50	43	192/253/278	86	262	5	13	27%	7%	51	-2.3	219/294/329	110	303	9	13	28%	9%	78	-0.3	221/301/335	114	300	11	14	28%	10%	80	-0.1
✕Carlos Jimenez 2022 · A	19	36→44	39→50	53→55	48	177/265/262	85	249	7	11	30%	9%	53	-2.1	194/283/299	105	299	9	16	34%	10%	68	-1.0	223/303/376	153	308	17	18	31%	10%	89	+0.4
✕Livan Soto 2021 · A	21	43→53	35→40	46→50	48	203/262/259	56	253	3	8	20%	7%	49	-2.4	215/278/306	91	295	7	11	27%	8%	66	-1.1	246/319/331	85	322	6	8	24%	9%	86	+0.2
✕Shawn O'Malley 2008 · A	20	42→52	36→40	50→60	41	199/263/266	68	282	4	11	29%	6%	52	-2.2	217/293/272	55	302	1	24	26%	7%	65	-1.2	259/320/356	97	321	5	23	20%	7%	91	+0.4
✕Nick Allen 2019 · A	20	43→53	35→40	52→50	42	200/249/258	58	260	2	14	23%	5%	44	-2.8	223/272/312	89	287	5	14	23%	6%	65	-1.2	253/316/328	75	310	5	13	19%	8%	84	+0.1
✕Brian Sanchez 2024 · A	20	43→42	36→50	50→55	50	202/282/280	78	270	2	12	24%	9%	62	-1.4	211/280/327	116	302	8	17	30%	8%	72	-0.7	209/280/344	135	298	11	18	31%	8%	74	-0.3

Luis Aguilera

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps