Brandon Vasquez

OF DSL Giants Orange

Age 20 L/L 5'10" / 165 lbs ROK HR -15%H -3% Svc 0.0 · Ctrl thru 2038

Overview

ROKPROSPECTMiLBFA 2039

OGV OFP35OGV rank#1917ETA2029MLB%0%

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	17	ROKDSL Giants Or…	103	.187/.282/.253	0	6	2	—	.128/.204/.170
2025	18	ROKDSL Giants Or…	96	.241/.344/.301	0	4	18	—	.151/.240/.186
2026	19	ROKDSL Giants Or…	184	.303/.414/.395	1	7	51	—	.199/.287/.248
2027PROJMLE	20	MLBSF	294	.232/.299/.316	2	5	76	0.0
2028PROJ34% MLB	21	MLBSF	49	.232/.301/.324	0	1	80	-0.0
2029PROJ48% MLB	22	MLBSF	116	.235/.304/.334	1	2	84	-0.0

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 Rk

K%98

Whiff%94

Z-Con%91

wOBA66

wRC+64

Chase%59

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsTirso Ornelas (age 21) · Dillon Thomas (age 21) · Buddy Kennedy (age 19)

2027 FULL-SEASON PROJECTIONpark-neutral Marcel · 95 proj PA

wRC+†76

AVG/OBP/SLG.230 / .297 / .314

PA95

HR1

K%23

BB%8

ISO84

MLB%0%

Value2027 · WAR

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

Tools · ContractCON 74 / POW 34

Toolsscout grade

CONTACT74

scouting grade only

POWER34

scouting grade only

EYE61

scouting grade only

SPEED54

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	Ext	beyond projection horizon · no WAR estimate
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 Giants Orange	—	103	91	17	4	1	0	11	17	1	6	2	187	282	253	534	66	230	17	11	253	2	—	—	—	—	—	—
2025	18	ROK	DSL Giants Orange	—	96	83	20	5	0	0	12	14	1	4	2	241	344	301	645	60	290	15	12	303	18	—	—	—	—	—	—
2026	19	ROK	DSL Giants Orange	—	184	152	46	9	1	1	28	15	1	7	2	303	414	395	809	92	328	8	15	365	51	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2024	17	ROK MLE	DSL Giants Orange	—	103	94	12	2	1	0	8	21	1	6	2	128	204	170	374	43	159	20	8	171	2	—	—	—	—	—	—
2025	18	ROK MLE	DSL Giants Orange	—	96	86	13	3	0	0	9	18	1	4	2	151	240	186	426	35	184	19	9	195	18	—	—	—	—	—	—
2026	19	ROK MLE	DSL Giants Orange	—	184	161	32	6	1	0	19	18	1	7	2	199	287	248	536	50	212	10	10	244	51	—	—	—	—	—	—
2024	17	ROK MLE	DSL Giants Orange	—	103	94	12	2	1	0	8	21	1	6	2	128	204	170	374	43	164	20	8	171	2	—	—	—	—	—	—
2024	17	ROK RAW	DSL Giants Orange	—	103	91	17	4	1	0	11	17	1	6	2	187	282	253	534	66	230	17	11	253	2	—	—	—	—	—	—
2025	18	ROK MLE	DSL Giants Orange	—	96	86	13	3	0	0	9	18	1	4	2	151	240	186	426	35	191	19	9	195	18	—	—	—	—	—	—
2025	18	ROK RAW	DSL Giants Orange	—	96	83	20	5	0	0	12	14	1	4	2	241	344	301	645	60	290	15	12	303	18	—	—	—	—	—	—
2026	19	ROK MLE	DSL Giants Orange	—	184	161	32	6	1	0	19	18	1	7	2	199	287	248	536	50	222	10	10	244	51	—	—	—	—	—	—
2026	19	ROK RAW	DSL Giants Orange	—	184	152	46	9	1	1	28	15	1	7	2	303	414	395	809	92	328	8	15	365	51	—	—	—	—	—	—
2024	17	ROK MLE	DSL Giants Orange	—	103	93	12	2	1	0	8	21	1	6	2	129	204	172	376	43	159	20	8	171	2	—	—	—	—	—	—
2025	18	ROK MLE	DSL Giants Orange	—	96	86	13	3	0	0	9	18	1	4	2	151	240	186	426	35	184	19	9	195	18	—	—	—	—	—	—
2026	19	ROK MLE	DSL Giants Orange	—	184	162	32	6	1	0	19	18	1	7	2	198	287	247	534	49	212	10	10	244	51	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	17	ROK MLE	DSL Giants Orange	—	103	93	12	2	1	0	8	21	1	6	2	129	204	172	376	43	159	20	8	171	2	—	—	—	—	—	—
2025	18	ROK MLE	DSL Giants Orange	—	96	86	13	3	0	0	9	18	1	4	2	151	240	186	426	35	184	19	9	195	18	—	—	—	—	—	—
2026	19	ROK MLE	DSL Giants Orange	—	184	162	32	6	1	0	19	18	1	7	2	198	287	247	534	49	212	10	10	244	51	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	20	MLB MLE	SF	0%	294	267	61	11	2	2	23	67	2	5	1	232	299	316	616	84	299	23	8	280	76	-9	+1	+0	-2	+6	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	21	MLB MLE	SF	34%	144	131	31	5	1	2	11	32	1	3	1	236	304	330	634	94	299	22	8	287	80	-3	+0	+0	-1	+3	-0.1
2029	22	MLB MLE	SF	48%	239	216	51	9	2	3	19	53	2	5	1	239	307	341	648	102	300	22	8	293	84	-5	+1	+0	-1	+5	-0.0
2030	23	MLB MLE	SF	54%	334	301	72	13	2	5	27	74	3	7	2	241	309	349	659	109	301	22	8	297	87	-5	+1	+0	-2	+7	0.1
2031	24	MLB MLE	SF	55%	399	360	88	16	3	7	32	89	4	8	2	242	311	356	667	114	301	22	8	300	89	-5	+1	+0	-2	+9	0.2
2032	25	MLB MLE	SF	56%	437	394	96	17	3	8	36	97	4	9	3	243	312	361	673	118	301	22	8	302	91	-5	+1	+0	-3	+9	0.3
2033	26	MLB MLE	SF	56%	455	411	100	18	3	8	37	101	4	9	3	243	312	361	673	118	300	22	8	303	91	-5	+1	+0	-3	+10	0.3
2034	27	MLB MLE	SF	55%	462	417	101	18	3	8	38	103	4	9	3	242	311	359	670	117	300	22	8	301	90	-6	+1	+0	-3	+10	0.2
2035	28	MLB MLE	SF	55%	461	416	100	18	3	8	38	104	4	9	3	240	309	354	663	114	299	23	8	299	88	-6	+1	-1	-3	+10	0.1
2036	29	MLB MLE	SF	53%	453	409	97	17	3	7	37	103	4	8	3	238	307	348	654	110	298	23	8	295	86	-8	+0	-1	-3	+10	-0.2
2028	21	MLB CTX	SF	34%	49	45	10	2	0	0	4	11	0	1	0	232	301	324	625	91	296	22	8	283	80	-1	+0	+0	-0	+1	-0.0
2029	22	MLB CTX	SF	48%	116	105	24	4	1	1	9	26	1	2	1	235	304	334	638	99	296	22	8	288	84	-2	+0	+0	-1	+3	-0.0
2030	23	MLB CTX	SF	54%	181	162	39	7	1	3	15	40	2	4	1	237	306	342	648	105	297	22	8	292	87	-3	+0	+0	-1	+4	0.0
2031	24	MLB CTX	SF	55%	221	199	48	9	2	3	18	49	2	5	1	238	308	348	656	110	297	22	8	296	89	-3	+1	+0	-1	+5	0.1
2032	25	MLB CTX	SF	56%	245	221	53	10	2	4	20	54	2	5	1	239	309	352	661	113	297	22	8	298	91	-3	+1	+0	-1	+5	0.2
2033	26	MLB CTX	SF	56%	256	231	55	10	2	4	21	57	2	5	2	239	309	353	661	114	296	22	8	298	91	-3	+0	+0	-2	+6	0.1
2034	27	MLB CTX	SF	55%	256	231	55	10	2	4	21	57	2	5	2	238	308	350	658	112	296	22	8	296	90	-3	+0	+0	-2	+6	0.1
2035	28	MLB CTX	SF	55%	253	228	55	10	2	4	21	57	2	5	2	236	306	346	652	110	295	23	8	294	88	-4	+0	-0	-2	+5	0.0
2036	29	MLB CTX	SF	53%	242	218	52	9	2	4	20	55	2	4	1	234	303	340	643	106	294	23	8	290	86	-4	+0	-1	-1	+5	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1819	1640	391	71	14	27	149	406	15	36	11	238	308	348	656	110	300	22	8	294	82	-25	+3	-1	-11	+39	0.5
/ 162G	—	A+C		—	650	586	140	25	5	10	53	145	5	13	4	239	307	350	657	111	300	22	8	294	82	-9	+1	-0	-4	+14	0.2
Career	—	MLE		—	3862	3483	814	146	26	57	318	835	34	86	27	234	304	340	644	106	290	22	8	290	82	-50	+5	-2	-21	+75	0.8
/ 162G	—	MLE		—	650	586	137	25	4	10	54	141	6	14	5	234	305	341	647	108	290	22	8	290	82	-9	+1	-0	-4	+14	0.1

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 DSLDSL Giants Orange · 184 PAwOBA .359 → .244 (−115)K% 8.2% → 9.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.15%	÷1.000	×1.220	—	—	9.95%
BB% (unintentional) /PA	15.22%	÷1.000	×0.700	—	×0.985	10.49%
HBP% /PA	0.54%	—	×0.700	—	×0.985	0.37%
Singles /BIP	25.55%	÷1.000	×0.680	×0.995	×0.985	17.03%
Doubles /BIP	6.57%	÷1.000	×0.600	×0.995	×0.985	3.86%
Triples /BIP	0.73%	÷1.000	×0.600	×0.995	×0.985	0.43%
Home runs /BIP	0.73%	÷1.000	×0.470	—	×0.985	0.34%

Factors used: level-wide DSL 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 18.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.995.

Result: wOBA .359 → .244; ISO .092 → .055; BABIP .328 → .212. 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 Giants Orange · 96 PAwOBA .296 → .195 (−101)K% 14.6% → 18.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.58%	÷0.972	×1.220	—	—	18.30%
BB% (unintentional) /PA	12.50%	÷0.974	×0.700	—	×0.995	8.94%
HBP% /PA	1.04%	—	×0.700	—	×0.995	0.73%
Singles /BIP	21.74%	÷0.995	×0.680	×0.950	×0.995	14.04%
Doubles /BIP	7.25%	÷0.933	×0.600	×0.950	×0.995	4.41%
Triples /BIP	0.00%	÷0.900	×0.600	×0.950	×0.995	0.00%
Home runs /BIP	0.00%	÷0.963	×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 93, 1B 99, 2B 87, 3B 80, K 94, BB 95 — 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 ×0.950.

Result: wOBA .296 → .195; ISO .060 → .037; BABIP .290 → .184. 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 Giants Orange · 103 PAwOBA .247 → .171 (−76)K% 16.5% → 20.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.50%	÷1.001	×1.220	—	—	20.12%
BB% (unintentional) /PA	10.68%	÷0.982	×0.700	—	×1.008	7.67%
HBP% /PA	0.97%	—	×0.700	—	×1.008	0.68%
Singles /BIP	16.22%	÷0.972	×0.680	×1.017	×1.008	11.62%
Doubles /BIP	5.41%	÷0.982	×0.600	×1.017	×1.008	3.38%
Triples /BIP	1.35%	÷0.971	×0.600	×1.017	×1.008	0.86%
Home runs /BIP	0.00%	÷0.914	×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 83, 1B 94, 2B 96, 3B 94, K 100, BB 96 — 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 ×1.017.

Result: wOBA .247 → .171; ISO .066 → .041; BABIP .230 → .159. 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
#1Willie Harrislast yr '11 career totals — 10 seasons, 2,743 PA	4.1	2,743	39	106	241	331	351	-11	-2	5.3	6.2
/162	664	9	26	-2.7	-0.5	1.3	pk7: 7
#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
#3Darren Bragg'94-'04 * career totals — 10 seasons, 2,835 PA	4.3	2,835	46	56	243*	324*	368*	-18	+2	2.5	3.8
/162	664	11	13	-4.1	+0.4	0.6	pk7: 5
#4Nate Schierholtzlast yr '14 career totals — 8 seasons, 2,275 PA	3.4	2,275	52	30	253	302	405	-24	-6	2.0	2.8
/162	664	15	9	-7.1	-1.8	0.6	pk7: 4
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	2.9	1,913	31	38	242	307	354	-11	+0	1.8	1.8
/162	664	11	13	-4.0	+0.0	0.6	pk7: 2
#5Carl Warwick'61-'66 * career totals — 5 seasons, 1,616 PA	2.4	1,616	31	13	245*	309*	381*	-9	-1	1.4	1.4
/162	664	13	5	-3.6	-0.6	0.6	pk7: 1
#6James Mouton'94-'01 * career totals — 8 seasons, 1,795 PA	2.7	1,795	18	109	235*	314*	329*	-11	-0	0.7	1.0
/162	664	7	40	-4.2	-0.1	0.3	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
Brandon Vasquez (OGILVIE)	20	69→74	29→34	49→54	61	230/297/314	83	299	1	2	23%	8%	76	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕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
✕Dillon Thomas 2014 · A	21	45→55	37→45	43→50	36	211/250/281	70	316	4	9	34%	5%	49	-2.4	223/262/316	93	350	6	13	36%	4%	61	-1.5	216/290/343	127	314	13	14	33%	6%	78	-0.2
✕Buddy Kennedy 2018 · A	19	43→53	36→45	54→50	39	197/252/278	81	302	2	9	34%	6%	49	-2.4	215/268/309	94	283	7	5	25%	6%	63	-1.4	237/323/352	115	299	9	6	22%	10%	93	+0.7
✕Yermín Mercedes 2013 · A	20	45→53	35→50	45	48	208/264/268	60	241	1	6	14%	6%	52	-2.2	203/261/288	85	243	7	6	19%	6%	56	-1.9	242/292/392	150	282	20	3	21%	6%	92	+0.5
●Jonathan Aranda 2018 · A	20	44→54	35→55	50→45	43	205/258/265	60	265	2	12	22%	5%	49	-2.4	217/273/297	80	282	4	6	23%	7%	62	-1.4	272/349/433	161	346	18	4	25%	8%	120	+2.3
✕Carlos Tocci 2015 · A	19	45→55	35→40	42→45	39	212/253/273	61	275	2	7	23%	4%	49	-2.4	250/290/323	73	317	3	8	21%	4%	74	-0.6	266/308/338	72	332	3	8	20%	4%	81	-0.1
✕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
●Domonic Brown 2008 · A	20	42→52	37→55	51→55	40	199/254/270	71	296	5	14	33%	6%	49	-2.4	256/312/386	130	320	12	16	23%	7%	97	+1.1	261/326/422	161	323	17	20	23%	8%	111	+1.5
✕Enmanuel Valdez 2019 · A	20	38→47	41→55	49→45	46	187/255/292	105	242	8	7	26%	8%	55	-2.0	196/249/318	122	264	13	7	30%	6%	59	-1.7	223/287/404	181	270	24	8	27%	8%	92	+0.5
✕Aldrem Corredor 2015 · A	19	43→53	34→45	43→40	54	199/278/253	54	246	1	6	18%	10%	55	-2.0	209/276/278	69	273	3	4	23%	8%	59	-1.6	231/276/321	90	307	6	1	26%	5%	66	-0.7
✕Marty Herum 2014 · A	22	45→54	36→45	50→45	43	210/268/278	68	301	3	7	30%	7%	56	-1.9	237/265/322	85	296	6	4	21%	3%	64	-1.3	259/291/356	98	314	8	4	20%	4%	80	-0.1
✕Jeremy Moore 2007 · A	20	41→51	38→55	44→55	37	193/252/272	80	315	6	11	38%	7%	49	-2.4	200/241/341	141	305	15	15	38%	5%	61	-1.5	246/283/398	152	347	14	19	32%	4%	87	+0.3
●Donovan Solano 2008 · A	20	49→59	33→45	44→45	44	224/263/264	39	261	1	5	15%	4%	49	-2.4	240/281/295	55	294	2	4	18%	5%	64	-1.3	280/350/391	111	346	9	1	20%	7%	114	+1.5
✕Christian Bethancourt 2011 · A	19	44→53	38→50	50	39	215/245/298	83	271	5	9	23%	4%	51	-2.3	234/256/321	87	287	8	10	21%	3%	60	-1.6	233/268/383	149	287	19	5	25%	4%	80	-0.1
✕Alexander Simon 2013 · A	20	42→52	37→40	49→50	46	197/258/274	77	259	3	11	24%	7%	51	-2.2	218/256/291	73	312	3	9	30%	5%	53	-2.1	223/250/294	71	320	4	7	31%	3%	49	-1.4
✕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
✕Felix Munoz 2014 · A	22	45→52	37→40	47→30	43	216/261/291	75	273	4	5	22%	6%	56	-1.9	233/278/336	103	281	9	2	20%	6%	73	-0.6	232/277/333	101	277	9	1	19%	6%	70	-0.7
●Francisco Peguero 2009 · A	21	44→54	37→50	57→55	39	212/250/284	72	277	4	19	25%	4%	50	-2.3	269/292/368	99	342	6	20	22%	3%	84	+0.2	276/316/422	146	324	18	7	20%	4%	105	+1.3
✕Wilson Garcia 2013 · A	19	47→53	37→55	50→40	48	216/256/289	74	234	4	4	10%	5%	53	-2.1	211/245/284	73	239	3	5	13%	4%	47	-2.5	240/269/398	158	268	21	0	20%	3%	82	+0.0
✕Tyler Massey 2009 · A	20	43→48	38→45	47→50	34	207/246/289	82	312	6	11	35%	4%	50	-2.3	188/222/256	68	278	3	7	32%	4%	32	-3.6	221/262/327	106	279	11	16	24%	5%	62	-1.2

Brandon Vasquez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps