Eric Aguilera

Pos1B

B/TL/L

Born1990-07-03

Age (2027)37

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2020

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2017	27	AATEX	448	.222/.324/.385	15	1	45	—	.172/.243/.280
2019	29	AAA/INTL2 orgs	652	.261/.346/.421	18	1	83	—	.233/.290/.356
2020	30	INTLAguilas de Me…	105	.250/.337/.402	3	0	110	—

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)
2013	23	ROK	Orem Owlz	—	257	232	71	22	1	10	14	60	2	1	1	306	351	539	890	233	361	23	5	375	56	—	—	—	—	—	—
2014	24	A+	Inland Empire 66ers	—	46	43	12	3	0	0	2	10	0	0	0	279	311	349	660	70	364	22	4	291	40	—	—	—	—	—	—
2014	24	A	Burlington Bees	—	524	469	137	22	4	14	35	101	7	17	3	292	350	446	796	154	336	19	7	346	84	—	—	—	—	—	—
2015	25	AA	Arkansas Travelers	—	34	33	4	2	0	0	1	11	0	0	0	121	147	182	329	61	182	32	3	149	-37	—	—	—	—	—	—
2015	25	A+	Inland Empire 66ers	—	520	462	151	38	3	17	47	110	6	14	6	327	396	532	929	206	394	21	9	405	103	—	—	—	—	—	—
2015	25	INTL	Mesa Solar Sox	—	76	69	19	4	1	2	6	9	1	1	0	275	342	449	791	174	293	12	8	351	124	—	—	—	—	—	—
2016	26	AA	Arkansas Travelers	—	495	459	124	25	4	14	27	130	4	0	9	270	316	434	750	163	344	26	5	329	69	—	—	—	—	—	—
2016	26	INTL	Charros de Jalisco	—	51	40	9	2	0	2	8	15	2	0	0	225	380	425	805	200	292	29	16	359	129	—	—	—	—	—	—
2017	27	AA	Frisco RoughRiders	—	448	387	86	18	0	15	53	120	5	1	2	222	324	385	709	163	278	27	12	319	45	—	—	—	—	—	—
2019	29	AAA	Tigres de Quintana Roo	—	423	376	108	23	0	14	39	118	6	1	2	287	363	460	824	173	382	28	9	365	79	—	—	—	—	—	—
2019	29	INTL	Aguilas de Mexicali	—	229	199	42	13	1	4	28	69	2	0	1	211	314	347	661	136	302	30	12	303	91	—	—	—	—	—	—
2020	30	INTL	Aguilas de Mexicali	—	105	92	23	5	0	3	10	25	2	0	0	250	337	402	739	152	308	24	10	330	110	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	23	ROK MLE	Orem Owlz	—	257	238	49	14	1	7	8	86	2	1	1	206	238	361	599	155	260	33	3	251	56	—	—	—	—	—	—
2014	24	A+ MLE	Inland Empire 66ers	—	46	44	10	2	0	0	1	13	0	0	0	227	244	273	517	45	318	28	2	227	40	—	—	—	—	—	—
2014	24	A MLE	Burlington Bees	—	524	481	123	18	4	12	23	134	7	17	3	256	299	385	684	129	306	26	4	293	84	—	—	—	—	—	—
2015	25	AA MLE	Arkansas Travelers	—	34	33	4	2	0	0	1	13	0	0	0	121	147	182	329	61	157	38	3	114	-37	—	—	—	—	—	—
2015	25	A+ MLE	Inland Empire 66ers	—	520	479	125	29	2	16	30	151	6	14	6	261	313	430	743	169	338	29	6	321	103	—	—	—	—	—	—
2016	26	AA MLE	Arkansas Travelers	—	495	471	108	21	3	11	15	157	4	0	9	229	259	357	616	127	312	32	3	270	69	—	—	—	—	—	—
2017	27	AA MLE	Frisco RoughRiders	—	448	407	70	14	0	10	33	153	5	1	2	172	243	280	523	108	237	34	7	234	45	—	—	—	—	—	—
2019	29	AAA MLE	Tigres de Quintana Roo	—	423	390	91	18	0	10	25	140	6	1	2	233	290	356	646	123	329	33	6	285	79	—	—	—	—	—	—
2013	23	ROK MLE	Orem Owlz	—	257	238	49	14	1	7	8	86	2	1	1	206	238	361	599	155	276	33	3	251	56	—	—	—	—	—	—
2013	23	ROK RAW	Orem Owlz	—	257	232	71	22	1	10	14	60	2	1	1	306	351	539	890	233	361	23	5	375	56	—	—	—	—	—	—
2014	24	A MLE	2 teams	—	570	525	133	20	4	12	24	147	7	17	3	253	295	375	670	122	320	26	4	288	81	—	—	—	—	—	—
2014	24	A RAW	2 teams	—	570	512	149	25	4	14	37	111	7	17	3	291	347	438	785	146	338	19	6	341	81	—	—	—	—	—	—
2015	25	A+ MLE	3 teams	—	630	583	146	35	2	18	35	187	7	15	6	250	301	410	711	160	334	30	6	308	95	—	—	—	—	—	—
2015	25	A+ RAW	3 teams	—	630	564	174	44	4	19	54	130	7	15	6	309	376	502	878	193	369	21	9	384	95	—	—	—	—	—	—
2016	26	AA MLE	2 teams	—	546	517	120	23	4	12	17	173	6	0	9	232	265	362	627	130	320	32	3	270	69	—	—	—	—	—	—
2016	26	AA RAW	2 teams	—	546	499	133	27	4	16	35	145	6	0	9	267	322	433	755	166	340	27	6	332	69	—	—	—	—	—	—
2017	27	AA MLE	Frisco RoughRiders	—	448	407	70	14	0	10	33	153	5	1	2	172	243	280	523	108	243	34	7	234	45	—	—	—	—	—	—
2017	27	AA RAW	Frisco RoughRiders	—	448	387	86	18	0	15	53	120	5	1	2	222	324	385	709	163	278	27	12	319	45	—	—	—	—	—	—
2019	29	AAA MLE	2 teams	—	652	603	139	27	0	16	39	216	8	1	3	231	286	355	641	124	330	33	6	285	79	—	—	—	—	—	—
2019	29	AAA RAW	2 teams	—	652	575	150	36	1	18	67	187	8	1	3	261	346	421	767	160	355	29	10	343	79	—	—	—	—	—	—
2020	30	INTL MLE	Aguilas de Mexicali	—	105	92	23	5	0	3	10	25	2	0	0	250	337	402	739	152	308	24	10	—	—	—	—	—	—	—	—
2020	30	INTL RAW	Aguilas de Mexicali	—	105	92	23	5	0	3	10	25	2	0	0	250	337	402	739	152	308	24	10	330	110	—	—	—	—	—	—
2013	23	ROK MLE	Orem Owlz	—	257	245	49	14	1	7	8	86	2	1	1	200	238	351	589	151	260	33	3	251	56	—	—	—	—	—	—
2014	24	A MLE	2 teams	—	570	534	133	20	4	12	24	147	7	17	3	249	295	369	664	120	307	26	4	288	81	—	—	—	—	—	—
2015	25	A+ MLE	3 teams	—	630	583	146	35	2	18	35	187	7	15	6	250	301	410	711	160	327	30	6	308	95	—	—	—	—	—	—
2016	26	AA MLE	2 teams	—	546	518	120	23	4	12	17	173	6	0	9	232	265	361	626	129	312	32	3	270	69	—	—	—	—	—	—
2017	27	AA MLE	Frisco RoughRiders	—	448	407	70	14	0	10	33	153	5	1	2	172	243	280	523	108	237	34	7	234	45	—	—	—	—	—	—
2019	29	AAA MLE	2 teams	—	652	600	139	27	0	16	39	216	8	1	3	232	286	357	643	125	329	33	6	285	79	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	3208	2965	680	138	11	78	166	987	37	35	24	229	279	362	641	133	311	31	5	268	68	-123	-3	+0	-57	+70	-11.6
/ 162G	—	MLE		—	650	601	138	28	2	16	34	200	7	7	5	230	279	363	642	133	311	31	5	268	68	-25	-1	+0	-12	+14	-2.4

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.

2019 AAATigres de Quintana Roo · 423 PAwOBA .355 → .285 (−70)K% 27.9% → 33.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.90%	÷1.008	×1.200	—	—	33.20%
BB% (unintentional) /PA	8.51%	÷0.966	×0.690	—	×0.982	5.97%
HBP% /PA	1.42%	—	×0.940	—	×0.982	1.31%
Singles /BIP	27.52%	÷0.962	×0.930	×0.950	×0.982	24.83%
Doubles /BIP	8.91%	÷0.990	×0.830	×0.950	×0.982	6.97%
Triples /BIP	0.00%	÷0.900	×0.920	×0.950	×0.982	0.00%
Home runs /BIP	5.43%	÷0.898	×0.700	—	×0.982	4.15%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 80, 1B 92, 2B 98, 3B 80, K 102, BB 93 — 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 ×0.950.

Result: wOBA .355 → .285; ISO .173 → .130; BABIP .382 → .329. 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 AAFrisco RoughRiders · 448 PAwOBA .313 → .234 (−79)K% 26.8% → 34.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.79%	÷0.959	×1.220	—	—	34.07%
BB% (unintentional) /PA	11.83%	÷1.095	×0.700	—	×0.978	7.39%
HBP% /PA	1.12%	—	×0.870	—	×0.978	0.95%
Singles /BIP	19.85%	÷1.022	×0.920	×1.011	×0.978	17.68%
Doubles /BIP	6.74%	÷1.051	×0.840	×1.011	×0.978	5.33%
Triples /BIP	0.00%	÷1.017	×0.940	×1.011	×0.978	0.00%
Home runs /BIP	5.62%	÷1.089	×0.800	—	×0.978	4.04%

Factors used: league row TL. Park (home-season share, regressed): HR 118, 1B 104, 2B 110, 3B 103, K 92, BB 119 — applied at half strength. Age: age 27 vs a level average of 24.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.011.

Result: wOBA .313 → .234; ISO .163 → .116; BABIP .278 → .237. 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 AAArkansas Travelers · 495 PAwOBA .319 → .270 (−49)K% 26.3% → 31.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.26%	÷1.009	×1.220	—	—	31.75%
BB% (unintentional) /PA	4.44%	÷0.979	×0.700	—	×0.988	3.14%
HBP% /PA	0.81%	—	×0.870	—	×0.988	0.69%
Singles /BIP	24.62%	÷0.995	×0.920	×1.023	×0.988	23.01%
Doubles /BIP	7.60%	÷0.975	×0.840	×1.023	×0.988	6.61%
Triples /BIP	1.22%	÷1.150	×0.940	×1.023	×0.988	1.00%
Home runs /BIP	4.26%	÷0.972	×0.800	—	×0.988	3.46%

Factors used: league row TL. Park (home-season share, regressed): HR 94, 1B 99, 2B 95, 3B 130, K 102, BB 96 — 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 ×1.023.

Result: wOBA .319 → .270; ISO .163 → .132; BABIP .344 → .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).

2015 A+Inland Empire 66ers · 520 PAwOBA .396 → .321 (−74)K% 21.2% → 29.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.15%	÷0.972	×1.340	—	—	29.15%
BB% (unintentional) /PA	8.46%	÷1.013	×0.710	—	×0.978	5.80%
HBP% /PA	1.15%	—	×0.790	—	×0.978	0.89%
Singles /BIP	26.42%	÷1.021	×0.910	×1.014	×0.978	23.35%
Doubles /BIP	10.80%	÷1.000	×0.820	×1.014	×0.978	8.78%
Triples /BIP	0.85%	÷1.150	×0.760	×1.014	×0.978	0.56%
Home runs /BIP	4.83%	÷0.896	×0.920	—	×0.978	4.85%

Factors used: league row CAL. Park (home-season share, regressed): HR 79, 1B 104, 2B 100, 3B 130, K 94, BB 103 — applied at half strength. Age: age 25 vs a level average of 22.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.014.

Result: wOBA .396 → .321; ISO .206 → .177; BABIP .394 → .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).

2015 AAArkansas Travelers · 34 PAwOBA .145 → .114 (−31)K% 32.4% → 37.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.35%	÷1.047	×1.220	—	—	37.69%
BB% (unintentional) /PA	2.94%	÷0.985	×0.700	—	×0.998	2.09%
HBP% /PA	0.00%	—	×0.870	—	×0.998	0.00%
Singles /BIP	9.09%	÷1.002	×0.920	—	×0.998	8.33%
Doubles /BIP	9.09%	÷1.033	×0.840	—	×0.998	7.38%
Triples /BIP	0.00%	÷1.150	×0.940	—	×0.998	0.00%
Home runs /BIP	0.00%	÷1.022	×0.800	—	×0.998	0.00%

Factors used: league row TL. Park (home-season share, regressed): HR 104, 1B 100, 2B 107, 3B 130, K 109, BB 97 — 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).

Result: wOBA .145 → .114; ISO .061 → .046; BABIP .182 → .157. 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 ABurlington Bees · 524 PAwOBA .343 → .293 (−50)K% 19.3% → 25.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.27%	÷1.030	×1.360	—	—	25.45%
BB% (unintentional) /PA	6.30%	÷0.998	×0.690	—	×0.980	4.27%
HBP% /PA	1.34%	—	×0.780	—	×0.980	1.02%
Singles /BIP	26.36%	÷0.994	×0.920	×1.030	×0.980	24.62%
Doubles /BIP	5.98%	÷1.023	×0.830	×1.030	×0.980	4.90%
Triples /BIP	1.09%	÷0.923	×0.910	×1.030	×0.980	1.08%
Home runs /BIP	3.80%	÷0.935	×0.800	—	×0.980	3.19%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 87, 1B 99, 2B 105, 3B 85, K 106, BB 100 — 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 ×1.030.

Result: wOBA .343 → .293; ISO .154 → .129; BABIP .336 → .306. 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 A+Inland Empire 66ers · 46 PAwOBA .283 → .227 (−56)K% 21.7% → 29.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.74%	÷0.994	×1.340	—	—	29.29%
BB% (unintentional) /PA	4.35%	÷1.048	×0.710	—	×0.988	2.91%
HBP% /PA	0.00%	—	×0.790	—	×0.988	0.00%
Singles /BIP	27.27%	÷0.984	×0.910	—	×0.988	24.91%
Doubles /BIP	9.09%	÷1.063	×0.820	—	×0.988	6.93%
Triples /BIP	0.00%	÷1.108	×0.760	—	×0.988	0.00%
Home runs /BIP	0.00%	÷0.820	×0.920	—	×0.988	0.00%

Factors used: league row CAL. Park (home-season share, regressed): HR 64, 1B 97, 2B 113, 3B 122, K 99, BB 110 — 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).

Result: wOBA .283 → .227; ISO .070 → .050; BABIP .364 → .318. 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 ROKOrem Owlz · 257 PAwOBA .374 → .251 (−123)K% 23.3% → 33.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.35%	÷1.000	×1.440	—	—	33.62%
BB% (unintentional) /PA	5.45%	÷1.000	×0.610	—	×0.965	3.21%
HBP% /PA	0.78%	—	×0.720	—	×0.965	0.54%
Singles /BIP	22.09%	÷1.000	×0.820	×0.974	×0.965	17.03%
Doubles /BIP	12.79%	÷1.000	×0.720	×0.974	×0.965	8.66%
Triples /BIP	0.58%	÷1.000	×0.720	×0.974	×0.965	0.39%
Home runs /BIP	5.81%	÷1.000	×0.750	—	×0.965	4.21%

Factors used: league row PIO. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 23 vs a level average of 19.5 → −3.5% on BB/HBP/hit rates (3.5 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.974.

Result: wOBA .374 → .251; ISO .233 → .153; BABIP .361 → .260. 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 — .