Fernando Cruz

SS ACL Cubs

Age 20 R/R 5'9" / 155 lbs ROK HR -8% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#1153ETA2030MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL Cubs Red	92	.215/.326/.329	2	11	9	—	.122/.217/.183
2025	18	ROKCHC	89	.165/.250/.316	3	5	-25	—	.073/.136/.159
2026	19	A/ROKCHC	280	.237/.327/.490	14	10	35	—	.148/.212/.300
2027PROJMLE	20	MLBCHC	390	.195/.255/.315	8	8	60	0.0
2028PROJ25% MLB	21	MLBCHC	56	.202/.264/.331	1	1	66	0.0
2029PROJ38% MLB	22	MLBCHC	127	.207/.269/.342	3	3	70	0.1

Next 3 projected WAR 0.1Projected 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 A

Z-Con%39

ISO29

Speed17

wRC+8

wOBA6

BB%5

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 96%

CompsSean Coyle (age 21) · Bryan Ramos (age 20) · Brayan Buelvas (age 20)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 167 proj PA

wRC+†60

AVG/OBP/SLG.194 / .253 / .312

PA167

HR4

K%34

BB%6

ISO120

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit+$13M ctrl surplus

Contract

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	+0.4	$1M	+$0.5M
2034	Pre-Arb	$1.0M	+0.4	$0.9M	+$0.5M
2035	Pre-Arb	$1.0M	+0.3	$0.7M	+$0.2M
2036	Arb-1	$2M	+0.2	$0.4M	+$0.0M (cut)
2037	Arb-2	$1M	+0.1	$0.2M	+$0.0M (cut)
2038	Ext	beyond projection horizon · no WAR estimate
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)
2024	17	ROK	DSL Cubs Red	—	92	79	17	3	0	2	10	25	3	11	1	215	326	329	655	114	288	27	11	305	9	—	—	—	—	—	—
2025	18	ROK	ACL Cubs	—	89	79	13	3	0	3	7	42	2	5	1	165	250	316	566	152	286	47	8	256	-25	—	—	—	—	—	—
2026	19	A	Myrtle Beach Pelicans	—	58	53	10	2	0	1	3	25	1	1	1	189	246	283	529	94	321	43	5	238	-4	—	—	—	—	—	—
2026	19	ROK	ACL Cubs	—	222	192	48	8	5	13	26	79	3	9	4	250	348	547	895	297	347	36	12	386	45	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Cubs Red	—	92	82	10	2	0	1	7	32	3	11	1	122	217	183	400	61	183	35	8	182	9	—	—	—	—	—	—
2025	18	ROK MLE	ACL Cubs	—	89	82	6	1	0	2	4	62	2	5	1	73	136	159	295	85	222	70	4	131	-25	—	—	—	—	—	—
2026	19	A MLE	Myrtle Beach Pelicans	—	58	54	7	1	0	1	2	34	1	1	1	130	175	204	379	74	293	59	3	163	-4	—	—	—	—	—	—
2026	19	ROK MLE	ACL Cubs	—	222	203	31	5	3	8	15	114	3	9	4	153	222	325	547	172	266	51	7	235	45	—	—	—	—	—	—
2024	17	ROK MLE	DSL Cubs Red	—	92	82	10	2	0	1	7	32	3	11	1	122	217	183	400	61	184	35	8	182	9	—	—	—	—	—	—
2024	17	ROK RAW	DSL Cubs Red	—	92	79	17	3	0	2	10	25	3	11	1	215	326	329	655	114	288	27	11	305	9	—	—	—	—	—	—
2025	18	ROK MLE	ACL Cubs	—	89	82	6	1	0	2	4	62	2	5	1	73	136	159	295	85	211	70	4	131	-25	—	—	—	—	—	—
2025	18	ROK RAW	ACL Cubs	—	89	79	13	3	0	3	7	42	2	5	1	165	250	316	566	152	286	47	8	256	-25	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	280	257	38	6	3	9	17	148	4	10	5	148	212	300	512	152	284	53	6	220	35	—	—	—	—	—	—
2026	19	ROK RAW	2 teams	—	280	245	58	10	5	14	29	104	4	10	5	237	327	490	817	253	341	37	10	355	35	—	—	—	—	—	—
2024	17	ROK MLE	DSL Cubs Red	—	92	82	10	2	0	1	7	32	3	11	1	122	217	183	400	61	183	35	8	182	9	—	—	—	—	—	—
2025	18	ROK MLE	ACL Cubs	—	89	83	6	1	0	2	4	62	2	5	1	72	136	157	293	84	222	70	4	131	-25	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	280	257	38	6	3	9	17	148	4	10	5	148	212	300	512	152	272	53	6	220	35	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Cubs Red	—	92	82	10	2	0	1	7	32	3	11	1	122	217	183	400	61	183	35	8	182	9	—	—	—	—	—	—
2025	18	ROK MLE	ACL Cubs	—	89	83	6	1	0	2	4	62	2	5	1	72	136	157	293	84	222	70	4	131	-25	—	—	—	—	—	—
2026	19	ROK MLE	2 teams	—	280	257	38	6	3	9	17	148	4	10	5	148	212	300	512	152	272	53	6	220	35	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	CHC	0%	390	359	70	12	3	8	24	131	4	8	2	195	255	315	570	120	277	34	6	256	60	-19	+1	+3	+4	+8	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	CHC	25%	226	206	41	7	2	5	15	74	3	5	1	201	262	329	591	128	279	33	7	265	66	-9	+1	+2	+2	+5	0.0
2029	22	MLB MLE	CHC	38%	333	304	63	11	2	9	22	106	4	8	2	205	268	340	608	135	281	32	7	272	70	-12	+1	+3	+4	+7	0.2
2030	23	MLB MLE	CHC	45%	407	371	78	14	3	11	28	128	5	10	3	209	272	349	621	140	282	31	7	277	74	-13	+1	+3	+4	+9	0.5
2031	24	MLB MLE	CHC	48%	453	414	89	16	3	13	31	140	5	11	3	212	276	355	631	143	284	31	7	282	77	-13	+1	+4	+5	+10	0.7
2032	25	MLB MLE	CHC	50%	479	437	94	17	3	14	34	145	5	12	3	214	279	359	638	145	284	30	7	285	79	-12	+1	+4	+5	+10	0.9
2033	26	MLB MLE	CHC	50%	492	448	96	17	3	14	35	149	6	12	3	214	279	360	639	146	284	30	7	285	79	-12	+1	+4	+5	+11	0.9
2034	27	MLB MLE	CHC	50%	495	451	96	17	3	14	35	151	6	12	4	213	278	357	635	144	283	31	7	283	78	-13	+1	+4	+5	+11	0.8
2035	28	MLB MLE	CHC	50%	490	448	94	17	3	13	34	151	5	11	3	211	276	353	629	142	282	31	7	281	76	-14	+1	+3	+5	+11	0.6
2036	29	MLB MLE	CHC	49%	481	439	92	16	3	13	34	149	5	10	3	209	273	347	620	138	281	31	7	277	74	-15	+1	+2	+5	+10	0.4
2037	30	MLB MLE	CHC	52%	469	429	89	16	3	12	32	147	5	9	4	206	270	340	610	134	280	31	7	273	71	-16	+0	+2	+5	+10	0.1
2028	21	MLB CTX	CHC	25%	56	51	10	2	0	1	4	18	1	1	0	202	264	331	595	129	283	32	7	267	66	-2	+0	+0	+1	+1	0.0
2029	22	MLB CTX	CHC	38%	127	117	24	4	1	3	8	41	1	3	1	207	269	342	611	135	284	32	6	273	70	-4	+0	+1	+1	+3	0.1
2030	23	MLB CTX	CHC	45%	185	168	35	6	1	5	13	58	2	4	1	210	274	350	624	140	286	31	7	279	74	-6	+0	+1	+2	+4	0.2
2031	24	MLB CTX	CHC	48%	218	198	43	8	2	6	15	67	3	5	2	213	277	357	634	143	287	31	7	283	77	-6	+0	+2	+2	+5	0.3
2032	25	MLB CTX	CHC	50%	238	216	46	8	2	6	17	72	3	6	2	216	280	361	641	145	288	30	7	286	79	-6	+0	+2	+3	+5	0.4
2033	26	MLB CTX	CHC	50%	248	226	49	9	2	7	17	75	3	6	2	215	280	361	641	146	287	30	7	286	79	-6	+0	+2	+3	+5	0.4
2034	27	MLB CTX	CHC	50%	248	226	49	9	2	7	17	76	3	6	2	214	279	359	638	144	287	31	7	284	78	-6	+0	+2	+3	+5	0.4
2035	28	MLB CTX	CHC	50%	244	222	48	9	2	6	17	75	3	5	2	213	277	354	631	142	286	31	7	282	76	-7	+0	+2	+3	+5	0.3
2036	29	MLB CTX	CHC	49%	233	213	45	8	2	6	16	72	2	5	2	211	274	348	623	138	285	31	7	278	74	-7	+0	+1	+2	+5	0.2
2037	30	MLB CTX	CHC	52%	245	224	46	8	2	6	17	77	2	5	2	208	271	341	612	133	283	31	7	274	71	-8	+0	+1	+3	+5	0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2042	1861	395	71	16	53	141	631	23	46	16	212	276	353	629	141	288	31	7	281	69	-60	+3	+14	+22	+44	2.3
/ 162G	—	A+C		—	650	592	126	23	5	17	45	201	7	15	5	213	276	355	631	142	289	31	7	281	69	-19	+1	+4	+7	+14	0.7
Career	—	MLE		—	4953	4521	916	162	32	134	338	1638	60	129	37	203	267	342	609	139	282	33	7	271	69	-137	+9	+31	+48	+97	5.0
/ 162G	—	MLE		—	650	593	120	21	4	18	44	215	8	17	5	202	266	342	609	140	281	33	7	271	69	-20	+1	+4	+7	+14	0.7

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 · 222 PAwOBA .376 → .235 (−141)K% 35.6% → 51.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	35.59%	÷1.000	×1.440	—	—	51.24%
BB% (unintentional) /PA	11.26%	÷1.000	×0.620	—	×0.995	6.95%
HBP% /PA	1.35%	—	×0.720	—	×0.995	0.97%
Singles /BIP	19.47%	÷1.000	×0.820	×1.017	×0.995	16.15%
Doubles /BIP	7.08%	÷1.000	×0.720	×1.017	×0.995	5.16%
Triples /BIP	4.42%	÷1.000	×0.720	×1.017	×0.995	3.22%
Home runs /BIP	11.50%	÷1.000	×0.780	—	×0.995	8.93%

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 ×1.017.

Result: wOBA .376 → .235; ISO .297 → .181; BABIP .347 → .266. 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 · 58 PAwOBA .236 → .163 (−73)K% 43.1% → 58.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	43.10%	÷1.000	×1.360	—	—	58.62%
BB% (unintentional) /PA	5.17%	÷1.000	×0.690	—	×1.030	3.68%
HBP% /PA	1.72%	—	×0.780	—	×1.030	1.39%
Singles /BIP	25.00%	÷1.000	×0.920	—	×1.030	23.69%
Doubles /BIP	7.14%	÷1.000	×0.830	—	×1.030	6.11%
Triples /BIP	0.00%	÷1.000	×0.910	—	×1.030	0.00%
Home runs /BIP	3.57%	÷1.000	×0.800	—	×1.030	2.94%

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 .236 → .163; ISO .094 → .059; BABIP .321 → .293. 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 ROKACL Cubs · 89 PAwOBA .252 → .131 (−121)K% 47.2% → 70.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	47.19%	÷0.969	×1.440	—	—	70.12%
BB% (unintentional) /PA	7.87%	÷0.983	×0.620	—	×1.008	5.00%
HBP% /PA	2.25%	—	×0.720	—	×1.008	1.63%
Singles /BIP	18.92%	÷1.004	×0.820	—	×1.008	15.57%
Doubles /BIP	8.11%	÷0.973	×0.720	—	×1.008	6.04%
Triples /BIP	0.00%	÷1.089	×0.720	—	×1.008	0.00%
Home runs /BIP	8.11%	÷0.868	×0.780	—	×1.008	7.34%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 74, 1B 101, 2B 95, 3B 118, K 94, BB 97 — applied at half strength. Age: age 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average).

Result: wOBA .252 → .131; ISO .152 → .073; BABIP .286 → .222. 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 · 92 PAwOBA .297 → .182 (−116)K% 27.2% → 34.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.17%	÷0.964	×1.220	—	—	34.38%
BB% (unintentional) /PA	10.87%	÷1.047	×0.700	—	×1.008	7.32%
HBP% /PA	3.26%	—	×0.700	—	×1.008	2.30%
Singles /BIP	22.22%	÷1.018	×0.680	×0.972	×1.008	14.54%
Doubles /BIP	5.56%	÷0.960	×0.600	×0.972	×1.008	3.40%
Triples /BIP	0.00%	÷1.000	×0.600	×0.972	×1.008	0.00%
Home runs /BIP	3.70%	÷1.025	×0.470	—	×1.008	1.71%

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 ×0.972.

Result: wOBA .297 → .182; ISO .114 → .056; BABIP .288 → .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
#1Danny Espinosalast yr '17 career totals — 8 seasons, 3,267 PA	4.9	3,267	98	64	221	297	378	+16	+36	11.0	11.4
/162	664	20	13	+3.2	+7.3	2.2	pk7: 12
#2Ronny 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	3.3	2,208	59	50	210	271	350	+24	+24	2.1	2.1
/162	664	18	15	+7.1	+7.2	0.6	pk7: 2
#3Ryan 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
#4Pete Mackanin'73-'81 * career totals — 6 seasons, 1,686 PA	2.5	1,686	30	27	222*	261*	370*	+6	+23	0.6	1.6
/162	664	12	11	+2.4	+8.9	0.2	pk7: 3
#5Benji Gil'93-'03 * career totals — 7 seasons, 1,767 PA	2.7	1,767	32	24	227*	272*	349*	+10	+30	0.6	1.0
/162	664	12	9	+3.8	+11.3	0.2	pk7: 1
#6Andres Thomas'85-'90 * career totals — 5 seasons, 2,185 PA	3.3	2,185	42	22	234*	256*	361*	+23	+24	0.5	0.5
/162	664	13	7	+7.1	+7.3	0.2	pk7: 0

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
Fernando Cruz (OGILVIE)	20	—	—	—	—	194/253/312	119	277	4	3	34%	6%	60	-0.4	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕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
✕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
✕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
✕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
✕Narciso Crook 2015 · A	20	42→43	42→50	55→50	35	200/246/303	103	314	9	14	38%	5%	53	-2.1	192/230/295	103	293	9	10	36%	4%	45	-2.7	211/273/363	152	309	16	14	35%	6%	75	-0.3
✕Sammy Hernandez 2024 · A	20	37	43→40	51→50	40	188/254/301	113	262	11	5	31%	6%	57	-1.8	203/291/298	95	270	8	9	26%	9%	71	-0.8	201/300/298	97	262	9	13	24%	10%	72	-0.4
✕Jorge Alcantara 2012 · A	20	44	40→45	52→50	42	209/274/307	98	306	7	12	32%	8%	65	-1.2	190/261/285	95	288	7	14	34%	8%	55	-1.9	143/221/238	95	216	5	25	34%	8%	30	-1.0
✕Jase Bowen 2022 · A	21	37→42	42→50	54→55	35	186/247/286	100	284	10	12	37%	5%	51	-2.2	197/249/316	119	284	14	16	34%	5%	59	-1.7	209/260/343	134	298	14	23	33%	6%	66	-0.7
✕Danny De Andrade 2024 · A	20	41	42→45	51→50	45	201/277/305	104	269	9	11	28%	8%	67	-1.1	201/270/315	114	278	10	11	30%	7%	66	-1.1	190/254/309	120	266	11	10	31%	6%	56	-1.1
✕Jeter Downs 2019 · A	21	42→41	43→50	52→55	44	208/273/317	109	269	11	18	26%	7%	68	-1.0	210/276/360	150	277	17	18	29%	7%	79	-0.2	176/270/315	139	246	15	26	33%	9%	66	-0.6
✕Jhostynxon Garcia 2024 · A	21	38→44	41→50	52→50	43	182/258/286	104	279	7	9	35%	8%	55	-1.9	220/276/370	150	298	17	10	31%	6%	81	-0.1	226/279/379	153	297	20	9	30%	5%	81	-0.0
✕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
✕Cayden Wallace 2023 · A	21	46→49	42→50	57→50	43	224/279/341	116	300	8	15	27%	6%	74	-0.5	220/277/337	117	289	10	12	26%	6%	73	-0.6	232/281/372	140	285	16	15	24%	5%	80	-0.1
✕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
✕Johan Mieses 2016 · A	21	40→33	45→55	52→50	40	204/250/330	126	265	12	14	28%	5%	61	-1.5	189/238/351	162	266	20	4	37%	5%	63	-1.4	192/268/358	166	237	23	7	30%	7%	73	-0.4
✕Junior Perez 2021 · A	20	37→40	44→50	50→55	43	187/261/304	117	279	12	11	36%	8%	61	-1.5	182/257/291	109	330	10	20	44%	9%	56	-1.9	172/245/318	146	265	16	25	39%	8%	56	-1.4
✕Rodolfo Castro 2019 · A	20	39→42	44→55	47→50	37	198/240/315	117	272	11	5	31%	5%	54	-2.0	203/245/352	149	282	17	6	33%	5%	65	-1.2	211/274/367	156	276	20	7	30%	7%	79	-0.2
✕Yu Chang 2017 · A	21	41→47	45→50	49→45	38	207/258/338	131	290	12	8	32%	6%	66	-1.1	209/270/355	146	291	16	8	32%	7%	75	-0.5	217/278/367	150	284	17	4	29%	7%	81	-0.0
✕Carson Williams 2023 · A	20	43	48→55	53→55	37	199/273/343	145	344	15	16	43%	8%	74	-0.6	200/270/360	160	316	19	19	40%	8%	77	-0.3	191/263/352	162	289	20	23	39%	8%	69	-0.8

Fernando Cruz

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps