Wilmer Flores — OGILVIE

Wilmer Flores1B San Francisco Giants

Age 34 R/R 6'3" / 225 lbs MLB BB -3% Svc 13.000 · Ctrl thru 2026

wRC+†vL 7698vR 85

AVG/OBP/SLG.236 / .307 / .392

PA347

HR12

K%17

BB%8

xwOBA.281

Barrel%4.8%

MLB%100%

Scouting · now → future

HIT

51→51

PWR

43↗46

SPD

23→23

FLD

45→45

EYE

48↘43

trajectory · 10 yrs

0.1peak

2026

Barrel%

244.8

xwOBA

270.281

Avg EV

1085.9

Whiff%

720.087

Chase%

470.322

Speed

1024.5

Bat Spd

1065.5

Contract

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

Status FA

MLB Debut 2013

Service 13.000 yrs.days

Team Control Through 2026

First FA Year 2027

Year	Status	Salary	Proj WAR	Value	Surplus
2026	Ext / FA-deal	$1M	—	—	—
Totals		$1M		$0.0M	-$1M

Career Projections (MLE)

All seasons translated to park-neutral MLB-equivalent (MLE) and combined per year. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve.

Year	Age	Lvl	Team	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
2008	16	ROK	Kingsport Mets	265	251	58	8	3	6	6	40	5	2	1	.231	.263	.359	.622	.127	.251	15	2	.271	66	-10	+0	+0	-5	+8	-0.8
2009	17	A	Savannah Sand Gnats	528	497	107	15	2	3	13	95	9	3	3	.215	.249	.272	.520	.056	.257	18	2	.224	30	-42	-1	+0	-9	+15	-3.8
2010	18	A	3 teams	713	677	165	35	3	12	19	125	9	5	5	.244	.274	.357	.631	.114	.280	18	3	.275	69	-25	-1	+0	-13	+20	-1.9
2011	19	A+	2 teams	711	671	152	30	2	9	22	130	7	4	2	.227	.259	.317	.576	.091	.264	18	3	.252	51	-39	+0	+0	-13	+20	-3.3
2012	20	AA	3 teams	765	707	185	37	2	21	36	117	7	3	3	.262	.304	.409	.713	.147	.283	15	5	.309	94	-5	-1	+0	-14	+22	0.3
2013	21	AAA	3 teams	663	621	160	41	3	14	25	126	4	1	5	.258	.291	.401	.692	.143	.297	19	4	.299	87	-10	-2	+1	+2	+19	1.1
2014	22	MLB	3 teams	611	574	150	25	3	20	26	99	5	4	2	.261	.299	.420	.719	.159	.283	16	4	.304	91	-6	+0	+6	+7	+17	2.4
2015	23	MLB	2 teams	527	498	138	22	0	17	20	65	5	0	1	.277	.312	.424	.735	.147	.289	12	4	.315	100	-0	-0	+4	+6	+15	2.4
2016	24	MLB	2 teams	354	324	86	15	0	15	24	50	2	1	1	.265	.320	.451	.771	.185	.270	14	7	.331	112	+5	-0	-5	+1	+10	1.1
2017	25	MLB	New York Mets	362	336	95	18	1	19	17	54	3	1	1	.283	.323	.512	.835	.229	.283	15	5	.355	130	+12	-0	-7	+1	+10	1.7
2018	26	MLB	New York Mets	429	386	109	28	0	11	29	42	5	0	0	.282	.340	.440	.781	.158	.287	10	7	.336	115	+7	+0	-1	-8	+12	1.1
2019	27	MLB	Arizona Diamondbacks	285	265	86	18	0	9	15	31	4	0	0	.325	.370	.494	.864	.170	.341	11	5	.375	145	+15	+0	+0	+1	+8	2.5
2020	28	MLB	San Francisco Giants	213	198	52	12	1	11	13	36	1	1	0	.263	.311	.500	.811	.237	.270	17	6	.340	119	+4	+0	+1	+1	+6	1.3
2021	29	MLB	San Francisco Giants	436	389	101	15	1	19	41	56	3	1	0	.260	.335	.450	.785	.190	.259	13	9	.338	117	+8	+0	+0	+2	+12	2.3
2022	30	MLB	San Francisco Giants	602	525	119	26	1	19	59	103	11	0	0	.227	.318	.389	.706	.162	.244	17	10	.309	95	-4	+0	-3	+2	+17	1.3
2023	31	MLB	2 teams	550	491	142	27	0	27	50	76	6	0	0	.289	.362	.509	.871	.220	.294	14	9	.377	147	+29	+0	-3	-10	+16	3.2
2024	32	MLB	San Francisco Giants	242	214	43	11	0	4	20	33	3	0	0	.201	.278	.308	.587	.107	.214	14	8	.266	62	-10	+0	-2	-4	+7	-1.0
2025	33	MLB	San Francisco Giants	463	419	102	10	0	16	34	88	7	1	0	.243	.311	.382	.693	.138	.270	19	7	.309	95	-3	+0	-2	-8	+13	0.1
▸ 2026 Season
2026	34	MLB	SF	347	311	74	13	0	12	28	58	5	1	1	.238	.311	.395	.707	.158	.255	17	8	.314	98	-1	-0	-3	-6	+10	-0.0
▸ 2027+ Projections — Projections at projected PA · Park-neutral MLB equivalent · Marcel + aging curve
2027	35	MLB	SF	287	259	59	10	0	9	22	51	4	0	0	.228	.298	.371	.669	.143	.252	18	8	.304	91	-3	+0	-8	-5	+8	-0.8
▸ Career Totals (MLE all levels + projections)
Career	—			9353	8613	2183	416	22	273	519	1475	105	28	25	.253	.304	.402	.706	.148	.274	16	6	.306	93	-78	-4	-21	-72	+265	9.1
/ 162G	—			650	599	152	29	2	19	36	103	7	2	2	.254	.304	.404	.708	.150	.275	16	6	.306	93	-5	-0	-1	-5	+18	0.6

Historical Stats — Raw (Per Stint)

Actual MLB + MiLB stats as they happened, one row per stint at each level. Use this to see what really got recorded; the table above shows MLB-equivalent translations + projections.

Year	Age	Lvl	Team	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
2008	16	ROK	Kingsport Mets	265	245	76	12	4	8	12	28	5	2	1	.310	.355	.490	.845	.180	.322	11	5	.368	140	+12	+0	—	—	+8	2.0
2009	17	A	Savannah Sand Gnats	528	488	129	20	2	3	22	72	9	3	3	.264	.308	.332	.640	.068	.301	14	4	.286	77	-13	-1	—	—	+15	0.1
2010	18	A+	St. Lucie Mets	290	277	83	18	1	4	9	40	2	2	4	.300	.326	.415	.742	.116	.336	14	3	.328	109	+3	-1	—	—	+8	1.0
2010	18	A	Savannah Sand Gnats	307	277	77	18	2	7	23	37	5	2	1	.278	.344	.433	.777	.155	.298	12	7	.345	122	+8	+0	—	—	+9	1.7
2010	18	INTL	Bravos de Margarita	116	103	33	6	0	2	7	14	2	1	0	.320	.375	.437	.812	.117	.344	12	6	.352	128	+4	+0	—	—	+3	0.7
2011	19	A+	St. Lucie Mets	559	516	139	26	2	9	27	68	6	2	2	.269	.313	.380	.693	.110	.291	12	5	.306	92	-5	-0	—	—	+16	1.1
2011	19	INTL	Bravos de Margarita	152	133	40	6	0	2	17	26	1	2	0	.301	.384	.391	.775	.090	.358	17	11	.351	127	+5	+0	—	—	+4	1.0
2012	20	AA	Binghamton Mets	275	251	78	18	2	8	20	30	1	0	0	.311	.364	.494	.858	.183	.326	11	7	.374	145	+14	+0	—	—	+8	2.2
2012	20	A+	St. Lucie Mets	272	242	70	12	0	10	18	30	3	3	2	.289	.346	.463	.809	.174	.286	11	7	.347	124	+7	-0	—	—	+8	1.5
2012	20	INTL	Bravos de Margarita	218	195	53	10	1	5	17	30	3	0	1	.272	.340	.410	.750	.138	.298	14	8	.332	112	+3	-0	—	—	+6	0.9
2013	21	MLB	New York Mets	101	95	20	5	0	1	5	23	0	0	0	.211	.250	.295	.545	.084	.264	23	5	.244	45	-6	+0	+1	+2	+3	0.0
2013	21	AAA	Las Vegas 51s	463	424	136	36	4	15	25	63	3	1	3	.321	.363	.531	.893	.210	.342	14	5	.382	150	+26	-1	—	—	+13	3.9
2013	21	INTL	Bravos de Margarita	99	88	33	6	0	3	9	10	1	0	2	.375	.439	.545	.984	.170	.395	10	9	.431	188	+10	-1	—	—	+3	1.2
2014	22	MLB	New York Mets	274	259	65	13	1	6	12	31	1	1	0	.251	.287	.378	.665	.127	.265	11	4	.294	83	-5	+0	+6	+7	+8	1.6
2014	22	AAA	Las Vegas 51s	241	220	71	11	2	13	16	39	1	0	2	.323	.371	.568	.939	.245	.339	16	7	.403	166	+18	-1	—	—	+7	2.5
2014	22	INTL	Bravos de Margarita	96	90	29	3	0	6	3	13	3	3	0	.322	.365	.556	.920	.233	.324	14	3	.403	167	+7	+1	—	—	+3	1.1
2015	23	MLB	New York Mets	510	483	127	22	0	16	19	63	4	0	1	.263	.296	.408	.704	.145	.273	12	4	.310	96	-2	-0	+4	+6	+14	2.1
2015	23	INTL	Bravos de Margarita	17	14	4	2	0	1	2	2	1	0	0	.286	.412	.643	1.055	.357	.273	12	12	.452	204	+2	+0	—	—	+0	0.3
2016	24	MLB	New York Mets	335	307	82	14	0	16	23	48	2	1	1	.267	.322	.469	.791	.202	.268	14	7	.346	123	+9	-0	-5	+1	+9	1.4
2016	24	AA	Binghamton Mets	19	17	4	0	0	0	1	2	0	0	0	.235	.278	.235	.513	.000	.250	11	5	.227	32	-1	+0	—	—	+1	-0.1
2017	25	MLB	New York Mets	362	336	91	17	1	18	17	54	3	1	1	.271	.312	.488	.800	.217	.270	15	5	.345	122	+9	-0	-7	+1	+10	1.4
2018	26	MLB	New York Mets	429	386	103	25	0	11	29	42	5	0	0	.267	.326	.417	.743	.150	.269	10	7	.325	107	+3	+0	-1	-8	+12	0.7
2019	27	MLB	Arizona Diamondbacks	285	265	84	18	0	9	15	31	4	0	0	.317	.363	.487	.849	.170	.332	11	5	.375	145	+14	+0	+0	+1	+8	2.5
2020	28	MLB	San Francisco Giants	213	198	53	11	1	12	13	36	1	1	0	.268	.316	.515	.831	.247	.272	17	6	.360	134	+8	+0	+1	+1	+6	1.6
2021	29	MLB	San Francisco Giants	436	389	102	16	1	18	41	56	3	1	0	.262	.337	.447	.784	.185	.264	13	9	.346	123	+11	+0	+0	+2	+12	2.6
2022	30	MLB	San Francisco Giants	602	525	120	28	1	19	59	103	11	0	0	.229	.319	.394	.714	.166	.246	17	10	.318	102	+1	+0	-3	+2	+17	1.8
2023	31	MLB	San Francisco Giants	454	405	115	22	0	23	41	63	5	0	0	.284	.357	.509	.866	.225	.286	14	9	.378	148	+24	+0	-3	-10	+13	2.5
2023	31	INTL	Navegantes del Magallanes	96	82	25	7	0	1	13	9	1	0	0	.305	.406	.427	.833	.122	.333	9	14	.378	147	+5	+0	—	—	+3	0.8
2024	32	MLB	San Francisco Giants	242	214	44	12	0	4	20	33	3	0	0	.206	.283	.318	.600	.112	.220	14	8	.270	64	-10	+0	-2	-4	+7	-1.0
2025	33	MLB	San Francisco Giants	463	419	101	10	0	16	34	88	7	1	0	.241	.309	.379	.688	.138	.267	19	7	.309	94	-3	+0	-2	-8	+13	0.0
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			4706	4281	1107	213	5	169	328	671	49	6	3	.259	.319	.429	.748	.171	.269	14	7	.329	110	+54	+0	-10	-7	+133	17.3

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
Wilmer Flores (OGILVIE)	34	51	43→46	23	43	.236/.307/.392	.155	.255	12	1	17%	8%	98	+0.9	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Shawn Wooten 2006 · MLB	34	46→45	47→50	38→30	46	.230/.284/.359	.128	.256	16	3	18%	6%	79	+0.3	.215/.262/.313	.098	.261	10	3	21%	5%	57	-1.2	.197/.245/.263	.066	.249	6	1	22%	5%	35	-1.1
✕Andy Abad 2007 · AAA	34	49→51	50	40→45	48	.249/.299/.403	.153	.265	19	4	15%	6%	97	+1.5	.242/.287/.370	.128	.269	15	8	16%	5%	82	+0.5	.242/.283/.350	.109	.270	14	7	16%	5%	77	+0.1
●Scott Brosius 2001 · MLB	34	46→56	50	36→40	54	.235/.303/.386	.150	.248	19	3	15%	9%	94	+1.3	.260/.322/.414	.154	.291	17	5	17%	8%	108	+2.3	.280/.339/.435	.155	.321	16	4	17%	7%	117	+2.3
✕Shelley Duncan 2013 · MLB	33	42→43	54→60	40→45	51	.223/.301/.401	.178	.257	23	4	24%	9%	98	+1.6	.197/.264/.333	.136	.240	16	4	25%	8%	64	-0.8	.164/.225/.275	.111	.202	12	0	26%	7%	30	-2.3
✕Matt McBride 2019 · MLB	34	40→50	50→55	42→40	45	.211/.268/.372	.161	.245	18	4	23%	6%	76	+0.0	.216/.266/.391	.175	.257	23	6	26%	6%	80	+0.4	.184/.222/.370	.186	.199	30	0	27%	4%	53	-0.4
✕Edgar Gonzalez 2011 · MLB	33	50→57	47→45	37→50	48	.247/.311/.383	.136	.295	15	5	22%	8%	96	+1.5	.256/.305/.371	.115	.302	12	13	18%	6%	90	+1.0	.261/.305/.362	.101	.311	11	15	19%	6%	84	+0.4
✕Jason Michaels 2010 · MLB	34	48→55	48→50	41→45	51	.241/.309/.390	.149	.282	15	6	21%	8%	98	+1.6	.230/.292/.380	.150	.265	15	5	19%	7%	88	+0.9	.212/.268/.341	.129	.240	13	1	18%	6%	63	-0.2
✕Carlos Valencia 2014 · AAA	34	47→57	51→60	38→40	39	.240/.269/.398	.158	.273	18	4	20%	3%	82	+0.5	.222/.254/.355	.133	.255	17	4	21%	4%	65	-0.7	.213/.246/.317	.104	.252	15	3	22%	4%	50	-0.9
✕Russ Johnson 2007 · MLB	34	48→47	48→50	41→45	53	.240/.308/.384	.144	.265	15	6	16%	9%	95	+1.4	.233/.295/.363	.130	.252	14	7	14%	8%	85	+0.7	.226/.288/.344	.118	.238	12	6	11%	8%	73	-0.1
●Vinny Castilla 2002 · MLB	35	48→53	52→60	36→40	47	.246/.293/.413	.167	.264	20	3	17%	6%	97	+1.5	.253/.297/.423	.170	.270	20	3	15%	5%	101	+1.8	.264/.321/.464	.200	.282	23	2	16%	7%	115	+2.8
✕Edgard Clemente 2010 · AAA	34	49	53→55	40	49	.251/.317/.425	.174	.293	22	6	22%	8%	110	+2.4	.259/.317/.432	.173	.312	21	7	23%	7%	112	+2.6	.244/.306/.429	.185	.305	25	9	28%	7%	104	+0.4
✕Abraham Valencia 2014 · AAA	34	47→53	51→50	43→45	41	.241/.298/.396	.155	.280	20	4	22%	4%	95	+1.4	.242/.303/.356	.114	.291	12	6	21%	5%	86	+0.8	.253/.319/.319	.065	.304	6	3	18%	5%	80	+0.2
✕Eric Karros 2002 · MLB	34	46→55	55	43→40	52	.243/.314/.423	.180	.268	23	5	20%	9%	108	+2.3	.260/.318/.409	.149	.285	17	5	15%	8%	106	+2.2	.266/.320/.403	.137	.286	15	3	13%	7%	101	+1.1
●Andy Tracy 2008 · AAA	34	42→48	51→55	41→45	50	.221/.296/.380	.159	.265	19	6	25%	9%	90	+1.0	.233/.302/.409	.176	.279	22	6	24%	8%	99	+1.7	.233/.303/.420	.187	.276	24	5	25%	8%	104	+1.7
●Ryan Ludwick 2012 · MLB	34	49→56	51→65	38→45	51	.249/.320/.408	.158	.291	19	3	21%	9%	107	+2.2	.248/.316/.415	.167	.293	20	2	22%	8%	107	+2.2	.246/.313/.411	.165	.291	19	0	22%	8%	99	+1.0
✕Ty Wigginton 2011 · MLB	33	50→55	52→60	37→50	50	.258/.317/.424	.166	.279	20	3	16%	7%	110	+2.4	.238/.308/.385	.147	.275	17	6	20%	9%	96	+1.5	.231/.310/.377	.146	.268	18	7	20%	9%	89	+0.6
✕Gerald Williams 2001 · MLB	34	52→53	50	42→55	47	.264/.306/.418	.153	.286	18	11	16%	5%	103	+1.9	.229/.283/.358	.129	.260	13	18	17%	6%	78	+0.2	.206/.255/.344	.138	.235	12	17	18%	5%	60	-0.4
●Steve Pearce 2018 · MLB	35	48→57	55→60	38→50	51	.251/.323/.436	.185	.278	23	3	20%	9%	115	+2.8	.248/.330/.420	.172	.288	20	3	21%	9%	115	+2.7	.236/.331/.400	.164	.278	19	0	22%	10%	108	+0.8
●Aaron Guiel 2005 · MLB	32	46→53	51→60	36→45	50	.237/.314/.402	.165	.272	18	6	20%	8%	103	+1.9	.233/.315/.424	.191	.266	23	6	22%	8%	109	+2.4	.228/.313/.423	.195	.258	24	4	22%	8%	107	+2.1
✕Chad Mottola 2006 · MLB	34	41→44	51→55	40→45	41	.218/.260/.378	.160	.253	20	5	23%	5%	74	-0.1	.224/.263/.377	.153	.270	18	8	24%	5%	75	-0.0	.224/.262/.376	.153	.268	18	8	24%	4%	70	-0.2

Contract

Career Projections (MLE) Show advanced cols

Historical Stats — Raw (Per Stint)

Career Path Comps

Career Projections (MLE)