Victor Robles

CF Seattle Mariners

Age 30 R/R 6'0" / 193 lbs MLB K +7%HR -5% Svc 8.192 · Ctrl thru 2027

Overview

MLB40-MANExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	27	MLBSEA	295	.307/.385/.433	4	34	130	2.5
2025	28	AAASEA	32	.310/.375/.517	1	2	93	—	.241/.312/.414
2025	28	MLBSEA	114	.245/.286/.330	1	6	73	-0.4
2026	29	AAASEA	54	.256/.396/.349	0	2	78	—	.217/.321/.283
2026	29	MLBSEA	149	.256/.317/.308	0	10	77	-0.2
2027PROJ	30	MLBSEA	154	.233/.302/.321	1	9	80	0.1
2028PROJ	31	MLBSEA	145	.228/.297/.309	1	6	75	-0.3

Last 3 seasons WAR 1.8 · Next 2 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.192First FA2028Options4

2027Ext / FA-deal$1M

Skills · percentileStatcast 2024-2026

Speed73

xwOBA41

Barrel%23

Bat Spd21

Avg EV10

CompsBilly Hamilton (age 30) · Tyler Graham (age 30) · Darin Mastroianni (age 29)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†vL 8080vR 78

AVG/OBP/SLG.233 / .302 / .321

PA154

HR1

SB9

K%21

BB%6

BABIP291

ISO79

MLB%100%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Splits · ContractCON 50 / POW 45

Toolsscout grade · Statcast %ile · 2024-2026

CONTACT50

xAVG

370.240

POWER45

Barrel%

234.7

Avg EV

1085.6

Bat Spd

2168.2

EYE40

scouting grade only

SPEED55

Sprint

7328.4

Platoon Splits2024-2025 · 409 PA

vs LHP

vs RHP

Edge

151

258

—

wRC+

131

▶▶R

wOBA

291

361

▶▶R

ISO

061

146

▶▶R

BABIP

304

381

▶▶R

16.6%

20.9%

◀◀L

BB%

7.9%

4.7%

◀◀L

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

Status FA

MLB Debut 2017

Service 8.192 yrs.days

Team Control Through 2027

First FA Year 2028

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext / FA-deal	$1M	—	—	—
Totals		$1M		$0.0M	-$1M

Options · projected decision
2027	CLUB OPT	$1.0M / $0.0M buyout	DECLINE
2028	CLUB OPT	$9.0M / $0.0M buyout	DECLINE
2029	CLUB OPT	$1.0M / $0.0M buyout	DECLINE
2030	CLUB OPT	$3.3M / $0.0M buyout	DECLINE

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)
2014	17	ROK	DSL Nationals	—	213	182	57	14	4	3	16	26	13	22	9	313	408	484	891	170	353	12	8	394	65	—	—	—	—	—	—
2015	18	ROK	GCL Nationals	—	94	73	27	6	1	2	10	12	7	12	1	370	489	562	1.051	192	417	13	11	446	123	—	—	—	—	—	—
2016	19	A+	Potomac Nationals	—	198	168	44	8	2	3	14	32	11	18	5	262	358	387	744	125	304	16	7	332	86	—	—	—	—	—	—
2016	19	A	Hagerstown Suns	—	285	233	71	9	6	5	18	38	22	19	8	305	407	459	866	155	346	13	6	374	116	—	—	—	—	—	—
2016	19	ROK	GCL Nationals	—	21	20	3	0	0	1	0	7	1	0	1	150	190	300	490	150	167	33	0	220	-20	—	—	—	—	—	—
2017	20	MLB	Washington Nationals	—	27	24	6	1	2	0	0	6	2	0	1	250	308	458	766	208	333	22	0	322	121	+1	-0	+0	-6	+1	-0.5
2017	20	AA	Harrisburg Senators	—	158	139	45	12	1	3	12	22	4	11	3	324	394	489	883	165	368	14	8	385	126	—	—	—	—	—	—
2017	20	A+	Potomac Nationals	—	338	291	84	25	7	7	25	62	17	16	7	289	378	495	873	206	345	18	7	381	83	—	—	—	—	—	—
2017	20	INTL	Mesa Solar Sox	—	54	41	10	1	0	3	10	9	1	7	0	244	404	488	892	244	226	17	19	383	145	—	—	—	—	—	—
2018	21	MLB	Washington Nationals	—	66	59	17	3	1	3	4	12	2	3	2	288	354	525	879	237	311	18	6	379	146	+4	-0	+2	+1	+1	0.8
2018	21	AAA	Syracuse Chiefs	—	182	158	44	9	1	2	18	26	2	14	6	278	358	386	744	108	318	14	10	331	85	—	—	—	—	—	—
2018	21	ROK	GCL Nationals	—	27	18	6	1	0	0	7	4	2	4	1	333	556	389	944	56	429	15	26	450	109	—	—	—	—	—	—
2018	21	INTL	Aguilas Cibaenas	—	110	98	26	2	0	1	11	20	1	4	1	265	345	316	662	51	325	18	10	308	95	—	—	—	—	—	—
2019	22	MLB	Washington Nationals	—	617	546	139	33	3	17	35	140	25	28	9	255	328	419	748	165	310	23	6	329	107	+5	+2	+18	+2	+13	4.2
2020	23	MLB	Washington Nationals	—	189	168	37	5	1	3	9	53	9	4	1	220	296	315	611	95	298	28	5	278	75	-6	+0	+1	+1	+4	0.1
2020	23	INTL	Aguilas Cibaenas	—	59	47	11	2	0	2	6	8	4	3	3	234	368	404	773	170	237	14	10	342	118	—	—	—	—	—	—
2021	24	MLB	Washington Nationals	—	369	315	64	21	1	2	33	85	16	8	6	203	310	295	606	92	271	23	9	281	72	-12	-1	+1	+2	+8	-0.2
2021	24	AAA	Rochester Red Wings	—	93	83	25	8	1	4	7	26	2	6	1	301	370	566	936	265	396	28	8	402	97	—	—	—	—	—	—
2022	25	MLB	Washington Nationals	—	407	366	82	10	2	6	17	104	9	15	4	224	276	311	587	87	292	26	4	258	61	-19	+1	+4	+2	+9	-0.3
2022	25	INTL	Aguilas Cibaenas	—	61	54	11	0	0	1	3	14	4	7	0	204	295	259	554	56	256	23	5	265	65	—	—	—	—	—	—
2023	26	MLB	Washington Nationals	—	126	107	32	5	1	0	11	18	4	8	1	299	385	364	750	65	360	14	9	335	114	+2	+1	-4	+1	+3	0.3
2023	26	INTL	Toros del Este	—	26	21	5	1	0	0	4	3	1	0	0	238	385	286	670	48	278	12	15	324	106	—	—	—	—	—	—
2024	27	MLB	Seattle Mariners	—	295	254	78	20	0	4	21	53	11	34	2	307	385	433	818	126	370	18	7	358	130	+11	+6	+0	+1	+6	2.5
2024	27	AAA	Rochester Red Wings	—	23	20	7	1	1	0	3	6	0	1	0	350	435	500	935	150	500	26	13	414	109	—	—	—	—	—	—
2025	28	MLB	Seattle Mariners	—	114	106	26	4	1	1	3	26	3	6	2	245	286	330	616	85	309	23	3	274	73	-4	+0	-2	-2	+2	-0.4
2025	28	AAA	Tacoma Rainiers	—	32	29	9	3	0	1	0	9	3	2	1	310	375	517	892	207	421	28	0	396	93	—	—	—	—	—	—
2026	29	MLB	Seattle Mariners	—	149	133	34	3	2	0	9	22	3	10	2	256	317	308	626	53	304	15	6	281	77	-4	+1	-0	-2	+3	-0.2
2026	29	AAA	Tacoma Rainiers	—	54	43	11	4	0	0	9	13	1	2	0	256	396	349	745	93	355	24	17	342	78	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2359	2078	515	105	14	36	142	519	84	116	30	248	322	364	685	116	311	22	6	305	92	-21	+11	+20	-0	+51	6.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	17	ROK MLE	DSL Nationals	—	213	186	40	9	3	1	12	32	13	22	9	215	308	312	620	97	241	15	6	265	65	—	—	—	—	—	—
2015	18	ROK MLE	GCL Nationals	—	94	77	24	5	1	2	6	17	7	12	1	312	411	481	892	169	328	18	6	350	123	—	—	—	—	—	—
2016	19	A+ MLE	Potomac Nationals	—	198	173	44	7	2	3	9	47	11	18	5	254	332	370	702	116	306	24	5	295	86	—	—	—	—	—	—
2016	19	A MLE	Hagerstown Suns	—	285	238	71	8	6	4	13	51	22	19	8	298	388	433	821	134	338	18	5	339	116	—	—	—	—	—	—
2016	19	ROK MLE	GCL Nationals	—	21	20	2	0	0	1	0	10	1	0	1	100	143	250	393	150	135	48	0	138	-20	—	—	—	—	—	—
2017	20	MLB MLE	Washington Nationals	—	27	24	6	1	2	0	0	6	2	0	1	250	308	458	766	208	333	22	0	347	121	+1	-0	+0	-6	+1	-0.5
2017	20	AA MLE	Harrisburg Senators	—	158	142	45	11	1	3	9	26	4	11	3	317	374	472	846	155	362	16	6	354	126	—	—	—	—	—	—
2017	20	A+ MLE	Potomac Nationals	—	338	300	69	20	5	5	16	91	17	16	7	230	306	380	686	150	301	27	5	291	83	—	—	—	—	—	—
2018	21	MLB MLE	Washington Nationals	—	66	59	17	3	1	3	4	12	2	3	2	288	354	525	879	237	311	18	6	383	146	+4	-0	+2	+1	+1	0.8
2018	21	AAA MLE	Syracuse Chiefs	—	182	165	43	9	1	2	12	30	2	14	6	261	318	364	682	103	291	16	7	294	85	—	—	—	—	—	—
2018	21	ROK MLE	GCL Nationals	—	27	21	5	1	0	0	4	6	2	4	1	238	407	286	693	48	339	22	15	330	109	—	—	—	—	—	—
2019	22	MLB MLE	Washington Nationals	—	617	549	139	32	4	17	32	140	25	28	9	253	323	419	742	166	310	23	5	327	107	+5	+2	+18	+2	+13	4.2
2020	23	MLB MLE	Washington Nationals	—	189	168	37	5	1	3	9	53	9	4	1	220	296	315	611	95	298	28	5	279	75	-6	+0	+1	+1	+4	0.1
2021	24	MLB MLE	Washington Nationals	—	369	318	64	21	1	2	30	85	16	8	6	201	302	292	595	91	271	23	8	275	72	-12	-1	+1	+2	+8	-0.2
2021	24	AAA MLE	Rochester Red Wings	—	93	85	21	6	1	3	5	32	2	6	1	247	304	447	751	200	344	34	5	311	97	—	—	—	—	—	—
2022	25	MLB MLE	Washington Nationals	—	407	366	82	10	2	6	17	104	9	15	4	224	276	311	587	87	292	26	4	259	61	-19	+1	+4	+2	+9	-0.3
2023	26	MLB MLE	Washington Nationals	—	126	107	32	5	1	0	11	18	4	8	1	299	385	364	750	65	360	14	9	337	114	+2	+1	-4	+1	+3	0.3
2024	27	MLB MLE	Seattle Mariners	—	295	254	78	20	0	4	21	53	11	34	2	307	385	433	818	126	370	18	7	361	130	+11	+6	+0	+1	+6	2.5
2024	27	AAA MLE	Rochester Red Wings	—	23	21	6	1	1	0	2	8	0	1	0	286	348	429	776	143	446	35	9	329	109	—	—	—	—	—	—
2025	28	MLB MLE	Seattle Mariners	—	114	106	26	4	1	1	3	26	3	6	2	245	286	330	616	85	309	23	3	276	73	-4	+0	-2	-2	+2	-0.4
2025	28	AAA MLE	Tacoma Rainiers	—	32	29	7	2	0	1	0	10	3	2	1	241	312	414	726	172	362	31	0	305	93	—	—	—	—	—	—
2026	29	MLB MLE	Seattle Mariners	—	149	133	34	3	2	0	9	22	3	10	2	256	317	308	626	53	304	15	6	282	77	-4	+1	-0	-2	+3	-0.2
2026	29	AAA MLE	Tacoma Rainiers	—	54	46	10	3	0	0	6	16	1	2	0	217	321	283	603	65	312	30	11	283	78	—	—	—	—	—	—
2014	17	ROK MLE	DSL Nationals	—	213	186	40	9	3	1	12	32	13	22	9	215	308	312	620	97	255	15	6	265	65	—	—	—	—	—	—
2014	17	ROK RAW	DSL Nationals	—	213	182	57	14	4	3	16	26	13	22	9	313	408	484	891	170	353	12	8	394	65	—	—	—	—	—	—
2015	18	ROK MLE	GCL Nationals	—	94	77	24	5	1	2	6	17	7	12	1	312	411	481	892	169	373	18	6	350	123	—	—	—	—	—	—
2015	18	ROK RAW	GCL Nationals	—	94	73	27	6	1	2	10	12	7	12	1	370	489	562	1.051	192	417	13	11	446	123	—	—	—	—	—	—
2016	19	A MLE	3 teams	—	504	431	116	15	8	7	22	108	34	37	14	269	353	390	743	121	342	21	4	313	98	—	—	—	—	—	—
2016	19	A RAW	3 teams	—	504	421	118	17	8	9	32	77	34	37	14	280	378	423	801	143	322	15	6	351	98	—	—	—	—	—	—
2017	20	A+ MLE	4 teams	—	577	515	131	35	9	8	27	136	24	34	11	254	322	404	725	150	329	24	5	313	98	—	—	—	—	—	—
2017	20	A+ RAW	4 teams	—	577	495	145	39	10	13	47	99	24	34	11	293	382	491	873	198	342	17	8	379	98	—	—	—	—	—	—
2018	21	AAA MLE	4 teams	—	385	345	89	17	3	6	29	67	7	25	10	258	328	377	705	119	302	17	8	319	102	—	—	—	—	—	—
2018	21	AAA RAW	4 teams	—	385	333	93	15	2	6	40	62	7	25	10	279	367	390	758	111	325	16	10	341	102	—	—	—	—	—	—
2019	22	MLB MLE	Washington Nationals	—	617	549	139	32	4	17	32	140	25	28	9	253	323	419	742	166	307	23	5	327	107	+5	+2	+18	+2	+13	4.2
2019	22	MLB RAW	Washington Nationals	—	617	546	139	33	3	17	35	140	25	28	9	255	328	419	748	165	310	23	6	329	107	+5	+2	+18	+2	+13	4.2
2020	23	MLB MLE	2 teams	—	248	218	49	6	2	4	12	70	13	7	4	225	305	326	630	101	306	28	5	279	75	-7	-0	+1	+1	+5	-0.0
2020	23	MLB RAW	2 teams	—	248	215	48	7	1	5	15	61	13	7	4	223	313	335	648	112	283	25	6	293	75	-7	-0	+1	+1	+5	-0.0
2021	24	MLB MLE	2 teams	—	462	403	85	27	2	5	35	117	18	14	7	211	303	325	628	114	284	25	8	282	77	-13	+0	+1	+2	+10	0.0
2021	24	MLB RAW	2 teams	—	462	398	89	29	2	6	40	111	18	14	7	224	322	352	674	128	294	24	9	306	77	-13	+0	+1	+2	+10	0.0
2022	25	MLB MLE	2 teams	—	468	420	95	11	3	7	20	120	13	22	4	226	283	317	599	90	296	26	4	259	61	-21	+3	+4	+2	+10	-0.3
2022	25	MLB RAW	2 teams	—	468	420	93	10	2	7	20	118	13	22	4	221	278	305	583	83	288	25	4	259	61	-21	+3	+4	+2	+10	-0.3
2023	26	MLB MLE	2 teams	—	152	130	38	6	1	0	13	22	5	8	1	292	378	354	732	62	352	14	9	337	114	+3	+1	-4	+1	+3	0.4
2023	26	MLB RAW	2 teams	—	152	128	37	6	1	0	15	21	5	8	1	289	385	352	737	62	346	14	10	333	114	+3	+1	-4	+1	+3	0.4
2024	27	MLB MLE	2 teams	—	318	275	85	21	1	4	23	61	11	35	2	309	385	436	821	127	380	19	7	359	129	+11	+6	+0	+1	+7	2.6
2024	27	MLB RAW	2 teams	—	318	274	85	21	1	4	24	59	11	35	2	310	388	438	826	128	379	19	8	362	129	+11	+6	+0	+1	+7	2.6
2025	28	MLB MLE	2 teams	—	146	135	33	6	1	2	3	36	6	8	3	244	292	348	640	104	313	25	2	283	77	-4	+0	-2	-2	+3	-0.4
2025	28	MLB RAW	2 teams	—	146	135	35	7	1	2	3	35	6	8	3	259	306	370	676	111	330	24	2	301	77	-4	+0	-2	-2	+3	-0.4
2026	29	MLB MLE	2 teams	—	203	179	44	6	2	0	15	38	4	12	2	246	318	302	620	56	308	19	7	283	77	-5	+2	-0	-2	+4	-0.2
2026	29	MLB RAW	2 teams	—	203	176	45	7	2	0	18	35	4	12	2	256	338	318	657	62	315	17	9	297	77	-5	+2	-0	-2	+4	-0.2
2014	17	ROK MLE	DSL Nationals	—	213	186	40	9	3	1	12	32	13	22	9	215	308	312	620	97	241	15	6	265	65	—	—	—	—	—	—
2015	18	ROK MLE	GCL Nationals	—	94	81	24	5	1	2	6	17	7	12	1	296	411	457	868	160	328	18	6	350	123	—	—	—	—	—	—
2016	19	A MLE	3 teams	—	504	443	116	15	8	7	22	108	34	37	14	262	353	379	732	117	317	21	4	313	98	—	—	—	—	—	—
2017	20	A+ MLE	4 teams	—	577	521	131	35	9	8	27	136	24	34	11	251	322	399	721	148	321	24	5	313	98	—	—	—	—	—	—
2018	21	AAA MLE	4 teams	—	385	346	89	17	3	6	29	67	7	25	10	257	328	376	704	118	301	17	8	319	102	—	—	—	—	—	—
2019	22	MLB MLE	Washington Nationals	—	617	555	139	32	4	17	32	140	25	28	9	250	323	414	738	164	310	23	5	327	107	—	—	—	—	—	—
2020	23	MLB MLE	2 teams	—	248	221	49	6	2	4	12	70	13	7	4	222	305	321	626	100	298	28	5	279	75	—	—	—	—	—	—
2021	24	MLB MLE	2 teams	—	462	406	85	27	2	5	35	117	18	14	7	209	303	323	625	113	285	25	8	282	77	—	—	—	—	—	—
2022	25	MLB MLE	2 teams	—	468	432	95	11	3	7	20	120	13	22	4	220	283	308	590	88	292	26	4	259	61	—	—	—	—	—	—
2023	26	MLB MLE	2 teams	—	152	133	38	6	1	0	13	22	5	8	1	286	378	346	724	60	360	14	9	337	114	—	—	—	—	—	—
2024	27	MLB MLE	2 teams	—	318	281	85	21	1	4	23	61	11	35	2	302	385	427	812	125	375	19	7	359	129	—	—	—	—	—	—
2025	28	MLB MLE	2 teams	—	146	136	33	6	1	2	3	36	6	8	3	243	292	346	637	103	320	25	2	283	77	—	—	—	—	—	—
2026	29	MLB MLE	2 teams	—	203	182	44	6	2	0	15	38	4	12	2	242	318	297	615	55	306	19	7	283	77	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	27	MLB MLE	2 teams	—	318	281	85	21	1	4	23	61	11	35	2	302	385	427	812	125	375	19	7	359	129	—	—	—	—	—	—
2025	28	MLB MLE	2 teams	—	146	136	33	6	1	2	3	36	6	8	3	243	292	346	637	103	320	25	2	283	77	—	—	—	—	—	—
2026	29	MLB MLE	2 teams	—	203	182	44	6	2	0	15	38	4	12	2	242	318	297	615	55	306	19	7	283	77	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	30	MLB MLE	SEA	100%	249	225	53	10	2	2	16	52	6	14	3	235	304	324	629	89	293	21	6	286	80	-6	+2	-0	+1	+5	0.0
▸ 2027 — real world (MLB)
2027	30	MLB CTX	SEA	100%	154	139	32	6	1	1	10	32	4	9	2	233	302	321	623	87	291	21	6	284	80	-4	+1	-0	+1	+3	0.1
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	31	MLB MLE	SEA	100%	145	131	31	6	1	1	9	31	4	6	2	230	298	313	611	83	289	21	6	279	75	-4	+0	-3	+1	+3	-0.3
2028	31	MLB CTX	SEA	100%	145	131	29	5	1	1	9	31	4	6	2	228	297	309	606	81	287	21	6	277	75	-4	+0	-3	+1	+3	-0.3
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2504	2209	544	110	15	37	151	550	88	122	32	246	320	360	680	114	309	22	6	303	91	-26	+12	+16	+0	+54	5.8
/ 162G	—	A+C		—	650	573	142	29	4	10	39	143	23	32	8	248	321	365	686	117	311	22	6	303	91	-7	+3	+4	+0	+14	1.5
Career	—	MLE		—	4686	4133	1031	208	42	65	268	1027	188	279	81	249	324	367	691	118	314	22	6	303	91	-29	+13	+16	+1	+58	5.9
/ 162G	—	MLE		—	650	573	143	29	6	9	37	142	26	39	11	250	323	368	692	119	315	22	6	303	91	-7	+3	+4	+0	+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 AAATacoma Rainiers · 54 PAwOBA .341 → .283 (−58)K% 24.1% → 28.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.07%	÷1.000	×1.200	—	—	28.89%
BB% (unintentional) /PA	16.67%	÷1.000	×0.690	—	×0.982	11.29%
HBP% /PA	1.85%	—	×0.940	—	×0.982	1.71%
Singles /BIP	23.33%	÷1.000	×0.930	—	×0.982	21.31%
Doubles /BIP	13.33%	÷1.000	×0.830	—	×0.982	10.87%
Triples /BIP	0.00%	÷1.000	×0.970	—	×0.982	0.00%
Home runs /BIP	0.00%	÷1.000	×0.700	—	×0.982	0.00%

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 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average).

Result: wOBA .341 → .283; ISO .093 → .079; BABIP .355 → .312. 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 AAATacoma Rainiers · 32 PAwOBA .385 → .305 (−79)K% 28.1% → 32.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.12%	÷1.035	×1.200	—	—	32.61%
BB% (unintentional) /PA	0.00%	÷1.023	×0.690	—	×0.992	0.00%
HBP% /PA	9.38%	—	×0.940	—	×0.992	8.74%
Singles /BIP	25.00%	÷1.019	×0.930	—	×0.992	22.64%
Doubles /BIP	15.00%	÷0.985	×0.830	—	×0.992	12.54%
Triples /BIP	0.00%	÷1.017	×0.970	—	×0.992	0.00%
Home runs /BIP	5.00%	÷1.204	×0.700	—	×0.992	2.88%

Factors used: league row International League. Park (home-season share, regressed): HR 141, 1B 104, 2B 97, 3B 103, K 107, BB 105 — 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).

Result: wOBA .385 → .305; ISO .207 → .137; BABIP .421 → .362. 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 AAARochester Red Wings · 23 PAwOBA .404 → .329 (−74)K% 26.1% → 32.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.09%	÷0.958	×1.200	—	—	32.66%
BB% (unintentional) /PA	13.04%	÷0.969	×0.690	—	×1.003	9.31%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	35.71%	÷1.029	×0.930	—	×1.003	32.37%
Doubles /BIP	7.14%	÷0.962	×0.830	—	×1.003	6.18%
Triples /BIP	7.14%	÷1.150	×0.970	—	×1.003	6.04%
Home runs /BIP	0.00%	÷0.986	×0.700	—	×1.003	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 97, 1B 106, 2B 92, 3B 130, K 92, BB 94 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average).

Result: wOBA .404 → .329; ISO .150 → .122; BABIP .500 → .446. 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 AAARochester Red Wings · 93 PAwOBA .391 → .311 (−80)K% 28.0% → 34.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.96%	÷0.979	×1.200	—	—	34.26%
BB% (unintentional) /PA	7.53%	÷1.014	×0.690	—	×1.048	5.37%
HBP% /PA	2.15%	—	×0.940	—	×1.048	2.12%
Singles /BIP	21.05%	÷0.994	×0.930	×0.950	×1.048	19.60%
Doubles /BIP	14.04%	÷1.005	×0.830	×0.950	×1.048	11.54%
Triples /BIP	1.75%	÷1.150	×0.920	×0.950	×1.048	1.40%
Home runs /BIP	7.02%	÷0.968	×0.700	—	×1.048	5.32%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 94, 1B 99, 2B 101, 3B 130, K 96, BB 103 — 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 ×0.950.

Result: wOBA .391 → .311; ISO .265 → .198; BABIP .396 → .344. 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 AAASyracuse Chiefs · 182 PAwOBA .323 → .294 (−29)K% 14.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.29%	÷1.044	×1.200	—	—	16.42%
BB% (unintentional) /PA	8.79%	÷0.956	×0.690	—	×1.050	6.66%
HBP% /PA	1.10%	—	×0.940	—	×1.050	1.08%
Singles /BIP	24.24%	÷1.044	×0.930	×0.977	×1.050	22.17%
Doubles /BIP	6.82%	÷0.933	×0.830	×0.977	×1.050	6.23%
Triples /BIP	0.76%	÷0.900	×0.970	×0.977	×1.050	0.84%
Home runs /BIP	1.52%	÷1.205	×0.840	—	×1.050	1.11%

Factors used: league row IL. Park (home-season share, regressed): HR 141, 1B 109, 2B 87, 3B 80, K 109, BB 91 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.977.

Result: wOBA .323 → .294; ISO .108 → .098; BABIP .318 → .291. 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 ROKGCL Nationals · 27 PAwOBA .441 → .330 (−112)K% 14.8% → 21.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.81%	÷1.000	×1.440	—	—	21.33%
BB% (unintentional) /PA	25.93%	÷1.000	×0.620	—	×0.985	15.83%
HBP% /PA	7.41%	—	×0.720	—	×0.985	5.25%
Singles /BIP	35.71%	÷1.000	×0.820	—	×0.985	28.85%
Doubles /BIP	7.14%	÷1.000	×0.720	—	×0.985	5.07%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.985	0.00%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×0.985	0.00%

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 21 vs a level average of 19.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average).

Result: wOBA .441 → .330; ISO .056 → .044; BABIP .429 → .339. 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).

2017 A+Potomac Nationals · 338 PAwOBA .371 → .291 (−80)K% 18.3% → 27.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.34%	÷0.963	×1.420	—	—	27.04%
BB% (unintentional) /PA	7.10%	÷0.982	×0.630	—	×1.042	4.75%
HBP% /PA	5.03%	—	×0.860	—	×1.042	4.51%
Singles /BIP	19.65%	÷1.050	×0.940	×0.990	×1.042	18.15%
Doubles /BIP	10.92%	÷1.012	×0.830	×0.990	×1.042	9.24%
Triples /BIP	3.06%	÷1.150	×0.800	×0.990	×1.042	2.19%
Home runs /BIP	3.06%	÷1.368	×0.900	—	×1.042	2.10%

Factors used: league row CAR. Park (home-season share, regressed): HR 174, 1B 110, 2B 102, 3B 130, K 93, BB 96 — 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 ×0.990.

Result: wOBA .371 → .291; ISO .206 → .147; BABIP .345 → .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).

2017 AAHarrisburg Senators · 158 PAwOBA .375 → .354 (−20)K% 13.9% → 16.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.92%	÷1.022	×1.220	—	—	16.62%
BB% (unintentional) /PA	7.59%	÷0.974	×0.700	—	×1.050	5.73%
HBP% /PA	2.53%	—	×0.850	—	×1.050	2.26%
Singles /BIP	24.79%	÷1.016	×0.970	×1.011	×1.050	25.10%
Doubles /BIP	10.26%	÷0.998	×0.860	×1.011	×1.050	9.37%
Triples /BIP	0.85%	÷0.906	×0.950	×1.011	×1.050	0.95%
Home runs /BIP	2.56%	÷0.970	×0.780	—	×1.050	2.16%

Factors used: league row EL. Park (home-season share, regressed): HR 94, 1B 103, 2B 100, 3B 81, K 104, BB 95 — applied at half strength. Age: age 20 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (4.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.011.

Result: wOBA .375 → .354; ISO .165 → .152; BABIP .368 → .362. 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
#1Cameron Maybinlast yr '20 ASSS career totals — 13 seasons, 4,182 PA	6.3	4,182	72	182	254	322	375	+9	+6	13.1	12.8
/162	664	11	29	+1.4	+1.0	2.1	pk7: 13
#2Bob Dernier'80-'89 * career totals — 8 seasons, 2,757 PA	4.2	2,757	23	218	253*	317*	360*	+2	+22	6.7	7.2
/162	664	6	53	+0.6	+5.3	1.6	pk7: 8
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 11 projected seasons	4.0	2,631	39	131	243	313	354	+7	+21	6.5	6.8
/162	664	10	33	+1.8	+5.4	1.6	pk7: 7
#3Delino DeShieldslast yr '21 career totals — 7 seasons, 2,114 PA	3.2	2,114	19	111	246	327	342	+1	+6	5.3	5.3
/162	664	6	35	+0.4	+1.8	1.7	pk7: 5
#4Darren Lewis'90-'02 * career totals — 12 seasons, 4,652 PA	7.0	4,652	27	247	239*	312*	319*	+0	+23	2.7	4.2
/162	664	4	35	+0.0	+3.3	0.4	pk7: 6
#5Luis Matos'00-'06 * career totals — 6 seasons, 1,773 PA	2.7	1,773	30	72	245*	304*	365*	+1	+10	3.2	3.2
/162	664	11	27	+0.3	+3.9	1.2	pk7: 3
#6Tony Scott'73-'84 * career totals — 9 seasons, 3,047 PA	4.6	3,047	17	125	243*	294*	352*	-0	+13	1.4	2.9
/162	664	4	27	-0.0	+2.8	0.3	pk7: 4

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
Victor Robles (OGILVIE)	30	50	45	55	40	233/302/322	88	293	1	9	21%	6%	80	-0.0	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Billy Hamilton 2021 · MLB	30	46→56	39→40	59→70	49	220/285/307	86	285	5	34	24%	8%	69	-0.9	195/248/294	99	291	8	34	33%	6%	52	-2.2	158/208/235	77	253	4	47	37%	6%	22	-1.0
✕Tyler Graham 2014 · AAA	30	47→54	39→40	60→65	45	225/290/311	86	287	6	33	23%	6%	72	-0.7	228/274/303	75	282	6	28	21%	5%	63	-1.3	230/270/276	46	284	3	38	19%	4%	52	-1.6
✕Darin Mastroianni 2015 · MLB	29	46→56	39→40	55→60	45	222/279/303	81	282	7	26	23%	6%	66	-1.1	216/264/288	72	272	5	22	21%	5%	56	-1.9	211/255/267	56	266	2	24	21%	5%	45	-1.7
✕Tony Gwynn Jr. 2013 · MLB	30	51→57	38→40	59→60	48	241/293/329	88	291	4	28	18%	7%	76	-0.4	227/289/299	72	274	4	17	17%	8%	68	-1.0	215/282/271	56	256	2	15	15%	8%	57	-1.0
✕Craig Gentry 2016 · MLB	32	48→55	37→40	57→60	46	228/284/295	67	282	5	29	20%	6%	65	-1.2	218/278/298	80	277	6	24	22%	7%	64	-1.3	218/282/291	73	279	4	29	22%	7%	64	-0.4
✕Jonathan Davis 2023 · MLB	31	46→52	40→45	57→55	51	219/314/311	92	297	8	27	27%	10%	82	+0.0	218/293/335	117	304	10	17	29%	8%	79	-0.2	204/277/324	120	289	10	14	31%	7%	68	-0.5
✕Jason Bourgeois 2011 · MLB	29	55→58	39→45	59→65	47	263/304/348	86	295	6	34	14%	5%	85	+0.2	253/294/331	78	283	5	35	12%	5%	77	-0.3	251/290/318	66	279	3	37	11%	5%	71	-0.4
✕Darren Ford 2016 · AAA	30	45→53	41→45	57→65	43	218/270/309	91	280	9	39	25%	6%	64	-1.3	218/270/298	80	283	6	24	24%	6%	61	-1.5	212/261/258	46	279	1	23	23%	6%	45	-1.9
✕Ben DeLuzio 2023 · MLB	28	47→50	42→45	60	41	224/281/335	111	303	8	29	28%	6%	74	-0.5	210/272/317	107	307	10	20	33%	7%	68	-1.0	148/218/218	71	242	7	18	39%	7%	24	-1.2
✕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
✕Quintin Berry 2015 · MLB	30	49→59	37→40	59→65	48	230/299/303	73	304	4	32	24%	8%	74	-0.6	214/279/277	63	292	5	33	26%	8%	60	-1.6	200/264/246	46	280	3	42	28%	7%	45	-1.4
✕Todd Donovan 2009 · AAA	30	49→52	36→40	61→65	48	232/291/301	69	291	3	38	21%	7%	70	-0.9	224/300/306	82	289	5	31	22%	10%	75	-0.5	214/305/285	71	275	3	38	21%	11%	71	-0.6
✕John Andreoli 2019 · MLB	29	46→56	42→45	56→60	47	218/295/331	113	309	9	25	30%	9%	79	-0.2	203/292/326	123	314	12	15	35%	11%	77	-0.3	159/263/282	124	258	14	17	41%	12%	56	-1.2
✕Delino DeShields 2023 · MLB	30	45→55	36→45	56→65	52	205/300/272	67	298	4	31	29%	11%	68	-1.0	214/295/288	74	313	5	23	30%	10%	70	-0.9	227/304/279	52	363	0	11	34%	9%	65	-0.3
✕Wynton Bernard 2021 · AAA	30	45→55	42→45	56→60	44	219/268/327	108	277	8	25	24%	6%	68	-1.0	229/277/348	119	287	10	29	23%	6%	76	-0.4	245/290/364	119	296	10	37	20%	5%	81	-0.1
✕Chase d'Arnaud 2017 · MLB	30	47→50	38→45	56→60	45	225/275/311	86	269	5	25	18%	5%	66	-1.1	217/276/332	115	282	12	23	26%	7%	72	-0.7	195/259/314	118	266	13	23	31%	7%	60	-0.9
✕Travis Jankowski 2021 · MLB	30	52→62	38→40	52→65	50	243/311/320	77	312	6	25	23%	9%	82	-0.0	235/323/314	79	297	5	26	20%	11%	85	+0.2	240/336/303	63	300	2	35	18%	12%	87	+0.1
✕Justin Christian 2010 · MLB	30	51→54	40→45	62→65	44	242/278/338	96	277	6	34	16%	4%	73	-0.6	247/297/362	115	278	9	29	14%	6%	86	+0.3	250/305/367	117	278	9	30	13%	6%	88	+0.3
✕Trent Durrington 2006 · MLB	30	51→43	41→40	58→60	47	243/304/344	101	305	8	36	22%	7%	84	+0.2	217/273/295	78	280	5	32	23%	6%	61	-1.5	202/256/260	57	263	3	36	23%	6%	45	-1.5
✕José Azocar 2024 · MLB	28	49→56	42→45	55→65	40	238/279/347	108	307	9	28	25%	5%	76	-0.4	232/272/322	90	292	7	34	22%	4%	68	-1.0	229/269/305	76	287	5	37	21%	4%	60	-1.0

Victor Robles

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps