Wilberson De Pena

OF FCL Yankees

Age 20 R/R 6'2" / 185 lbs ROK HR +14% Svc 0.0 · Ctrl thru 2036

Overview

ROKPROSPECTMiLBFA 2037

OGV OFP35OGV rank#1669ETA2030MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKLAA	77	.226/.377/.274	0	4	26	—	.154/.286/.200
2025	18	ROKDSL NYY Yanke…	121	.206/.325/.451	5	9	17	—	.102/.192/.204
2026	19	A/ROKNYY	340	.312/.375/.594	20	25	83	—	.223/.274/.422
2027PROJMLE	20	MLBNYY	450	.216/.270/.362	13	10	76	-0.2
2028PROJ25% MLB	21	MLBNYY	72	.223/.278/.384	2	2	82	-0.0
2029PROJ38% MLB	22	MLBNYY	148	.227/.283/.394	5	3	86	-0.0

Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2036Service0.0First FA2037

2027MiLB2028MiLB2029MiLB2030MiLB2031Pre-Arb$0.9M2032Pre-Arb$0.9M2033Pre-Arb$0.9M2034Arb-1$2M+2

Skills · percentileMiLB Statcast 2026 A

Max EV80

Speed75

K%31

Z-Con%28

BB%27

Whiff%20

Career WAR0.0 WAR median (P10 0.0 / P90 3.0, comp-based) · star 1% · didn't stick 89%

CompsCeddanne Rafaela (age 21) · Max Muncy (age 20) · José Rodríguez (age 20)

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

wRC+†76

AVG/OBP/SLG.214 / .268 / .359

PA210

HR6

SB5

K%29

BB%6

ISO146

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$1M ctrl surplus

Contract

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
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	+0.2	$0.6M	+$0.0M
2032	Pre-Arb	$0.9M	+0.2	$0.5M	+$0.0M
2033	Pre-Arb	$0.9M	+0.3	$0.8M	+$0.3M
2034	Arb-1	$2M	+0.2	$0.5M	+$0.0M (cut)
2035	Arb-2	$2M	+0.1	$0.2M	+$0.0M (cut)
2036	Arb-3	$1M	—	—	—
Totals		$3M		$3M	+$0.3M

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 Angels	—	77	62	14	1	1	0	10	14	5	4	0	226	377	274	651	48	292	18	13	317	26	—	—	—	—	—	—
2025	18	ROK	DSL NYY Yankees	—	121	102	21	6	2	5	16	26	2	9	4	206	325	451	776	245	222	21	13	341	17	—	—	—	—	—	—
2026	19	A	Tampa Tarpons	—	92	82	15	1	1	4	8	27	2	2	2	183	272	366	638	183	216	29	9	287	34	—	—	—	—	—	—
2026	19	ROK	FCL Yankees	—	248	226	81	20	2	16	17	49	4	23	7	358	413	677	1.090	319	401	20	7	467	101	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Angels	—	77	65	10	1	1	0	7	16	5	4	0	154	286	200	486	46	183	21	9	207	26	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	121	108	11	3	1	2	10	32	2	9	4	102	192	204	395	102	127	26	8	193	17	—	—	—	—	—	—
2026	19	A MLE	Tampa Tarpons	—	92	84	13	1	1	3	6	37	2	2	2	155	228	298	526	143	210	40	7	218	34	—	—	—	—	—	—
2026	19	ROK MLE	FCL Yankees	—	248	233	58	13	1	12	10	71	4	23	7	249	291	468	759	219	299	29	4	317	101	—	—	—	—	—	—
2024	17	ROK MLE	DSL Angels	—	77	65	10	1	1	0	7	16	5	4	0	154	286	200	486	46	204	21	9	207	26	—	—	—	—	—	—
2024	17	ROK RAW	DSL Angels	—	77	62	14	1	1	0	10	14	5	4	0	226	377	274	651	48	292	18	13	317	26	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	121	108	11	3	1	2	10	32	2	9	4	102	192	204	395	102	120	26	8	193	17	—	—	—	—	—	—
2025	18	ROK RAW	DSL NYY Yankees	—	121	102	21	6	2	5	16	26	2	9	4	206	325	451	776	245	222	21	13	341	17	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	340	317	70	14	2	14	16	107	6	25	9	221	271	410	681	189	284	31	5	290	83	—	—	—	—	—	—
2026	19	ROK RAW	2 teams	—	340	308	96	21	3	20	25	76	6	25	9	312	375	594	969	282	357	22	7	419	83	—	—	—	—	—	—
2024	17	ROK MLE	DSL Angels	—	77	65	10	1	1	0	7	16	5	4	0	154	286	200	486	46	183	21	9	207	26	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	121	108	11	3	1	2	10	32	2	9	4	102	192	204	395	102	127	26	8	193	17	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	340	315	70	14	2	14	16	107	6	25	9	222	271	413	684	190	275	31	5	290	83	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Angels	—	77	65	10	1	1	0	7	16	5	4	0	154	286	200	486	46	183	21	9	207	26	—	—	—	—	—	—
2025	18	ROK MLE	DSL NYY Yankees	—	121	108	11	3	1	2	10	32	2	9	4	102	192	204	395	102	127	26	8	193	17	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	340	315	70	14	2	14	16	107	6	25	9	222	271	413	684	190	275	31	5	290	83	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	NYY	0%	450	417	90	16	3	13	25	129	5	10	3	216	270	362	632	146	278	29	6	280	76	-13	+1	-2	-3	+10	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	NYY	25%	291	268	60	11	2	9	17	81	4	7	2	221	276	375	652	154	279	28	6	289	82	-6	+1	-1	-2	+6	-0.2
2029	22	MLB MLE	NYY	38%	388	357	81	14	3	13	23	107	5	9	3	225	281	385	667	160	281	28	6	295	86	-7	+1	-1	-2	+8	-0.1
2030	23	MLB MLE	NYY	45%	451	414	94	17	3	15	28	122	6	11	3	228	285	392	678	165	282	27	6	300	89	-6	+1	-0	-3	+10	0.2
2031	24	MLB MLE	NYY	48%	489	449	103	18	3	17	31	131	6	12	3	230	289	397	686	167	284	27	6	303	91	-5	+1	+0	-3	+11	0.4
2032	25	MLB MLE	NYY	50%	512	468	108	19	3	18	33	136	6	12	4	231	291	400	691	169	284	27	6	305	93	-4	+1	+0	-3	+11	0.5
2033	26	MLB MLE	NYY	50%	523	478	110	20	3	18	34	139	6	12	4	231	291	401	692	169	284	27	7	306	93	-4	+1	+0	-3	+11	0.5
2034	27	MLB MLE	NYY	50%	525	480	110	20	3	18	34	140	6	12	4	230	290	398	688	168	283	27	6	304	92	-5	+1	+0	-3	+11	0.5
2035	28	MLB MLE	NYY	50%	520	475	109	19	3	18	34	140	6	11	4	228	288	394	681	165	282	27	7	301	90	-6	+1	-0	-3	+11	0.2
2036	29	MLB MLE	NYY	49%	509	465	106	19	3	17	33	138	6	10	4	226	285	387	672	161	281	27	6	298	88	-8	+0	-1	-3	+11	-0.0
2037	30	MLB MLE	NYY	48%	495	456	102	18	3	16	31	136	5	9	4	223	281	380	661	157	279	27	6	293	84	-9	+0	-2	-3	+11	-0.3
2028	21	MLB CTX	NYY	25%	72	67	14	3	0	2	4	20	1	2	0	223	278	384	662	161	280	28	6	293	82	-2	+0	-0	-0	+2	-0.0
2029	22	MLB CTX	NYY	38%	148	136	30	5	1	5	9	41	2	3	1	227	283	394	677	167	281	28	6	299	86	-3	+0	-0	-1	+3	-0.0
2030	23	MLB CTX	NYY	45%	205	187	43	8	1	7	13	56	3	5	1	230	287	401	689	172	283	27	6	304	89	-3	+1	-0	-1	+4	0.1
2031	24	MLB CTX	NYY	48%	235	215	51	9	2	9	15	63	3	6	2	232	291	407	697	174	284	27	6	307	91	-2	+0	+0	-1	+5	0.2
2032	25	MLB CTX	NYY	50%	254	233	55	10	2	9	16	67	3	6	2	234	293	410	702	176	285	26	6	310	93	-2	+0	+0	-2	+6	0.2
2033	26	MLB CTX	NYY	50%	264	242	57	10	2	10	17	70	3	6	2	234	293	410	703	177	284	27	6	310	93	-2	+0	+0	-2	+6	0.3
2034	27	MLB CTX	NYY	50%	263	241	57	10	2	10	17	70	3	6	2	232	292	408	699	175	284	27	6	308	92	-3	+0	+0	-2	+6	0.2
2035	28	MLB CTX	NYY	50%	259	237	55	10	2	9	17	70	3	5	2	231	290	403	693	172	283	27	7	306	90	-3	+0	-0	-2	+6	0.1
2036	29	MLB CTX	NYY	49%	247	226	51	9	1	9	16	67	3	5	2	228	287	396	683	168	281	27	6	302	88	-4	+0	-0	-1	+5	-0.0
2037	30	MLB CTX	NYY	48%	236	216	48	8	1	8	15	65	3	4	2	225	283	388	671	163	279	28	6	297	84	-4	+0	-1	-1	+5	-0.2
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2183	2000	461	82	14	78	139	589	27	48	16	231	289	403	692	172	285	27	6	305	86	-27	+3	-1	-13	+47	0.9
/ 162G	—	A+C		—	650	596	136	24	4	23	41	175	8	14	5	228	287	398	684	169	282	27	6	305	86	-8	+1	-0	-4	+14	0.3
Career	—	MLE		—	5451	4993	1116	201	34	181	343	1485	72	148	49	224	283	386	669	163	279	27	6	295	86	-67	+8	-4	-29	+106	1.4
/ 162G	—	MLE		—	650	595	133	24	4	22	41	177	9	18	6	224	284	388	672	165	278	27	6	295	86	-9	+1	-1	-4	+14	0.2

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 Yankees · 248 PAwOBA .456 → .317 (−138)K% 19.8% → 28.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.76%	÷1.000	×1.440	—	—	28.45%
BB% (unintentional) /PA	6.85%	÷1.000	×0.620	—	×0.995	4.23%
HBP% /PA	1.61%	—	×0.720	—	×0.995	1.16%
Singles /BIP	24.29%	÷1.000	×0.820	×0.974	×0.995	19.31%
Doubles /BIP	11.30%	÷1.000	×0.720	×0.974	×0.995	7.89%
Triples /BIP	1.13%	÷1.000	×0.720	×0.974	×0.995	0.79%
Home runs /BIP	9.04%	÷1.000	×0.780	—	×0.995	7.02%

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 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 ×0.974.

Result: wOBA .456 → .317; ISO .319 → .222; BABIP .401 → .299. 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).

2026 ATampa Tarpons · 92 PAwOBA .279 → .218 (−62)K% 29.3% → 39.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.35%	÷1.000	×1.360	—	—	39.91%
BB% (unintentional) /PA	8.70%	÷1.000	×0.690	—	×1.030	6.18%
HBP% /PA	2.17%	—	×0.780	—	×1.030	1.75%
Singles /BIP	16.36%	÷1.000	×0.920	×1.050	×1.030	16.28%
Doubles /BIP	1.82%	÷1.000	×0.830	×1.050	×1.030	1.63%
Triples /BIP	1.82%	÷1.000	×0.910	×1.050	×1.030	1.79%
Home runs /BIP	7.27%	÷1.000	×0.800	—	×1.030	5.99%

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 ×1.050.

Result: wOBA .279 → .218; ISO .183 → .136; BABIP .216 → .210. 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 NYY Yankees · 121 PAwOBA .335 → .193 (−141)K% 21.5% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.49%	÷0.988	×1.220	—	—	26.53%
BB% (unintentional) /PA	13.22%	÷1.066	×0.700	—	×0.995	8.64%
HBP% /PA	1.65%	—	×0.700	—	×0.995	1.15%
Singles /BIP	10.53%	÷1.113	×0.680	×1.006	×0.995	6.44%
Doubles /BIP	7.89%	÷1.069	×0.600	×1.006	×0.995	4.44%
Triples /BIP	2.63%	÷0.943	×0.600	×1.006	×0.995	1.68%
Home runs /BIP	6.58%	÷1.093	×0.470	—	×0.995	2.82%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 119, 1B 123, 2B 114, 3B 89, K 98, BB 113 — 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 ×1.006.

Result: wOBA .335 → .193; ISO .245 → .123; BABIP .222 → .127. 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 Angels · 77 PAwOBA .310 → .207 (−104)K% 18.2% → 21.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.18%	÷1.038	×1.220	—	—	21.37%
BB% (unintentional) /PA	12.99%	÷1.064	×0.700	—	×1.008	8.61%
HBP% /PA	6.49%	—	×0.700	—	×1.008	4.58%
Singles /BIP	25.00%	÷1.052	×0.680	×0.977	×1.008	15.91%
Doubles /BIP	2.08%	÷1.081	×0.600	×0.977	×1.008	1.14%
Triples /BIP	2.08%	÷0.961	×0.600	×0.977	×1.008	1.28%
Home runs /BIP	0.00%	÷1.068	×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 114, 1B 110, 2B 116, 3B 92, K 108, BB 113 — 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 ×0.977.

Result: wOBA .310 → .207; ISO .048 → .030; BABIP .292 → .183. 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
#1Franklin Stubbs'84-'95 * career totals — 9 seasons, 2,899 PA	4.4	2,899	104	74	229*	301*	428*	-43	+18	6.0	6.2
/162	664	24	17	-9.8	+4.2	1.4	pk7: 6
#2Michael Saunderslast yr '17 career totals — 8 seasons, 2,711 PA	4.1	2,711	81	55	233	305	399	-12	-13	4.1	4.5
/162	664	20	13	-2.9	-3.2	1.0	pk7: 5
#3Emil Brown'97-'09 * career totals — 7 seasons, 2,508 PA	3.8	2,508	59	52	247*	314*	388*	-25	+8	3.5	4.0
/162	664	16	14	-6.6	+2.1	0.9	pk7: 5
#4Chris Heiseylast yr '17 career totals — 8 seasons, 1,758 PA	2.6	1,758	62	25	238	296	413	-18	+3	3.0	3.2
/162	664	23	9	-6.7	+1.0	1.1	pk7: 4
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	3.6	2,393	79	52	228	283	392	-14	+5	2.3	2.3
/162	664	22	14	-4.0	+1.4	0.6	pk7: 2
#5Jake Cavelast yr '24 career totals — 7 seasons, 1,564 PA	2.4	1,564	45	13	236	292	400	-11	-6	1.3	1.3
/162	664	19	6	-4.5	-2.5	0.6	pk7: 1
#6Karim Garcia'95-'04 * career totals — 6 seasons, 1,560 PA	2.3	1,560	66	10	231*	269*	413*	-16	-3	-1.0	0.1
/162	664	28	4	-6.7	-1.3	-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
Wilberson De Pena (OGILVIE)	20	—	—	—	—	214/268/359	145	278	6	5	29%	6%	76	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Ceddanne Rafaela 2022 · A	21	43→53	46→55	59→55	39	215/259/351	136	270	13	15	26%	4%	70	-0.9	243/280/401	158	309	17	22	26%	4%	89	+0.5	250/287/402	152	300	17	19	22%	4%	93	+0.8
✕Max Muncy 2023 · A	20	39→49	47→55	50	41	193/269/328	134	304	15	12	39%	8%	69	-0.9	221/286/348	127	329	13	9	35%	7%	80	-0.2	234/300/394	160	319	20	5	31%	6%	95	+0.5
✕José Rodríguez 2021 · A	20	41→51	43→50	52→55	37	208/240/316	109	266	11	11	27%	4%	54	-2.0	248/280/380	132	299	14	24	21%	4%	84	+0.1	248/280/383	135	297	15	29	22%	4%	81	-0.0
✕Sean Henry 2006 · A	20	42→52	43→50	55	42	204/269/312	108	298	11	15	34%	8%	65	-1.2	229/283/355	126	291	11	19	24%	6%	80	-0.2	251/305/379	128	300	11	17	19%	6%	91	+0.6
✕Bryan Ramos 2022 · A	20	41→42	45→50	49→50	42	206/277/332	126	281	12	8	30%	7%	73	-0.6	219/279/362	143	273	18	5	26%	6%	80	-0.1	214/275/354	140	261	19	5	25%	6%	74	-0.4
✕Noelvi Marte 2022 · A	20	45→55	48→50	51→55	44	224/289/369	144	298	16	14	29%	8%	86	+0.3	237/299/368	131	306	15	18	26%	7%	88	+0.5	247/296/385	137	310	14	21	24%	5%	91	+0.4
✕Christian Villanueva 2012 · A	21	45→47	44→55	53→50	41	221/269/340	119	276	11	16	24%	5%	71	-0.8	222/273/353	131	287	13	9	27%	5%	76	-0.4	228/286/406	177	263	24	3	23%	6%	93	+0.6
✕Brayan Buelvas 2022 · A	20	39→45	46→50	51→55	41	199/261/328	129	275	14	13	32%	7%	65	-1.2	195/257/323	128	268	13	17	31%	7%	63	-1.4	205/266/334	130	290	12	14	32%	7%	66	-0.8
✕Daz Cameron 2018 · A	21	42→48	45→50	53→55	40	206/268/336	130	291	12	19	32%	6%	70	-0.8	209/279/335	126	306	11	17	33%	7%	74	-0.5	227/297/394	166	289	18	26	27%	8%	92	+0.3
✕Ronny Rodríguez 2012 · A	20	41→51	45→55	48→50	35	209/237/345	136	278	11	9	29%	3%	60	-1.6	221/248/349	128	278	13	8	25%	3%	65	-1.2	254/282/422	168	303	21	13	23%	3%	93	+0.7
✕Michael A. Taylor 2012 · A	21	40→50	44→55	49→60	36	200/244/319	120	279	11	12	32%	5%	57	-1.8	207/260/324	117	316	10	22	35%	6%	64	-1.3	240/297/382	142	309	19	14	28%	7%	92	+0.6
✕Jhonkensy Noel 2021 · A	20	40→42	43→55	47→45	42	202/266/309	107	265	11	7	28%	6%	63	-1.3	222/273/394	172	288	23	5	31%	5%	86	+0.3	200/264/382	182	250	25	1	31%	6%	78	-0.3
●Lewis Brinson 2014 · A	20	38→48	46→55	52→50	31	180/237/309	129	331	14	14	48%	6%	53	-2.1	230/281/382	152	336	17	14	35%	6%	85	+0.2	247/299/427	180	310	20	17	26%	6%	100	+1.0
✕Ezequiel Tovar 2022 · A	20	48→49	45→55	52→50	40	237/268/365	129	269	13	15	18%	3%	76	-0.4	249/287/399	150	313	16	13	25%	4%	91	+0.7	251/287/411	161	323	17	11	27%	4%	94	+0.8
✕Orelvis Martinez 2021 · A	19	42→36	47→60	53→40	42	214/272/355	141	275	14	6	27%	6%	76	-0.4	204/272/397	193	262	26	4	32%	7%	86	+0.3	192/264/389	197	235	28	3	32%	7%	80	-0.1
✕A.J. Vukovich 2022 · A	21	44→52	46→50	51→55	34	219/260/347	128	321	15	13	36%	4%	70	-0.9	225/267/360	135	322	15	18	33%	5%	75	-0.5	242/296/390	149	347	17	2	33%	6%	89	+0.4
✕Echedry Vargas 2024 · A	19	40→47	44→50	53→55	40	202/260/326	123	269	11	15	29%	6%	65	-1.2	215/258/351	136	288	15	14	30%	4%	70	-0.9	218/259/369	151	284	19	13	30%	4%	72	-0.5
✕Kevin Padlo 2016 · A	20	39→42	46→55	50	46	197/276/332	135	270	13	8	31%	9%	73	-0.6	186/272/313	127	276	12	8	34%	10%	67	-1.1	196/269/361	165	267	20	12	33%	8%	75	-0.3
✕Sean Coyle 2013 · A	21	40→38	45→50	54→50	38	199/264/327	128	286	12	13	34%	6%	67	-1.1	211/271/364	153	307	18	14	36%	6%	78	-0.3	204/267/368	165	294	22	15	37%	7%	75	-0.2
✕Agustín Ramírez 2023 · A	21	43→48	45→55	51→55	44	213/272/340	128	284	12	11	29%	7%	72	-0.7	233/294/390	157	279	18	13	23%	7%	93	+0.8	236/301/405	169	279	19	20	22%	7%	97	+1.1

Wilberson De Pena

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps