Miguel Gómez

Pos2B

B/TS/R

Born1992-12-17

Age (2027)34

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2019

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2017	24	AA/INTL2 orgs	371	.293/.320/.434	9	0	81	—	.270/.291/.395
2017	24	MLBSF	34	.242/.242/.303	0	0	47	0.1
2018	25	AAA/AA/INTL2 orgs	527	.271/.286/.406	9	2	70	—	.269/.279/.380
2018	25	MLBSF	15	.267/.267/.267	0	0	52	0.2
2019	26	INTLLeones del Es…	47	.286/.362/.310	0	0	99	—
2020	27	No MLB games played
2021	28	No MLB games played
2022	29	No MLB games played
2023	30	No MLB games played
2024	31	No MLB games played
2025	32	No MLB games played
2026	33	No MLB games played

Last 3 seasons WAR 0.3

Contract

No contract data on file.

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)
2012	19	ROK	DSL Giants	—	136	121	28	6	2	1	11	25	4	2	1	231	316	339	655	107	284	18	8	300	17	—	—	—	—	—	—
2013	20	ROK	DSL Giants	—	123	111	35	12	1	2	10	27	1	1	0	315	377	495	873	180	398	22	8	382	44	—	—	—	—	—	—
2014	21	ROK	DSL Giants	—	283	258	82	18	1	5	17	37	5	3	0	318	371	453	825	136	352	13	6	365	39	—	—	—	—	—	—
2016	23	A+	San Jose Giants	—	182	172	46	9	2	9	8	28	1	1	0	267	304	500	804	233	272	15	4	348	81	—	—	—	—	—	—
2016	23	A	Augusta GreenJackets	—	285	267	99	17	1	8	12	25	3	3	2	371	404	532	936	161	386	9	4	410	124	—	—	—	—	—	—
2017	24	MLB	San Francisco Giants	—	34	33	8	2	0	0	0	6	0	0	0	242	242	303	545	61	286	18	0	235	47	-2	+0	+1	+1	+1	0.1
2017	24	AA	Richmond Flying Squirrels	—	322	308	94	19	2	8	12	36	0	0	0	305	331	458	789	153	325	11	4	346	86	—	—	—	—	—	—
2017	24	INTL	Tigres del Licey	—	49	47	10	0	0	1	2	10	0	0	0	213	245	277	521	64	250	20	4	237	47	—	—	—	—	—	—
2018	25	MLB	San Francisco Giants	—	15	15	4	0	0	0	0	5	0	0	0	267	267	267	533		400	33	0	241	52	-1	+0	+1	+2	+0	0.2
2018	25	AAA	Sacramento River Cats	—	236	231	63	14	1	2	2	35	1	0	0	273	282	368	650	95	311	15	1	286	61	—	—	—	—	—	—
2018	25	AA	Richmond Flying Squirrels	—	201	192	60	12	4	4	7	28	0	1	0	312	337	479	816	167	346	14	3	355	95	—	—	—	—	—	—
2018	25	INTL	Leones del Escogido	—	90	87	15	4	1	3	1	17	0	1	0	172	182	345	527	172	174	19	1	223	37	—	—	—	—	—	—
2019	26	INTL	Leones del Escogido	—	47	42	12	1	0	0	3	6	2	0	0	286	362	310	671	24	333	13	6	315	99	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	49	48	12	2	0	0	0	11	0	0	0	250	250	292	542	42	316	22	0	237	47	-3	+0	+1	+3	+1	0.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	19	ROK MLE	DSL Giants	—	136	124	18	4	1	0	8	30	4	2	1	145	221	194	414	48	190	22	6	193	17	—	—	—	—	—	—
2013	20	ROK MLE	DSL Giants	—	123	115	22	7	1	1	6	33	1	1	0	191	238	296	533	104	254	27	5	233	44	—	—	—	—	—	—
2014	21	ROK MLE	DSL Giants	—	283	263	53	11	1	2	12	45	5	3	0	202	250	274	524	72	224	16	4	226	39	—	—	—	—	—	—
2016	23	A+ MLE	San Jose Giants	—	182	174	40	8	2	7	6	38	1	1	0	230	260	420	679	190	248	21	3	288	81	—	—	—	—	—	—
2016	23	A MLE	Augusta GreenJackets	—	285	273	89	15	1	8	6	33	3	3	2	326	348	476	824	150	338	12	2	351	124	—	—	—	—	—	—
2017	24	MLB MLE	San Francisco Giants	—	34	33	8	2	0	0	0	6	0	0	0	242	242	303	545	61	286	18	0	237	47	-2	+0	+1	+1	+1	0.1
2017	24	AA MLE	Richmond Flying Squirrels	—	322	311	84	14	2	7	9	46	0	0	0	270	291	395	686	125	295	14	3	295	86	—	—	—	—	—	—
2018	25	MLB MLE	San Francisco Giants	—	15	15	4	0	0	0	0	5	0	0	0	267	267	267	533		400	33	0	245	52	-1	+0	+1	+2	+0	0.2
2018	25	AAA MLE	Sacramento River Cats	—	236	232	60	13	1	2	1	42	1	0	0	259	265	349	614	91	300	18	0	259	61	—	—	—	—	—	—
2018	25	AA MLE	Richmond Flying Squirrels	—	201	195	55	11	3	3	4	35	0	1	0	282	296	415	712	133	321	17	2	309	95	—	—	—	—	—	—
2012	19	ROK MLE	DSL Giants	—	136	124	18	4	1	0	8	30	4	2	1	145	221	194	414	48	191	22	6	193	17	—	—	—	—	—	—
2012	19	ROK RAW	DSL Giants	—	136	121	28	6	2	1	11	25	4	2	1	231	316	339	655	107	284	18	8	300	17	—	—	—	—	—	—
2013	20	ROK MLE	DSL Giants	—	123	115	22	7	1	1	6	33	1	1	0	191	238	296	533	104	256	27	5	233	44	—	—	—	—	—	—
2013	20	ROK RAW	DSL Giants	—	123	111	35	12	1	2	10	27	1	1	0	315	377	495	873	180	398	22	8	382	44	—	—	—	—	—	—
2014	21	ROK MLE	DSL Giants	—	283	263	53	11	1	2	12	45	5	3	0	202	250	274	524	72	233	16	4	226	39	—	—	—	—	—	—
2014	21	ROK RAW	DSL Giants	—	283	258	82	18	1	5	17	37	5	3	0	318	371	453	825	136	352	13	6	365	39	—	—	—	—	—	—
2016	23	A MLE	2 teams	—	467	447	129	23	3	15	12	70	4	4	2	289	313	454	767	166	312	15	3	326	107	—	—	—	—	—	—
2016	23	A RAW	2 teams	—	467	439	145	26	3	17	20	53	4	4	2	330	365	519	884	189	344	11	4	386	107	—	—	—	—	—	—
2017	24	AA MLE	3 teams	—	405	392	105	19	2	8	10	60	0	0	0	268	286	388	674	120	298	15	2	289	82	—	—	—	—	—	—
2017	24	AA RAW	3 teams	—	405	388	112	21	2	9	14	52	0	0	0	289	313	423	736	134	313	13	3	324	82	—	—	—	—	—	—
2018	25	AAA MLE	4 teams	—	542	528	142	28	5	6	7	99	1	2	0	269	280	375	655	106	317	18	1	281	76	—	—	—	—	—	—
2018	25	AAA RAW	4 teams	—	542	525	142	30	6	9	10	85	1	2	0	270	285	402	687	131	304	16	2	300	76	—	—	—	—	—	—
2019	26	INTL MLE	Leones del Escogido	—	47	42	12	1	0	0	3	6	2	0	0	286	362	310	671	24	333	13	6	—	—	—	—	—	—	—	—
2019	26	INTL RAW	Leones del Escogido	—	47	42	12	1	0	0	3	6	2	0	0	286	362	310	671	24	333	13	6	315	99	—	—	—	—	—	—
2012	19	ROK MLE	DSL Giants	—	136	123	18	4	1	0	8	30	4	2	1	146	221	195	416	49	190	22	6	193	17	—	—	—	—	—	—
2013	20	ROK MLE	DSL Giants	—	123	115	22	7	1	1	6	33	1	1	0	191	238	296	533	104	254	27	5	233	44	—	—	—	—	—	—
2014	21	ROK MLE	DSL Giants	—	283	264	53	11	1	2	12	45	5	3	0	201	250	273	523	72	224	16	4	226	39	—	—	—	—	—	—
2016	23	A MLE	2 teams	—	467	448	129	23	3	15	12	70	4	4	2	288	313	453	766	165	303	15	3	326	107	—	—	—	—	—	—
2017	24	AA MLE	3 teams	—	405	392	105	19	2	8	10	60	0	0	0	268	286	388	674	120	294	15	2	289	82	—	—	—	—	—	—
2018	25	AAA MLE	4 teams	—	542	529	142	28	5	6	7	99	1	2	0	268	280	374	654	106	313	18	1	281	76	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	49	48	12	2	0	0	0	11	0	0	0	250	250	292	542	42	316	22	0	237	69	-3	+0	+1	+3	+1	0.3
/ 162G	—	A+C		—	650	637	160	27	0	0	0	146	0	0	0	251	251	294	545	42	317	22	0	237	69	-41	+0	+16	+45	+14	3.4
Career	—	MLE		—	2003	1911	481	93	13	32	58	343	17	12	3	252	280	364	644	113	289	17	3	270	69	-3	+0	+1	+3	+1	0.3
/ 162G	—	MLE		—	650	620	155	30	4	10	19	111	6	4	1	250	280	360	639	110	288	17	3	270	69	-41	+0	+16	+45	+14	3.4

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.

2018 AAASacramento River Cats · 236 PAwOBA .280 → .259 (−22)K% 14.8% → 17.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.83%	÷1.071	×1.290	—	—	17.86%
BB% (unintentional) /PA	0.85%	÷1.043	×0.710	—	×1.018	0.59%
HBP% /PA	0.42%	—	×0.980	—	×1.018	0.42%
Singles /BIP	23.47%	÷0.963	×0.900	×1.030	×1.018	22.99%
Doubles /BIP	7.14%	÷0.910	×0.810	×1.030	×1.018	6.66%
Triples /BIP	0.51%	÷1.150	×0.810	×1.030	×1.018	0.38%
Home runs /BIP	1.02%	÷0.998	×0.780	—	×1.018	0.81%

Factors used: league row PCL. Park (home-season share, regressed): HR 100, 1B 93, 2B 82, 3B 130, K 114, BB 109 — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.030.

Result: wOBA .280 → .259; ISO .095 → .082; BABIP .311 → .300. 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 AARichmond Flying Squirrels · 201 PAwOBA .346 → .309 (−37)K% 13.9% → 17.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.93%	÷0.975	×1.220	—	—	17.42%
BB% (unintentional) /PA	2.99%	÷0.983	×0.700	—	×0.988	2.10%
HBP% /PA	0.00%	—	×0.850	—	×0.988	0.00%
Singles /BIP	24.39%	÷0.995	×0.970	×0.993	×0.988	23.34%
Doubles /BIP	7.32%	÷0.949	×0.860	×0.993	×0.988	6.51%
Triples /BIP	2.44%	÷1.150	×0.950	×0.993	×0.988	1.98%
Home runs /BIP	2.44%	÷0.869	×0.780	—	×0.988	2.16%

Factors used: league row EL. Park (home-season share, regressed): HR 74, 1B 99, 2B 90, 3B 130, K 95, BB 97 — applied at half strength. Age: age 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.

Result: wOBA .346 → .309; ISO .167 → .143; BABIP .346 → .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).

2017 AARichmond Flying Squirrels · 322 PAwOBA .337 → .295 (−42)K% 11.2% → 14.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.18%	÷0.948	×1.220	—	—	14.39%
BB% (unintentional) /PA	3.73%	÷0.974	×0.700	—	×0.998	2.67%
HBP% /PA	0.00%	—	×0.850	—	×0.998	0.00%
Singles /BIP	23.90%	÷1.004	×0.970	×0.985	×0.998	22.68%
Doubles /BIP	6.99%	÷1.096	×0.860	×0.985	×0.998	5.39%
Triples /BIP	0.74%	÷0.900	×0.950	×0.985	×0.998	0.76%
Home runs /BIP	2.94%	÷0.848	×0.780	—	×0.998	2.70%

Factors used: league row EL. Park (home-season share, regressed): HR 70, 1B 101, 2B 119, 3B 80, K 90, BB 95 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.985.

Result: wOBA .337 → .295; ISO .153 → .130; BABIP .325 → .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).

2016 AAugusta GreenJackets · 285 PAwOBA .399 → .351 (−48)K% 8.8% → 11.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.77%	÷1.025	×1.340	—	—	11.47%
BB% (unintentional) /PA	3.51%	÷1.020	×0.660	—	×0.980	2.22%
HBP% /PA	1.05%	—	×0.770	—	×0.980	0.79%
Singles /BIP	30.17%	÷1.054	×0.920	×1.026	×0.980	26.47%
Doubles /BIP	7.02%	÷0.944	×0.820	×1.026	×0.980	6.13%
Triples /BIP	0.41%	÷0.919	×0.940	×1.026	×0.980	0.43%
Home runs /BIP	3.31%	÷0.834	×0.820	—	×0.980	3.18%

Factors used: league row SAL. Park (home-season share, regressed): HR 67, 1B 111, 2B 89, 3B 84, K 105, BB 104 — applied at half strength. Age: age 24 vs a level average of 22.0 → −2.0% on BB/HBP/hit rates (2.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.026.

Result: wOBA .399 → .351; ISO .161 → .151; BABIP .386 → .338. 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 A+San Jose Giants · 182 PAwOBA .340 → .288 (−52)K% 15.4% → 20.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.38%	÷0.998	×1.340	—	—	20.66%
BB% (unintentional) /PA	4.40%	÷0.992	×0.710	—	×0.988	3.11%
HBP% /PA	0.55%	—	×0.790	—	×0.988	0.43%
Singles /BIP	18.06%	÷1.008	×0.910	×1.045	×0.988	16.83%
Doubles /BIP	6.25%	÷0.951	×0.820	×1.045	×0.988	5.56%
Triples /BIP	1.39%	÷0.900	×0.760	×1.045	×0.988	1.21%
Home runs /BIP	6.25%	÷1.045	×0.920	—	×0.988	5.44%

Factors used: league row CAL. Park (home-season share, regressed): HR 109, 1B 102, 2B 90, 3B 80, K 100, BB 98 — applied at half strength. Age: age 24 vs a level average of 22.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.045.

Result: wOBA .340 → .288; ISO .233 → .195; BABIP .272 → .248. 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).

2014 DSLDSL Giants · 283 PAwOBA .358 → .226 (−132)K% 13.1% → 16.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.07%	÷1.000	×1.220	—	—	15.95%
BB% (unintentional) /PA	6.01%	÷1.000	×0.700	—	×0.965	4.06%
HBP% /PA	1.77%	—	×0.700	—	×0.965	1.19%
Singles /BIP	26.24%	÷1.000	×0.680	×1.012	×0.965	17.43%
Doubles /BIP	8.14%	÷1.000	×0.600	×1.012	×0.965	4.77%
Triples /BIP	0.45%	÷1.000	×0.600	×1.012	×0.965	0.27%
Home runs /BIP	2.26%	÷1.000	×0.470	—	×0.965	1.03%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 18.5 → −3.5% on BB/HBP/hit rates (3.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.012.

Result: wOBA .358 → .226; ISO .136 → .072; BABIP .352 → .224. 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).

2013 DSLDSL Giants · 123 PAwOBA .372 → .233 (−139)K% 22.0% → 26.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.95%	÷1.000	×1.220	—	—	26.78%
BB% (unintentional) /PA	7.32%	÷1.000	×0.700	—	×0.975	4.99%
HBP% /PA	0.81%	—	×0.700	—	×0.975	0.55%
Singles /BIP	23.81%	÷1.000	×0.680	×1.026	×0.975	16.19%
Doubles /BIP	14.29%	÷1.000	×0.600	×1.026	×0.975	8.57%
Triples /BIP	1.19%	÷1.000	×0.600	×1.026	×0.975	0.71%
Home runs /BIP	2.38%	÷1.000	×0.470	—	×0.975	1.09%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 18.5 → −2.5% on BB/HBP/hit rates (2.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.026.

Result: wOBA .372 → .233; ISO .180 → .100; BABIP .398 → .254. 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).

2012 DSLDSL Giants · 136 PAwOBA .293 → .193 (−100)K% 18.4% → 22.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.38%	÷1.000	×1.220	—	—	22.43%
BB% (unintentional) /PA	8.09%	÷1.000	×0.700	—	×0.985	5.58%
HBP% /PA	2.94%	—	×0.700	—	×0.985	2.03%
Singles /BIP	19.79%	÷1.000	×0.680	×1.042	×0.985	13.81%
Doubles /BIP	6.25%	÷1.000	×0.600	×1.042	×0.985	3.85%
Triples /BIP	2.08%	÷1.000	×0.600	×1.042	×0.985	1.28%
Home runs /BIP	1.04%	÷1.000	×0.470	—	×0.985	0.48%

Factors used: level-wide DSL factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 20 vs a level average of 18.5 → −1.5% on BB/HBP/hit rates (1.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.042.

Result: wOBA .293 → .193; ISO .107 → .062; BABIP .284 → .190. 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 — .