Ángel Pagán

PosCF

B/TS/R

Born1981-07-02

Age (2027)46

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2016

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2014	33	MLBSF	413	.300/.345/.389	3	16	109	1.3
2015	34	MLBSF	551	.262/.306/.332	3	12	83	-0.3
2016	35	MLBSF	543	.277/.331/.418	12	15	114	1.1
2017	36	No MLB games played
2018	37	No MLB games played
2019	38	No MLB games played
2020	39	No MLB games played
2021	40	No MLB games played
2022	41	No MLB games played
2023	42	No MLB games played
2024	43	No MLB games played
2025	44	No MLB games played
2026	45	No MLB games played

Last 3 seasons WAR 2.1

Contract

No contract data on file.

Skills · percentileStatcast 2015-2016

Speed55

xwOBA43

Barrel%10

Avg EV10

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)
2005	24	AAA	Norfolk Tides	—	579	516	140	20	10	8	49	111	1	27	15	271	336	395	731	124	329	19	8	321	83	—	—	—	—	—	—
2006	25	MLB	Chicago Cubs	—	187	170	42	6	2	5	15	28	0	4	2	247	308	394	702	147	268	15	8	310	96	-1	+0	+1	-2	+4	0.2
2006	25	AAA	Iowa Cubs	—	16	15	4	1	0	0	1	4	0	1	0	267	312	333	646	67	364	25	6	294	43	—	—	—	—	—	—
2007	26	MLB	Chicago Cubs	—	161	148	39	10	2	4	10	32	0	4	1	264	310	439	749	176	307	20	6	324	106	+1	+0	+2	+1	+3	0.8
2007	26	AAA	Iowa Cubs	—	127	116	29	4	3	3	10	20	0	6	1	250	310	414	723	164	280	16	8	318	63	—	—	—	—	—	—
2008	27	MLB	New York Mets	—	105	91	25	7	1	0	11	18	0	4	0	275	353	374	727	99	333	17	10	321	103	+0	+1	-1	-1	+2	0.1
2009	28	MLB	New York Mets	—	376	343	105	22	11	6	25	56	0	14	7	306	353	487	840	181	349	15	7	361	128	+12	+0	+7	+1	+8	2.9
2009	28	A+	St. Lucie Mets	—	16	12	5	2	0	0	4	2	0	2	0	417	562	583	1.146	167	500	12	25	505	168	—	—	—	—	—	—
2010	29	MLB	New York Mets	—	633	579	168	31	7	11	44	97	1	37	9	290	341	425	766	135	331	15	7	337	116	+12	+4	+15	+2	+14	4.8
2011	30	MLB	New York Mets	—	532	478	125	24	4	7	44	62	1	32	7	262	325	372	697	111	285	12	8	310	98	-2	+4	-12	+2	+12	0.3
2011	30	A+	St. Lucie Mets	—	36	31	7	1	1	1	4	5	1	0	2	226	333	419	753	194	240	14	11	337	55	—	—	—	—	—	—
2012	31	MLB	San Francisco Giants	—	659	605	174	38	15	8	48	97	0	29	7	288	340	440	780	152	329	15	7	342	117	+13	+3	+3	+2	+14	3.7
2013	32	MLB	San Francisco Giants	—	305	280	79	16	3	5	23	36	0	9	4	282	337	414	751	132	307	12	8	333	115	+5	+0	-3	+1	+7	1.1
2013	32	AAA	Fresno Grizzlies	—	22	18	5	0	0	0	2	2	1	0	0	278	381	278	659		294	9	9	303	68	—	—	—	—	—	—
2014	33	MLB	San Francisco Giants	—	413	383	115	21	2	3	25	53	1	16	6	300	345	389	734	89	339	13	6	327	109	+5	+1	-3	+1	+9	1.3
2015	34	MLB	San Francisco Giants	—	551	512	134	21	3	3	32	93	1	12	4	262	306	332	638	70	310	17	6	287	83	-11	+1	-6	+2	+12	-0.3
2016	35	MLB	San Francisco Giants	—	543	495	137	24	5	12	42	66	0	15	4	277	331	418	750	141	298	12	8	332	114	+9	+1	-5	-6	+12	1.1
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4465	4084	1143	220	55	64	319	638	4	176	51	280	332	408	740	128	316	14	7	326	107	+38	+15	-3	+5	+97	15.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	24	AAA MLE	Norfolk Tides	—	579	531	137	18	10	7	34	133	1	27	15	258	304	369	673	111	319	23	6	291	83	—	—	—	—	—	—
2006	25	MLB MLE	Chicago Cubs	—	187	170	42	6	2	5	15	28	0	4	2	247	308	394	702	147	268	15	8	310	96	-1	+0	+1	-2	+4	0.2
2006	25	AAA MLE	Iowa Cubs	—	16	15	4	1	0	0	1	5	0	1	0	267	312	333	646	67	330	31	6	232	43	—	—	—	—	—	—
2007	26	MLB MLE	Chicago Cubs	—	161	148	39	10	2	4	10	32	0	4	1	264	310	439	749	176	307	20	6	324	106	+1	+0	+2	+1	+3	0.8
2007	26	AAA MLE	Iowa Cubs	—	127	120	26	3	3	2	6	26	0	6	1	217	254	342	596	125	255	20	5	261	63	—	—	—	—	—	—
2008	27	MLB MLE	New York Mets	—	105	91	25	7	1	0	11	18	0	4	0	275	353	374	727	99	333	17	10	321	103	+0	+1	-1	-1	+2	0.1
2009	28	MLB MLE	New York Mets	—	376	345	105	22	11	6	23	56	0	14	7	304	348	484	832	180	349	15	6	357	128	+12	+0	+7	+1	+8	2.9
2009	28	A+ MLE	St. Lucie Mets	—	16	13	5	2	0	0	3	3	0	2	0	385	500	538	1.038	154	444	19	19	417	168	—	—	—	—	—	—
2010	29	MLB MLE	New York Mets	—	633	584	173	33	7	11	39	97	1	37	9	296	341	433	775	137	331	15	6	340	116	+12	+4	+15	+2	+14	4.8
2011	30	MLB MLE	New York Mets	—	532	482	128	25	4	7	40	62	1	32	7	266	323	378	701	112	285	12	8	312	98	-2	+4	-12	+2	+12	0.3
2011	30	A+ MLE	St. Lucie Mets	—	36	32	6	1	1	1	3	7	1	0	2	188	278	375	653	188	199	19	8	249	55	—	—	—	—	—	—
2012	31	MLB MLE	San Francisco Giants	—	659	610	177	38	15	9	43	97	0	29	7	290	337	446	783	156	329	15	7	341	117	+13	+3	+3	+2	+14	3.7
2013	32	MLB MLE	San Francisco Giants	—	305	280	80	16	3	5	23	36	0	9	4	286	340	418	758	132	307	12	8	338	115	+5	+0	-3	+1	+7	1.1
2013	32	AAA MLE	Fresno Grizzlies	—	22	19	5	0	0	0	1	3	1	0	0	263	333	263	596		254	14	5	268	68	—	—	—	—	—	—
2014	33	MLB MLE	San Francisco Giants	—	413	384	116	21	2	3	24	53	1	16	6	302	345	391	735	89	339	13	6	330	109	+5	+1	-3	+1	+9	1.3
2015	34	MLB MLE	San Francisco Giants	—	551	512	136	21	3	3	32	93	1	12	4	266	310	336	646	70	310	17	6	290	83	-11	+1	-6	+2	+12	-0.3
2016	35	MLB MLE	San Francisco Giants	—	543	499	139	24	5	13	41	66	0	15	4	279	333	425	758	146	298	12	8	336	114	+9	+1	-5	-6	+12	1.1
2005	24	AAA MLE	Norfolk Tides	—	579	531	137	18	10	7	34	133	1	27	15	258	304	369	673	111	329	23	6	291	83	—	—	—	—	—	—
2005	24	AAA RAW	Norfolk Tides	—	579	516	140	20	10	8	49	111	1	27	15	271	336	395	731	124	329	19	8	321	83	—	—	—	—	—	—
2006	25	MLB MLE	2 teams	—	203	185	46	7	2	5	16	33	0	5	2	249	308	389	698	141	277	16	8	304	92	-2	+0	+1	-2	+4	0.2
2006	25	MLB RAW	2 teams	—	203	185	46	7	2	5	16	32	0	5	2	249	308	389	698	141	275	16	8	309	92	-2	+0	+1	-2	+4	0.2
2007	26	MLB MLE	2 teams	—	288	268	65	13	5	6	16	58	0	10	2	243	285	396	681	153	286	20	6	296	87	-5	+1	+2	+1	+6	0.6
2007	26	MLB RAW	2 teams	—	288	264	68	14	5	7	20	52	0	10	2	258	310	428	738	170	295	18	7	321	87	-5	+1	+2	+1	+6	0.6
2008	27	MLB MLE	New York Mets	—	105	91	25	7	1	0	11	18	0	4	0	275	353	374	727	99	333	17	10	321	103	+0	+1	-1	-1	+2	0.1
2008	27	MLB RAW	New York Mets	—	105	91	25	7	1	0	11	18	0	4	0	275	353	374	727	99	333	17	10	321	103	+0	+1	-1	-1	+2	0.1
2009	28	MLB MLE	2 teams	—	392	358	110	24	11	6	26	59	0	16	7	307	354	486	840	179	351	15	7	360	129	+14	+0	+7	+1	+8	3.2
2009	28	MLB RAW	2 teams	—	392	355	110	24	11	6	29	58	0	16	7	310	362	490	852	180	354	15	7	367	129	+14	+0	+7	+1	+8	3.2
2010	29	MLB MLE	New York Mets	—	633	584	173	33	7	11	39	97	1	37	9	296	341	433	775	137	338	15	6	340	116	+12	+4	+15	+2	+14	4.8
2010	29	MLB RAW	New York Mets	—	633	579	168	31	7	11	44	97	1	37	9	290	341	425	766	135	331	15	7	337	116	+12	+4	+15	+2	+14	4.8
2011	30	MLB MLE	2 teams	—	568	514	135	26	5	8	43	69	2	32	9	263	322	379	701	117	287	12	8	308	95	-3	+3	-12	+2	+12	0.1
2011	30	MLB RAW	2 teams	—	568	509	132	25	5	8	48	67	2	32	9	259	326	375	701	116	282	12	8	311	95	-3	+3	-12	+2	+12	0.1
2012	31	MLB MLE	San Francisco Giants	—	659	610	177	38	15	9	43	97	0	29	7	290	337	446	783	156	331	15	7	341	117	+13	+3	+3	+2	+14	3.7
2012	31	MLB RAW	San Francisco Giants	—	659	605	174	38	15	8	48	97	0	29	7	288	340	440	780	152	329	15	7	342	117	+13	+3	+3	+2	+14	3.7
2013	32	MLB MLE	2 teams	—	327	299	85	16	3	5	24	39	1	9	4	284	340	408	748	124	310	12	7	334	112	+5	+0	-3	+1	+7	1.1
2013	32	MLB RAW	2 teams	—	327	298	84	16	3	5	25	38	1	9	4	282	340	406	746	124	306	12	8	331	112	+5	+0	-3	+1	+7	1.1
2014	33	MLB MLE	San Francisco Giants	—	413	384	116	21	2	3	24	53	1	16	6	302	345	391	735	89	341	13	6	330	109	+5	+1	-3	+1	+9	1.3
2014	33	MLB RAW	San Francisco Giants	—	413	383	115	21	2	3	25	53	1	16	6	300	345	389	734	89	339	13	6	327	109	+5	+1	-3	+1	+9	1.3
2015	34	MLB MLE	San Francisco Giants	—	551	512	136	21	3	3	32	93	1	12	4	266	310	336	646	70	315	17	6	290	83	-11	+1	-6	+2	+12	-0.3
2015	34	MLB RAW	San Francisco Giants	—	551	512	134	21	3	3	32	93	1	12	4	262	306	332	638	70	310	17	6	287	83	-11	+1	-6	+2	+12	-0.3
2016	35	MLB MLE	San Francisco Giants	—	543	499	139	24	5	13	41	66	0	15	4	279	333	425	758	146	298	12	8	336	114	+9	+1	-5	-6	+12	1.1
2016	35	MLB RAW	San Francisco Giants	—	543	495	137	24	5	12	42	66	0	15	4	277	331	418	750	141	298	12	8	332	114	+9	+1	-5	-6	+12	1.1
2005	24	AAA MLE	Norfolk Tides	—	579	539	137	18	10	7	34	133	1	27	15	254	304	364	668	109	319	23	6	291	83	—	—	—	—	—	—
2006	25	MLB MLE	2 teams	—	203	185	46	7	2	5	16	33	0	5	2	249	308	389	698	141	273	16	8	304	92	—	—	—	—	—	—
2007	26	MLB MLE	2 teams	—	288	270	65	13	5	6	16	58	0	10	2	241	285	393	678	152	284	20	6	296	87	—	—	—	—	—	—
2008	27	MLB MLE	New York Mets	—	105	93	25	7	1	0	11	18	0	4	0	269	353	366	719	97	333	17	10	321	103	—	—	—	—	—	—
2009	28	MLB MLE	2 teams	—	392	363	110	24	11	6	26	59	0	16	7	303	354	479	834	176	352	15	7	360	129	—	—	—	—	—	—
2010	29	MLB MLE	New York Mets	—	633	588	173	33	7	11	39	97	1	37	9	294	341	430	772	136	331	15	6	340	116	—	—	—	—	—	—
2011	30	MLB MLE	2 teams	—	568	518	135	26	5	8	43	69	2	32	9	261	322	376	698	116	280	12	8	308	95	—	—	—	—	—	—
2012	31	MLB MLE	San Francisco Giants	—	659	611	177	38	15	9	43	97	0	29	7	290	337	445	782	155	329	15	7	341	117	—	—	—	—	—	—
2013	32	MLB MLE	2 teams	—	327	299	85	16	3	5	24	39	1	9	4	284	340	408	748	124	303	12	7	334	112	—	—	—	—	—	—
2014	33	MLB MLE	San Francisco Giants	—	413	385	116	21	2	3	24	53	1	16	6	301	345	390	734	88	339	13	6	330	109	—	—	—	—	—	—
2015	34	MLB MLE	San Francisco Giants	—	551	513	136	21	3	3	32	93	1	12	4	265	310	335	645	70	310	17	6	290	83	—	—	—	—	—	—
2016	35	MLB MLE	San Francisco Giants	—	543	497	139	24	5	13	41	66	0	15	4	280	333	427	760	147	298	12	8	336	114	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4465	4084	1143	220	55	64	319	638	4	176	51	280	332	408	740	128	316	14	7	326	104	+38	+15	-3	+5	+97	15.3
/ 162G	—	A+C		—	650	595	166	32	8	9	46	93	1	26	7	279	332	405	737	126	315	14	7	326	104	+5	+2	-0	+1	+14	2.2
Career	—	MLE		—	5261	4835	1344	248	69	76	349	815	7	212	69	278	327	405	732	127	318	15	7	322	104	+38	+15	-3	+5	+97	15.3
/ 162G	—	MLE		—	650	597	166	31	9	9	43	101	1	26	9	278	328	405	733	127	319	16	7	322	104	+5	+2	-0	+1	+14	2.2

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.

2013 AAAFresno Grizzlies · 22 PAwOBA .291 → .268 (−22)K% 9.1% → 11.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.09%	÷0.989	×1.290	—	—	11.85%
BB% (unintentional) /PA	4.55%	÷0.908	×0.710	—	×0.952	3.39%
HBP% /PA	4.55%	—	×0.980	—	×0.952	4.24%
Singles /BIP	31.25%	÷0.999	×0.900	—	×0.952	26.81%
Doubles /BIP	0.00%	÷0.974	×0.810	—	×0.952	0.00%
Triples /BIP	0.00%	÷0.954	×0.810	—	×0.952	0.00%
Home runs /BIP	0.00%	÷0.994	×0.780	—	×0.952	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 99, 1B 100, 2B 95, 3B 91, K 98, BB 82 — 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).

Result: wOBA .291 → .268; ISO .000 → .000; BABIP .294 → .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).

2011 A+St. Lucie Mets · 36 PAwOBA .328 → .249 (−80)K% 13.9% → 20.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.89%	÷0.947	×1.420	—	—	20.82%
BB% (unintentional) /PA	11.11%	÷1.042	×0.750	—	×0.940	7.52%
HBP% /PA	2.78%	—	×0.930	—	×0.940	2.43%
Singles /BIP	15.38%	÷1.009	×0.920	—	×0.940	13.18%
Doubles /BIP	3.85%	÷1.013	×0.960	—	×0.940	3.43%
Triples /BIP	3.85%	÷1.097	×0.810	—	×0.940	2.67%
Home runs /BIP	3.85%	÷1.095	×0.880	—	×0.940	2.91%

Factors used: league row FSL. Park (home-season share, regressed): HR 119, 1B 102, 2B 103, 3B 119, K 89, BB 108 — applied at half strength. Age: age 30 vs a level average of 22.8 → −6.0% on BB/HBP/hit rates (7.2 yr older than average).

Result: wOBA .328 → .249; ISO .194 → .141; BABIP .240 → .199. 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).

2009 A+St. Lucie Mets · 16 PAwOBA .493 → .417 (−76)K% 12.5% → 17.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.50%	÷1.000	×1.420	—	—	17.75%
BB% (unintentional) /PA	25.00%	÷1.000	×0.750	—	×0.948	17.77%
HBP% /PA	0.00%	—	×0.930	—	×0.948	0.00%
Singles /BIP	30.00%	÷1.000	×0.920	—	×0.948	26.16%
Doubles /BIP	20.00%	÷1.000	×0.960	—	×0.948	18.20%
Triples /BIP	0.00%	÷1.000	×0.810	—	×0.948	0.00%
Home runs /BIP	0.00%	÷1.000	×0.880	—	×0.948	0.00%

Factors used: league row FSL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 28 vs a level average of 22.8 → −5.2% on BB/HBP/hit rates (5.2 yr older than average).

Result: wOBA .493 → .417; ISO .167 → .156; BABIP .500 → .444. 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).

2007 AAAIowa Cubs · 127 PAwOBA .307 → .261 (−45)K% 15.7% → 20.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.75%	÷1.000	×1.290	—	—	20.31%
BB% (unintentional) /PA	7.09%	÷1.000	×0.710	—	×1.018	5.12%
HBP% /PA	0.00%	—	×0.980	—	×1.018	0.00%
Singles /BIP	19.79%	÷1.000	×0.900	×1.031	×1.018	18.70%
Doubles /BIP	4.17%	÷1.000	×0.810	×1.031	×1.018	3.54%
Triples /BIP	3.12%	÷1.000	×0.810	×1.031	×1.018	2.66%
Home runs /BIP	3.12%	÷1.000	×0.780	—	×1.018	2.48%

Factors used: league row PCL. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×1.031.

Result: wOBA .307 → .261; ISO .164 → .133; BABIP .280 → .255. 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).

2006 AAAIowa Cubs · 16 PAwOBA .286 → .232 (−54)K% 25.0% → 32.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.000	×1.290	—	—	32.25%
BB% (unintentional) /PA	6.25%	÷1.000	×0.710	—	×1.033	4.58%
HBP% /PA	0.00%	—	×0.980	—	×1.033	0.00%
Singles /BIP	27.27%	÷1.000	×0.900	—	×1.033	25.36%
Doubles /BIP	9.09%	÷1.000	×0.810	—	×1.033	7.61%
Triples /BIP	0.00%	÷1.000	×0.810	—	×1.033	0.00%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×1.033	0.00%

Factors used: league row PCL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average).

Result: wOBA .286 → .232; ISO .067 → .051; BABIP .364 → .330. 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).

2005 AAANorfolk Tides · 579 PAwOBA .313 → .291 (−23)K% 19.2% → 23.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.17%	÷1.000	×1.200	—	—	23.01%
BB% (unintentional) /PA	8.12%	÷1.000	×0.690	—	×1.048	5.87%
HBP% /PA	0.17%	—	×0.940	—	×1.048	0.17%
Singles /BIP	25.19%	÷1.000	×0.930	×1.009	×1.048	24.76%
Doubles /BIP	4.94%	÷1.000	×0.830	×1.009	×1.048	4.33%
Triples /BIP	2.47%	÷1.000	×0.970	×1.009	×1.048	2.53%
Home runs /BIP	1.98%	÷1.000	×0.840	—	×1.048	1.74%

Factors used: league row IL. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×1.009.

Result: wOBA .313 → .291; ISO .124 → .116; BABIP .329 → .319. 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).