Yolmer Sánchez

2B Salt Lake Bees

Age 35 S/R 5'8" / 210 lbs AAA K +5%HR +4% Svc 13.000 · Ctrl thru 2027

Overview

AAAExt / FA-dealFA 2028

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2024	32	AAANYM	399	.226/.347/.393	9	9	56	—	.175/.266/.294
2025	33	AAALAA	492	.246/.358/.329	4	9	49	—	.197/.280/.261
2026	34	AAALAA	513	.274/.380/.407	8	20	70	—	.219/.296/.311
2027PROJ10% MLB	35	MLBLAA	38	.211/.290/.297	0	1	70	-0.0
2028PROJ	36	MLBLAA	278	.199/.277/.273	2	3	60	-1.1

Next 2 projected WAR -1.1Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service13.000First FA2028

2027Ext / FA-deal$1M

Skills · percentileStatcast 2019-2022

Speed30

Avg EV23

xwOBA20

Barrel%10

CompsDaniel Hinojosa (age 35) · Munenori Kawasaki (age 35) · Ramon Valdez (age 35)

2027 FULL-SEASON PROJECTIONstats below = full-season projection

showingPROJ

wRC+†70

AVG/OBP/SLG.211 / .290 / .297

PA38

HR0

K%26

BB%8

BABIP286

ISO29

MLB%10%

Value2027 · WAR

trajectory · projected WAR by year

Tools · Contract

ToolsStatcast %ile · 2019-2022

CONTACT

xAVG

160.223

POWER

Barrel%

101.5

Avg EV

2387.0

SPEED

Sprint

3026.5

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

Status FA

MLB Debut 2014

Service 13.000 yrs.days

Team Control Through 2027

First FA Year 2028

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

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)
2009	17	ROK	DSL White Sox	—	42	32	5	0	0	0	8	10	1	1	0	156	341	156	498		227	24	19	258	11	—	—	—	—	—	—
2010	18	ROK	DSL White Sox	—	203	156	42	5	2	1	41	26	4	7	3	269	433	346	779	77	315	13	20	365	59	—	—	—	—	—	—
2011	19	A	Kannapolis Intimidators	—	294	264	76	10	1	1	15	49	7	7	8	288	343	345	687	57	349	17	5	306	71	—	—	—	—	—	—
2011	19	ROK	Bristol White Sox	—	24	16	4	1	0	0	5	2	3	1	2	250	500	312	812	62	286	8	21	404	95	—	—	—	—	—	—
2012	20	AAA	Charlotte Knights	—	39	39	10	2	0	0	0	6	0	0	0	256	256	308	564	51	303	15	0	251	35	—	—	—	—	—	—
2012	20	AA	Birmingham Barons	—	133	119	44	9	1	0	10	22	2	7	5	370	427	462	890	92	449	17	8	394	144	—	—	—	—	—	—
2012	20	A+	Winston-Salem Dash	—	416	365	115	14	6	1	31	64	7	19	10	315	380	395	774	79	373	15	7	340	93	—	—	—	—	—	—
2012	20	INTL	Tiburones de La Guaira	—	136	120	36	7	2	0	13	26	1	11	3	300	373	392	765	92	379	19	10	342	117	—	—	—	—	—	—
2013	21	AAA	Charlotte Knights	—	479	432	104	20	2	0	29	76	4	16	7	241	295	296	591	56	290	16	6	264	57	—	—	—	—	—	—
2013	21	INTL	Tiburones de La Guaira	—	265	221	77	10	4	1	30	35	3	5	4	348	433	443	877	95	404	13	11	380	143	—	—	—	—	—	—
2014	22	MLB	Chicago White Sox	—	104	100	25	5	0	0	3	25	0	1	1	250	272	300	572	50	329	24	3	256	59	-5	-0	+2	+3	+2	0.2
2014	22	AAA	Charlotte Knights	—	494	437	128	19	6	7	36	84	5	16	4	293	354	412	765	119	344	17	7	333	103	—	—	—	—	—	—
2014	22	INTL	Tiburones de La Guaira	—	177	155	41	9	0	2	14	24	5	4	1	265	345	361	706	97	300	14	8	318	101	—	—	—	—	—	—
2015	23	MLB	Chicago White Sox	—	420	389	87	23	1	5	19	81	5	2	2	224	269	326	595	103	270	19	5	264	64	-18	-0	+7	+2	+9	-0.0
2015	23	AAA	Charlotte Knights	—	137	131	45	10	0	2	4	28	1	5	2	344	368	466	833	122	426	20	3	368	97	—	—	—	—	—	—
2015	23	INTL	Tiburones de La Guaira	—	47	46	16	2	1	2	0	9	1	2	0	348	362	565	927	217	400	19	0	405	160	—	—	—	—	—	—
2016	24	MLB	Chicago White Sox	—	163	154	32	9	1	4	5	42	1	0	1	208	237	357	595	149	257	26	3	258	59	-8	-0	-0	+2	+4	-0.4
2016	24	AAA	Charlotte Knights	—	260	235	60	11	2	8	17	55	2	10	4	255	311	421	732	166	299	21	7	318	82	—	—	—	—	—	—
2017	25	MLB	Chicago White Sox	—	534	484	129	19	8	12	35	111	4	8	9	267	321	413	734	147	321	21	7	320	100	+0	-2	+6	+2	+12	1.8
2018	26	MLB	Chicago White Sox	—	662	600	145	34	10	8	49	138	8	14	6	242	307	372	679	130	300	21	7	303	91	-7	+0	+8	+2	+14	1.8
2019	27	MLB	Chicago White Sox	—	555	496	125	20	4	2	44	117	5	5	4	252	319	321	640	69	324	21	8	289	80	-13	-1	+1	+2	+12	0.1
2020	28	MLB	Chicago White Sox	—	21	16	5	3	0	1	5	5	0	0	0	312	476	688	1.164	375	400	24	24	492	217	+3	+0	-1	+0	+0	0.2
2021	29	AAA	Gwinnett Stripers	—	355	310	67	9	3	9	35	88	7	6	3	216	310	352	661	135	271	25	10	299	38	—	—	—	—	—	—
2022	30	MLB	New York Mets	—	44	37	4	0	0	0	5	13	0	0	2	108	214	108	322		167	30	11	162	-3	-5	-1	+1	+2	+1	-0.2
2022	30	AAA	Syracuse Mets	—	396	325	80	16	1	10	60	86	7	6	1	246	375	394	769	148	302	22	15	348	71	—	—	—	—	—	—
2022	30	INTL	Tiburones de La Guaira	—	168	135	30	2	2	0	30	28	1	2	2	222	367	267	634	44	278	17	18	304	92	—	—	—	—	—	—
2023	31	AAA	Gwinnett Stripers	—	481	377	89	15	2	8	89	106	5	4	3	236	389	350	739	114	298	22	19	339	70	—	—	—	—	—	—
2024	32	AAA	Syracuse Mets	—	399	336	76	23	3	9	55	84	7	9	0	226	347	393	740	167	275	21	14	335	56	—	—	—	—	—	—
2025	33	AAA	Salt Lake Bees	—	492	414	102	16	3	4	67	114	5	9	3	246	358	329	687	82	329	23	14	316	49	—	—	—	—	—	—
2026	34	AAA	Salt Lake Bees	—	513	430	118	29	2	8	61	117	12	20	5	274	380	407	787	133	353	23	12	351	70	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2503	2276	552	113	24	32	165	532	23	30	25	243	300	355	656	113	301	21	7	291	83	-50	-4	+23	+15	+54	3.9
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2009	17	ROK MLE	DSL White Sox	—	42	34	4	0	0	0	6	12	1	1	0	118	268	118	386		158	29	14	184	11	—	—	—	—	—	—
2010	18	ROK MLE	DSL White Sox	—	203	168	30	3	1	1	29	32	4	7	3	179	313	226	540	48	214	16	14	255	59	—	—	—	—	—	—
2011	19	A MLE	Kannapolis Intimidators	—	294	269	73	10	1	1	10	63	7	7	8	271	315	327	642	56	334	21	3	273	71	—	—	—	—	—	—
2011	19	ROK MLE	Bristol White Sox	—	24	18	4	1	0	0	3	3	3	1	2	222	417	278	694	56	235	12	12	308	95	—	—	—	—	—	—
2012	20	AAA MLE	Charlotte Knights	—	39	39	9	2	0	0	0	7	0	0	0	231	231	282	513	51	284	18	0	220	35	—	—	—	—	—	—
2012	20	AA MLE	Birmingham Barons	—	133	122	46	10	1	0	7	27	2	7	5	377	420	475	895	98	461	20	5	381	144	—	—	—	—	—	—
2012	20	A+ MLE	Winston-Salem Dash	—	416	376	111	13	5	1	20	93	7	19	10	295	342	364	707	69	365	22	5	306	93	—	—	—	—	—	—
2013	21	AAA MLE	Charlotte Knights	—	479	439	107	19	2	0	22	89	4	16	7	244	286	296	582	52	291	19	5	253	57	—	—	—	—	—	—
2014	22	MLB MLE	Chicago White Sox	—	104	100	25	5	0	0	3	25	0	1	1	250	272	300	572	50	329	24	3	255	59	-5	-0	+2	+3	+2	0.2
2014	22	AAA MLE	Charlotte Knights	—	494	447	134	18	7	6	26	103	5	16	4	300	345	412	757	112	354	21	5	320	103	—	—	—	—	—	—
2015	23	MLB MLE	Chicago White Sox	—	420	389	87	23	1	5	19	81	5	2	2	224	269	326	595	103	270	19	5	263	64	-18	-0	+7	+2	+9	-0.0
2015	23	AAA MLE	Charlotte Knights	—	137	132	40	8	0	1	3	35	1	5	2	303	324	386	710	83	401	26	2	311	97	—	—	—	—	—	—
2016	24	MLB MLE	Chicago White Sox	—	163	154	32	9	1	4	5	42	1	0	1	208	237	357	595	149	257	26	3	256	59	-8	-0	-0	+2	+4	-0.4
2016	24	AAA MLE	Charlotte Knights	—	260	240	58	10	2	8	12	63	2	10	4	242	283	400	683	158	285	24	5	290	82	—	—	—	—	—	—
2017	25	MLB MLE	Chicago White Sox	—	534	486	129	19	8	12	33	111	4	8	9	265	317	412	729	146	321	21	6	316	100	+0	-2	+6	+2	+12	1.8
2018	26	MLB MLE	Chicago White Sox	—	662	600	145	34	10	8	49	138	8	14	6	242	307	372	679	130	300	21	7	302	91	-7	+0	+8	+2	+14	1.8
2019	27	MLB MLE	Chicago White Sox	—	555	497	125	20	4	2	43	117	5	5	4	252	317	320	637	68	324	21	8	287	80	-13	-1	+1	+2	+12	0.1
2020	28	MLB MLE	Chicago White Sox	—	21	16	5	3	0	1	5	5	0	0	0	312	476	688	1.164	375	400	24	24	488	217	+3	+0	-1	+0	+0	0.2
2021	29	AAA MLE	Gwinnett Stripers	—	355	322	55	7	2	6	23	108	7	6	3	171	241	261	502	90	229	30	6	225	38	—	—	—	—	—	—
2022	30	MLB MLE	New York Mets	—	44	37	4	0	0	0	5	13	0	0	2	108	214	108	322		167	30	11	164	-3	-5	-1	+1	+2	+1	-0.2
2022	30	AAA MLE	Syracuse Mets	—	396	347	71	13	1	7	38	107	7	6	1	205	296	308	604	104	268	27	10	273	71	—	—	—	—	—	—
2023	31	AAA MLE	Gwinnett Stripers	—	481	407	81	13	2	6	59	127	5	4	3	199	308	285	593	86	256	26	12	272	70	—	—	—	—	—	—
2024	32	AAA MLE	Syracuse Mets	—	399	354	62	18	3	6	37	104	7	9	0	175	266	294	560	119	227	26	9	251	56	—	—	—	—	—	—
2025	33	AAA MLE	Salt Lake Bees	—	492	436	86	13	3	3	45	140	5	9	3	197	280	261	541	64	272	28	9	241	49	—	—	—	—	—	—
2026	34	AAA MLE	Salt Lake Bees	—	513	453	99	23	2	5	38	141	12	20	5	219	296	311	607	93	288	27	7	272	70	—	—	—	—	—	—
2009	17	ROK MLE	DSL White Sox	—	42	34	4	0	0	0	6	12	1	1	0	118	268	118	386		182	29	14	184	11	—	—	—	—	—	—
2009	17	ROK RAW	DSL White Sox	—	42	32	5	0	0	0	8	10	1	1	0	156	341	156	498		227	24	19	258	11	—	—	—	—	—	—
2010	18	ROK MLE	DSL White Sox	—	203	168	30	3	1	1	29	32	4	7	3	179	313	226	540	48	213	16	14	255	59	—	—	—	—	—	—
2010	18	ROK RAW	DSL White Sox	—	203	156	42	5	2	1	41	26	4	7	3	269	433	346	779	77	315	13	20	365	59	—	—	—	—	—	—
2011	19	A MLE	2 teams	—	318	287	76	10	1	1	13	66	10	8	10	265	319	317	636	52	339	21	4	276	73	—	—	—	—	—	—
2011	19	A RAW	2 teams	—	318	280	80	11	1	1	20	51	10	8	10	286	355	343	698	57	345	16	6	314	73	—	—	—	—	—	—
2012	20	A+ MLE	4 teams	—	724	664	203	30	7	1	33	157	10	37	18	306	348	377	724	71	393	22	5	317	101	—	—	—	—	—	—
2012	20	A+ RAW	4 teams	—	724	643	205	32	9	1	54	118	10	37	18	319	380	401	782	82	383	16	7	346	101	—	—	—	—	—	—
2013	21	AAA MLE	2 teams	—	744	679	166	29	4	0	33	138	7	21	11	244	287	299	585	54	303	19	4	253	57	—	—	—	—	—	—
2013	21	AAA RAW	2 teams	—	744	653	181	30	6	1	59	111	7	21	11	277	344	346	690	69	329	15	8	305	57	—	—	—	—	—	—
2014	22	AAA MLE	3 teams	—	775	708	205	30	9	7	37	166	10	21	6	290	334	387	721	97	365	21	5	309	95	—	—	—	—	—	—
2014	22	AAA RAW	3 teams	—	775	692	194	33	6	9	53	133	10	21	6	280	340	384	725	104	332	17	7	319	95	—	—	—	—	—	—
2015	23	MLB MLE	3 teams	—	604	565	138	34	1	7	24	125	7	9	4	244	284	345	629	101	302	21	4	275	72	-20	+0	+7	+2	+13	0.2
2015	23	MLB RAW	3 teams	—	604	566	148	35	2	9	23	118	7	9	4	261	299	378	677	117	316	20	4	299	72	-20	+0	+7	+2	+13	0.2
2016	24	AAA MLE	2 teams	—	423	394	89	19	3	11	17	105	3	10	5	226	263	373	636	147	278	25	4	277	74	—	—	—	—	—	—
2016	24	AAA RAW	2 teams	—	423	389	92	20	3	12	22	97	3	10	5	237	283	396	678	159	283	23	5	295	74	—	—	—	—	—	—
2017	25	MLB MLE	Chicago White Sox	—	534	486	129	19	8	12	33	111	4	8	9	265	317	412	729	146	319	21	6	316	100	+0	-2	+6	+2	+12	1.8
2017	25	MLB RAW	Chicago White Sox	—	534	484	129	19	8	12	35	111	4	8	9	267	321	413	734	147	321	21	7	320	100	+0	-2	+6	+2	+12	1.8
2018	26	MLB MLE	Chicago White Sox	—	662	600	145	34	10	8	49	138	8	14	6	242	307	372	679	130	300	21	7	302	91	-7	+0	+8	+2	+14	1.8
2018	26	MLB RAW	Chicago White Sox	—	662	600	145	34	10	8	49	138	8	14	6	242	307	372	679	130	300	21	7	303	91	-7	+0	+8	+2	+14	1.8
2019	27	MLB MLE	Chicago White Sox	—	555	497	125	20	4	2	43	117	5	5	4	252	317	320	637	68	323	21	8	287	80	-13	-1	+1	+2	+12	0.1
2019	27	MLB RAW	Chicago White Sox	—	555	496	125	20	4	2	44	117	5	5	4	252	319	321	640	69	324	21	8	289	80	-13	-1	+1	+2	+12	0.1
2020	28	MLB MLE	Chicago White Sox	—	21	16	5	3	0	1	5	5	0	0	0	312	476	688	1.164	375	400	24	24	488	217	+3	+0	-1	+0	+0	0.2
2020	28	MLB RAW	Chicago White Sox	—	21	16	5	3	0	1	5	5	0	0	0	312	476	688	1.164	375	400	24	24	492	217	+3	+0	-1	+0	+0	0.2
2021	29	AAA MLE	Gwinnett Stripers	—	355	322	55	7	2	6	23	108	7	6	3	171	241	261	502	90	234	30	6	225	38	—	—	—	—	—	—
2021	29	AAA RAW	Gwinnett Stripers	—	355	310	67	9	3	9	35	88	7	6	3	216	310	352	661	135	271	25	10	299	38	—	—	—	—	—	—
2022	30	AAA MLE	3 teams	—	608	533	104	19	1	9	59	166	8	8	5	195	285	285	570	90	262	27	10	262	64	—	—	—	—	—	—
2022	30	AAA RAW	3 teams	—	608	497	114	18	3	10	95	127	8	8	5	229	362	338	700	109	286	21	16	322	64	—	—	—	—	—	—
2023	31	AAA MLE	Gwinnett Stripers	—	481	407	81	13	2	6	59	127	5	4	3	199	308	285	593	86	265	26	12	272	70	—	—	—	—	—	—
2023	31	AAA RAW	Gwinnett Stripers	—	481	377	89	15	2	8	89	106	5	4	3	236	389	350	739	114	298	22	19	339	70	—	—	—	—	—	—
2024	32	AAA MLE	Syracuse Mets	—	399	354	62	18	3	6	37	104	7	9	0	175	266	294	560	119	229	26	9	251	56	—	—	—	—	—	—
2024	32	AAA RAW	Syracuse Mets	—	399	336	76	23	3	9	55	84	7	9	0	226	347	393	740	167	275	21	14	335	56	—	—	—	—	—	—
2025	33	AAA MLE	Salt Lake Bees	—	492	436	86	13	3	3	45	140	5	9	3	197	280	261	541	64	281	28	9	241	49	—	—	—	—	—	—
2025	33	AAA RAW	Salt Lake Bees	—	492	414	102	16	3	4	67	114	5	9	3	246	358	329	687	82	329	23	14	316	49	—	—	—	—	—	—
2026	34	AAA MLE	Salt Lake Bees	—	513	453	99	23	2	5	38	141	12	20	5	219	296	311	607	93	299	27	7	272	70	—	—	—	—	—	—
2026	34	AAA RAW	Salt Lake Bees	—	513	430	118	29	2	8	61	117	12	20	5	274	380	407	787	133	353	23	12	351	70	—	—	—	—	—	—
2009	17	ROK MLE	DSL White Sox	—	42	35	4	0	0	0	6	12	1	1	0	114	268	114	383		158	29	14	184	11	—	—	—	—	—	—
2010	18	ROK MLE	DSL White Sox	—	203	168	30	3	1	1	29	32	4	7	3	179	313	226	540	48	214	16	14	255	59	—	—	—	—	—	—
2011	19	A MLE	2 teams	—	318	292	76	10	1	1	13	66	10	8	10	260	319	312	631	51	327	21	4	276	73	—	—	—	—	—	—
2012	20	A+ MLE	4 teams	—	724	675	203	30	7	1	33	157	10	37	18	301	348	370	718	70	381	22	5	317	101	—	—	—	—	—	—
2013	21	AAA MLE	2 teams	—	744	698	166	29	4	0	33	138	7	21	11	238	287	291	577	53	291	19	4	253	57	—	—	—	—	—	—
2014	22	AAA MLE	3 teams	—	775	722	205	30	9	7	37	166	10	21	6	284	334	380	713	96	350	21	5	309	95	—	—	—	—	—	—
2015	23	MLB MLE	3 teams	—	604	568	138	34	1	7	24	125	7	9	4	243	284	343	627	100	302	21	4	275	72	—	—	—	—	—	—
2016	24	AAA MLE	2 teams	—	423	400	89	19	3	11	17	105	3	10	5	223	263	367	631	145	274	25	4	277	74	—	—	—	—	—	—
2017	25	MLB MLE	Chicago White Sox	—	534	492	129	19	8	12	33	111	4	8	9	262	317	407	724	144	321	21	6	316	100	—	—	—	—	—	—
2018	26	MLB MLE	Chicago White Sox	—	662	600	145	34	10	8	49	138	8	14	6	242	307	372	679	130	300	21	7	302	91	—	—	—	—	—	—
2019	27	MLB MLE	Chicago White Sox	—	555	502	125	20	4	2	43	117	5	5	4	249	317	317	634	68	324	21	8	287	80	—	—	—	—	—	—
2020	28	MLB MLE	Chicago White Sox	—	21	16	5	3	0	1	5	5	0	0	0	312	476	688	1.164	375	400	24	24	488	217	—	—	—	—	—	—
2021	29	AAA MLE	Gwinnett Stripers	—	355	322	55	7	2	6	23	108	7	6	3	171	241	261	502	90	229	30	6	225	38	—	—	—	—	—	—
2022	30	AAA MLE	3 teams	—	608	536	104	19	1	9	59	166	8	8	5	194	285	284	569	90	258	27	10	262	64	—	—	—	—	—	—
2023	31	AAA MLE	Gwinnett Stripers	—	481	414	81	13	2	6	59	127	5	4	3	196	308	280	588	85	256	26	12	272	70	—	—	—	—	—	—
2024	32	AAA MLE	Syracuse Mets	—	399	352	62	18	3	6	37	104	7	9	0	176	266	295	562	119	227	26	9	251	56	—	—	—	—	—	—
2025	33	AAA MLE	Salt Lake Bees	—	492	439	86	13	3	3	45	140	5	9	3	196	280	260	540	64	272	28	9	241	49	—	—	—	—	—	—
2026	34	AAA MLE	Salt Lake Bees	—	513	458	99	23	2	5	38	141	12	20	5	216	296	308	604	92	288	27	7	272	70	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	32	AAA MLE	Syracuse Mets	—	399	352	62	18	3	6	37	104	7	9	0	176	266	295	562	119	227	26	9	251	56	—	—	—	—	—	—
2025	33	AAA MLE	Salt Lake Bees	—	492	439	86	13	3	3	45	140	5	9	3	196	280	260	540	64	272	28	9	241	49	—	—	—	—	—	—
2026	34	AAA MLE	Salt Lake Bees	—	513	458	99	23	2	5	38	141	12	20	5	216	296	308	604	92	288	27	7	272	70	—	—	—	—	—	—
▸ 2027 season
▸ 2027 — full MLE projection (neutral park, full availability)
2027	35	MLB MLE	LAA	10%	465	416	88	19	2	4	39	124	7	11	3	212	291	300	591	88	288	27	8	271	70	-17	+1	+2	+2	+10	0.0
▸ 2027 — real world (MLB)
2027	35	MLB CTX	LAA	10%	38	34	6	1	0	0	3	10	1	1	0	211	290	297	587	86	286	26	8	269	70	-1	+0	+0	+0	+1	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (PA × MLB%)
2028	36	MLB MLE	LAA	100%	278	249	50	10	1	2	23	77	4	3	1	201	279	276	555	75	278	28	8	256	60	-13	+0	-5	+1	+6	-1.1
2028	36	MLB CTX	LAA	100%	278	249	50	10	1	2	23	77	4	3	1	199	277	273	551	74	276	28	8	255	60	-13	+0	-5	+1	+6	-1.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2781	2525	602	123	25	34	188	609	27	33	26	238	298	347	646	109	300	22	7	288	74	-63	-4	+18	+16	+60	2.8
/ 162G	—	A+C		—	650	590	141	29	6	8	44	142	6	8	6	239	298	349	647	110	300	22	7	288	74	-15	-1	+4	+4	+14	0.6
Career	—	MLE		—	9108	8188	1924	349	64	92	638	2136	123	209	98	235	300	327	627	92	304	23	7	278	74	-77	-3	+19	+17	+68	2.6
/ 162G	—	MLE		—	650	584	138	25	5	7	46	152	9	15	7	236	303	332	635	96	305	23	7	278	74	-16	-1	+4	+4	+14	0.5

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 AAASalt Lake Bees · 513 PAwOBA .346 → .272 (−74)K% 22.8% → 27.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.81%	÷1.000	×1.200	—	—	27.37%
BB% (unintentional) /PA	11.50%	÷1.000	×0.690	—	×0.940	7.46%
HBP% /PA	2.34%	—	×0.940	—	×0.940	2.07%
Singles /BIP	25.24%	÷1.000	×0.930	×0.968	×0.940	21.36%
Doubles /BIP	9.27%	÷1.000	×0.830	×0.968	×0.940	7.00%
Triples /BIP	0.64%	÷1.000	×0.970	×0.968	×0.940	0.56%
Home runs /BIP	2.56%	÷1.000	×0.700	—	×0.940	1.68%

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 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.968.

Result: wOBA .346 → .272; ISO .133 → .099; BABIP .353 → .288. 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 AAASalt Lake Bees · 492 PAwOBA .310 → .241 (−69)K% 23.2% → 28.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.17%	÷0.978	×1.200	—	—	28.43%
BB% (unintentional) /PA	13.62%	÷0.964	×0.690	—	×0.942	9.18%
HBP% /PA	1.02%	—	×0.940	—	×0.942	0.90%
Singles /BIP	26.33%	÷1.046	×0.930	×1.001	×0.942	22.09%
Doubles /BIP	5.33%	÷1.005	×0.830	×1.001	×0.942	4.15%
Triples /BIP	1.00%	÷1.079	×0.970	×1.001	×0.942	0.85%
Home runs /BIP	1.33%	÷0.989	×0.700	—	×0.942	0.89%

Factors used: league row International League. Park (home-season share, regressed): HR 98, 1B 109, 2B 101, 3B 116, K 96, BB 93 — applied at half strength. Age: age 33 vs a level average of 27.2 → −5.8% on BB/HBP/hit rates (5.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.001.

Result: wOBA .310 → .241; ISO .082 → .062; BABIP .329 → .272. 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 AAASyracuse Mets · 399 PAwOBA .326 → .251 (−75)K% 21.1% → 26.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.05%	÷0.968	×1.200	—	—	26.11%
BB% (unintentional) /PA	13.28%	÷0.933	×0.690	—	×0.952	9.35%
HBP% /PA	1.75%	—	×0.940	—	×0.952	1.57%
Singles /BIP	16.27%	÷1.006	×0.930	×0.971	×0.952	13.90%
Doubles /BIP	9.13%	÷0.972	×0.830	×0.971	×0.952	7.20%
Triples /BIP	1.19%	÷0.900	×0.970	×0.971	×0.952	1.19%
Home runs /BIP	3.57%	÷1.059	×0.700	—	×0.952	2.25%

Factors used: league row International League. Park (home-season share, regressed): HR 112, 1B 101, 2B 94, 3B 80, K 94, BB 87 — applied at half strength. Age: age 32 vs a level average of 27.2 → −4.8% on BB/HBP/hit rates (4.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.

Result: wOBA .326 → .251; ISO .167 → .122; BABIP .275 → .227. 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 AAAGwinnett Stripers · 481 PAwOBA .337 → .272 (−66)K% 22.0% → 26.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.04%	÷1.005	×1.200	—	—	26.32%
BB% (unintentional) /PA	18.50%	÷0.997	×0.690	—	×0.962	12.32%
HBP% /PA	1.04%	—	×0.940	—	×0.962	0.94%
Singles /BIP	23.62%	÷0.968	×0.930	×0.951	×0.962	20.75%
Doubles /BIP	5.54%	÷0.933	×0.830	×0.951	×0.962	4.51%
Triples /BIP	0.74%	÷0.999	×0.970	×0.951	×0.962	0.66%
Home runs /BIP	2.95%	÷0.984	×0.700	—	×0.962	2.02%

Factors used: league row International League. Park (home-season share, regressed): HR 97, 1B 94, 2B 87, 3B 100, K 101, BB 99 — applied at half strength. Age: age 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.951.

Result: wOBA .337 → .272; ISO .114 → .092; BABIP .298 → .256. 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 AAASyracuse Mets · 396 PAwOBA .341 → .273 (−68)K% 21.7% → 27.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.72%	÷0.961	×1.200	—	—	27.12%
BB% (unintentional) /PA	14.65%	÷1.019	×0.690	—	×0.972	9.64%
HBP% /PA	1.77%	—	×0.940	—	×0.972	1.62%
Singles /BIP	22.18%	÷0.953	×0.930	×0.973	×0.972	20.47%
Doubles /BIP	6.69%	÷0.951	×0.830	×0.973	×0.972	5.53%
Triples /BIP	0.42%	÷1.000	×0.970	×0.973	×0.972	0.38%
Home runs /BIP	4.18%	÷1.033	×0.700	—	×0.972	2.76%

Factors used: league row International League. Park (home-season share, regressed): HR 107, 1B 91, 2B 90, 3B 100, K 92, BB 104 — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.973.

Result: wOBA .341 → .273; ISO .148 → .109; BABIP .302 → .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).

2021 AAAGwinnett Stripers · 355 PAwOBA .293 → .225 (−68)K% 24.8% → 30.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.79%	÷0.975	×1.200	—	—	30.50%
BB% (unintentional) /PA	9.86%	÷1.014	×0.690	—	×0.982	6.59%
HBP% /PA	1.97%	—	×0.940	—	×0.982	1.82%
Singles /BIP	20.72%	÷1.011	×0.930	×0.975	×0.982	18.26%
Doubles /BIP	4.05%	÷1.039	×0.830	×0.975	×0.982	3.10%
Triples /BIP	1.35%	÷1.150	×0.920	×0.975	×0.982	1.04%
Home runs /BIP	4.05%	÷1.001	×0.700	—	×0.982	2.79%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 100, 1B 102, 2B 108, 3B 130, K 95, BB 103 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.975.

Result: wOBA .293 → .225; ISO .135 → .095; BABIP .271 → .229. 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).

2016 AAACharlotte Knights · 260 PAwOBA .311 → .290 (−22)K% 21.2% → 24.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.15%	÷1.053	×1.200	—	—	24.11%
BB% (unintentional) /PA	6.54%	÷0.990	×0.690	—	×1.048	4.78%
HBP% /PA	0.77%	—	×0.940	—	×1.048	0.76%
Singles /BIP	21.67%	÷1.031	×0.930	×1.017	×1.048	20.81%
Doubles /BIP	6.11%	÷0.974	×0.830	×1.017	×1.048	5.55%
Triples /BIP	1.11%	÷0.926	×0.970	×1.017	×1.048	1.24%
Home runs /BIP	4.44%	÷0.950	×0.840	—	×1.048	4.12%

Factors used: league row IL. Park (home-season share, regressed): HR 90, 1B 106, 2B 95, 3B 85, K 111, BB 98 — 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 ×1.017.

Result: wOBA .311 → .290; ISO .166 → .159; BABIP .299 → .285. 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).

2015 AAACharlotte Knights · 137 PAwOBA .358 → .311 (−47)K% 20.4% → 25.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.44%	÷0.971	×1.200	—	—	25.26%
BB% (unintentional) /PA	2.92%	÷1.017	×0.690	—	×1.050	2.08%
HBP% /PA	0.73%	—	×0.940	—	×1.050	0.72%
Singles /BIP	32.04%	÷0.973	×0.930	×0.973	×1.050	31.29%
Doubles /BIP	9.71%	÷0.993	×0.830	×0.973	×1.050	8.29%
Triples /BIP	0.00%	÷1.150	×0.970	×0.973	×1.050	0.00%
Home runs /BIP	1.94%	÷1.306	×0.840	—	×1.050	1.31%

Factors used: league row IL. Park (home-season share, regressed): HR 161, 1B 95, 2B 99, 3B 130, K 94, 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 ×0.973.

Result: wOBA .358 → .311; ISO .122 → .092; BABIP .426 → .401. 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
#1Gordon Beckhamlast yr '19 career totals — 10 seasons, 3,764 PA	5.7	3,764	80	34	237	301	368	+13	+19	8.2	8.4
/162	664	14	6	+2.4	+3.4	1.4	pk7: 9
#2Ronny Cedenolast yr '13 career totals — 9 seasons, 2,783 PA	4.2	2,783	40	39	246	289	354	+28	+19	5.5	5.6
/162	664	10	9	+6.7	+4.5	1.3	pk7: 6
#3Casey Candaele'86-'97 * career totals — 7 seasons, 2,132 PA	3.2	2,132	11	37	246*	305*	350*	+5	+26	4.2	4.6
/162	664	3	12	+1.5	+8.1	1.3	pk7: 5
#4Carlos Sanchez'14-'22 * career totals — 6 seasons, 2,503 PA	3.8	2,503	32	30	248*	305*	353*	+8	+0	2.1	2.6
/162	664	8	8	+2.0	+0.0	0.6	pk7: 3
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 7 projected seasons	4.1	2,754	33	34	239	294	347	+4	+23	1.9	2.3
/162	664	8	8	+0.9	+5.6	0.5	pk7: 3
#5Chuck Schilling'61-'65 * career totals — 5 seasons, 2,192 PA	3.3	2,192	23	11	239*	302*	331*	+8	+20	1.3	1.3
/162	664	7	3	+2.4	+6.0	0.4	pk7: 1
#6Jose Macias'99-'05 * career totals — 6 seasons, 1,789 PA	2.7	1,789	26	43	247*	289*	362*	+2	+12	1.0	1.0
/162	664	10	16	+0.7	+4.3	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
Yolmer Sánchez (OGILVIE)	35	—	—	—	—	210/289/297	87	288	4	9	27%	8%	70	-0.6	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Daniel Hinojosa 2019 · AAA	35	46	39→40	49→55	43	218/276/297	79	299	6	11	28%	7%	63	-1.3	207/259/340	133	322	16	10	39%	6%	68	-1.0	127/163/250	124	192	20	5	47%	4%	9	-1.0
✕Munenori Kawasaki 2016 · MLB	35	50→54	35→30	47→50	51	231/296/292	61	279	2	11	17%	8%	70	-0.9	226/291/300	74	282	5	20	20%	8%	70	-0.9	224/291/274	50	284	1	28	20%	8%	64	-0.9
✕Ramon Valdez 2012 · AAA	35	48	39→30	54→55	46	230/292/317	87	277	6	18	19%	6%	74	-0.5	246/319/322	76	279	5	22	13%	7%	86	+0.3	256/334/311	55	287	2	26	11%	7%	85	+0.1
✕Daniel Nunez 2017 · AAA	35	49	37→30	44→50	46	233/287/305	71	278	5	11	18%	6%	70	-0.9	219/278/279	60	270	4	11	19%	6%	60	-1.6	202/263/229	27	254	0	9	19%	6%	40	-1.3
✕Alfredo Amezaga 2013 · MLB	35	46→56	39→40	49→55	47	221/273/306	85	260	7	11	18%	6%	64	-1.3	243/293/327	84	288	6	8	17%	6%	76	-0.4	253/302/326	73	298	5	6	16%	6%	77	-0.2
✕Andrew Romine 2021 · MLB	35	46→55	42→40	55	43	225/272/327	102	272	10	19	21%	5%	69	-0.9	231/281/321	90	298	8	9	24%	6%	70	-0.8	235/280/294	59	309	3	3	24%	5%	61	-0.8
✕Cliff Pennington 2019 · MLB	35	42→52	38→45	47→55	47	200/268/277	77	272	6	8	27%	8%	56	-1.9	205/276/328	123	264	13	12	26%	8%	72	-0.7	149/227/307	158	162	21	18	26%	8%	50	-0.4
✕Michael Martinez 2017 · MLB	34	48→52	39→45	46→50	43	228/267/321	93	278	6	10	20%	5%	65	-1.2	227/269/320	93	288	6	10	22%	5%	65	-1.2	226/260/293	67	290	0	8	21%	4%	53	-1.0
✕Eloy Arano 2009 · AAA	35	56→57	37→30	44→50	43	264/290/332	68	301	4	10	14%	3%	75	-0.5	252/289/314	62	287	4	12	13%	4%	71	-0.8	260/296/296	37	291	1	12	11%	4%	68	-0.4
✕Doug Bernier 2015 · MLB	35	47→52	39→40	45	44	226/278/314	89	286	6	7	23%	6%	68	-1.0	221/274/303	82	283	7	6	23%	6%	64	-1.3	211/266/280	69	273	7	4	24%	6%	53	-1.3
✕Sergio Palafox 2015 · AAA	35	47	37→40	49→45	43	225/264/298	73	264	5	11	17%	4%	58	-1.7	226/273/321	95	269	8	11	19%	5%	68	-1.0	215/255/278	63	250	4	5	15%	4%	48	-0.4
✕Niuman Romero 2019 · AAA	34	46→56	40	46→50	48	222/282/312	90	274	7	8	21%	7%	69	-0.9	240/286/338	98	280	8	9	17%	6%	76	-0.4	250/293/334	84	288	5	7	15%	5%	75	-0.3
✕Quinton McCracken 2006 · MLB	35	50→60	39→40	49→50	52	236/295/320	84	270	6	11	15%	8%	76	-0.4	239/292/341	102	275	9	11	16%	7%	79	-0.2	245/283/316	71	283	6	11	15%	5%	66	-0.4
✕Elliot Soto 2023 · AAA	33	42→52	39→40	52→50	45	200/263/285	85	269	5	12	27%	7%	56	-1.9	190/253/266	76	278	5	19	31%	7%	48	-2.5	171/236/227	56	256	3	23	32%	7%	30	-2.0
✕Trinidad Robles 2008 · AAA	35	46	42→40	46→45	46	227/280/332	105	272	10	10	20%	6%	73	-0.6	209/264/288	79	260	6	7	21%	6%	57	-1.8	208/262/234	26	270	0	0	21%	5%	41	-1.2
✕Nick Punto 2013 · MLB	35	50→60	39→40	53→55	58	233/319/324	91	281	5	12	18%	11%	86	+0.3	236/314/329	93	301	7	9	22%	10%	85	+0.2	235/314/312	78	303	4	6	22%	10%	83	+0.1
✕Robinson Cancel 2012 · AAA	36	49	39→45	49→50	46	233/284/320	87	285	6	14	20%	6%	72	-0.7	242/290/355	113	285	12	16	19%	6%	82	-0.0	255/302/364	110	293	13	17	17%	6%	85	+0.1
✕Sandy León 2024 · MLB	35	41→51	41→45	46→30	48	199/279/294	95	266	9	4	27%	9%	65	-1.2	168/243/261	93	254	11	5	36%	8%	44	-2.8	127/200/199	72	195	10	3	39%	8%	13	-1.9
✕Carlos Orrantia 2016 · AAA	34	49→54	39→45	47→55	41	233/275/316	83	290	6	10	22%	4%	67	-1.1	224/263/301	77	282	7	9	22%	5%	59	-1.7	219/248/272	53	273	5	8	21%	4%	43	-1.0
✕Drew Maggi 2024 · AAA	35	37→47	38→45	53→60	41	180/249/254	74	254	5	20	30%	6%	45	-2.7	204/260/322	118	277	13	12	30%	6%	63	-1.3	167/212/305	138	216	20	4	33%	5%	40	-0.6

Yolmer Sánchez

Career Stats + Projections

How the minor-league lines were translated

Career Comps

Career Path Comps