Aldo Gaxiola

3B Dunedin Blue Jays

Age 21 R/R 6'2" / 187 lbs A Svc 0.0 · Ctrl thru 2037

Overview

APROSPECTMiLBFA 2038

ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	18	ROKTOR	133	.286/.389/.464	4	1	53	—	.179/.267/.274
2025	19	ROKTOR	225	.258/.342/.333	2	3	31	—	.183/.244/.231
2026	20	A/INTL2 orgs	411	.262/.325/.481	19	2	74	—	.208/.264/.372
2027PROJMLE	21	MLBTOR	479	.199/.253/.329	13	3	62	-0.3
2028PROJ34% MLB	22	MLBTOR	110	.204/.260/.340	3	1	67	-0.1
2029PROJ48% MLB	23	MLBTOR	192	.208/.265/.348	6	2	71	-0.1

Next 3 projected WAR -0.6Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2037Service0.0First FA2038

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032Pre-Arb$0.9M2033Pre-Arb$0.9M2034Pre-Arb$1.0M+3

Skills · percentileMiLB Statcast 2026 A

Max EV94

Z-Con%45

Speed45

K%40

Whiff%36

Chase%16

Career WAR0.0 WAR median (P10 -0.2 / P90 4.9, comp-based) · star 2% · didn't stick 82%

CompsTravis Harrison (age 21) · Omar Estévez (age 21) · Dante Bichette Jr. (age 21)

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

wRC+†62

AVG/OBP/SLG.197 / .251 / .326

PA210

HR6

K%34

BB%5

ISO130

MLB%0%

Value2027 · WAR

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

Tools · ContractCON 40 / POW 20

Toolsscout grade

CONTACT40

scouting grade only

POWER20

scouting grade only

EYE40

scouting grade only

SPEED40

scouting grade only

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

Status MiLB

MLB Debut 2032

Service 0 yrs (est)

Team Control Through 2037

First FA Year 2038

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2032
2028	MiLB	still in minors · estimated debut 2032
2029	MiLB	still in minors · estimated debut 2032
2030	MiLB	still in minors · estimated debut 2032
2031	MiLB	still in minors · estimated debut 2032
2032	Pre-Arb	$0.9M	—	—	—
2033	Pre-Arb	$0.9M	—	—	—
2034	Pre-Arb	$1.0M	—	—	—
2035	Arb-1	$0.2M	—	—	—
2036	Ext	beyond projection horizon · no WAR estimate
2037	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-1M	+$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 Blue Jays	—	74	61	15	2	0	1	10	16	2	3	1	246	370	328	698	82	311	22	14	324	29	—	—	—	—	—	—
2024	18	ROK	DSL Blue Jays	—	133	112	32	8	0	4	13	20	6	1	0	286	389	464	854	179	311	15	10	377	53	—	—	—	—	—	—
2025	19	ROK	FCL Blue Jays	—	225	198	51	7	1	2	25	40	1	3	1	258	342	333	676	76	314	18	11	311	31	—	—	—	—	—	—
2026	20	A	Dunedin Blue Jays	—	369	335	88	17	2	18	21	101	11	1	0	263	327	487	814	224	321	27	6	356	70	—	—	—	—	—	—
2026	20	INTL	Mayos de Navojoa	—	42	39	10	2	1	1	3	12	0	1	0	256	310	436	745	179	346	29	7	328	108	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2023	17	ROK MLE	DSL Blue Jays	—	74	64	9	1	0	0	7	19	2	3	1	141	247	156	403	16	196	26	9	211	29	—	—	—	—	—	—
2024	18	ROK MLE	DSL Blue Jays	—	133	117	21	5	0	2	8	25	6	1	0	179	267	274	541	94	204	19	6	247	53	—	—	—	—	—	—
2025	19	ROK MLE	FCL Blue Jays	—	225	208	38	5	1	1	16	58	1	3	1	183	244	231	475	48	241	26	7	214	31	—	—	—	—	—	—
2026	20	A MLE	Dunedin Blue Jays	—	369	341	71	13	2	13	15	137	11	1	0	208	264	372	637	164	295	37	4	272	70	—	—	—	—	—	—
2023	17	ROK MLE	DSL Blue Jays	—	74	64	9	1	0	0	7	19	2	3	1	141	247	156	403	16	196	26	9	211	29	—	—	—	—	—	—
2023	17	ROK RAW	DSL Blue Jays	—	74	61	15	2	0	1	10	16	2	3	1	246	370	328	698	82	311	22	14	324	29	—	—	—	—	—	—
2024	18	ROK MLE	DSL Blue Jays	—	133	117	21	5	0	2	8	25	6	1	0	179	267	274	541	94	207	19	6	247	53	—	—	—	—	—	—
2024	18	ROK RAW	DSL Blue Jays	—	133	112	32	8	0	4	13	20	6	1	0	286	389	464	854	179	311	15	10	377	53	—	—	—	—	—	—
2025	19	ROK MLE	FCL Blue Jays	—	225	208	38	5	1	1	16	58	1	3	1	183	244	231	475	48	248	26	7	214	31	—	—	—	—	—	—
2025	19	ROK RAW	FCL Blue Jays	—	225	198	51	7	1	2	25	40	1	3	1	258	342	333	676	76	314	18	11	311	31	—	—	—	—	—	—
2026	20	A MLE	2 teams	—	411	382	79	14	2	15	16	153	11	2	0	207	259	372	631	165	296	37	4	272	70	—	—	—	—	—	—
2026	20	A RAW	2 teams	—	411	374	98	19	3	19	24	113	11	2	0	262	325	481	806	219	324	27	6	353	70	—	—	—	—	—	—
2023	17	ROK MLE	DSL Blue Jays	—	74	65	9	1	0	0	7	19	2	3	1	138	247	154	400	15	196	26	9	211	29	—	—	—	—	—	—
2024	18	ROK MLE	DSL Blue Jays	—	133	118	21	5	0	2	8	25	6	1	0	178	267	271	538	93	204	19	6	247	53	—	—	—	—	—	—
2025	19	ROK MLE	FCL Blue Jays	—	225	206	38	5	1	1	16	58	1	3	1	184	244	233	477	49	241	26	7	214	31	—	—	—	—	—	—
2026	20	A MLE	2 teams	—	411	381	79	14	2	15	16	153	11	2	0	207	259	373	632	165	295	37	4	272	70	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	18	ROK MLE	DSL Blue Jays	—	133	118	21	5	0	2	8	25	6	1	0	178	267	271	538	93	204	19	6	247	53	—	—	—	—	—	—
2025	19	ROK MLE	FCL Blue Jays	—	225	206	38	5	1	1	16	58	1	3	1	184	244	233	477	49	241	26	7	214	31	—	—	—	—	—	—
2026	20	A MLE	2 teams	—	411	381	79	14	2	15	16	153	11	2	0	207	259	373	632	165	295	37	4	272	70	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	21	MLB MLE	TOR	0%	479	444	89	16	2	13	24	163	8	3	1	199	253	329	582	130	279	34	5	260	62	-21	+0	+0	+2	+10	-0.3
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	22	MLB MLE	TOR	34%	320	294	60	11	1	9	17	106	6	2	1	204	260	339	599	135	280	33	5	268	67	-12	+0	+0	+1	+7	-0.5
2029	23	MLB MLE	TOR	48%	397	365	76	14	2	11	22	128	7	3	1	207	265	347	612	140	282	32	6	273	71	-14	+0	+0	+1	+9	-0.4
2030	24	MLB MLE	TOR	53%	446	411	86	15	2	13	25	141	7	3	1	211	269	353	622	143	283	32	6	277	74	-14	+0	+0	+2	+10	-0.2
2031	25	MLB MLE	TOR	55%	473	434	93	17	2	14	28	148	8	4	1	213	272	357	629	144	283	31	6	281	76	-14	+0	+0	+2	+10	-0.1
2032	26	MLB MLE	TOR	56%	486	446	95	17	2	14	29	149	8	3	1	214	274	359	634	145	284	31	6	282	77	-13	+0	+0	+2	+11	-0.1
2033	27	MLB MLE	TOR	55%	489	448	95	17	2	14	30	151	8	3	1	213	273	356	630	144	283	31	6	281	76	-14	+0	+0	+2	+11	-0.1
2034	28	MLB MLE	TOR	55%	486	447	94	17	2	14	29	151	7	2	1	211	271	352	623	141	282	31	6	278	74	-15	+0	-1	+2	+11	-0.3
2035	29	MLB MLE	TOR	53%	475	437	90	16	2	13	28	149	7	0	0	208	268	345	613	137	280	31	6	274	72	-16	+0	-1	+2	+10	-0.5
2028	22	MLB CTX	TOR	34%	110	101	21	4	0	3	6	36	2	1	0	204	260	340	600	136	281	33	5	268	67	-4	+0	+0	+0	+2	-0.1
2029	23	MLB CTX	TOR	48%	192	176	38	7	1	6	11	62	3	2	0	208	265	348	613	140	283	32	6	274	71	-7	+0	+0	+1	+4	-0.1
2030	24	MLB CTX	TOR	53%	235	216	46	8	1	7	13	74	4	2	0	211	270	354	624	143	284	31	6	278	74	-7	+0	+0	+1	+5	-0.1
2031	25	MLB CTX	TOR	55%	259	238	51	9	1	8	15	81	4	2	0	213	273	358	631	145	285	31	6	281	76	-7	+0	+0	+1	+6	-0.0
2032	26	MLB CTX	TOR	56%	271	249	54	10	1	8	16	83	4	2	0	215	275	360	635	145	285	31	6	283	77	-7	+0	+0	+1	+6	-0.0
2033	27	MLB CTX	TOR	55%	269	247	52	9	1	8	16	83	4	2	0	214	274	357	631	144	284	31	6	282	76	-8	+0	+0	+1	+6	-0.0
2034	28	MLB CTX	TOR	55%	266	244	52	9	1	8	16	83	4	1	0	212	272	353	624	141	283	31	6	279	74	-8	+0	-0	+1	+6	-0.2
2035	29	MLB CTX	TOR	53%	253	232	49	9	1	7	15	79	4	0	0	209	269	346	615	137	281	31	6	275	72	-9	+0	-1	+1	+5	-0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1855	1703	363	65	7	55	108	581	29	12	0	213	272	356	628	143	287	31	6	278	70	-57	+2	-1	+7	+40	-0.9
/ 162G	—	A+C		—	650	597	127	23	2	19	38	204	10	4	0	213	271	353	625	141	286	31	6	278	70	-20	+1	-0	+2	+14	-0.3
Career	—	MLE		—	4625	4247	875	156	19	126	265	1449	82	30	9	206	266	341	607	135	278	31	6	271	70	-121	+1	-2	+14	+82	-2.6
/ 162G	—	MLE		—	650	597	124	22	3	18	37	204	12	4	1	208	268	345	613	137	280	31	6	271	70	-21	+0	-0	+2	+14	-0.5

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 ADunedin Blue Jays · 369 PAwOBA .348 → .272 (−76)K% 27.4% → 37.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.37%	÷1.000	×1.360	—	—	37.22%
BB% (unintentional) /PA	5.69%	÷1.000	×0.690	—	×1.030	4.04%
HBP% /PA	2.98%	—	×0.780	—	×1.030	2.39%
Singles /BIP	21.79%	÷1.000	×0.920	×1.007	×1.030	20.81%
Doubles /BIP	7.26%	÷1.000	×0.830	×1.007	×1.030	6.26%
Triples /BIP	0.85%	÷1.000	×0.910	×1.007	×1.030	0.81%
Home runs /BIP	7.69%	÷1.000	×0.800	—	×1.030	6.34%

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 ×1.007.

Result: wOBA .348 → .272; ISO .224 → .167; BABIP .321 → .295. 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 Blue Jays · 225 PAwOBA .304 → .214 (−90)K% 17.8% → 25.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.78%	÷1.002	×1.440	—	—	25.56%
BB% (unintentional) /PA	11.11%	÷1.001	×0.620	—	×1.008	6.93%
HBP% /PA	0.44%	—	×0.720	—	×1.008	0.32%
Singles /BIP	25.95%	÷1.038	×0.820	×0.980	×1.008	20.24%
Doubles /BIP	4.43%	÷0.956	×0.720	×0.980	×1.008	3.29%
Triples /BIP	0.63%	÷1.150	×0.720	×0.980	×1.008	0.39%
Home runs /BIP	1.27%	÷1.077	×0.780	—	×1.008	0.92%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 115, 1B 108, 2B 91, 3B 130, K 100, BB 100 — 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 ×0.980.

Result: wOBA .304 → .214; ISO .076 → .052; BABIP .314 → .241. 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 Blue Jays · 133 PAwOBA .371 → .247 (−124)K% 15.0% → 18.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.04%	÷0.973	×1.220	—	—	18.86%
BB% (unintentional) /PA	9.02%	÷1.015	×0.700	—	×1.008	6.27%
HBP% /PA	4.51%	—	×0.700	—	×1.008	3.18%
Singles /BIP	21.74%	÷0.958	×0.680	×0.969	×1.008	15.06%
Doubles /BIP	8.70%	÷0.964	×0.600	×0.969	×1.008	5.28%
Triples /BIP	0.00%	÷0.900	×0.600	×0.969	×1.008	0.00%
Home runs /BIP	4.35%	÷0.892	×0.470	—	×1.008	2.31%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 78, 1B 92, 2B 93, 3B 80, K 95, BB 103 — 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 ×0.969.

Result: wOBA .371 → .247; ISO .179 → .104; BABIP .311 → .204. 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 Blue Jays · 74 PAwOBA .321 → .211 (−109)K% 21.6% → 26.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.62%	÷1.014	×1.220	—	—	26.02%
BB% (unintentional) /PA	13.51%	÷0.979	×0.700	—	×1.022	9.88%
HBP% /PA	2.70%	—	×0.700	—	×1.022	1.93%
Singles /BIP	26.67%	÷1.016	×0.680	×0.950	×1.022	17.34%
Doubles /BIP	4.44%	÷1.059	×0.600	×0.950	×1.022	2.45%
Triples /BIP	0.00%	÷0.900	×0.600	×0.950	×1.022	0.00%
Home runs /BIP	2.22%	÷1.083	×0.470	—	×1.022	0.99%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 117, 1B 103, 2B 112, 3B 80, K 103, BB 96 — 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 ×0.950.

Result: wOBA .321 → .211; ISO .082 → .041; BABIP .311 → .196. 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
#1Ryan 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
#2Pete Mackanin'73-'81 * career totals — 6 seasons, 1,686 PA	2.5	1,686	30	27	222*	261*	370*	+6	+23	0.6	1.6
/162	664	12	11	+2.4	+8.9	0.2	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	3.1	2,065	59	12	210	266	351	+7	+2	-0.1	0.2
/162	664	19	4	+2.4	+0.8	-0.0	pk7: 0
#3Doug Strange'89-'98 * career totals — 8 seasons, 2,067 PA	3.1	2,067	31	14	225*	286*	340*	+5	-0	-1.5	0.0
/162	664	10	4	+1.6	-0.1	-0.5	pk7: 1
#4Pedro Garcia'73-'77 * career totals — 5 seasons, 1,967 PA	3.0	1,967	37	35	220*	270*	388*	+6	-6	-0.3	-0.3
/162	664	12	12	+2.1	-2.0	-0.1	pk7: -0
#5Abraham Torolast yr '25 career totals — 6 seasons, 1,561 PA	2.4	1,561	39	16	220	282	351	-1	-8	-0.5	-0.5
/162	664	17	7	-0.2	-3.2	-0.2	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
Aldo Gaxiola (OGILVIE)	21	40	20	40	40	197/251/326	128	279	6	1	34%	5%	62	-0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Travis Harrison 2014 · A	21	43→50	43→40	41→45	42	209/282/320	110	300	11	3	32%	7%	72	-0.7	215/292/306	91	298	6	6	27%	8%	72	-0.7	209/291/292	83	290	4	7	27%	9%	67	-0.9
✕Omar Estévez 2019 · A	21	43	42→45	42→40	37	210/253/317	107	293	10	3	31%	5%	59	-1.6	215/266/322	107	302	10	3	30%	6%	65	-1.2	201/256/294	92	277	9	1	29%	6%	54	-1.1
✕Dante Bichette Jr. 2014 · A	21	43→49	40→45	43→40	41	210/265/299	89	288	8	3	29%	6%	60	-1.6	218/274/317	99	292	8	2	27%	7%	68	-1.0	242/301/331	90	300	7	3	21%	7%	77	-0.2
✕Gabriel Lino 2014 · A	21	41	42→40	41→30	36	200/252/309	109	301	9	4	35%	5%	57	-1.8	199/247/285	86	299	7	2	34%	5%	50	-2.3	206/255/293	86	293	6	0	30%	5%	53	-1.0
✕Imeldo Diaz 2019 · A	21	44	41→40	46→45	41	215/264/307	91	269	9	5	23%	5%	61	-1.5	231/265/311	80	306	5	5	25%	4%	61	-1.5	238/261/300	62	316	3	2	25%	2%	55	-0.6
✕Randy César 2016 · A	21	39→49	38→40	40	40	191/243/266	75	268	6	2	30%	6%	44	-2.8	214/255/298	84	323	8	3	34%	5%	55	-1.9	237/283/328	91	347	8	2	32%	6%	69	-0.6
✕Darwin Rivera 2013 · A	21	42	40	37→30	38	206/249/294	88	289	8	2	31%	5%	53	-2.1	199/249/282	83	281	6	4	30%	5%	49	-2.4	155/200/218	63	212	5	0	29%	4%	14	-1.4
✕Ethan Workinger 2023 · A	21	37→41	42→45	45	39	187/239/300	113	260	9	5	31%	6%	51	-2.3	205/255/326	121	270	13	6	28%	6%	63	-1.4	198/253/321	123	239	15	9	24%	6%	58	-1.1
✕Jose Peroza 2021 · A	21	43→46	47→45	49→45	38	215/268/352	137	302	14	7	33%	6%	74	-0.6	212/282/332	120	317	12	5	34%	7%	75	-0.5	207/280/327	120	310	12	4	35%	7%	71	-0.6
✕Payton Henry 2018 · A	21	39→32	41→45	46→30	38	189/254/293	104	302	8	3	38%	7%	55	-2.0	185/251/286	101	320	10	2	43%	6%	53	-2.1	244/299/348	104	334	12	0	29%	5%	81	-0.0
✕Sebastian Valle 2011 · A	21	42→45	46→45	42→40	38	216/257/348	132	277	14	3	28%	4%	68	-1.0	214/242/326	112	298	12	2	31%	3%	57	-1.8	217/269/329	111	291	11	2	28%	6%	66	-0.6
✕Sherten Apostel 2020 · A	21	38→35	47→45	45→40	45	195/272/324	128	273	15	4	33%	9%	70	-0.9	207/271/335	128	319	14	4	37%	7%	71	-0.8	208/271/342	134	323	16	0	38%	7%	70	-0.4
✕Gabriel Rodriguez 2023 · A	21	47→42	40	44→40	40	224/274/316	92	314	8	5	30%	6%	67	-1.1	206/275/298	92	318	8	6	35%	7%	64	-1.3	177/270/258	82	285	7	3	37%	9%	53	-1.1
✕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
✕Victor Bericoto 2023 · A	21	46→49	43→50	41→40	42	223/284/326	103	320	11	4	32%	8%	74	-0.6	230/278/363	133	307	16	4	29%	6%	80	-0.2	230/278/364	134	300	16	3	28%	6%	78	-0.2
✕Rayner Contreras 2008 · A	21	47	41→40	45→50	42	228/274/327	99	295	9	7	25%	6%	69	-0.9	230/288/312	82	303	5	11	24%	6%	72	-0.7	252/307/308	55	348	0	13	26%	6%	72	-0.2
✕Julian Leon 2017 · A	21	37	44→45	40→30	32	185/236/296	110	307	12	2	42%	5%	49	-2.4	193/273/313	120	306	14	2	39%	8%	68	-1.0	172/272/288	117	267	14	0	38%	10%	61	-0.6
✕Brian Sanchez 2017 · A	21	37	43→50	45	42	189/257/303	113	261	11	4	31%	7%	59	-1.7	184/237/278	94	281	8	4	35%	6%	45	-2.7	133/186/201	68	218	4	0	39%	6%	6	-1.0
✕Braulio Vasquez 2021 · A	22	42	39→40	44→65	38	197/260/278	81	313	6	7	37%	6%	53	-2.1	207/282/301	94	302	7	30	31%	8%	68	-1.0	200/280/292	92	287	6	42	30%	8%	62	-0.6
✕Ronaldo Flores 2023 · A	21	43	43→40	49→30	35	215/255/321	106	302	12	6	32%	4%	61	-1.5	211/251/308	97	300	8	4	31%	5%	57	-1.8	202/239/292	90	285	7	2	31%	4%	44	-1.0

Aldo Gaxiola

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps