Nico Perez

2B Great Lakes Loons

Age 22 R/R 5'10" / 175 lbs A+ HR +8%BB -8% Svc 0.0 · Ctrl thru 2036

Overview

A+PROSPECTMiLBFA 2037

OGV OFP35OGV rank#977ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	19	ROKLAD	126	.264/.381/.387	3	14	36	—	.159/.246/.230
2025	20	ALAA	251	.280/.389/.401	3	35	73	—	.217/.303/.295
2026	21	A+LAD	358	.270/.383/.450	9	35	84	—	.217/.307/.350
2027PROJMLE	22	MLBLAD	1	.210/.297/.324	0	0	80	-0.0
2028PROJ31% MLB	23	MLBLAD	91	.215/.301/.340	2	3	86	0.0
2029PROJ45% MLB	24	MLBLAD	165	.219/.305/.351	4	5	89	0.2

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$1M+2

Skills · percentileMiLB Statcast 2026 A+

Speed98

Z-Con%82

Whiff%78

Chase%76

wOBA72

wRC+70

Career WAR0.0 WAR median (P10 -0.1 / P90 9.8, comp-based) · star 3% · didn't stick 79%

CompsJakob Marsee (age 22) · Brice Matthews (age 22) · Jason Taylor (age 22)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†80

AVG/OBP/SLG.210 / .297 / .324

PA1

HR0

K%27

BB%10

BABIP277

ISO130

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	+0.4	$1M	+$0.6M
2032	Pre-Arb	$0.9M	+0.4	$1M	+$0.6M
2033	Pre-Arb	$0.9M	+0.3	$0.8M	+$0.3M
2034	Arb-1	$1M	+0.1	$0.2M	+$0.0M (cut)
2035	Arb-2	$1M	—	—	—
2036	Arb-3	$7M	—	—	—
Totals		$3M		$3M	+$1M

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	18	INTL	RA12	—	16	16	3	0	0	0	0	7	0	0	0	188	188	188	375		333	44	0	170	1	—	—	—	—	—	—
2024	19	ROK	ACL Dodgers	—	126	106	28	4	0	3	17	36	3	14	1	264	381	387	768	123	373	29	13	353	36	—	—	—	—	—	—
2025	20	A	Rancho Cucamonga Quakes	—	251	207	58	12	2	3	35	55	2	35	6	280	389	401	790	121	355	22	14	350	73	—	—	—	—	—	—
2026	21	A+	Great Lakes Loons	—	358	300	81	17	5	9	48	82	7	35	6	270	383	450	833	180	340	23	13	370	84	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	19	ROK MLE	ACL Dodgers	—	126	113	18	2	0	2	10	53	3	14	1	159	246	230	476	71	278	42	8	222	36	—	—	—	—	—	—
2025	20	A MLE	Rancho Cucamonga Quakes	—	251	217	47	9	1	2	25	76	2	35	6	217	303	295	598	78	301	30	10	276	73	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	358	314	68	13	4	7	34	104	7	35	6	217	307	350	657	134	292	29	9	292	84	—	—	—	—	—	—
2023	18	INTL MLE	RA12	—	16	16	3	0	0	0	0	7	0	0	0	188	188	188	375		333	44	0	—	—	—	—	—	—	—	—
2023	18	INTL RAW	RA12	—	16	16	3	0	0	0	0	7	0	0	0	188	188	188	375		333	44	0	170	1	—	—	—	—	—	—
2024	19	ROK MLE	ACL Dodgers	—	126	113	18	2	0	2	10	53	3	14	1	159	246	230	476	71	276	42	8	222	36	—	—	—	—	—	—
2024	19	ROK RAW	ACL Dodgers	—	126	106	28	4	0	3	17	36	3	14	1	264	381	387	768	123	373	29	13	353	36	—	—	—	—	—	—
2025	20	A MLE	Rancho Cucamonga Quakes	—	251	217	47	9	1	2	25	76	2	35	6	217	303	295	598	78	310	30	10	276	73	—	—	—	—	—	—
2025	20	A RAW	Rancho Cucamonga Quakes	—	251	207	58	12	2	3	35	55	2	35	6	280	389	401	790	121	355	22	14	350	73	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	358	314	68	13	4	7	34	104	7	35	6	217	307	350	657	134	296	29	9	292	84	—	—	—	—	—	—
2026	21	A+ RAW	Great Lakes Loons	—	358	300	81	17	5	9	48	82	7	35	6	270	383	450	833	180	340	23	13	370	84	—	—	—	—	—	—
2024	19	ROK MLE	ACL Dodgers	—	126	112	18	2	0	2	10	53	3	14	1	161	246	232	478	71	278	42	8	222	36	—	—	—	—	—	—
2025	20	A MLE	Rancho Cucamonga Quakes	—	251	222	47	9	1	2	25	76	2	35	6	212	303	288	592	77	301	30	10	276	73	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	358	314	68	13	4	7	34	104	7	35	6	217	307	350	657	134	292	29	9	292	84	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	19	ROK MLE	ACL Dodgers	—	126	112	18	2	0	2	10	53	3	14	1	161	246	232	478	71	278	42	8	222	36	—	—	—	—	—	—
2025	20	A MLE	Rancho Cucamonga Quakes	—	251	222	47	9	1	2	25	76	2	35	6	212	303	288	592	77	301	30	10	276	73	—	—	—	—	—	—
2026	21	A+ MLE	Great Lakes Loons	—	358	314	68	13	4	7	34	104	7	35	6	217	307	350	657	134	292	29	9	292	84	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	22	MLB MLE	LAD	0%	468	414	89	17	4	8	45	125	6	21	4	214	300	331	631	117	284	27	10	287	80	-11	+3	-3	+2	+10	0.3
▸ 2027 — real world (MLB)
2027	22	MLB CTX	LAD	0%	1	1	0	0	0	0	0	0	0	0	0	210	297	324	620	114	277	0	0	283	80	-0	+0	-0	+0	+0	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	23	MLB MLE	LAD	31%	290	256	56	11	2	6	28	76	4	11	2	219	305	347	652	127	286	26	10	295	86	-5	+1	-2	+1	+6	0.2
2029	24	MLB MLE	LAD	45%	363	320	72	14	3	8	35	94	5	12	2	223	308	357	666	134	287	26	10	300	89	-5	+2	-1	+1	+8	0.5
2030	25	MLB MLE	LAD	54%	403	356	80	15	3	9	39	103	5	11	2	225	310	363	673	138	287	26	10	303	91	-4	+1	-1	+1	+9	0.6
2031	26	MLB MLE	LAD	58%	426	377	85	16	3	10	41	109	5	11	2	226	311	366	677	140	287	26	10	304	92	-4	+1	-2	+2	+9	0.7
2032	27	MLB MLE	LAD	59%	435	385	87	17	3	10	42	111	5	10	2	226	310	366	676	140	287	26	10	304	92	-4	+1	-2	+2	+9	0.7
2033	28	MLB MLE	LAD	60%	434	384	86	16	3	10	42	111	5	9	2	225	308	361	670	137	286	26	10	302	90	-5	+1	-2	+2	+9	0.5
2034	29	MLB MLE	LAD	59%	425	377	84	16	3	10	40	110	5	8	1	222	306	355	661	133	285	26	9	298	88	-6	+1	-3	+2	+9	0.3
2035	30	MLB MLE	LAD	59%	414	367	81	15	3	9	39	109	5	7	1	219	302	348	650	129	284	26	9	294	85	-7	+1	-4	+1	+9	0.0
2036	31	MLB MLE	LAD	58%	398	354	75	14	2	8	37	106	4	5	2	215	298	338	636	123	281	27	9	288	81	-9	+0	-4	+1	+9	-0.3
2037	32	MLB MLE	LAD	58%	376	334	70	13	2	7	35	102	4	4	2	210	292	326	618	116	277	27	9	281	76	-11	+0	-5	+1	+8	-0.6
2028	23	MLB CTX	LAD	31%	91	81	18	3	1	2	9	24	1	3	1	215	301	340	642	125	278	26	10	291	86	-2	+0	-0	+0	+2	0.0
2029	24	MLB CTX	LAD	45%	165	146	32	6	1	4	16	43	2	5	1	219	305	351	656	132	280	26	10	296	89	-2	+1	-1	+1	+4	0.2
2030	25	MLB CTX	LAD	54%	216	190	42	8	1	5	21	55	3	6	1	221	306	357	664	136	280	25	10	299	91	-2	+1	-1	+1	+5	0.3
2031	26	MLB CTX	LAD	58%	248	219	48	9	1	6	24	63	3	6	1	222	307	361	668	138	280	25	10	301	92	-2	+1	-1	+1	+5	0.4
2032	27	MLB CTX	LAD	59%	258	228	51	9	2	6	25	66	3	6	1	222	307	360	667	138	280	26	10	300	92	-2	+1	-1	+1	+6	0.4
2033	28	MLB CTX	LAD	60%	261	231	51	9	2	6	25	67	3	5	1	221	305	356	661	135	279	26	10	298	90	-3	+1	-1	+1	+6	0.3
2034	29	MLB CTX	LAD	59%	252	223	49	9	1	6	24	65	3	4	1	218	302	350	652	132	278	26	10	294	88	-4	+0	-2	+1	+5	0.1
2035	30	MLB CTX	LAD	59%	243	215	45	8	1	5	23	64	3	4	1	215	299	342	641	127	277	26	9	290	85	-4	+0	-2	+1	+5	0.0
2036	31	MLB CTX	LAD	58%	232	206	44	8	1	5	22	62	2	3	1	211	294	333	627	121	274	27	9	284	81	-5	+0	-2	+1	+5	-0.2
2037	32	MLB CTX	LAD	58%	218	194	40	7	1	4	20	59	2	2	1	207	288	321	609	114	271	27	9	277	76	-6	+0	-3	+1	+5	-0.4
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2184	1933	420	76	12	49	209	568	25	44	10	217	302	345	647	128	280	26	10	293	84	-33	+5	-14	+8	+47	1.3
/ 162G	—	A+C		—	650	575	126	23	4	15	62	169	7	13	3	219	302	351	654	132	282	26	10	293	84	-10	+1	-4	+2	+14	0.4
Career	—	MLE		—	4925	4355	953	179	34	102	467	1327	62	181	33	219	303	346	649	127	288	27	9	292	84	-65	+11	-27	+15	+90	2.6
/ 162G	—	MLE		—	650	575	125	24	4	13	62	175	8	24	4	217	303	341	644	123	286	27	10	292	84	-10	+2	-4	+2	+14	0.4

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 A+Great Lakes Loons · 358 PAwOBA .364 → .292 (−72)K% 22.9% → 29.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.91%	÷1.000	×1.270	—	—	29.09%
BB% (unintentional) /PA	13.41%	÷1.000	×0.710	—	×1.012	9.63%
HBP% /PA	1.96%	—	×0.790	—	×1.012	1.56%
Singles /BIP	22.94%	÷1.000	×0.920	×0.964	×1.012	20.59%
Doubles /BIP	7.80%	÷1.000	×0.810	×0.964	×1.012	6.16%
Triples /BIP	2.29%	÷1.000	×0.850	×0.964	×1.012	1.90%
Home runs /BIP	4.13%	÷1.000	×0.800	—	×1.012	3.34%

Factors used: league row Midwest League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.964.

Result: wOBA .364 → .292; ISO .180 → .142; BABIP .340 → .292. 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 ARancho Cucamonga Quakes · 251 PAwOBA .350 → .276 (−75)K% 21.9% → 30.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.91%	÷0.987	×1.360	—	—	30.19%
BB% (unintentional) /PA	13.94%	÷0.981	×0.690	—	×1.015	9.95%
HBP% /PA	0.80%	—	×0.780	—	×1.015	0.63%
Singles /BIP	26.97%	÷1.004	×0.920	×0.950	×1.015	23.83%
Doubles /BIP	7.89%	÷1.054	×0.830	×0.950	×1.015	5.99%
Triples /BIP	1.32%	÷1.150	×0.910	×0.950	×1.015	1.00%
Home runs /BIP	1.97%	÷1.055	×0.800	—	×1.015	1.52%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 111, 1B 101, 2B 111, 3B 130, K 97, BB 96 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .350 → .276; ISO .121 → .090; BABIP .355 → .301. 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 ROKACL Dodgers · 126 PAwOBA .344 → .222 (−122)K% 28.6% → 41.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.57%	÷0.984	×1.440	—	—	41.81%
BB% (unintentional) /PA	13.49%	÷1.070	×0.620	—	×0.995	7.78%
HBP% /PA	2.38%	—	×0.720	—	×0.995	1.71%
Singles /BIP	30.00%	÷1.011	×0.820	×0.950	×0.995	22.99%
Doubles /BIP	5.71%	÷1.010	×0.720	×0.950	×0.995	3.85%
Triples /BIP	0.00%	÷0.967	×0.720	×0.950	×0.995	0.00%
Home runs /BIP	4.29%	÷0.942	×0.780	—	×0.995	3.53%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 88, 1B 102, 2B 102, 3B 93, K 97, BB 114 — 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 ×0.950.

Result: wOBA .344 → .222; ISO .123 → .084; BABIP .373 → .278. 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
#1Alex Gonzalez'94-'06 * career totals — 12 seasons, 5,528 PA	8.3	5,528	137	97	232*	290*	379*	+55	+6	8.3	10.0
/162	664	16	12	+6.6	+0.8	1.0	pk7: 12
#2Trevor Plouffelast yr '17 career totals — 7 seasons, 3,178 PA	4.8	3,178	103	12	243	306	411	+14	-18	8.4	8.4
/162	664	22	3	+2.8	-3.8	1.8	pk7: 8
#3Angel Berroalast yr '09 career totals — 8 seasons, 2,794 PA	4.2	2,794	46	50	259	303	375	+27	-6	6.7	7.1
/162	664	11	12	+6.5	-1.4	1.6	pk7: 7
#4Tim Beckhamlast yr '19 career totals — 5 seasons, 1,743 PA	2.6	1,743	63	13	248	301	431	+19	-13	6.1	6.1
/162	664	24	5	+7.1	-4.8	2.3	pk7: 6
#5U. L. Washington'77-'87 * career totals — 9 seasons, 3,124 PA	4.7	3,124	27	132	246*	313*	363*	+30	-28	4.2	5.1
/162	664	6	28	+6.3	-6.0	0.9	pk7: 6
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 5 projected seasons	3.3	2,183	48	46	222	303	355	+23	-12	5.4	5.1
/162	664	15	14	+7.1	-3.5	1.6	pk7: 5
#6Frank Duffy'70-'79 * career totals — 7 seasons, 2,924 PA	4.4	2,924	26	49	234*	283*	348*	+30	-2	0.9	2.1
/162	664	6	11	+6.7	-0.5	0.2	pk7: 3

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
Nico Perez (OGILVIE)	22	—	—	—	—	212/298/328	116	284	4	9	27%	10%	80	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
●Jakob Marsee 2023 · A	22	44→49	42→45	58→60	54	211/313/323	113	290	8	21	28%	12%	85	+0.2	220/320/345	125	277	13	33	24%	11%	93	+0.8	217/321/350	133	273	12	37	23%	11%	92	+0.8
✕Brice Matthews 2024 · A	22	45	44→50	54→60	46	211/306/329	118	322	12	22	35%	10%	84	+0.1	217/298/371	154	326	18	30	36%	9%	90	+0.6	208/288/365	156	305	19	33	36%	9%	82	+0.0
✕Jason Taylor 2010 · A	22	45→40	45→50	52→55	50	222/296/347	125	272	12	21	23%	9%	83	+0.1	209/261/319	110	272	10	13	26%	6%	63	-1.4	145/173/232	87	187	9	6	28%	3%	9	-1.1
✕Taylor Motter 2012 · A	22	48→49	42→50	55	53	232/307/339	107	284	9	20	21%	10%	85	+0.2	227/290/330	103	280	8	20	21%	8%	76	-0.4	245/294/375	130	284	13	21	18%	6%	86	+0.2
✕Felix Valerio 2023 · AA	22	43→49	44→45	53→55	49	215/287/333	118	255	12	23	20%	8%	76	-0.4	206/269/308	102	265	9	16	25%	7%	64	-1.3	193/254/279	87	254	8	13	26%	6%	48	-1.1
✕Jared Serna 2023 · A	21	40→48	42→45	54→50	51	196/289/300	104	251	9	21	24%	9%	71	-0.8	219/276/335	116	269	11	15	22%	6%	72	-0.7	216/271/322	106	262	11	16	21%	6%	65	-1.1
✕Mario Lisson 2006 · A	22	46→49	43→50	57→55	50	221/307/345	123	302	9	19	28%	10%	86	+0.3	220/283/335	115	289	10	21	26%	7%	75	-0.5	222/292/345	123	288	15	8	27%	7%	80	-0.1
✕Masyn Winn 2023 · AA	21	48→53	44→50	61→55	46	231/292/359	128	308	9	28	27%	8%	84	+0.1	243/298/376	133	291	13	16	20%	7%	90	+0.6	248/309/365	117	296	11	11	19%	7%	93	+0.8
●Matt McLain 2022 · A	22	46→56	44→55	53→55	48	221/299/337	116	298	11	20	28%	9%	82	+0.0	239/322/420	181	326	19	22	30%	9%	109	+2.0	234/319/405	170	315	19	23	30%	10%	104	+1.4
✕Jett Williams 2024 · AA	20	44→48	45→50	60→55	54	209/324/338	129	296	11	25	30%	12%	93	+0.8	216/310/345	129	299	10	23	28%	11%	88	+0.4	214/300/348	134	288	11	26	27%	10%	82	+0.0
✕José Caballero 2021 · A	24	46→45	41→45	52→70	47	220/294/323	104	279	8	25	24%	8%	77	-0.3	220/322/335	115	284	11	35	24%	11%	91	+0.7	226/318/339	113	301	10	63	26%	9%	91	+0.4
✕Cooper Bowman 2022 · A	22	44	45	56→60	41	214/289/346	132	303	12	19	32%	7%	81	-0.1	204/281/321	117	287	12	34	31%	8%	72	-0.7	210/283/330	120	279	11	40	27%	8%	72	-0.5
✕Juan Mora 2022 · A	22	44	42→45	55	47	215/295/325	110	284	9	14	26%	8%	78	-0.3	222/280/325	103	297	9	9	27%	6%	72	-0.7	218/275/319	102	286	9	8	26%	5%	67	-0.5
✕Lolo Sanchez 2022 · A	23	44→45	45	53→55	48	220/295/343	124	262	13	23	21%	8%	82	+0.0	208/283/298	90	252	9	13	20%	8%	68	-1.0	193/271/258	65	233	6	9	19%	8%	51	-0.9
✕Adrian Pinto 2024 · A	21	48	38→45	56→65	53	222/315/303	82	283	4	25	21%	10%	81	-0.1	237/306/380	143	292	14	11	23%	8%	95	+0.9	237/306/381	144	288	10	4	20%	8%	90	+0.2
✕Tim Tawa 2022 · A	23	45	47→55	58→50	45	221/289/359	138	303	14	18	30%	8%	83	+0.1	213/278/339	126	273	14	11	26%	8%	74	-0.5	223/286/391	168	267	21	13	25%	7%	88	+0.3
✕Tommy Troy 2024 · A	22	47→55	46→45	57→50	44	228/298/359	132	326	13	18	32%	8%	86	+0.3	223/292/336	113	299	10	17	27%	8%	79	-0.2	233/306/347	114	304	10	17	25%	8%	84	+0.1
✕Johan Rojas 2022 · A	21	45→55	44→45	55→65	43	223/276/341	119	284	11	22	25%	6%	74	-0.6	237/281/346	109	298	8	37	22%	5%	76	-0.4	260/302/359	100	326	7	41	21%	5%	85	+0.2
✕Luke Adams 2024 · A	20	42→39	44→50	53→55	51	201/318/323	122	288	11	21	31%	11%	88	+0.4	207/347/351	144	268	15	19	27%	12%	106	+1.8	200/355/358	159	246	17	19	24%	12%	108	+1.1
✕Dylan Moore 2017 · A	24	43→49	44→55	54→65	47	213/291/334	121	270	11	23	24%	8%	78	-0.3	209/274/329	120	265	11	18	25%	7%	71	-0.8	207/326/378	171	283	16	41	30%	12%	103	+0.8

Nico Perez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps