Carlos Moncrief

PosRF

B/TL/R

Born1988-11-03

Age (2027)38

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2019

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2016	27	AA/INTL2 orgs	276	.244/.354/.380	5	7	77	—	.234/.304/.351
2017	28	AAA/INTL2 orgs	286	.271/.353/.410	5	4	81	—	.227/.277/.335
2017	28	MLBSF	43	.211/.268/.237	0	0	40	-0.6
2019	30	AAAGenerales de …	61	.192/.283/.327	2	0	18	—	.145/.217/.218
2020	31	No MLB games played
2021	32	No MLB games played
2022	33	No MLB games played
2023	34	No MLB games played
2024	35	No MLB games played
2025	36	No MLB games played
2026	37	No MLB games played

Last 3 seasons WAR -0.6

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)
2011	22	A	Lake County Captains	—	552	464	108	26	7	16	76	158	6	20	7	233	348	422	770	190	314	29	14	342	55	—	—	—	—	—	—
2011	22	INTL	Phoenix Desert Dogs	—	30	23	4	1	0	0	5	8	2	0	0	174	367	217	584	43	267	27	17	299	88	—	—	—	—	—	—
2012	23	A+	Carolina Mudcats	—	407	353	88	23	4	15	46	126	3	17	2	249	341	465	805	215	341	31	11	352	55	—	—	—	—	—	—
2012	23	INTL	Scottsdale Scorpions	—	48	42	7	2	0	1	6	19	0	3	0	167	271	286	557	119	273	40	12	259	62	—	—	—	—	—	—
2013	24	AA	Akron Aeros	—	552	489	139	26	7	17	55	98	1	15	7	284	358	470	828	186	321	18	10	362	101	—	—	—	—	—	—
2013	24	INTL	Gigantes de Carolina	—	107	100	23	2	0	1	5	34	1	0	1	230	274	280	554	50	338	32	5	252	57	—	—	—	—	—	—
2014	25	AAA	Columbus Clippers	—	530	480	130	33	4	12	38	130	4	8	3	271	330	431	761	160	347	25	7	333	78	—	—	—	—	—	—
2014	25	INTL	Aguilas del Zulia	—	121	108	28	6	0	1	13	32	0	0	0	259	339	343	681	83	360	26	11	313	98	—	—	—	—	—	—
2015	26	AAA	Columbus Clippers	—	203	166	31	3	0	7	32	59	2	5	0	187	325	331	656	145	235	29	16	302	43	—	—	—	—	—	—
2015	26	AA	Akron RubberDucks	—	237	199	52	9	3	4	34	28	0	6	4	261	368	397	765	136	286	12	14	342	91	—	—	—	—	—	—
2015	26	INTL	Mayos de Navojoa	—	201	165	49	9	1	3	31	30	1	5	1	297	411	418	829	121	348	15	15	370	136	—	—	—	—	—	—
2016	27	AA	Richmond Flying Squirrels	—	209	176	46	11	0	5	28	38	3	6	0	261	372	409	781	148	308	18	13	351	78	—	—	—	—	—	—
2016	27	INTL	Mayos de Navojoa	—	67	58	11	6	0	0	9	17	0	1	0	190	299	293	592	103	268	25	13	276	73	—	—	—	—	—	—
2017	28	MLB	San Francisco Giants	—	43	38	8	1	0	0	3	15	0	0	0	211	268	237	505	26	320	35	7	226	40	-3	+0	-0	-4	+1	-0.6
2017	28	AAA	Sacramento River Cats	—	190	171	49	17	0	2	17	45	0	4	2	287	351	421	772	135	376	24	9	342	65	—	—	—	—	—	—
2017	28	INTL	Aguilas del Zulia	—	96	80	19	3	0	3	15	23	0	0	1	237	358	388	745	150	291	24	16	337	114	—	—	—	—	—	—
2019	30	AAA	Generales de Durango	—	61	52	10	1	0	2	6	10	1	0	0	192	283	327	610	135	195	16	10	274	18	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	43	38	8	1	0	0	3	15	0	0	0	211	268	237	505	26	320	35	7	226	39	-3	+0	-0	-4	+1	-0.6
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2011	22	A MLE	Lake County Captains	—	552	489	87	20	6	10	51	217	6	20	7	178	264	305	568	127	284	39	9	250	55	—	—	—	—	—	—
2012	23	A+ MLE	Carolina Mudcats	—	407	373	67	16	3	13	26	186	3	17	2	180	239	343	582	164	297	46	6	250	55	—	—	—	—	—	—
2013	24	AA MLE	Akron Aeros	—	552	509	134	24	7	15	35	121	1	15	7	263	312	426	738	163	307	22	6	318	101	—	—	—	—	—	—
2014	25	AAA MLE	Columbus Clippers	—	530	495	120	28	4	10	23	154	4	8	3	242	282	376	657	133	321	29	4	283	78	—	—	—	—	—	—
2015	26	AAA MLE	Columbus Clippers	—	203	178	28	3	0	5	20	70	2	5	0	157	250	258	508	101	212	34	10	232	43	—	—	—	—	—	—
2015	26	AA MLE	Akron RubberDucks	—	237	210	52	8	3	4	24	33	0	6	4	248	325	371	696	124	270	14	10	302	91	—	—	—	—	—	—
2016	27	AA MLE	Richmond Flying Squirrels	—	209	188	44	10	0	4	16	48	3	6	0	234	304	351	655	117	284	23	8	284	78	—	—	—	—	—	—
2017	28	MLB MLE	San Francisco Giants	—	43	38	8	1	0	0	3	15	0	0	0	211	268	237	505	26	320	35	7	228	40	-3	+0	-0	-4	+1	-0.6
2017	28	AAA MLE	Sacramento River Cats	—	190	176	40	13	0	2	12	59	0	4	2	227	277	335	612	108	321	31	6	265	65	—	—	—	—	—	—
2019	30	AAA MLE	Generales de Durango	—	61	55	8	1	0	1	4	13	1	0	0	145	217	218	435	73	161	21	7	195	18	—	—	—	—	—	—
2011	22	A MLE	2 teams	—	582	514	91	21	6	10	54	229	8	20	7	177	266	300	565	123	291	39	9	250	55	—	—	—	—	—	—
2011	22	A RAW	2 teams	—	582	487	112	27	7	16	81	166	8	20	7	230	349	413	762	183	312	29	14	340	55	—	—	—	—	—	—
2012	23	A+ MLE	2 teams	—	455	417	73	17	3	14	30	207	3	20	2	175	236	331	566	156	298	45	7	250	55	—	—	—	—	—	—
2012	23	A+ RAW	2 teams	—	455	395	95	25	4	16	52	145	3	20	2	241	333	446	779	205	335	32	11	342	55	—	—	—	—	—	—
2013	24	AA MLE	2 teams	—	659	607	159	28	8	18	42	145	2	15	8	262	312	423	735	161	313	22	6	318	101	—	—	—	—	—	—
2013	24	AA RAW	2 teams	—	659	589	162	28	7	18	60	132	2	15	8	275	344	438	782	163	324	20	9	344	101	—	—	—	—	—	—
2014	25	AAA MLE	2 teams	—	651	611	146	34	5	12	28	189	4	8	3	239	277	370	647	131	325	29	4	283	78	—	—	—	—	—	—
2014	25	AAA RAW	2 teams	—	651	588	158	39	4	13	51	162	4	8	3	269	331	415	746	146	349	25	8	329	78	—	—	—	—	—	—
2015	26	AA MLE	3 teams	—	641	564	116	15	4	13	64	151	3	16	5	206	290	316	606	110	256	24	10	270	69	—	—	—	—	—	—
2015	26	AA RAW	3 teams	—	641	530	132	21	4	14	97	117	3	16	5	249	368	383	751	134	294	18	15	338	69	—	—	—	—	—	—
2016	27	AA MLE	2 teams	—	276	250	57	13	0	5	21	63	3	7	0	228	296	340	636	112	286	23	8	284	78	—	—	—	—	—	—
2016	27	AA RAW	2 teams	—	276	234	57	17	0	5	37	55	3	7	0	244	354	380	734	137	299	20	13	333	78	—	—	—	—	—	—
2017	28	AAA MLE	3 teams	—	329	303	67	20	0	2	21	104	0	4	3	221	272	307	579	86	323	32	6	258	61	—	—	—	—	—	—
2017	28	AAA RAW	3 teams	—	329	289	76	21	0	5	35	83	0	4	3	263	343	388	730	125	346	25	11	325	61	—	—	—	—	—	—
2019	30	AAA MLE	Generales de Durango	—	61	55	8	1	0	1	4	13	1	0	0	145	217	218	435	73	167	21	7	195	18	—	—	—	—	—	—
2019	30	AAA RAW	Generales de Durango	—	61	52	10	1	0	2	6	10	1	0	0	192	283	327	610	135	195	16	10	274	18	—	—	—	—	—	—
2011	22	A MLE	2 teams	—	582	515	91	21	6	10	54	229	8	20	7	177	266	299	565	122	284	39	9	250	55	—	—	—	—	—	—
2012	23	A+ MLE	2 teams	—	455	419	73	17	3	14	30	207	3	20	2	174	236	329	565	155	297	45	7	250	55	—	—	—	—	—	—
2013	24	AA MLE	2 teams	—	659	610	159	28	8	18	42	145	2	15	8	261	312	421	733	161	307	22	6	318	101	—	—	—	—	—	—
2014	25	AAA MLE	2 teams	—	651	614	146	34	5	12	28	189	4	8	3	238	277	368	645	130	321	29	4	283	78	—	—	—	—	—	—
2015	26	AA MLE	3 teams	—	641	569	116	15	4	13	64	151	3	16	5	204	290	313	603	109	243	24	10	270	69	—	—	—	—	—	—
2016	27	AA MLE	2 teams	—	276	250	57	13	0	5	21	63	3	7	0	228	296	340	636	112	284	23	8	284	78	—	—	—	—	—	—
2017	28	AAA MLE	3 teams	—	329	305	67	20	0	2	21	104	0	4	3	220	272	305	577	85	321	32	6	258	61	—	—	—	—	—	—
2019	30	AAA MLE	Generales de Durango	—	61	56	8	1	0	1	4	13	1	0	0	143	217	214	431	71	161	21	7	195	18	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	43	38	8	1	0	0	3	15	0	0	0	211	268	237	505	26	320	35	7	226	72	-3	+0	-0	-4	+1	-0.6
/ 162G	—	A+C		—	650	574	121	15	0	0	45	227	0	0	0	211	268	237	505	26	321	35	7	226	72	-47	+0	-6	-53	+14	-9.4
Career	—	MLE		—	3654	3321	717	149	26	75	264	1101	24	90	28	216	278	344	623	128	296	30	7	274	72	-3	+0	-0	-4	+1	-0.6
/ 162G	—	MLE		—	650	591	128	27	5	13	47	196	4	16	5	217	279	345	624	129	298	30	7	274	72	-47	+0	-6	-53	+14	-9.4

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 AAAGenerales de Durango · 61 PAwOBA .271 → .195 (−76)K% 16.4% → 20.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.39%	÷0.946	×1.200	—	—	20.79%
BB% (unintentional) /PA	9.84%	÷1.118	×0.690	—	×0.962	5.84%
HBP% /PA	1.64%	—	×0.940	—	×0.962	1.48%
Singles /BIP	16.67%	÷1.034	×0.930	—	×0.962	14.41%
Doubles /BIP	2.38%	÷1.163	×0.830	—	×0.962	1.63%
Triples /BIP	0.00%	÷1.150	×0.920	—	×0.962	0.00%
Home runs /BIP	4.76%	÷1.311	×0.700	—	×0.962	2.45%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 162, 1B 107, 2B 133, 3B 130, K 89, BB 124 — 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).

Result: wOBA .271 → .195; ISO .135 → .076; BABIP .195 → .161. 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 AAASacramento River Cats · 190 PAwOBA .333 → .265 (−68)K% 23.7% → 30.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.68%	÷0.989	×1.290	—	—	30.89%
BB% (unintentional) /PA	8.42%	÷0.952	×0.710	—	×0.982	6.17%
HBP% /PA	0.00%	—	×0.980	—	×0.982	0.00%
Singles /BIP	23.81%	÷1.027	×0.900	×1.013	×0.982	20.76%
Doubles /BIP	13.49%	÷0.975	×0.810	×1.013	×0.982	11.15%
Triples /BIP	0.00%	÷0.920	×0.810	×1.013	×0.982	0.00%
Home runs /BIP	1.59%	÷0.889	×0.780	—	×0.982	1.37%

Factors used: league row PCL. Park (home-season share, regressed): HR 78, 1B 105, 2B 95, 3B 84, K 98, BB 90 — 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 ×1.013.

Result: wOBA .333 → .265; ISO .135 → .107; BABIP .376 → .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).

2016 AARichmond Flying Squirrels · 209 PAwOBA .341 → .284 (−57)K% 18.2% → 22.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.18%	÷0.975	×1.220	—	—	22.75%
BB% (unintentional) /PA	12.92%	÷1.155	×0.700	—	×0.968	7.58%
HBP% /PA	1.44%	—	×0.850	—	×0.968	1.18%
Singles /BIP	21.74%	÷0.994	×0.970	×1.011	×0.968	20.76%
Doubles /BIP	7.97%	÷0.975	×0.860	×1.011	×0.968	6.88%
Triples /BIP	0.00%	÷1.150	×0.950	×1.011	×0.968	0.00%
Home runs /BIP	3.62%	÷0.978	×0.780	—	×0.968	2.80%

Factors used: league row EL. Park (home-season share, regressed): HR 96, 1B 99, 2B 95, 3B 130, K 95, BB 131 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.011.

Result: wOBA .341 → .284; ISO .148 → .124; BABIP .308 → .284. 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 AAAkron RubberDucks · 237 PAwOBA .334 → .302 (−32)K% 11.8% → 14.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.81%	÷1.019	×1.220	—	—	14.15%
BB% (unintentional) /PA	13.92%	÷0.934	×0.700	—	×0.978	10.20%
HBP% /PA	0.00%	—	×0.850	—	×0.978	0.00%
Singles /BIP	21.05%	÷0.971	×0.970	×1.016	×0.978	20.89%
Doubles /BIP	5.26%	÷1.053	×0.860	×1.016	×0.978	4.27%
Triples /BIP	1.75%	÷1.150	×0.950	×1.016	×0.978	1.44%
Home runs /BIP	2.34%	÷0.842	×0.780	—	×0.978	2.12%

Factors used: league row EL. Park (home-season share, regressed): HR 68, 1B 94, 2B 111, 3B 130, K 104, BB 87 — 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 ×1.016.

Result: wOBA .334 → .302; ISO .136 → .122; BABIP .286 → .270. 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 AAAColumbus Clippers · 203 PAwOBA .295 → .232 (−63)K% 29.1% → 34.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.06%	÷1.009	×1.200	—	—	34.55%
BB% (unintentional) /PA	15.27%	÷1.068	×0.690	—	×1.003	9.90%
HBP% /PA	0.99%	—	×0.940	—	×1.003	0.93%
Singles /BIP	19.63%	÷1.005	×0.930	×1.007	×1.003	18.36%
Doubles /BIP	2.80%	÷1.019	×0.830	×1.007	×1.003	2.31%
Triples /BIP	0.00%	÷0.900	×0.970	×1.007	×1.003	0.00%
Home runs /BIP	6.54%	÷1.217	×0.840	—	×1.003	4.53%

Factors used: league row IL. Park (home-season share, regressed): HR 143, 1B 101, 2B 104, 3B 80, K 102, BB 114 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.007.

Result: wOBA .295 → .232; ISO .145 → .106; BABIP .235 → .212. 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 AAAColumbus Clippers · 530 PAwOBA .322 → .283 (−39)K% 24.5% → 29.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.53%	÷1.016	×1.200	—	—	28.96%
BB% (unintentional) /PA	6.23%	÷1.015	×0.690	—	×1.018	4.31%
HBP% /PA	0.75%	—	×0.940	—	×1.018	0.72%
Singles /BIP	23.14%	÷1.034	×0.930	×1.047	×1.018	22.20%
Doubles /BIP	9.43%	÷1.047	×0.830	×1.047	×1.018	7.97%
Triples /BIP	1.14%	÷1.007	×0.970	×1.047	×1.018	1.17%
Home runs /BIP	3.43%	÷1.028	×0.840	—	×1.018	2.85%

Factors used: league row IL. Park (home-season share, regressed): HR 106, 1B 107, 2B 109, 3B 102, K 103, BB 103 — 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 ×1.047.

Result: wOBA .322 → .283; ISO .160 → .138; BABIP .347 → .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).

2013 AAAkron Aeros · 552 PAwOBA .354 → .318 (−37)K% 17.8% → 22.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.75%	÷0.984	×1.220	—	—	22.02%
BB% (unintentional) /PA	9.42%	÷1.029	×0.700	—	×0.998	6.40%
HBP% /PA	0.18%	—	×0.850	—	×0.998	0.15%
Singles /BIP	22.76%	÷1.037	×0.970	×1.048	×0.998	22.27%
Doubles /BIP	6.65%	÷1.001	×0.860	×1.048	×0.998	5.98%
Triples /BIP	1.79%	÷1.049	×0.950	×1.048	×0.998	1.70%
Home runs /BIP	4.35%	÷0.879	×0.780	—	×0.998	3.85%

Factors used: league row EL. Park (home-season share, regressed): HR 76, 1B 107, 2B 100, 3B 110, K 97, BB 106 — 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 ×1.048.

Result: wOBA .354 → .318; ISO .186 → .169; BABIP .321 → .307. 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 A+Carolina Mudcats · 407 PAwOBA .342 → .250 (−93)K% 31.0% → 45.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.96%	÷0.963	×1.420	—	—	45.63%
BB% (unintentional) /PA	10.81%	÷1.035	×0.630	—	×0.988	6.50%
HBP% /PA	0.74%	—	×0.860	—	×0.988	0.63%
Singles /BIP	20.26%	÷1.054	×0.940	×1.029	×0.988	18.37%
Doubles /BIP	10.13%	÷1.054	×0.830	×1.029	×0.988	8.11%
Triples /BIP	1.76%	÷0.900	×0.800	×1.029	×0.988	1.59%
Home runs /BIP	6.61%	÷0.895	×0.900	—	×0.988	6.56%

Factors used: league row CAR. Park (home-season share, regressed): HR 79, 1B 111, 2B 111, 3B 80, K 93, BB 107 — 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 ×1.029.

Result: wOBA .342 → .250; ISO .215 → .169; BABIP .341 → .297. 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 — .