Wagnel Luna — OGILVIE

Wagnel LunaIF DSL Tigers 1

Age 20 R/R 6'0" / 155 lbs ROK HR +5%H +3% Svc 0.0 · Ctrl thru 2037 peak 2.0 · 2033

wRC+†73

AVG/OBP/SLG.207 / .289 / .325

PA118

HR2

K%29

BB%9

MLB%0%

Scouting · now → future

HIT

24↗29

PWR

29↗34

SPD

52↗57

EYE

57↗62

trajectory · 10 yrs

2.0peak

2032

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
2026	MiLB	still in minors · estimated debut 2032
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	+1.9	$18M	+$17M
2033	Pre-Arb	$1.0M	+2.0	$20M	+$19M
2034	Pre-Arb	$1.0M	+1.9	$19M	+$18M
2035	Arb-1	$3M	+1.7	$18M	+$14M
2036	Arb-2	$5M	+1.5	$16M	+$11M
2037	Arb-3	$5M	+1.1	$12M	+$7M
Totals		$17M		$103M	+$86M

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 Tigers 1	127	103	12	2	1	1	20	44	4	5	2	.117	.283	.184	.468	.068	.190	35	16	.225	30	-10	+0	+0	+0	+4	-0.6
2024	18	ROK	DSL Tigers 1	124	109	9	0	0	1	12	52	3	5	1	.083	.194	.110	.304	.028	.143	42	10	.154	-24	-17	+1	+0	+0	+4	-1.4
2025	19	ROK	DSL Tigers 1	142	122	21	5	0	0	15	41	1	9	5	.172	.268	.213	.481	.041	.256	29	11	.223	29	-11	-0	+0	+0	+4	-0.8
▸ 2026 Season
2026	20	MLB	DET	118	105	22	4	1	2	11	34	1	2	1	.210	.291	.324	.614	.114	.282	29	9	.281	73	-4	+0	+0	+0	+3	-0.0
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	21	MLB 11%	DET	202	178	39	7	1	5	20	55	2	5	1	.219	.305	.354	.659	.135	.284	27	10	.297	85	-3	+1	+0	+0	+6	0.3
2028	22	MLB 28%	DET	328	288	65	12	2	9	33	86	4	8	2	.226	.314	.375	.689	.149	.285	26	10	.307	93	-3	+1	+0	+0	+9	0.8
2029	23	MLB 48%	DET	413	362	82	15	2	12	43	106	5	10	2	.227	.317	.378	.696	.152	.286	26	10	.313	98	-1	+1	+0	+0	+12	1.2
2030	24	MLB 62%	DET	470	412	95	17	3	14	50	118	5	11	2	.231	.321	.388	.710	.158	.287	25	11	.318	101	+1	+1	+0	+0	+13	1.6
2031	25	MLB 80%	DET	502	436	101	18	3	15	55	126	6	12	3	.232	.326	.390	.716	.158	.287	25	11	.321	104	+2	+1	+0	+0	+14	1.8
2032	26	MLB 94%	DET	521	453	106	19	3	16	57	130	6	12	3	.234	.328	.395	.723	.161	.288	25	11	.323	105	+3	+1	+0	+0	+15	1.9
2033	27	MLB	DET	528	458	106	19	3	16	59	133	6	12	2	.231	.327	.391	.718	.159	.288	25	11	.323	105	+3	+2	+0	+0	+15	2.0
2034	28	MLB	DET	528	458	106	19	3	16	59	134	6	12	2	.231	.327	.391	.718	.159	.287	25	11	.322	104	+3	+2	-1	+0	+15	1.9
2035	29	MLB	DET	521	451	105	19	3	16	59	133	6	11	2	.233	.329	.395	.724	.162	.286	26	11	.319	103	+2	+1	-1	+0	+15	1.7
2036	30	MLB	DET	512	443	101	18	3	15	58	133	6	11	1	.228	.325	.384	.709	.156	.285	26	11	.316	100	+0	+2	-2	+0	+15	1.5
2037	31	MLB	DET	499	434	96	17	2	14	56	132	6	9	1	.221	.319	.366	.685	.145	.284	26	11	.313	97	-1	+1	-3	+0	+14	1.1
2038	32	MLB	DET	482	420	91	16	2	13	54	130	5	9	0	.217	.313	.357	.670	.140	.282	27	11	.308	94	-3	+2	-4	+0	+14	0.9
2039	33	MLB	DET	453	394	85	15	2	12	51	125	5	8	0	.216	.313	.355	.669	.140	.280	28	11	.302	90	-5	+2	-4	+0	+13	0.5
2040	34	MLB	DET	407	355	75	13	2	10	45	116	4	7	0	.211	.307	.344	.651	.132	.278	29	11	.296	85	-7	+1	-5	+0	+12	0.1
2041	35	MLB	DET	353	307	63	11	2	8	39	104	4	7	0	.205	.303	.332	.635	.127	.276	29	11	.288	79	-8	+1	-6	+0	+10	-0.3
2042	36	MLB	DET	294	257	51	9	1	6	32	90	3	6	0	.198	.295	.311	.606	.113	.273	31	11	.279	72	-9	+1	-6	+0	+8	-0.6
▸ Career Totals (MLE all levels + projections)
Career	—			7524	6545	1431	255	39	201	828	2022	88	171	30	.219	.315	.362	.676	.143	.282	27	11	.305	92	-71	+22	-31	+0	+213	13.5
/ 162G	—			650	565	123	22	3	17	72	175	8	15	3	.218	.315	.358	.672	.140	.282	27	11	.305	92	-6	+2	-3	+0	+18	1.2

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 Tigers 1	127	90	15	2	1	1	33	30	4	5	2	.167	.409	.244	.654	.078	.237	24	26	.332	112	+2	+0	—	—	+4	0.6
2024	18	ROK	DSL Tigers 1	124	101	14	0	1	1	20	36	3	5	1	.139	.298	.188	.487	.050	.203	29	16	.248	48	-7	+1	—	—	+4	-0.3
2025	19	ROK	DSL Tigers 1	142	111	28	7	0	0	26	28	1	9	5	.252	.399	.315	.714	.063	.333	20	18	.330	111	+2	-0	—	—	+4	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
Wagnel Luna (OGILVIE)	20	24→29	29→34	52→57	62	.207/.289/.325	.118	.282	2	2	29%	9%	73	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Jose Meza 2023 · A	20	41→35	41→45	47→50	40	.199/.265/.295	.096	.286	9	10	32%	6%	55	-1.4	.204/.294/.305	.101	.301	9	8	32%	10%	70	-0.3	.186/.292/.283	.097	.277	9	10	33%	11%	63	-0.5
✕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
✕Efrain Contreras 2007 · A	20	44	41→45	51→55	44	.212/.278/.308	.097	.264	8	8	22%	6%	63	-0.8	.227/.291/.336	.109	.276	10	14	21%	6%	76	+0.0	.227/.291/.331	.104	.281	10	15	22%	5%	72	-0.1
✕Robert Gonzalez 2021 · A	20	41	40→45	54→60	47	.189/.291/.289	.100	.303	7	8	36%	10%	66	-0.6	.201/.301/.282	.081	.273	6	17	26%	10%	68	-0.5	.180/.308/.228	.048	.225	5	30	19%	12%	56	-0.5
✕Guillermo Pimentel 2010 · A	20	42	38→40	49→55	44	.200/.281/.272	.073	.296	6	16	32%	8%	56	-1.3	.200/.259/.281	.081	.332	7	9	39%	6%	47	-1.9	.171/.216/.243	.071	.295	8	2	43%	4%	17	-1.1
✕Zack Larson 2014 · A	20	46→37	41→45	53→50	41	.221/.280/.317	.096	.294	8	12	27%	6%	66	-0.6	.205/.260/.273	.068	.276	3	10	25%	6%	46	-2.0	.186/.243/.235	.049	.252	1	10	25%	6%	28	-1.8
✕Carlos Jimenez 2023 · A	20	38→41	46→50	53→55	45	.189/.278/.319	.129	.289	14	15	37%	10%	67	-0.5	.210/.289/.331	.121	.326	12	16	36%	9%	74	-0.1	.216/.296/.349	.133	.314	15	19	33%	9%	78	+0.1
●Davis Schneider 2018 · A	19	40→44	41→55	48→50	50	.198/.276/.300	.102	.259	8	6	26%	9%	60	-1.0	.193/.268/.290	.097	.299	8	7	35%	8%	54	-1.4	.213/.322/.409	.196	.275	24	9	30%	12%	106	+1.6
✕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
✕Bryan Ramos 2022 · A	20	40	45→50	49→50	41	.203/.270/.328	.125	.273	12	8	30%	6%	66	-0.6	.212/.271/.357	.145	.264	19	5	27%	6%	73	-0.1	.206/.264/.348	.141	.251	20	5	26%	6%	65	-0.5
✕Luis Hidalgo 2017 · A	21	39	43→45	46→45	44	.196/.254/.303	.107	.234	12	12	22%	6%	52	-1.6	.223/.274/.346	.123	.264	13	9	21%	5%	71	-0.3	.259/.302/.380	.121	.288	12	8	14%	4%	89	+0.4
✕Cesar Quintas 2022 · A	19	46→36	40→45	50	43	.220/.300/.314	.095	.296	7	7	26%	6%	75	-0.0	.204/.282/.283	.079	.308	6	5	33%	6%	59	-1.1	.200/.289/.313	.113	.283	11	6	31%	7%	69	-0.2
✕Carlos Rodriguez 2023 · A	20	38	40→45	47→45	45	.183/.271/.272	.089	.286	7	6	36%	10%	52	-1.6	.190/.265/.267	.077	.298	5	6	35%	9%	47	-1.9	.182/.268/.267	.085	.274	6	3	33%	10%	48	-0.6
✕Ravel Santana 2011 · A	19	43	46→50	51→55	47	.214/.294/.340	.125	.274	14	15	26%	8%	79	+0.3	.220/.281/.362	.142	.292	16	13	29%	7%	79	+0.3	.205/.253/.387	.182	.264	22	15	31%	6%	72	-0.1
✕Albertson Asigen 2022 · A	20	43	39→40	53→55	44	.207/.262/.299	.092	.279	5	7	27%	7%	53	-1.5	.223/.296/.298	.075	.324	4	17	30%	8%	68	-0.5	.211/.299/.301	.089	.346	7	27	37%	9%	66	-0.2
✕Jaden Rudd 2023 · A	20	40→36	40→30	49→50	49	.191/.281/.282	.091	.264	6	11	28%	9%	59	-1.1	.179/.294/.247	.068	.289	3	14	35%	11%	57	-1.2	.155/.287/.208	.053	.265	2	16	36%	11%	43	-1.1
✕Ameilis Carvajal 2009 · A	20	40	39→40	50	47	.189/.277/.272	.083	.292	6	12	34%	10%	54	-1.4	.193/.265/.266	.073	.318	4	10	37%	8%	46	-2.0	.140/.204/.175	.034	.267	0	8	44%	7%	-3	-1.2
✕Luke Adams 2023 · A	19	49→37	40→45	54→55	45	.229/.303/.328	.098	.328	7	17	30%	8%	79	+0.3	.197/.323/.323	.126	.275	12	20	30%	11%	89	+1.0	.179/.324/.312	.133	.244	14	22	29%	12%	86	+0.5
✕Jose Paez 2014 · A	20	46	39→45	51→50	38	.218/.263/.312	.093	.303	5	12	29%	5%	56	-1.3	.209/.259/.289	.080	.322	4	10	34%	6%	50	-1.8	.195/.251/.252	.057	.320	4	11	38%	6%	32	-0.6

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)