Ezequiel Pena

SS ACL Cubs

Age 20 L/R 6'0" / 165 lbs ROK HR -8% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#1468ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL Cubs Red	130	.259/.333/.328	0	13	17	—	.167/.225/.217
2025	18	ROKDSL Cubs Blue	143	.327/.469/.381	0	17	71	—	.221/.336/.262
2026	19	A/ROKCHC	126	.261/.349/.315	1	4	34	—	.188/.246/.231
2027PROJMLE	20	MLBCHC	236	.213/.282/.292	2	5	64	0.0
2028PROJ34% MLB	21	MLBCHC	47	.219/.289/.310	1	1	69	0.0
2029PROJ48% MLB	22	MLBCHC	112	.223/.293/.322	2	3	74	0.0

Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2038Service0.0First FA2039

2027MiLB2028MiLB2029MiLB2030MiLB2031MiLB2032MiLB2033Pre-Arb$0.9M2034Pre-Arb$1.0M+4

Skills · percentileMiLB Statcast 2026 Rk

Z-Con%71

Whiff%52

wRC+47

wOBA39

BB%32

K%28

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsLuis Liberato (age 20) · Conner Capel (age 20) · Luis Barrera (age 20)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 76 proj PA

wRC+†64

AVG/OBP/SLG.211 / .280 / .289

PA76

HR1

K%28

BB%8

ISO79

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$7M ctrl surplus

Tools · ContractCON 57 / POW 35

Toolsscout grade

CONTACT57

scouting grade only

POWER35

scouting grade only

EYE65

scouting grade only

SPEED61

scouting grade only

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

Status MiLB

MLB Debut 2033

Service 0 yrs (est)

Team Control Through 2038

First FA Year 2039

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2033
2028	MiLB	still in minors · estimated debut 2033
2029	MiLB	still in minors · estimated debut 2033
2030	MiLB	still in minors · estimated debut 2033
2031	MiLB	still in minors · estimated debut 2033
2032	MiLB	still in minors · estimated debut 2033
2033	Pre-Arb	$0.9M	+0.3	$0.8M	+$0.3M
2034	Pre-Arb	$1.0M	+0.3	$0.7M	+$0.2M
2035	Pre-Arb	$1.0M	+0.2	$0.4M	+$0.0M
2036	Arb-1	$1M	+0.1	$0.2M	+$0.0M (cut)
2037	Arb-2	$0.7M	—	—	—
2038	Ext	beyond projection horizon · no WAR estimate
Totals		$3M		$2M	+$0.5M

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 Cubs Red	—	130	116	30	6	1	0	12	31	1	13	2	259	333	328	661	69	349	24	9	302	17	—	—	—	—	—	—
2025	18	ROK	DSL Cubs Blue	—	143	113	37	4	1	0	28	12	2	17	2	327	469	381	849	53	366	8	20	397	71	—	—	—	—	—	—
2026	19	A	Myrtle Beach Pelicans	—	32	29	5	0	0	0	3	8	0	3	0	172	250	172	422		238	25	9	207	-3	—	—	—	—	—	—
2026	19	ROK	ACL Cubs	—	94	82	24	3	0	1	12	25	0	1	5	293	383	366	749	73	411	27	13	345	47	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Cubs Red	—	130	120	20	4	1	0	8	39	1	13	2	167	225	217	441	50	234	30	6	193	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Blue	—	143	122	27	3	1	0	19	15	2	17	2	221	336	262	598	41	245	10	13	273	71	—	—	—	—	—	—
2026	19	A MLE	Myrtle Beach Pelicans	—	32	30	4	0	0	0	2	11	0	3	0	133	188	133	321		226	34	6	164	-3	—	—	—	—	—	—
2026	19	ROK MLE	ACL Cubs	—	94	87	18	2	0	1	7	36	0	1	5	207	266	264	530	57	345	38	7	238	47	—	—	—	—	—	—
2024	17	ROK MLE	DSL Cubs Red	—	130	120	20	4	1	0	8	39	1	13	2	167	225	217	441	50	244	30	6	193	17	—	—	—	—	—	—
2024	17	ROK RAW	DSL Cubs Red	—	130	116	30	6	1	0	12	31	1	13	2	259	333	328	661	69	349	24	9	302	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Blue	—	143	122	27	3	1	0	19	15	2	17	2	221	336	262	598	41	252	10	13	273	71	—	—	—	—	—	—
2025	18	ROK RAW	DSL Cubs Blue	—	143	113	37	4	1	0	28	12	2	17	2	327	469	381	849	53	366	8	20	397	71	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	126	116	22	2	0	1	10	47	0	4	5	190	254	233	487	43	309	37	8	219	35	—	—	—	—	—	—
2026	19	ROK RAW	2 teams	—	126	111	29	3	0	1	15	33	0	4	5	261	349	315	665	54	364	26	12	310	35	—	—	—	—	—	—
2024	17	ROK MLE	DSL Cubs Red	—	130	120	20	4	1	0	8	39	1	13	2	167	225	217	441	50	234	30	6	193	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Blue	—	143	121	27	3	1	0	19	15	2	17	2	223	336	264	600	41	245	10	13	273	71	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	126	115	22	2	0	1	10	47	0	4	5	191	254	235	489	43	315	37	8	219	35	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Cubs Red	—	130	120	20	4	1	0	8	39	1	13	2	167	225	217	441	50	234	30	6	193	17	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Blue	—	143	121	27	3	1	0	19	15	2	17	2	223	336	264	600	41	245	10	13	273	71	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	126	115	22	2	0	1	10	47	0	4	5	191	254	235	489	43	315	37	8	219	35	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	CHC	0%	236	213	44	7	1	2	19	66	2	5	1	213	282	292	574	79	292	28	8	262	64	-10	+1	+0	+3	+5	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	CHC	34%	138	125	27	4	1	2	11	38	1	3	1	217	287	307	594	90	293	28	8	271	69	-5	+0	+0	+1	+3	-0.0
2029	22	MLB MLE	CHC	48%	232	209	45	7	1	3	19	62	2	6	1	221	291	319	610	98	294	27	8	277	74	-7	+1	+0	+2	+5	0.1
2030	23	MLB MLE	CHC	54%	325	293	66	11	2	5	26	86	3	8	2	224	294	328	622	104	295	26	8	282	77	-9	+1	+0	+3	+7	0.2
2031	24	MLB MLE	CHC	55%	391	352	79	13	2	7	32	103	4	10	2	226	297	335	632	109	296	26	8	286	80	-10	+1	+0	+4	+8	0.4
2032	25	MLB MLE	CHC	56%	428	386	88	14	3	8	35	111	4	11	2	227	298	340	639	113	296	26	8	288	81	-10	+1	+0	+5	+9	0.6
2033	26	MLB MLE	CHC	56%	447	403	91	15	3	8	37	116	4	11	3	227	298	341	639	113	295	26	8	288	81	-10	+1	+0	+5	+10	0.6
2034	27	MLB MLE	CHC	55%	454	410	92	15	3	8	37	119	4	11	3	226	298	338	636	112	295	26	8	287	80	-11	+1	+0	+5	+10	0.5
2035	28	MLB MLE	CHC	55%	453	409	92	15	3	8	37	120	4	10	3	225	296	334	629	109	294	26	8	285	79	-11	+1	-1	+5	+10	0.3
2036	29	MLB MLE	CHC	53%	445	402	90	15	2	8	36	119	4	9	2	222	293	328	621	105	293	27	8	281	76	-12	+1	-1	+5	+10	0.2
2037	30	MLB MLE	CHC	53%	435	394	86	14	2	7	35	117	3	9	3	220	290	321	610	101	292	27	8	277	73	-14	+1	-2	+5	+9	-0.1
2028	21	MLB CTX	CHC	34%	47	43	10	2	0	1	4	13	0	1	0	219	289	310	599	91	297	28	9	273	69	-2	+0	+0	+1	+1	0.0
2029	22	MLB CTX	CHC	48%	112	101	23	4	1	2	9	30	1	3	1	223	293	322	615	99	298	27	8	279	74	-4	+0	+0	+1	+2	0.0
2030	23	MLB CTX	CHC	54%	176	158	36	6	1	3	14	47	2	4	1	225	296	331	627	105	298	27	8	284	77	-5	+0	+0	+2	+4	0.1
2031	24	MLB CTX	CHC	55%	217	195	45	7	2	4	18	57	2	5	1	228	299	338	637	110	299	26	8	288	80	-5	+1	+0	+2	+5	0.2
2032	25	MLB CTX	CHC	56%	240	216	49	8	2	4	20	62	2	6	1	229	300	343	643	114	299	26	8	290	81	-5	+1	+0	+3	+5	0.3
2033	26	MLB CTX	CHC	56%	251	226	53	9	2	5	21	65	2	6	1	229	300	343	643	114	299	26	8	290	81	-6	+1	+0	+3	+5	0.3
2034	27	MLB CTX	CHC	55%	251	226	52	9	2	4	21	66	2	6	1	228	299	341	640	113	298	26	8	289	80	-6	+1	+0	+3	+5	0.3
2035	28	MLB CTX	CHC	55%	248	224	50	8	2	4	20	65	2	6	1	226	297	336	634	110	297	26	8	286	79	-6	+1	-0	+3	+5	0.2
2036	29	MLB CTX	CHC	53%	238	215	49	8	2	4	19	63	2	5	1	224	295	330	625	106	296	26	8	283	76	-7	+1	-1	+3	+5	0.1
2037	30	MLB CTX	CHC	53%	229	206	46	8	1	4	19	62	2	5	1	221	291	323	614	102	295	27	8	278	73	-7	+1	-1	+2	+5	-0.0
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2009	1810	413	69	15	35	165	530	17	47	9	228	299	341	640	113	301	26	8	285	74	-52	+6	-2	+22	+44	1.7
/ 162G	—	A+C		—	650	586	133	22	5	11	53	171	6	15	3	227	298	338	636	111	300	26	8	285	74	-17	+2	-1	+7	+14	0.5
Career	—	MLE		—	4223	3810	839	134	24	66	348	1113	37	124	31	220	292	320	612	100	292	26	8	278	74	-102	+9	-4	+41	+83	2.8
/ 162G	—	MLE		—	650	586	130	21	4	10	54	171	6	19	5	222	294	323	617	101	294	26	8	278	74	-17	+2	-1	+7	+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 ROKACL Cubs · 94 PAwOBA .336 → .238 (−98)K% 26.6% → 38.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.60%	÷1.000	×1.440	—	—	38.30%
BB% (unintentional) /PA	12.77%	÷1.000	×0.620	—	×0.995	7.88%
HBP% /PA	0.00%	—	×0.720	—	×0.995	0.00%
Singles /BIP	35.09%	÷1.000	×0.820	×1.050	×0.995	30.06%
Doubles /BIP	5.26%	÷1.000	×0.720	×1.050	×0.995	3.96%
Triples /BIP	0.00%	÷1.000	×0.720	×1.050	×0.995	0.00%
Home runs /BIP	1.75%	÷1.000	×0.780	—	×0.995	1.36%

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 ×1.050.

Result: wOBA .336 → .238; ISO .073 → .050; BABIP .411 → .345. 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 AMyrtle Beach Pelicans · 32 PAwOBA .202 → .164 (−38)K% 25.0% → 34.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.000	×1.360	—	—	34.00%
BB% (unintentional) /PA	9.38%	÷1.000	×0.690	—	×1.030	6.66%
HBP% /PA	0.00%	—	×0.780	—	×1.030	0.00%
Singles /BIP	23.81%	÷1.000	×0.920	—	×1.030	22.56%
Doubles /BIP	0.00%	÷1.000	×0.830	—	×1.030	0.00%
Triples /BIP	0.00%	÷1.000	×0.910	—	×1.030	0.00%
Home runs /BIP	0.00%	÷1.000	×0.800	—	×1.030	0.00%

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).

Result: wOBA .202 → .164; ISO .000 → .000; BABIP .238 → .226. 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 Cubs Blue · 143 PAwOBA .388 → .273 (−115)K% 8.4% → 10.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.39%	÷1.001	×1.220	—	—	10.23%
BB% (unintentional) /PA	19.58%	÷1.006	×0.700	—	×0.995	13.55%
HBP% /PA	1.40%	—	×0.700	—	×0.995	0.97%
Singles /BIP	31.68%	÷1.016	×0.680	×1.011	×0.995	21.32%
Doubles /BIP	3.96%	÷0.928	×0.600	×1.011	×0.995	2.57%
Triples /BIP	0.99%	÷1.038	×0.600	×1.011	×0.995	0.58%
Home runs /BIP	0.00%	÷0.926	×0.470	—	×0.995	0.00%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 85, 1B 103, 2B 86, 3B 108, K 100, BB 101 — 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 ×1.011.

Result: wOBA .388 → .273; ISO .053 → .035; BABIP .366 → .245. 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 Cubs Red · 130 PAwOBA .297 → .193 (−103)K% 23.8% → 30.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.85%	÷0.964	×1.220	—	—	30.17%
BB% (unintentional) /PA	9.23%	÷1.047	×0.700	—	×1.008	6.22%
HBP% /PA	0.77%	—	×0.700	—	×1.008	0.54%
Singles /BIP	27.06%	÷1.018	×0.680	×1.014	×1.008	18.46%
Doubles /BIP	7.06%	÷0.960	×0.600	×1.014	×1.008	4.51%
Triples /BIP	1.18%	÷1.000	×0.600	×1.014	×1.008	0.72%
Home runs /BIP	0.00%	÷1.025	×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 105, 1B 104, 2B 92, 3B 100, K 93, BB 109 — 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 ×1.014.

Result: wOBA .297 → .193; ISO .069 → .042; BABIP .349 → .234. 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
#1Cliff Penningtonlast yr '17 career totals — 10 seasons, 3,108 PA	4.7	3,108	36	84	243	310	341	+28	+29	9.2	9.5
/162	664	8	18	+5.9	+6.2	2.0	pk7: 10
#2Jose Uribe'84-'93 * career totals — 9 seasons, 3,369 PA	5.1	3,369	19	74	240*	300*	338*	+36	+27	7.8	7.7
/162	664	4	15	+7.1	+5.3	1.5	pk7: 8
#3Gene Michael'66-'75 * career totals — 9 seasons, 3,095 PA	4.7	3,095	15	22	233*	291*	316*	+32	+27	4.6	5.8
/162	664	3	5	+6.8	+5.8	1.0	pk7: 7
#4Ronny 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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	3.1	2,086	36	49	225	292	332	+22	+18	3.1	3.0
/162	664	11	16	+7.1	+5.7	1.0	pk7: 3
#5Tim Cullen'66-'72 * career totals — 6 seasons, 1,960 PA	3.0	1,960	9	10	229*	288*	313*	+10	+27	2.7	2.7
/162	664	3	3	+3.6	+9.1	0.9	pk7: 3
#6Ryan 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

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
Ezequiel Pena (OGILVIE)	20	52→57	30→35	56→61	65	211/280/289	79	292	1	2	28%	8%	64	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Luis Liberato 2016 · A	20	37→47	37→50	53→50	42	177/241/251	73	261	4	13	32%	7%	40	-3.1	211/262/329	118	307	9	6	32%	7%	65	-1.2	221/286/368	148	299	15	9	30%	8%	83	+0.0
✕Conner Capel 2017 · A	20	40→48	36→45	52→55	44	191/238/258	68	240	2	13	21%	5%	40	-3.1	210/265/335	125	281	12	11	28%	7%	68	-1.0	226/297/349	123	283	12	19	23%	8%	80	-0.1
✕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
✕Andy Sugilio 2017 · A	20	40→50	35→40	52→50	43	188/238/250	62	246	2	9	24%	6%	38	-3.2	232/264/308	76	300	4	14	23%	4%	60	-1.6	244/271/312	68	315	4	16	23%	3%	61	-1.0
✕Luis Ayala 2016 · A	20	39→49	34→40	53→55	48	182/265/242	60	263	1	18	28%	9%	48	-2.5	205/263/270	65	288	2	17	27%	6%	52	-2.2	204/256/260	57	286	2	18	28%	6%	45	-1.3
✕Steward Berroa 2018 · A	19	40→50	36→45	52→65	45	189/257/257	67	264	2	17	28%	8%	47	-2.5	204/269/271	67	302	2	17	30%	8%	55	-2.0	227/306/323	96	332	8	52	31%	10%	79	-0.1
✕Edison Lantigua 2017 · A	20	41	36→45	52→50	42	195/250/272	77	278	3	6	29%	7%	47	-2.5	201/260/293	92	331	6	8	38%	7%	57	-1.8	178/240/274	95	303	8	7	41%	7%	42	-0.8
✕Henry Ramos 2023 · A	18	36→46	34→40	55	49	170/255/219	49	238	2	17	27%	9%	39	-3.1	176/240/238	62	262	3	16	31%	7%	37	-3.3	201/266/273	72	289	5	18	30%	7%	51	-1.1
✕Alberto Rodriguez 2019 · A	18	38→48	37→50	51→50	46	184/251/255	71	245	5	16	26%	8%	45	-2.7	213/271/308	95	288	7	14	27%	7%	64	-1.3	228/292/360	132	326	11	7	31%	7%	81	-0.1
✕Daniel Montano 2019 · A	20	37→47	40→45	47→50	42	182/236/275	92	242	6	9	27%	6%	43	-2.8	187/232/268	81	275	5	10	32%	5%	40	-3.1	213/289/324	112	322	9	6	34%	9%	73	-0.5
✕Matt McPhearson 2015 · A	20	45→52	33→30	55	41	201/267/240	40	322	1	22	35%	8%	47	-2.5	204/262/246	42	319	1	26	34%	7%	46	-2.6	214/264/256	42	321	0	31	31%	6%	45	-1.1
✕Ricardo Rosario 2023 · A	20	39	36→40	50→55	44	186/249/258	71	249	3	12	26%	7%	45	-2.7	204/271/288	84	283	7	19	28%	7%	60	-1.6	202/282/289	86	263	10	29	26%	8%	63	-0.7
✕Joe Naranjo 2021 · A	20	43→48	36→40	50→45	42	203/259/270	67	299	4	5	32%	7%	51	-2.3	200/278/288	88	301	8	5	33%	9%	63	-1.3	191/279/279	88	283	9	4	33%	10%	60	-1.2
✕Tirso Ornelas 2021 · A	21	41→51	37→50	51→45	44	194/259/266	72	281	4	6	31%	8%	50	-2.3	230/293/336	106	308	8	6	26%	8%	79	-0.2	262/321/391	130	320	13	7	22%	7%	99	+1.1
✕Sócrates Brito 2012 · A	19	44→54	35→50	49→55	38	207/245/270	63	284	2	13	27%	4%	44	-2.8	221/256/300	79	320	4	15	31%	4%	55	-1.9	226/270/372	146	299	14	12	28%	6%	76	-0.3
✕Franchy Cordero 2015 · A	20	42→52	37→55	53→50	35	195/245/272	77	318	4	12	38%	6%	46	-2.6	225/262/327	102	338	8	14	34%	4%	64	-1.3	250/293/418	168	373	15	17	35%	5%	94	+0.7
✕Carlos Franco 2013 · A	21	41→49	37→45	49→45	46	195/264/270	75	273	5	9	29%	8%	53	-2.1	208/262/288	80	293	6	7	29%	7%	55	-1.9	214/266/324	110	318	13	2	35%	6%	64	-1.1
✕Michael Beltre 2016 · A	21	40→50	35→45	50→60	39	185/254/245	60	288	3	12	34%	7%	44	-2.8	212/276/297	85	297	4	12	28%	7%	63	-1.3	224/296/341	118	306	9	22	28%	9%	78	-0.2
✕Eudy Pina 2011 · A	20	39→47	37→45	55	41	189/257/262	73	254	4	22	26%	6%	49	-2.4	185/243/272	87	270	6	12	32%	5%	46	-2.6	217/270/333	115	305	8	11	30%	5%	67	-0.8
●Ezequiel Carrera 2007 · A	20	42→52	34→45	49→60	44	197/251/250	52	248	2	16	21%	5%	42	-2.9	243/305/323	80	312	4	20	22%	7%	80	-0.2	274/343/361	88	352	5	25	22%	8%	99	+0.8

Ezequiel Pena

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps