Vidal Bruján

2B Syracuse Mets

Age 29 S/R 5'9" / 180 lbs AAA H -5% Svc 3.337 · Ctrl thru 2029

Overview

AAAArb-1FA 2030

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	26	INTLEstrellas Ori…	152	.230/.349/.286	1	10	87	—
2024	26	MLBMIA	278	.222/.303/.319	2	5	80	0.0
2025	27	INTLEstrellas Ori…	107	.213/.340/.225	0	5	73	—
2025	27	MLBATL	95	.253/.309/.310	0	2	77	-0.0
2026	28	AAA/INTL2 orgs	289	.270/.382/.427	6	18	96	—	.254/.333/.373
2027PROJ10% MLB	29	MLBNYM	16	.211/.289/.308	0	1	75	0.0
2028PROJ27% MLB	30	MLBNYM	54	.208/.285/.300	1	2	72	-0.1

Last 3 seasons WAR 0.0 · Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.337First FA2030

2027Arb-1$0.2M2028Arb-2$0.4M2029Ext$0.6M

Skills · percentileStatcast 2024-2026

Bat Spd23

xwOBA13

Speed13

Barrel%10

Avg EV10

CompsZach Sorensen (age 29) · Wilton Guerrero (age 29) · Andrew Romine (age 30)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 7575vR 75

AVG/OBP/SLG.211 / .289 / .308

PA16

HR0

K%19

BB%6

BABIP256

ISO67

MLB%10%

Value2027 · WAR

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

Tools · Splits · ContractCON 45 / POW 30

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT45

xAVG

100.218

POWER30

Barrel%

101.1

Avg EV

1085.8

Bat Spd

2368.5

EYE50

scouting grade only

SPEED50

Sprint

1325.7

Platoon Splits2024-2025 · 356 PA

vs LHP

vs RHP

Edge

285

—

wRC+

—

wOBA

274

277

—

ISO

098

085

◀L

BABIP

267

286

▶R

22.5%

18.2%

▶▶R

BB%

9.9%

7.0%

◀◀L

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

Status Arb-1

MLB Debut 2021

Service 3.337 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$0.2M	—	—	—
2028	Arb-2	$0.4M	—	—	—
2029	Ext	beyond projection horizon · no WAR estimate
Totals		$0.0M		$-0.4M	+$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)
2015	17	ROK	DSL Rays	—	272	226	68	9	4	2	38	16	5	22	12	301	413	403	815	102	316	6	14	369	59	—	—	—	—	—	—
2016	18	ROK	GCL Rays	—	223	202	57	12	5	1	14	15	5	8	5	282	342	406	748	124	301	7	6	333	61	—	—	—	—	—	—
2018	20	A+	Charlotte Stone Crabs	—	114	98	34	7	2	4	15	15	0	12	4	347	434	582	1.015	235	380	13	13	439	153	—	—	—	—	—	—
2018	20	A	Bowling Green Hot Rods	—	434	377	118	18	5	5	48	53	5	43	15	313	398	427	825	114	351	12	11	369	101	—	—	—	—	—	—
2019	21	AA	Montgomery Biscuits	—	233	207	55	9	4	3	20	35	3	24	8	266	339	391	730	126	304	15	9	325	76	—	—	—	—	—	—
2019	21	A+	Charlotte Stone Crabs	—	196	176	51	8	3	1	17	26	2	24	5	290	359	386	745	97	333	13	9	336	76	—	—	—	—	—	—
2019	21	INTL	Salt River Rafters	—	100	82	21	3	4	2	15	17	2	4	5	256	384	463	847	207	297	17	15	373	138	—	—	—	—	—	—
2020	22	INTL	Toros del Este	—	75	63	16	2	1	0	11	10	1	10	3	254	373	317	691	63	302	13	15	325	106	—	—	—	—	—	—
2021	23	MLB	Tampa Bay Rays	—	26	26	2	0	0	0	0	8	0	1	0	77	77	77	154		111	31	0	70	-68	-5	+0	-1	+2	+1	-0.3
2021	23	AAA	Durham Bulls	—	441	389	102	31	1	12	49	68	1	44	8	262	346	440	786	177	290	15	11	349	81	—	—	—	—	—	—
2021	23	INTL	Toros del Este	—	69	63	13	2	1	0	6	11	0	8	3	206	275	270	545	63	250	16	9	252	57	—	—	—	—	—	—
2022	24	MLB	Tampa Bay Rays	—	162	147	24	5	0	3	12	37	1	5	5	163	231	259	490	95	193	23	7	224	38	-12	-1	+1	+2	+4	-0.7
2022	24	AAA	Durham Bulls	—	290	257	75	14	3	6	27	48	5	26	13	292	370	440	810	148	338	17	9	362	95	—	—	—	—	—	—
2022	24	INTL	Toros del Este	—	60	54	13	4	0	0	4	10	0	2	1	241	293	315	608	74	295	17	7	268	67	—	—	—	—	—	—
2023	25	MLB	Tampa Bay Rays	—	84	76	13	2	0	0	5	21	2	3	2	171	241	197	438	26	236	25	6	208	26	-7	-0	-3	+2	+2	-0.7
2023	25	AAA	Durham Bulls	—	276	239	65	11	4	10	31	49	4	19	14	272	365	477	842	205	302	18	11	370	88	—	—	—	—	—	—
2023	25	INTL	Estrellas Orientales	—	186	145	38	7	1	0	36	27	1	23	4	262	412	324	736	62	314	15	19	342	118	—	—	—	—	—	—
2024	26	MLB	Miami Marlins	—	278	248	55	14	2	2	25	54	4	5	6	222	303	319	622	97	276	19	9	285	80	-7	-1	-3	+5	+6	0.0
2024	26	INTL	Estrellas Orientales	—	152	126	29	4	0	1	20	19	3	10	4	230	349	286	635	56	259	12	13	297	87	—	—	—	—	—	—
2025	27	MLB	Atlanta Braves	—	95	87	22	5	0	0	6	21	1	2	1	253	309	310	619	57	328	22	6	281	77	-3	+0	-0	+1	+2	-0.0
2025	27	INTL	Estrellas Orientales	—	107	89	19	1	0	0	15	21	2	5	3	213	340	225	564	11	275	20	14	276	73	—	—	—	—	—	—
2026	28	AAA	Syracuse Mets	—	258	216	60	12	2	5	35	41	4	16	5	278	388	421	810	144	320	16	14	362	93	—	—	—	—	—	—
2026	28	INTL	Leones del Escogido	—	31	25	5	2	1	1	5	7	0	2	0	200	333	480	813	280	235	23	16	344	119	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	645	584	116	26	2	5	48	141	8	16	14	199	269	276	544	77	252	22	7	250	56	-34	-2	-6	+11	+14	-1.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2015	17	ROK MLE	DSL Rays	—	272	237	49	6	3	1	27	20	5	22	12	207	301	270	571	63	216	7	10	256	59	—	—	—	—	—	—
2016	18	ROK MLE	GCL Rays	—	223	209	48	9	4	1	8	22	5	8	5	230	275	325	600	96	249	10	4	258	61	—	—	—	—	—	—
2018	20	A+ MLE	Charlotte Stone Crabs	—	114	101	33	7	2	4	12	22	0	12	4	327	398	554	953	228	372	19	11	395	153	—	—	—	—	—	—
2018	20	A MLE	Bowling Green Hot Rods	—	434	391	110	15	5	4	34	72	5	43	15	281	347	376	722	95	330	17	8	318	101	—	—	—	—	—	—
2019	21	AA MLE	Montgomery Biscuits	—	233	212	51	8	3	3	15	43	3	24	8	241	300	349	649	108	278	18	6	280	76	—	—	—	—	—	—
2019	21	A+ MLE	Charlotte Stone Crabs	—	196	181	45	7	3	1	12	36	2	24	5	249	303	337	640	88	298	18	6	281	76	—	—	—	—	—	—
2021	23	MLB MLE	Tampa Bay Rays	—	26	26	2	0	0	0	0	8	0	1	0	77	77	77	154		111	31	0	68	-68	-5	+0	-1	+2	+1	-0.3
2021	23	AAA MLE	Durham Bulls	—	441	403	93	25	1	8	35	79	1	44	8	231	294	357	651	127	268	18	8	288	81	—	—	—	—	—	—
2022	24	MLB MLE	Tampa Bay Rays	—	162	147	24	5	0	3	12	37	1	5	5	163	231	259	490	95	193	23	7	224	38	-12	-1	+1	+2	+4	-0.7
2022	24	AAA MLE	Durham Bulls	—	290	265	70	11	3	4	19	58	5	26	13	264	325	374	699	109	321	20	7	308	95	—	—	—	—	—	—
2023	25	MLB MLE	Tampa Bay Rays	—	84	76	13	2	0	0	5	21	2	3	2	171	241	197	438	26	236	25	6	206	26	-7	-0	-3	+2	+2	-0.7
2023	25	AAA MLE	Durham Bulls	—	276	248	57	9	4	6	22	58	4	19	14	230	303	371	674	141	274	21	8	299	88	—	—	—	—	—	—
2024	26	MLB MLE	Miami Marlins	—	278	251	57	15	2	2	22	54	4	5	6	227	300	327	626	100	276	19	8	287	80	-7	-1	-3	+5	+6	0.0
2025	27	MLB MLE	Atlanta Braves	—	95	87	22	5	0	0	6	21	1	2	1	253	309	310	619	57	328	22	6	281	77	-3	+0	-0	+1	+2	-0.0
2026	28	AAA MLE	Syracuse Mets	—	258	228	58	11	2	4	23	49	4	16	5	254	333	373	706	118	295	19	9	306	93	—	—	—	—	—	—
2015	17	ROK MLE	DSL Rays	—	272	237	49	6	3	1	27	20	5	22	12	207	301	270	571	63	221	7	10	256	59	—	—	—	—	—	—
2015	17	ROK RAW	DSL Rays	—	272	226	68	9	4	2	38	16	5	22	12	301	413	403	815	102	316	6	14	369	59	—	—	—	—	—	—
2016	18	ROK MLE	GCL Rays	—	223	209	48	9	4	1	8	22	5	8	5	230	275	325	600	96	253	10	4	258	61	—	—	—	—	—	—
2016	18	ROK RAW	GCL Rays	—	223	202	57	12	5	1	14	15	5	8	5	282	342	406	748	124	301	7	6	333	61	—	—	—	—	—	—
2018	20	A MLE	2 teams	—	548	492	143	22	7	8	46	94	5	55	19	291	357	413	770	122	344	17	8	334	112	—	—	—	—	—	—
2018	20	A RAW	2 teams	—	548	475	152	25	7	9	63	68	5	55	19	320	405	459	864	139	357	12	11	384	112	—	—	—	—	—	—
2019	21	AA MLE	3 teams	—	529	484	118	19	7	5	33	97	7	52	18	244	302	343	645	99	293	18	6	280	76	—	—	—	—	—	—
2019	21	AA RAW	3 teams	—	529	465	127	20	11	6	52	78	7	52	18	273	355	402	757	129	314	15	10	338	76	—	—	—	—	—	—
2020	22	INTL MLE	Toros del Este	—	75	63	16	2	1	0	11	10	1	10	3	254	373	317	691	63	302	13	15	—	—	—	—	—	—	—	—
2020	22	INTL RAW	Toros del Este	—	75	63	16	2	1	0	11	10	1	10	3	254	373	317	691	63	302	13	15	325	106	—	—	—	—	—	—
2021	23	AAA MLE	3 teams	—	536	493	111	29	1	10	40	100	1	53	11	225	285	349	634	124	263	19	7	276	73	—	—	—	—	—	—
2021	23	AAA RAW	3 teams	—	536	478	117	33	2	12	55	87	1	53	11	245	324	397	721	153	276	16	10	323	73	—	—	—	—	—	—
2022	24	AAA MLE	3 teams	—	512	466	107	19	3	8	35	107	6	33	19	230	292	335	627	105	280	21	7	278	74	—	—	—	—	—	—
2022	24	AAA RAW	3 teams	—	512	458	112	23	3	9	43	95	6	33	19	245	318	367	684	122	289	19	8	307	74	—	—	—	—	—	—
2023	25	AAA MLE	3 teams	—	546	491	107	17	6	10	41	120	7	45	20	218	288	338	626	120	265	22	8	277	74	—	—	—	—	—	—
2023	25	AAA RAW	3 teams	—	546	460	116	20	5	10	72	97	7	45	20	252	362	383	744	130	296	18	13	336	74	—	—	—	—	—	—
2024	26	MLB MLE	2 teams	—	430	385	88	24	3	3	34	84	7	15	10	229	303	330	633	101	283	20	8	287	80	-10	-1	-3	+5	+9	0.0
2024	26	MLB RAW	2 teams	—	430	374	84	18	2	3	45	73	7	15	10	225	319	307	627	83	270	17	10	289	80	-10	-1	-3	+5	+9	0.0
2025	27	INTL MLE	2 teams	—	202	184	47	11	0	0	13	45	3	7	4	255	315	315	630	60	333	22	6	281	77	—	—	—	—	—	—
2025	27	INTL RAW	2 teams	—	202	176	41	6	0	0	21	42	3	7	4	233	325	267	592	34	301	21	10	278	77	—	—	—	—	—	—
2026	28	AAA MLE	2 teams	—	289	255	63	12	2	4	26	55	4	18	5	247	326	357	683	110	298	19	9	306	93	—	—	—	—	—	—
2026	28	AAA RAW	2 teams	—	289	241	65	14	3	6	40	48	4	18	5	270	382	427	810	158	312	17	14	360	93	—	—	—	—	—	—
2015	17	ROK MLE	DSL Rays	—	272	238	49	6	3	1	27	20	5	22	12	206	301	269	570	63	216	7	10	256	59	—	—	—	—	—	—
2016	18	ROK MLE	GCL Rays	—	223	208	48	9	4	1	8	22	5	8	5	231	275	327	602	96	249	10	4	258	61	—	—	—	—	—	—
2018	20	A MLE	2 teams	—	548	492	143	22	7	8	46	94	5	55	19	291	357	413	770	122	339	17	8	334	112	—	—	—	—	—	—
2019	21	AA MLE	3 teams	—	529	484	118	19	7	5	33	97	7	52	18	244	302	343	645	99	287	18	6	280	76	—	—	—	—	—	—
2021	23	AAA MLE	3 teams	—	536	490	111	29	1	10	40	100	1	53	11	227	285	351	636	124	259	19	7	276	73	—	—	—	—	—	—
2022	24	AAA MLE	3 teams	—	512	466	107	19	3	8	35	107	6	33	19	230	292	335	627	105	275	21	7	278	74	—	—	—	—	—	—
2023	25	AAA MLE	3 teams	—	546	493	107	17	6	10	41	120	7	45	20	217	288	337	624	120	265	22	8	277	74	—	—	—	—	—	—
2024	26	MLB MLE	2 teams	—	430	386	88	24	3	3	34	84	7	15	10	228	303	329	632	101	276	20	8	287	80	—	—	—	—	—	—
2025	27	INTL MLE	2 teams	—	202	184	47	11	0	0	13	45	3	7	4	255	315	315	630	60	328	22	6	281	77	—	—	—	—	—	—
2026	28	AAA MLE	2 teams	—	289	257	63	12	2	4	26	55	4	18	5	245	326	354	680	109	295	19	9	306	93	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	26	MLB MLE	2 teams	—	430	386	88	24	3	3	34	84	7	15	10	228	303	329	632	101	276	20	8	287	80	—	—	—	—	—	—
2025	27	INTL MLE	2 teams	—	202	184	47	11	0	0	13	45	3	7	4	255	315	315	630	60	328	22	6	281	77	—	—	—	—	—	—
2026	28	AAA MLE	2 teams	—	289	257	63	12	2	4	26	55	4	18	5	245	326	354	680	109	295	19	9	306	93	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	29	MLB MLE	NYM	10%	258	231	49	10	1	3	22	52	3	9	2	218	295	318	613	100	265	20	9	279	75	-8	+1	-1	+1	+6	-0.1
▸ 2027 — real world (MLB)
2027	29	MLB CTX	NYM	10%	16	15	3	1	0	0	1	3	0	1	0	211	289	308	597	97	256	19	6	273	75	-0	+0	-0	+0	+0	0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	30	MLB MLE	NYM	27%	199	177	38	8	1	2	17	41	3	6	2	215	291	309	600	95	263	21	9	274	72	-7	+0	-3	+1	+4	-0.4
2028	30	MLB CTX	NYM	27%	54	48	10	2	0	1	5	11	1	2	0	208	285	300	585	92	254	20	9	268	72	-2	+0	-1	+0	+1	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	699	632	126	28	2	6	53	152	9	18	14	199	271	278	549	79	252	22	8	252	76	-36	-2	-7	+11	+15	-1.9
/ 162G	—	A+C		—	650	588	118	26	2	6	49	141	8	17	13	201	271	282	554	82	252	22	8	252	76	-33	-2	-6	+10	+14	-1.7
Career	—	MLE		—	4521	4079	966	184	39	54	345	827	56	330	129	237	305	341	646	104	283	18	8	280	76	-46	-1	-9	+12	+22	-2.2
/ 162G	—	MLE		—	650	586	139	26	6	8	50	119	8	47	19	237	306	343	649	106	283	18	8	280	76	-29	-1	-6	+8	+14	-1.4

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 AAASyracuse Mets · 258 PAwOBA .355 → .306 (−49)K% 15.9% → 19.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.89%	÷1.000	×1.200	—	—	19.07%
BB% (unintentional) /PA	13.18%	÷1.000	×0.690	—	×0.992	9.02%
HBP% /PA	1.55%	—	×0.940	—	×0.992	1.45%
Singles /BIP	23.43%	÷1.000	×0.930	×1.033	×0.992	22.32%
Doubles /BIP	6.86%	÷1.000	×0.830	×1.033	×0.992	5.83%
Triples /BIP	1.14%	÷1.000	×0.970	×1.033	×0.992	1.14%
Home runs /BIP	2.86%	÷1.000	×0.700	—	×0.992	1.98%

Factors used: league row International League. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.033.

Result: wOBA .355 → .306; ISO .144 → .118; BABIP .320 → .295. 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).

2023 AAADurham Bulls · 276 PAwOBA .363 → .299 (−64)K% 17.8% → 21.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.75%	÷1.009	×1.200	—	—	21.12%
BB% (unintentional) /PA	11.23%	÷1.011	×0.690	—	×1.033	7.92%
HBP% /PA	1.45%	—	×0.940	—	×1.033	1.41%
Singles /BIP	21.05%	÷1.006	×0.930	×0.987	×1.033	19.84%
Doubles /BIP	5.79%	÷1.020	×0.830	×0.987	×1.033	4.81%
Triples /BIP	2.11%	÷1.003	×0.970	×0.987	×1.033	2.08%
Home runs /BIP	5.26%	÷1.137	×0.700	—	×1.033	3.35%

Factors used: league row International League. Park (home-season share, regressed): HR 127, 1B 101, 2B 104, 3B 101, K 102, BB 102 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.987.

Result: wOBA .363 → .299; ISO .205 → .153; BABIP .302 → .274. 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).

2022 AAADurham Bulls · 290 PAwOBA .353 → .308 (−46)K% 16.6% → 19.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.55%	÷0.999	×1.200	—	—	19.89%
BB% (unintentional) /PA	9.31%	÷1.059	×0.690	—	×1.048	6.36%
HBP% /PA	1.72%	—	×0.940	—	×1.048	1.70%
Singles /BIP	24.88%	÷0.988	×0.930	×1.014	×1.048	24.89%
Doubles /BIP	6.70%	÷1.091	×0.830	×1.014	×1.048	5.41%
Triples /BIP	1.44%	÷1.150	×0.970	×1.014	×1.048	1.29%
Home runs /BIP	2.87%	÷1.034	×0.700	—	×1.048	2.04%

Factors used: league row International League. Park (home-season share, regressed): HR 107, 1B 98, 2B 118, 3B 130, K 100, BB 112 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.014.

Result: wOBA .353 → .308; ISO .148 → .115; BABIP .338 → .321. 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).

2021 AAADurham Bulls · 441 PAwOBA .340 → .288 (−52)K% 15.4% → 18.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.42%	÷1.029	×1.200	—	—	17.99%
BB% (unintentional) /PA	11.11%	÷1.016	×0.690	—	×1.050	7.93%
HBP% /PA	0.23%	—	×0.940	—	×1.050	0.22%
Singles /BIP	18.07%	÷0.945	×0.930	×0.978	×1.050	18.26%
Doubles /BIP	9.66%	÷1.067	×0.830	×0.978	×1.050	7.71%
Triples /BIP	0.31%	÷1.150	×0.920	×0.978	×1.050	0.26%
Home runs /BIP	3.74%	÷1.059	×0.700	—	×1.050	2.59%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 112, 1B 89, 2B 113, 3B 130, K 106, BB 103 — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.978.

Result: wOBA .340 → .288; ISO .177 → .134; BABIP .290 → .268. 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).

2019 AAMontgomery Biscuits · 233 PAwOBA .319 → .280 (−40)K% 15.0% → 18.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.02%	÷0.985	×1.220	—	—	18.61%
BB% (unintentional) /PA	8.58%	÷0.963	×0.680	—	×1.050	6.36%
HBP% /PA	1.29%	—	×0.840	—	×1.050	1.14%
Singles /BIP	22.67%	÷0.978	×0.920	×0.950	×1.050	21.28%
Doubles /BIP	5.23%	÷1.028	×0.910	×0.950	×1.050	4.62%
Triples /BIP	2.33%	÷1.150	×0.880	×0.950	×1.050	1.78%
Home runs /BIP	1.74%	÷0.920	×0.800	—	×1.050	1.59%

Factors used: league row SL. Park (home-season share, regressed): HR 84, 1B 96, 2B 106, 3B 130, K 97, BB 93 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .319 → .280; ISO .126 → .108; BABIP .304 → .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).

2019 A+Charlotte Stone Crabs · 196 PAwOBA .327 → .281 (−47)K% 13.3% → 18.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.27%	÷1.033	×1.420	—	—	18.24%
BB% (unintentional) /PA	8.16%	÷1.018	×0.750	—	×1.027	6.18%
HBP% /PA	1.02%	—	×0.930	—	×1.027	0.97%
Singles /BIP	26.00%	÷1.008	×0.920	×0.950	×1.027	23.14%
Doubles /BIP	5.33%	÷1.011	×0.960	×0.950	×1.027	4.94%
Triples /BIP	2.00%	÷0.900	×0.810	×0.950	×1.027	1.76%
Home runs /BIP	0.67%	÷0.939	×0.880	—	×1.027	0.64%

Factors used: league row FSL. Park (home-season share, regressed): HR 88, 1B 102, 2B 102, 3B 80, K 107, BB 104 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .327 → .281; ISO .097 → .086; BABIP .333 → .298. 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).

2018 ABowling Green Hot Rods · 434 PAwOBA .362 → .318 (−44)K% 12.2% → 16.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.21%	÷1.000	×1.360	—	—	16.61%
BB% (unintentional) /PA	11.06%	÷0.991	×0.690	—	×1.030	7.93%
HBP% /PA	1.15%	—	×0.780	—	×1.030	0.93%
Singles /BIP	27.78%	÷1.004	×0.920	×1.018	×1.030	26.67%
Doubles /BIP	5.56%	÷1.057	×0.830	×1.018	×1.030	4.57%
Triples /BIP	1.54%	÷0.900	×0.910	×1.018	×1.030	1.64%
Home runs /BIP	1.54%	÷1.037	×0.800	—	×1.030	1.23%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 107, 1B 101, 2B 111, 3B 80, K 100, BB 98 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.018.

Result: wOBA .362 → .318; ISO .114 → .099; BABIP .351 → .330. 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).

2018 A+Charlotte Stone Crabs · 114 PAwOBA .427 → .395 (−32)K% 13.2% → 19.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.16%	÷0.983	×1.420	—	—	19.00%
BB% (unintentional) /PA	13.16%	÷1.022	×0.750	—	×1.042	10.06%
HBP% /PA	0.00%	—	×0.930	—	×1.042	0.00%
Singles /BIP	25.30%	÷1.031	×0.920	×1.050	×1.042	24.71%
Doubles /BIP	8.43%	÷1.012	×0.960	×1.050	×1.042	8.76%
Triples /BIP	2.41%	÷1.150	×0.810	×1.050	×1.042	1.86%
Home runs /BIP	4.82%	÷0.857	×0.880	—	×1.042	5.15%

Factors used: league row FSL. Park (home-season share, regressed): HR 71, 1B 106, 2B 102, 3B 130, K 97, BB 104 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .427 → .395; ISO .235 → .231; BABIP .380 → .372. 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
#1Ryan 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
#2Abraham Torolast yr '25 career totals — 6 seasons, 1,561 PA	2.4	1,561	39	16	220	282	351	-1	-8	-0.5	-0.5
/162	664	17	7	-0.2	-3.2	-0.2	pk7: -0
#3Hector Torres'68-'77 * career totals — 9 seasons, 1,889 PA	2.8	1,889	18	7	215*	262*	312*	+16	+3	-2.1	-0.9
/162	664	6	2	+5.7	+1.2	-0.7	pk7: 0
#4Alexi 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
#5Vic Harris'72-'80 * career totals — 8 seasons, 1,805 PA	2.7	1,805	13	36	215*	286*	325*	+4	-7	-1.9	-1.1
/162	664	5	13	+1.5	-2.7	-0.7	pk7: -0
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 4 projected seasons	1.0	689	6	17	206	276	289	+2	-4	-1.3	-1.3
/162	664	6	16	+2.4	-4.3	-1.3	pk7: -1
#6Jim Mason'71-'79 * career totals — 8 seasons, 1,756 PA	2.6	1,756	12	2	204*	262*	306*	+18	-14	-4.1	-2.9
/162	664	5	1	+6.7	-5.3	-1.6	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
Vidal Bruján (OGILVIE)	29	45	30	50	50	216/292/315	99	265	2	6	20%	8%	75	-0.1	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Zach Sorensen 2006 · MLB	29	50	38→30	52→60	48	239/297/319	80	302	6	25	22%	8%	76	-0.4	230/294/312	82	296	7	15	23%	8%	74	-0.6	222/283/279	57	290	4	10	23%	7%	59	-0.7
✕Wilton Guerrero 2004 · MLB	29	50	40→30	54→50	44	239/279/325	86	283	7	18	18%	5%	70	-0.8	233/277/352	119	263	11	12	16%	5%	76	-0.4	241/275/361	120	263	9	6	12%	4%	74	-0.2
✕Andrew Romine 2016 · MLB	30	50→55	38→40	51→55	45	241/293/315	74	302	6	21	22%	6%	73	-0.6	234/292/329	95	292	8	16	21%	6%	77	-0.3	228/287/314	86	288	6	13	21%	6%	72	-0.3
✕Wilmer Difo 2021 · MLB	29	47→56	42→45	50→55	48	226/287/327	102	281	9	14	22%	8%	74	-0.5	229/284/330	101	283	10	11	22%	7%	74	-0.6	216/273/305	88	267	8	15	21%	7%	63	-0.7
✕Richy Pedroza 2019 · AAA	28	49→54	37→30	46→50	52	229/298/300	71	275	4	15	18%	8%	72	-0.7	242/319/331	89	292	5	19	17%	10%	87	+0.4	249/333/325	77	299	2	23	16%	11%	88	+0.4
✕Michael Martinez 2012 · MLB	29	46→52	41→45	50	45	222/266/323	101	257	9	14	18%	5%	65	-1.2	221/259/306	85	259	7	10	17%	5%	59	-1.7	234/269/323	88	293	4	9	21%	4%	63	-0.7
✕Alfredo Amezaga 2007 · MLB	29	54→56	39→40	52→55	51	256/313/343	87	291	6	27	14%	7%	87	+0.4	253/309/349	96	289	5	17	14%	7%	87	+0.4	247/306/338	91	286	4	13	14%	7%	84	+0.1
✕Pedro Florimón 2015 · MLB	28	43→53	41→45	54→55	43	212/265/311	100	285	8	19	28%	6%	62	-1.4	212/264/318	106	304	8	18	31%	6%	63	-1.3	217/272/330	113	320	10	11	33%	6%	68	-0.5
✕Anderson Hernandez 2012 · MLB	29	51→61	38→40	47→55	47	244/292/322	79	290	5	15	18%	6%	74	-0.5	240/281/331	91	282	8	13	17%	5%	72	-0.7	249/282/342	93	289	6	11	16%	4%	73	-0.4
✕Cesar Crespo 2007 · MLB	28	48→51	40	53→55	48	230/287/325	95	279	8	21	20%	7%	74	-0.6	226/280/312	86	283	7	15	21%	7%	68	-1.0	221/272/283	61	279	4	14	21%	6%	55	-1.3
✕Skyler Stromsmoe 2013 · AAA	29	46	38→40	49→50	47	216/284/296	80	276	5	15	23%	7%	67	-1.1	213/289/285	72	266	3	13	19%	8%	66	-1.1	204/286/259	56	252	1	11	18%	8%	57	-0.7
✕Eric Bruntlett 2008 · MLB	30	50→51	38→40	52→55	54	233/308/313	80	281	4	20	18%	9%	79	-0.2	212/276/299	87	259	6	16	19%	7%	64	-1.3	190/248/275	85	236	7	13	22%	6%	47	-1.2
✕Jason Ellison 2006 · MLB	28	52→54	41→40	50	49	248/299/348	101	276	8	17	14%	6%	84	+0.1	252/306/347	95	296	6	16	16%	6%	86	+0.3	238/298/312	74	288	3	15	17%	7%	73	-0.4
✕Tyler Saladino 2018 · MLB	29	47	41→45	51→55	46	227/284/324	97	281	8	18	22%	6%	73	-0.6	216/285/355	139	279	16	15	27%	8%	81	-0.1	204/276/354	151	260	19	17	29%	8%	76	-0.2
✕Jack Reinheimer 2021 · MLB	29	44→52	40	51→55	44	213/269/306	93	275	8	16	25%	7%	63	-1.4	205/257/288	83	287	7	20	29%	6%	54	-2.0	184/232/243	59	253	4	22	28%	5%	33	-1.5
✕Tommy Murphy 2009 · MLB	29	50→53	40→45	55→60	43	237/284/332	95	310	7	29	25%	6%	74	-0.6	218/275/310	92	291	7	25	26%	7%	66	-1.1	186/247/252	65	251	4	26	26%	7%	39	-1.6
✕Nick Punto 2006 · MLB	28	49→59	41→40	50→55	51	235/299/332	98	283	8	17	20%	8%	80	-0.2	249/316/334	85	297	4	18	16%	9%	86	+0.3	252/321/328	77	299	2	20	15%	9%	87	+0.3
✕Todd Cunningham 2017 · MLB	28	49→59	39→40	52→55	47	233/293/318	84	273	6	19	17%	6%	75	-0.5	227/307/323	96	274	7	15	19%	8%	82	+0.0	239/338/336	96	293	5	10	18%	8%	95	+0.6
✕Johnny Raburn 2008 · AAA	29	50→56	36→30	56→55	50	234/293/300	66	284	2	23	18%	7%	70	-0.9	217/275/285	68	258	4	15	16%	7%	59	-1.6	212/271/272	60	248	3	13	15%	7%	55	-1.0
✕Jonathan Diaz 2014 · AAA	29	47→48	36→30	49→50	51	220/298/281	61	274	4	14	20%	8%	68	-1.0	204/277/268	64	254	3	10	20%	8%	58	-1.7	191/272/239	49	239	3	6	20%	9%	47	-1.5

Vidal Bruján

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps