Leonel Vivas

SS ACL Cubs

Age 20 R/R 6'0" / 168 lbs ROK HR -8% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#2169ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL Cubs Red	49	.188/.469/.281	0	9	64	—	.139/.367/.222
2025	18	ROKDSL Cubs Red	125	.217/.419/.402	4	10	57	—	.143/.323/.245
2026	19	ROKCHC	151	.231/.400/.333	2	8	38	—	.142/.273/.197
2027PROJMLE	20	MLBCHC	261	.183/.275/.272	3	6	58	-0.1
2028PROJ34% MLB	21	MLBCHC	45	.190/.282/.289	1	1	63	-0.0
2029PROJ48% MLB	22	MLBCHC	108	.195/.286/.300	2	3	67	-0.1

Next 3 projected WAR -0.2Projected 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

BB%63

Speed58

wRC+50

wOBA42

ISO42

Chase%27

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 1% · didn't stick 98%

CompsHans Montero (age 20) · Robert Gonzalez (age 20) · Frankeny Fernandez (age 20)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 78 proj PA

wRC+†58

AVG/OBP/SLG.182 / .273 / .269

PA78

HR1

K%31

BB%9

ISO89

MLB%0%

Value2027 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit-$0M ctrl surplus

Tools · ContractCON 26 / POW 42

Toolsscout grade

CONTACT26

scouting grade only

POWER42

scouting grade only

EYE63

scouting grade only

SPEED59

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	+0.1	$0.3M	+$0.0M (cut)
2034	Pre-Arb	$1.0M	+0.1	$0.2M	+$0.0M (cut)
2035	Pre-Arb	$1.0M	—	—	—
2036	Arb-1	$0.2M	—	—	—
2037	Arb-2	$0.4M	—	—	—
2038	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.3M	+$0.0M

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	—	49	32	6	1	1	0	11	12	6	9	0	188	469	281	751	94	300	24	22	380	64	—	—	—	—	—	—
2025	18	ROK	DSL Cubs Red	—	125	92	20	3	1	4	19	25	13	10	3	217	419	402	822	185	250	20	15	380	57	—	—	—	—	—	—
2026	19	ROK	ACL Cubs	—	151	117	27	4	1	2	26	48	7	8	4	231	400	333	733	103	368	32	17	346	38	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Cubs Red	—	49	36	5	1	1	0	7	15	6	9	0	139	367	222	590	83	199	31	14	263	64	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Red	—	125	98	14	2	1	2	13	32	13	10	3	143	323	245	567	102	163	26	10	252	57	—	—	—	—	—	—
2026	19	ROK MLE	ACL Cubs	—	151	127	18	2	1	1	16	69	7	8	4	142	273	197	470	55	279	46	11	225	38	—	—	—	—	—	—
2024	17	ROK MLE	DSL Cubs Red	—	49	36	5	1	1	0	7	15	6	9	0	139	367	222	590	83	238	31	14	263	64	—	—	—	—	—	—
2024	17	ROK RAW	DSL Cubs Red	—	49	32	6	1	1	0	11	12	6	9	0	188	469	281	751	94	300	24	22	380	64	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Red	—	125	98	14	2	1	2	13	32	13	10	3	143	323	245	567	102	185	26	10	252	57	—	—	—	—	—	—
2025	18	ROK RAW	DSL Cubs Red	—	125	92	20	3	1	4	19	25	13	10	3	217	419	402	822	185	250	20	15	380	57	—	—	—	—	—	—
2026	19	ROK MLE	ACL Cubs	—	151	127	18	2	1	1	16	69	7	8	4	142	273	197	470	55	293	46	11	225	38	—	—	—	—	—	—
2026	19	ROK RAW	ACL Cubs	—	151	117	27	4	1	2	26	48	7	8	4	231	400	333	733	103	368	32	17	346	38	—	—	—	—	—	—
2024	17	ROK MLE	DSL Cubs Red	—	49	36	5	1	1	0	7	15	6	9	0	139	367	222	590	83	199	31	14	263	64	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Red	—	125	98	14	2	1	2	13	32	13	10	3	143	323	245	567	102	163	26	10	252	57	—	—	—	—	—	—
2026	19	ROK MLE	ACL Cubs	—	151	127	18	2	1	1	16	69	7	8	4	142	273	197	470	55	279	46	11	225	38	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Cubs Red	—	49	36	5	1	1	0	7	15	6	9	0	139	367	222	590	83	199	31	14	263	64	—	—	—	—	—	—
2025	18	ROK MLE	DSL Cubs Red	—	125	98	14	2	1	2	13	32	13	10	3	143	323	245	567	102	163	26	10	252	57	—	—	—	—	—	—
2026	19	ROK MLE	ACL Cubs	—	151	127	18	2	1	1	16	69	7	8	4	142	273	197	470	55	279	46	11	225	38	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	CHC	0%	261	230	42	7	2	3	23	82	6	6	1	183	275	272	547	89	264	31	9	255	58	-13	+1	+0	+3	+6	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	CHC	34%	130	115	22	4	1	2	11	40	3	3	1	189	280	286	566	97	267	31	8	262	63	-6	+0	+0	+1	+3	-0.1
2029	22	MLB MLE	CHC	48%	222	195	37	6	1	4	20	67	5	5	1	193	284	297	581	104	269	30	9	268	67	-9	+1	+0	+2	+5	-0.1
2030	23	MLB MLE	CHC	54%	316	278	55	9	2	6	28	94	7	8	2	197	287	306	593	109	271	30	9	272	71	-11	+1	+0	+3	+7	-0.0
2031	24	MLB MLE	CHC	55%	387	341	68	11	3	7	34	113	9	9	2	201	290	314	604	113	273	29	9	276	73	-12	+1	+0	+4	+8	0.1
2032	25	MLB MLE	CHC	56%	427	377	76	13	3	8	38	123	9	10	2	203	292	319	611	116	275	29	9	279	75	-13	+1	+0	+5	+9	0.2
2033	26	MLB MLE	CHC	56%	448	395	81	14	3	9	40	129	10	11	2	203	292	319	611	116	274	29	9	279	75	-13	+1	+0	+5	+10	0.3
2034	27	MLB MLE	CHC	60%	455	402	82	14	3	9	40	132	10	11	2	202	291	316	607	114	274	29	9	278	74	-14	+1	+0	+5	+10	0.2
2035	28	MLB MLE	CHC	62%	455	402	81	14	3	9	40	133	10	10	2	200	289	312	601	112	273	29	9	275	72	-15	+1	-1	+5	+10	0.0
2036	29	MLB MLE	CHC	63%	447	396	78	13	3	8	39	132	9	9	2	198	286	306	592	108	272	30	9	272	70	-16	+1	-1	+5	+10	-0.2
2037	30	MLB MLE	CHC	63%	437	387	76	13	3	7	38	131	9	8	2	195	283	299	581	103	270	30	9	267	67	-17	+1	-2	+5	+9	-0.4
2028	21	MLB CTX	CHC	34%	45	40	7	1	0	1	4	14	1	1	0	190	282	289	571	98	271	31	9	264	63	-2	+0	+0	+0	+1	-0.0
2029	22	MLB CTX	CHC	48%	108	95	19	3	1	2	9	33	3	3	1	195	286	300	586	105	273	31	8	270	67	-4	+0	+0	+1	+2	-0.1
2030	23	MLB CTX	CHC	54%	171	150	30	5	1	3	15	51	4	4	1	199	289	309	598	110	275	30	9	274	71	-6	+0	+0	+2	+4	-0.0
2031	24	MLB CTX	CHC	55%	215	189	39	7	2	4	19	63	5	5	1	202	292	316	608	114	277	29	9	278	73	-7	+1	+0	+2	+5	0.1
2032	25	MLB CTX	CHC	56%	239	211	43	7	2	5	21	69	5	6	1	205	293	322	615	117	278	29	9	281	75	-7	+1	+0	+3	+5	0.1
2033	26	MLB CTX	CHC	56%	252	222	46	8	2	5	22	73	6	6	1	205	293	322	615	117	278	29	9	281	75	-8	+1	+0	+3	+5	0.1
2034	27	MLB CTX	CHC	60%	271	239	48	8	2	5	24	79	6	6	1	204	292	319	611	115	277	29	9	279	74	-8	+1	+0	+3	+6	0.1
2035	28	MLB CTX	CHC	62%	281	248	50	9	2	5	25	82	6	6	1	202	290	315	605	113	276	29	9	277	72	-9	+1	-0	+3	+6	0.0
2036	29	MLB CTX	CHC	63%	280	247	49	8	2	5	25	83	6	6	1	200	288	309	596	109	275	30	9	273	70	-10	+1	-1	+3	+6	-0.1
2037	30	MLB CTX	CHC	63%	277	245	49	8	2	5	24	83	6	5	1	197	284	301	585	104	273	30	9	269	67	-11	+1	-1	+3	+6	-0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2139	1886	380	64	16	40	188	630	48	48	9	201	290	316	606	115	278	29	9	276	70	-72	+6	-3	+23	+46	0.1
/ 162G	—	A+C		—	650	573	115	19	5	12	57	191	15	15	3	201	290	314	604	113	276	29	9	276	70	-22	+2	-1	+7	+14	0.0
Career	—	MLE		—	4127	3618	706	118	29	73	371	1234	109	113	25	195	289	304	594	109	272	30	9	271	70	-130	+10	-4	+41	+82	-0.1
/ 162G	—	MLE		—	650	570	112	19	5	11	58	194	17	18	4	196	289	305	595	109	274	30	9	271	70	-22	+2	-1	+7	+14	-0.0

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 · 151 PAwOBA .341 → .225 (−116)K% 31.8% → 45.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.79%	÷1.000	×1.440	—	—	45.77%
BB% (unintentional) /PA	17.22%	÷1.000	×0.620	—	×1.008	10.76%
HBP% /PA	4.64%	—	×0.720	—	×1.008	3.36%
Singles /BIP	28.99%	÷1.000	×0.820	×0.950	×1.008	22.75%
Doubles /BIP	5.80%	÷1.000	×0.720	×0.950	×1.008	3.99%
Triples /BIP	1.45%	÷1.000	×0.720	×0.950	×1.008	1.00%
Home runs /BIP	2.90%	÷1.000	×0.780	—	×1.008	2.28%

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 19 vs a level average of 19.5 → +0.8% on BB/HBP/hit rates (0.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .341 → .225; ISO .103 → .066; BABIP .368 → .279. 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 Red · 125 PAwOBA .374 → .252 (−122)K% 20.0% → 25.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷0.966	×1.220	—	—	25.26%
BB% (unintentional) /PA	15.20%	÷1.036	×0.700	—	×1.008	10.35%
HBP% /PA	10.40%	—	×0.700	—	×1.008	7.33%
Singles /BIP	17.91%	÷0.981	×0.680	×0.999	×1.008	12.50%
Doubles /BIP	4.48%	÷1.012	×0.600	×0.999	×1.008	2.67%
Triples /BIP	1.49%	÷1.150	×0.600	×0.999	×1.008	0.78%
Home runs /BIP	5.97%	÷0.876	×0.470	—	×1.008	3.23%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 75, 1B 96, 2B 102, 3B 130, K 93, BB 107 — 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 ×0.999.

Result: wOBA .374 → .252; ISO .185 → .108; BABIP .250 → .163. 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 · 49 PAwOBA .373 → .263 (−110)K% 24.5% → 31.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.49%	÷0.964	×1.220	—	—	30.98%
BB% (unintentional) /PA	22.45%	÷1.047	×0.700	—	×1.022	15.35%
HBP% /PA	12.24%	—	×0.700	—	×1.022	8.76%
Singles /BIP	20.00%	÷1.018	×0.680	—	×1.022	13.65%
Doubles /BIP	5.00%	÷0.960	×0.600	—	×1.022	3.20%
Triples /BIP	5.00%	÷1.000	×0.600	—	×1.022	3.07%
Home runs /BIP	0.00%	÷1.025	×0.470	—	×1.022	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 17 vs a level average of 18.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average).

Result: wOBA .373 → .263; ISO .094 → .064; BABIP .300 → .199. 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
#1Adam Rosaleslast yr '17 career totals — 9 seasons, 1,756 PA	2.6	1,756	47	16	227	293	367	+6	+8	3.0	3.5
/162	664	18	6	+2.4	+3.0	1.1	pk7: 4
#2Dal Maxvill'62-'75 * career totals — 12 seasons, 3,898 PA	5.9	3,898	6	7	216*	295*	283*	+38	+40	1.2	3.2
/162	664	1	1	+6.4	+6.8	0.2	pk7: 5
#3Tim Bogar'93-'01 * career totals — 8 seasons, 1,710 PA	2.6	1,710	24	13	217*	284*	324*	+11	+37	2.1	2.9
/162	664	9	5	+4.2	+14.4	0.8	pk7: 4
#4Ryan 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
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 7 projected seasons	3.3	2,216	40	50	200	285	310	+24	+21	1.4	1.4
/162	664	12	15	+7.1	+6.3	0.4	pk7: 1
#5David Howard'91-'99 * career totals — 8 seasons, 1,795 PA	2.7	1,795	11	23	220*	280*	301*	+10	+23	-1.6	-0.8
/162	664	4	9	+3.7	+8.5	-0.6	pk7: -0
#6Alexi Amaristalast yr '17 career totals — 7 seasons, 1,901 PA	2.9	1,901	21	39	231	275	323	+14	-6	-1.1	-1.1
/162	664	7	14	+4.9	-2.1	-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
Leonel Vivas (OGILVIE)	20	21→26	37→42	54→59	63	182/273/269	88	264	1	2	31%	9%	58	-0.2	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Hans Montero 2024 · A	20	36→37	37→45	55	49	172/276/241	69	264	5	18	33%	11%	53	-2.1	182/260/285	103	297	10	17	39%	8%	56	-1.9	173/254/287	113	278	12	22	39%	9%	52	-1.5
✕Robert Gonzalez 2021 · A	20	40	39→40	54→60	52	186/296/275	89	275	5	8	30%	12%	68	-1.0	190/293/264	74	252	5	17	24%	10%	64	-1.3	151/292/187	36	182	3	30	16%	14%	48	-0.8
✕Frankeny Fernandez 2017 · A	20	36	38→40	53→60	42	174/249/256	81	276	5	19	36%	8%	45	-2.7	192/257/267	75	279	5	10	31%	7%	50	-2.3	170/235/212	43	235	3	6	27%	7%	28	-1.2
✕Pablo Aliendo 2021 · A	20	38	36→50	50→45	44	181/261/246	65	268	3	13	31%	8%	47	-2.5	202/271/300	98	303	9	5	34%	6%	63	-1.3	206/275/350	144	296	17	5	34%	7%	73	-0.3
✕Chris Suero 2024 · A	20	41→38	41→45	50→55	50	196/295/291	95	281	8	8	31%	10%	71	-0.8	193/290/309	116	280	12	20	33%	10%	74	-0.6	181/287/307	126	264	14	27	34%	10%	70	-0.7
✕Ismael Alcantara 2019 · A	20	36→30	38→45	50	43	177/250/254	77	257	5	13	32%	7%	45	-2.7	207/272/309	102	322	8	15	36%	7%	65	-1.2	191/253/307	116	283	12	16	35%	6%	55	-0.9
✕Anyelo Encarnación 2024 · A	20	41→36	38→40	54→50	49	188/284/272	84	293	5	14	34%	11%	62	-1.4	183/267/272	89	313	8	14	40%	9%	56	-1.9	171/261/262	92	293	9	17	41%	10%	49	-1.4
✕Christian Cerda 2023 · A	20	40	39→45	50→40	53	189/279/278	88	244	6	9	23%	10%	61	-1.5	198/297/302	104	263	10	4	26%	12%	74	-0.5	187/288/292	105	240	12	2	26%	12%	67	-0.7
✕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
✕Gilbert Gomez 2012 · A	20	40→39	40	52→50	42	194/257/287	92	271	7	14	30%	6%	55	-2.0	204/277/282	78	309	4	8	32%	9%	61	-1.5	194/278/266	72	301	3	7	33%	10%	55	-1.3
✕Nelson Medina 2022 · A	21	38	38→45	53→50	51	181/272/260	79	252	4	15	28%	10%	55	-2.0	185/255/278	93	317	6	13	40%	8%	52	-2.2	140/198/215	76	278	6	16	49%	6%	14	-1.7
✕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
✕Max George 2016 · A	20	40→39	40→45	54→55	43	189/275/278	90	295	7	14	35%	8%	61	-1.5	189/271/295	106	262	9	15	30%	8%	63	-1.4	166/254/289	123	223	13	23	31%	8%	53	-1.3
✕Johan Mieses 2015 · A	20	39→33	39→55	59→50	45	191/248/281	90	242	5	22	23%	6%	49	-2.4	195/243/347	152	271	18	8	34%	5%	63	-1.3	192/268/358	166	237	23	7	30%	7%	73	-0.4
✕Jesus Hernandez 2024 · A	20	42	37→40	51→55	53	199/281/271	72	257	5	13	23%	10%	60	-1.6	199/278/287	88	284	6	18	29%	9%	63	-1.4	199/280/289	90	282	6	24	29%	9%	62	-0.7
✕Rafael Morel 2022 · A	20	36	39→40	51→50	40	181/244/269	88	257	7	13	31%	6%	46	-2.6	196/262/273	77	311	7	10	36%	7%	53	-2.1	190/263/263	73	291	8	10	35%	7%	49	-1.2
✕Troy Stokes Jr. 2016 · A	20	42→40	38→50	54→55	44	200/273/281	81	280	6	20	29%	7%	59	-1.6	210/281/330	120	279	11	18	27%	7%	74	-0.6	204/280/342	138	273	13	19	29%	8%	74	-0.5
✕Javier Herrera 2024 · A	19	38	39→40	51→55	45	184/262/268	84	272	6	10	32%	9%	53	-2.1	204/298/290	86	279	5	15	26%	11%	71	-0.8	210/307/297	87	289	5	18	26%	11%	74	-0.2
✕Neyfy Castillo 2021 · A	20	39→33	37→45	54→55	39	187/245/260	73	279	3	11	32%	6%	43	-2.8	186/260/317	131	336	16	16	46%	8%	63	-1.3	173/250/304	131	303	16	19	45%	8%	53	-1.4
✕Ameilis Carvajal 2009 · A	20	38	37→40	50	53	178/278/250	72	254	4	12	29%	11%	55	-1.9	187/261/255	68	287	3	9	33%	8%	49	-2.4	130/199/162	32	218	0	8	37%	8%	5	-1.2

Leonel Vivas

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps