Aldo Gaxiola — OGILVIE

Aldo Gaxiola3B Dunedin Blue Jays

Age 20 R/R 6'2" / 187 lbs A HR +12%BB +4% Svc 0.0 · Ctrl thru 2036 peak 2.4 · 2032

wRC+†65

AVG/OBP/SLG.219 / .287 / .331

PA211

HR4

K%26

BB%8

MLB%0%

Scouting · now → future

HIT

40→40

PWR

20→20

SPD

40→40

EYE

43↘40

trajectory · 10 yrs

2.4peak

2032

Contract

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

Status MiLB

MLB Debut 2031

Service 0 yrs (est)

Team Control Through 2036

First FA Year 2037

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2031
2027	MiLB	still in minors · estimated debut 2031
2028	MiLB	still in minors · estimated debut 2031
2029	MiLB	still in minors · estimated debut 2031
2030	MiLB	still in minors · estimated debut 2031
2031	Pre-Arb	$0.9M	+2.3	$21M	+$20M
2032	Pre-Arb	$0.9M	+2.4	$23M	+$22M
2033	Pre-Arb	$1.0M	+2.4	$24M	+$23M
2034	Arb-1	$5M	+2.3	$23M	+$19M
2035	Arb-2	$7M	+2.1	$22M	+$15M
2036	Arb-3	$9M	+1.8	$19M	+$10M
Totals		$23M		$132M	+$109M

Career Projections (MLE)

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	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
2023	17	ROK	DSL Blue Jays	74	65	11	1	0	1	6	23	2	3	1	.169	.260	.231	.491	.062	.238	31	8	.221	27	-6	+0	+0	+0	+2	-0.4
2024	18	ROK	DSL Blue Jays	133	118	27	6	0	4	7	30	6	1	0	.229	.305	.381	.687	.153	.267	23	5	.290	80	-3	+0	+0	+0	+4	0.1
2025	19	ROK	FCL Blue Jays	225	208	36	5	0	1	16	57	1	3	1	.173	.236	.212	.447	.038	.233	25	7	.209	18	-21	+0	+0	+1	+6	-1.4
▸ 2026 Season (actual · ROS · total)
2026	20	A	Dunedin Blue Jays	61	55	9	2	0	2	2	26	4	0	0	.164	.246	.309	.555	.145	.259	43	3	.254	53	-3	+0	+0	+0	+2	-0.1
ROS	20	MLB	TOR	150	136	30	6	1	3	10	42	3	2	0	.221	.289	.346	.634	.125	.282	28	7	.277	70	-5	+0	+0	+1	+4	0.0
TOT	20	MLB	TOR	211	191	39	8	1	5	12	68	7	2	0	.204	.276	.335	.611	.131	.286	32	6	.271	65	-8	+0	+0	+1	+6	-0.1
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	21	MLB 11%	TOR	290	260	59	12	1	7	23	62	5	4	1	.227	.302	.362	.664	.135	.270	21	8	.302	89	-4	+0	+0	+1	+8	0.6
2028	22	MLB 28%	TOR	393	350	82	16	2	11	33	82	7	6	1	.234	.313	.386	.699	.151	.272	21	8	.312	97	-1	+1	+0	+1	+11	1.2
2029	23	MLB 48%	TOR	461	409	97	19	2	14	41	94	8	7	1	.237	.319	.396	.715	.159	.273	20	9	.318	102	+1	+1	+0	+2	+13	1.7
2030	24	MLB 62%	TOR	505	445	106	21	2	15	46	102	9	7	1	.238	.322	.396	.718	.157	.274	20	9	.322	105	+3	+1	+0	+2	+14	2.0
2031	25	MLB 80%	TOR	530	466	113	22	3	17	49	106	10	7	1	.242	.328	.412	.740	.170	.274	20	9	.325	107	+4	+1	+0	+2	+15	2.3
2032	26	MLB 94%	TOR	543	476	115	22	3	17	52	109	10	7	1	.242	.329	.408	.737	.166	.275	20	10	.327	109	+5	+1	+0	+2	+15	2.4
2033	27	MLB	TOR	546	479	115	22	3	17	52	110	10	7	1	.240	.327	.405	.732	.165	.275	20	10	.327	109	+5	+1	+0	+2	+15	2.4
2034	28	MLB	TOR	544	476	114	22	2	17	53	110	10	7	1	.239	.328	.401	.730	.162	.274	20	10	.326	108	+5	+1	-1	+2	+15	2.3
2035	29	MLB	TOR	536	469	111	21	2	17	52	110	10	6	0	.237	.326	.399	.725	.162	.273	21	10	.324	106	+4	+1	-1	+2	+15	2.1
2036	30	MLB	TOR	526	461	108	21	2	16	51	110	9	6	0	.234	.322	.393	.715	.158	.272	21	10	.321	104	+2	+1	-2	+2	+15	1.8
2037	31	MLB	TOR	512	448	104	20	2	15	50	109	9	5	0	.232	.321	.386	.708	.154	.271	21	10	.317	101	+0	+1	-3	+2	+15	1.5
2038	32	MLB	TOR	494	434	99	19	2	14	48	108	9	4	0	.228	.318	.378	.696	.150	.269	22	10	.312	97	-2	+1	-4	+2	+14	1.2
2039	33	MLB	TOR	465	409	92	17	2	13	45	105	8	4	0	.225	.314	.372	.685	.147	.267	23	10	.307	93	-4	+1	-4	+2	+13	0.8
2040	34	MLB	TOR	418	368	81	15	2	11	40	98	7	3	0	.220	.308	.361	.670	.141	.265	23	10	.300	88	-6	+1	-5	+1	+12	0.3
2041	35	MLB	TOR	365	321	69	13	1	9	35	89	6	3	0	.215	.304	.346	.650	.131	.263	24	10	.292	82	-7	+1	-6	+1	+10	-0.1
2042	36	MLB	TOR	306	269	55	10	1	7	29	78	5	3	0	.204	.294	.327	.621	.123	.260	25	9	.283	75	-9	+1	-6	+1	+9	-0.5
▸ Career Totals (MLE all levels + projections)
Career	—			8016	7067	1624	310	33	226	738	1734	144	95	10	.230	.315	.379	.694	.149	.271	22	9	.311	96	-38	+15	-31	+29	+227	20.6
/ 162G	—			650	573	132	25	3	18	60	141	12	8	1	.230	.316	.379	.695	.148	.273	22	9	.311	96	-3	+1	-3	+2	+18	1.7

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

Year	Age	Lvl	Team	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
2023	17	ROK	DSL Blue Jays	74	61	15	2	0	1	10	16	2	3	1	.246	.370	.328	.698	.082	.311	22	14	.324	106	+0	+0	—	—	+2	0.3
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	147	+7	+0	—	—	+4	1.1
2025	19	ROK	FCL Blue Jays	225	198	51	7	1	2	25	40	1	3	1	.258	.342	.333	.676	.076	.314	18	11	.311	96	-1	+0	—	—	+6	0.6

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)	20	40	20	40	40	.219/.287/.331	.112	.285	4	3	26%	8%	73	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jenner Emeterio 2013 · A	20	45	38→30	48→60	46	.214/.278/.298	.084	.285	5	12	26%	8%	60	-1.0	.216/.302/.277	.061	.288	3	24	23%	10%	66	-0.6	.216/.317/.260	.044	.285	1	34	22%	12%	65	-0.3
✕Ronarsy Ledesma 2012 · A	19	42	42→45	47→50	43	.205/.277/.309	.104	.271	9	8	27%	6%	64	-0.8	.224/.284/.326	.102	.290	5	11	24%	5%	70	-0.3	.226/.280/.337	.111	.291	6	11	23%	4%	69	-0.2
✕Rudy van Heydoorn 2009 · A	20	40	43→45	43→50	47	.193/.290/.298	.105	.281	11	10	32%	10%	67	-0.5	.182/.264/.285	.103	.284	10	6	37%	8%	52	-1.6	.153/.236/.254	.101	.237	11	2	38%	9%	32	-0.9
●Daniel Robertson 2014 · A	20	46→54	43→45	38→40	46	.227/.287/.337	.110	.280	10	4	22%	7%	74	-0.1	.243/.310/.355	.112	.303	9	3	22%	7%	89	+0.9	.234/.338/.350	.116	.305	12	4	25%	11%	96	+0.8
✕Manuel Joseph 2013 · A	19	46	40→45	44→50	45	.221/.275/.318	.097	.272	8	8	21%	6%	63	-0.8	.243/.298/.349	.106	.288	8	15	18%	6%	82	+0.5	.263/.321/.381	.118	.302	10	21	15%	5%	101	+0.8
✕Dyan Jorge 2023 · A	20	47→46	39→30	45→55	47	.225/.285/.313	.088	.280	6	12	21%	7%	66	-0.6	.226/.277/.294	.068	.305	4	18	25%	6%	57	-1.2	.215/.265/.264	.049	.298	2	22	27%	6%	42	-1.6
✕Cutter Dykstra 2009 · A	20	44→54	42→40	42→55	45	.215/.279/.314	.100	.288	9	7	28%	8%	65	-0.7	.213/.274/.292	.079	.296	7	14	28%	7%	56	-1.3	.236/.303/.323	.087	.313	6	16	25%	8%	75	-0.0
✕Ramon Mendoza 2021 · A	20	46→48	40→45	41→45	44	.216/.286/.311	.096	.298	6	4	28%	7%	67	-0.5	.198/.271/.278	.080	.286	4	5	30%	8%	53	-1.5	.219/.298/.332	.113	.294	11	3	27%	9%	76	+0.0
✕Raul Juarez 2018 · A	20	43	39→45	42→40	40	.208/.266/.286	.078	.272	7	6	26%	5%	53	-1.5	.203/.254/.282	.079	.287	6	5	30%	5%	46	-2.0	.147/.189/.214	.067	.208	8	0	33%	3%	-2	-1.0
✕Antonio Negron 2006 · A	20	43	40→45	43→50	49	.208/.290/.302	.094	.274	7	10	25%	9%	67	-0.5	.202/.287/.306	.104	.252	10	10	23%	9%	67	-0.5	.187/.280/.293	.106	.224	11	11	21%	9%	60	-0.4
✕Sam McMillan 2019 · A	20	47	41→30	47→45	49	.227/.314/.329	.102	.280	8	6	21%	8%	85	+0.7	.215/.317/.288	.073	.287	4	7	24%	10%	76	+0.1	.207/.331/.267	.060	.268	4	7	21%	12%	75	-0.0
✕Fernando Pujadas 2012 · A	20	43	42→40	43→30	43	.215/.267/.320	.105	.262	10	4	22%	6%	61	-1.0	.214/.288/.305	.091	.276	7	4	23%	8%	66	-0.6	.208/.295/.292	.084	.266	6	1	22%	9%	63	-0.2
✕Armando Sierra 2023 · A	19	46	41→45	43→40	47	.224/.286/.319	.095	.281	8	4	22%	7%	69	-0.4	.214/.270/.313	.099	.303	9	4	30%	7%	60	-1.0	.189/.239/.286	.097	.292	10	0	37%	6%	38	-0.5
✕Andy Paz 2014 · A	21	46	37→40	42→45	48	.215/.279/.290	.075	.276	4	5	23%	8%	58	-1.2	.200/.260/.272	.072	.277	5	5	27%	7%	45	-2.1	.210/.261/.258	.048	.277	3	6	24%	6%	38	-0.7
✕Yeison Santana 2021 · A	20	47	38→30	46→55	47	.220/.292/.303	.083	.305	5	7	28%	8%	67	-0.5	.211/.276/.274	.063	.315	3	13	31%	7%	53	-1.5	.204/.277/.247	.043	.301	2	19	30%	8%	43	-0.9
✕Johnabiell Laureano 2021 · A	20	45	39→30	40→45	44	.215/.279/.301	.087	.296	6	6	28%	7%	62	-0.9	.191/.253/.265	.074	.328	7	5	40%	7%	41	-2.3	.155/.228/.211	.056	.285	7	2	45%	8%	14	-1.1
✕Yusniel Díaz 2017 · A	20	45→52	43→45	45→50	41	.221/.268/.332	.111	.293	11	9	28%	6%	64	-0.8	.231/.286/.350	.119	.305	12	9	27%	7%	76	+0.1	.231/.291/.359	.128	.299	13	7	26%	8%	78	+0.2
✕Alexander Campos 2022 · A	22	43	42→40	46→45	48	.209/.289/.317	.108	.281	9	6	28%	9%	70	-0.3	.221/.304/.311	.090	.312	8	6	29%	9%	75	-0.0	.236/.329/.308	.072	.330	7	6	28%	11%	83	+0.2
✕Blake Ochoa 2007 · A	21	45	40→45	46→40	44	.215/.280/.308	.092	.280	6	5	24%	6%	64	-0.8	.217/.270/.311	.094	.277	7	4	23%	6%	60	-1.0	.236/.301/.377	.140	.278	16	2	21%	7%	89	+0.3
✕Elio Prado 2022 · A	20	46→37	38→40	44→50	47	.219/.287/.300	.081	.277	6	10	22%	7%	65	-0.7	.195/.272/.278	.083	.270	7	9	28%	8%	53	-1.5	.180/.259/.266	.086	.241	9	13	28%	7%	42	-1.3

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)