Jesús Sucre

PosC

B/TR/R

Born1988-04-30

Age (2027)39

No MLB projection yet. Career stats below are historical.

Overview

INTL

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	wRC+	WAR
2023	35	INTLAguilas del Z…	103	.258/.317/.387	2	96	—
2024	36	INTLTigres de Ara…	128	.342/.389/.436	2	133	—
2025	37	INTLCaribes de An…	118	.301/.374/.398	1	117	—

Contract

No contract data on file.

Skills · percentileStatcast 2017-2019

xwOBA15

Avg EV15

Barrel%10

Speed10

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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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)
2006	18	ROK	DSL Braves	—	145	133	37	8	1	1	9	12	2	1	1	278	333	376	709	98	298	8	6	318	30	—	—	—	—	—	—
2007	19	ROK	GCL Braves	—	114	104	23	5	0	0	7	10	0	1	1	221	270	269	540	48	240	9	6	242	14	—	—	—	—	—	—
2008	20	ROK	Danville Braves	—	163	154	28	2	0	3	7	24	1	1	1	182	222	253	475	71	197	15	4	216	-4	—	—	—	—	—	—
2009	21	A+	Myrtle Beach Pelicans	—	206	197	51	8	1	5	8	33	0	3	1	259	288	386	674	127	287	16	4	298	57	—	—	—	—	—	—
2009	21	A	Rome Braves	—	176	169	55	15	0	1	6	17	1	1	4	325	352	432	784	107	358	10	3	350	93	—	—	—	—	—	—
2010	22	AA	Mississippi Braves	—	147	145	43	11	1	2	1	17	0	0	2	297	301	428	729	131	325	12	1	319	69	—	—	—	—	—	—
2010	22	A+	Myrtle Beach Pelicans	—	200	191	42	9	0	5	7	26	1	1	0	220	251	346	597	126	231	13	4	265	42	—	—	—	—	—	—
2011	23	AA	Jackson Generals	—	237	221	48	8	0	1	11	19	1	0	2	217	258	267	524	50	233	8	5	237	34	—	—	—	—	—	—
2011	23	INTL	Leones del Caracas	—	54	44	9	1	0	0	4	6	3	0	1	205	314	227	541	23	237	11	7	250	56	—	—	—	—	—	—
2012	24	AA	Jackson Generals	—	349	321	87	11	0	1	20	39	3	1	1	271	320	315	634	44	305	11	6	287	65	—	—	—	—	—	—
2012	24	INTL	Leones del Caracas	—	54	46	11	2	0	0	5	9	0	0	1	239	314	283	596	43	282	17	9	263	64	—	—	—	—	—	—
2013	25	MLB	Seattle Mariners	—	29	26	5	0	0	0	2	1	0	0	0	192	250	192	442		192	3	7	204	25	-3	+0	+2	+3	+1	0.4
2013	25	AAA	Tacoma Rainiers	—	95	87	26	3	0	0	7	10	0	1	1	299	351	333	684	34	338	11	7	311	74	—	—	—	—	—	—
2013	25	ROK	AZL Mariners	—	20	19	6	1	0	0	1	2	0	0	0	316	350	368	718	53	353	10	5	325	40	—	—	—	—	—	—
2013	25	INTL	Leones del Caracas	—	49	45	8	0	0	0	3	7	0	0	0	178	229	178	407		211	14	6	190	15	—	—	—	—	—	—
2014	26	MLB	Seattle Mariners	—	64	61	13	2	0	0	0	17	0	0	0	213	213	246	459	33	295	27	0	196	20	-6	+0	+4	+5	+1	0.4
2014	26	AAA	Tacoma Rainiers	—	181	175	48	7	1	2	4	29	1	0	1	274	294	360	654	86	317	16	2	291	46	—	—	—	—	—	—
2014	26	INTL	Leones del Caracas	—	18	18	2	0	0	0	0	2	0	0	0	111	111	111	222		125	11	0	101	-46	—	—	—	—	—	—
2015	27	MLB	Seattle Mariners	—	142	127	20	6	0	1	6	21	0	0	0	157	195	228	424	71	181	15	4	181	10	-15	+0	+11	+4	+3	0.2
2015	27	AAA	Tacoma Rainiers	—	26	23	6	0	0	0	3	8	0	0	0	261	346	261	607		400	31	12	289	40	—	—	—	—	—	—
2015	27	INTL	Navegantes del Magallanes	—	45	40	14	0	0	0	4	2	0	0	0	350	409	350	759		368	4	9	344	119	—	—	—	—	—	—
2016	28	MLB	Seattle Mariners	—	29	25	12	2	0	1	2	5	2	0	0	480	552	680	1.232	200	579	17	7	540	255	+5	+0	+1	+5	+1	1.2
2016	28	AAA	Tacoma Rainiers	—	104	99	27	4	1	0	3	15	1	0	1	273	301	333	634	61	321	14	3	284	49	—	—	—	—	—	—
2016	28	INTL	Navegantes del Magallanes	—	149	129	30	9	0	0	17	20	0	0	0	233	322	302	624	70	270	13	11	285	79	—	—	—	—	—	—
2017	29	MLB	Tampa Bay Rays	—	192	176	45	6	0	7	7	35	3	2	0	256	296	409	705	153	275	18	4	304	92	-2	+0	+6	+5	+4	1.5
2017	29	INTL	Navegantes del Magallanes	—	110	103	32	2	0	3	3	13	2	0	0	311	343	417	760	107	333	12	3	335	113	—	—	—	—	—	—
2018	30	MLB	Tampa Bay Rays	—	198	182	38	5	0	1	9	29	1	1	0	209	250	253	503	44	240	15	5	225	32	-16	+0	-0	+5	+4	-0.6
2018	30	INTL	Navegantes del Magallanes	—	93	83	21	2	1	0	7	6	0	0	0	253	311	301	612	48	269	6	8	273	71	—	—	—	—	—	—
2019	31	MLB	Baltimore Orioles	—	67	62	13	2	0	0	4	13	1	0	0	210	269	242	511	32	265	19	6	240	48	-4	+0	+1	+5	+1	0.4
2019	31	AAA	Norfolk Tides	—	198	184	52	15	0	0	12	29	2	0	0	283	333	364	697	82	335	15	6	316	47	—	—	—	—	—	—
2019	31	INTL	Caribes de Anzoategui	—	29	27	7	0	0	0	1	3	1	0	0	259	310	259	570		292	10	3	268	67	—	—	—	—	—	—
2020	32	INTL	Venezuela	—	120	113	37	7	0	2	4	11	0	0	0	327	350	442	793	115	350	9	3	344	119	—	—	—	—	—	—
2021	33	INTL	Caribes de Anzoategui	—	108	97	27	2	0	1	10	11	0	0	0	278	346	330	676	52	306	10	9	309	95	—	—	—	—	—	—
2022	34	INTL	Caribes de Anzoategui	—	153	142	38	5	1	3	6	12	2	0	0	268	307	380	687	113	271	8	4	302	90	—	—	—	—	—	—
2023	35	INTL	Aguilas del Zulia	—	103	93	24	6	0	2	7	10	1	0	0	258	317	387	704	129	272	10	7	310	96	—	—	—	—	—	—
2024	36	INTL	Tigres de Aragua	—	128	117	40	5	0	2	9	6	0	0	0	342	389	436	825	94	342	5	7	365	133	—	—	—	—	—	—
2025	37	INTL	Caribes de Anzoategui	—	118	103	31	7	0	1	10	20	2	0	0	301	374	398	772	97	361	17	8	342	117	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	721	659	146	23	0	10	30	121	7	3	0	222	263	302	565	80	254	17	4	248	54	-40	+1	+25	+33	+16	3.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2006	18	ROK MLE	DSL Braves	—	145	136	25	5	1	0	6	15	2	1	1	184	229	235	464	51	202	10	4	212	30	—	—	—	—	—	—
2007	19	ROK MLE	GCL Braves	—	114	107	19	4	0	0	4	14	0	1	1	178	207	215	422	37	197	12	4	189	14	—	—	—	—	—	—
2008	20	ROK MLE	Danville Braves	—	163	157	22	1	0	2	4	34	1	1	1	140	167	185	351	45	166	21	2	162	-4	—	—	—	—	—	—
2009	21	A+ MLE	Myrtle Beach Pelicans	—	206	200	46	7	1	4	5	47	0	3	1	230	249	335	584	105	277	23	2	253	57	—	—	—	—	—	—
2009	21	A MLE	Rome Braves	—	176	171	51	13	0	1	4	23	1	1	4	298	318	392	710	94	340	13	2	305	93	—	—	—	—	—	—
2010	22	AA MLE	Mississippi Braves	—	147	146	38	10	1	2	0	21	0	0	2	260	260	384	644	123	291	14	0	270	69	—	—	—	—	—	—
2010	22	A+ MLE	Myrtle Beach Pelicans	—	200	194	39	8	0	4	4	37	1	1	0	201	221	304	525	103	231	18	2	230	42	—	—	—	—	—	—
2011	23	AA MLE	Jackson Generals	—	237	225	49	8	0	1	7	23	1	0	2	218	245	267	511	49	230	10	3	219	34	—	—	—	—	—	—
2012	24	AA MLE	Jackson Generals	—	349	328	88	9	0	1	13	49	3	1	1	268	302	305	607	37	304	14	4	265	65	—	—	—	—	—	—
2013	25	MLB MLE	Seattle Mariners	—	29	26	5	0	0	0	2	1	0	0	0	192	250	192	442		192	3	7	205	25	-3	+0	+2	+3	+1	0.4
2013	25	AAA MLE	Tacoma Rainiers	—	95	89	25	3	0	0	5	13	0	1	1	281	319	315	634	34	322	14	5	277	74	—	—	—	—	—	—
2013	25	ROK MLE	AZL Mariners	—	20	19	5	1	0	0	1	3	0	0	0	263	300	316	616	53	268	15	5	227	40	—	—	—	—	—	—
2014	26	MLB MLE	Seattle Mariners	—	64	61	13	2	0	0	0	17	0	0	0	213	213	246	459	33	295	27	0	197	20	-6	+0	+4	+5	+1	0.4
2014	26	AAA MLE	Tacoma Rainiers	—	181	176	41	6	1	2	3	37	1	0	1	233	250	312	562	80	277	20	2	236	46	—	—	—	—	—	—
2015	27	MLB MLE	Seattle Mariners	—	142	127	20	6	0	1	6	21	0	0	0	157	195	228	424	71	181	15	4	183	10	-15	+0	+11	+4	+3	0.2
2015	27	AAA MLE	Tacoma Rainiers	—	26	24	5	0	0	0	2	10	0	0	0	208	269	208	478		363	38	8	228	40	—	—	—	—	—	—
2016	28	MLB MLE	Seattle Mariners	—	29	25	12	2	0	1	2	5	2	0	0	480	552	680	1.232	200	579	17	7	545	255	+5	+0	+1	+5	+1	1.2
2016	28	AAA MLE	Tacoma Rainiers	—	104	100	25	4	1	0	2	19	1	0	1	250	272	310	582	60	293	18	2	241	49	—	—	—	—	—	—
2017	29	MLB MLE	Tampa Bay Rays	—	192	176	44	6	0	7	7	35	3	2	0	250	290	403	694	153	275	18	4	304	92	-2	+0	+6	+5	+4	1.5
2018	30	MLB MLE	Tampa Bay Rays	—	198	184	37	5	0	1	7	29	1	1	0	201	234	245	479	43	240	15	4	216	32	-16	+0	-0	+5	+4	-0.6
2019	31	MLB MLE	Baltimore Orioles	—	67	62	13	2	0	0	4	13	1	0	0	210	269	242	511	32	265	19	6	239	48	-4	+0	+1	+5	+1	0.4
2019	31	AAA MLE	Norfolk Tides	—	198	189	41	11	0	0	7	36	2	0	0	217	253	275	528	58	271	18	4	237	47	—	—	—	—	—	—
2006	18	ROK MLE	DSL Braves	—	145	136	25	5	1	0	6	15	2	1	1	184	229	235	464	51	205	10	4	212	30	—	—	—	—	—	—
2006	18	ROK RAW	DSL Braves	—	145	133	37	8	1	1	9	12	2	1	1	278	333	376	709	98	298	8	6	318	30	—	—	—	—	—	—
2007	19	ROK MLE	GCL Braves	—	114	107	19	4	0	0	4	14	0	1	1	178	207	215	422	37	200	12	4	189	14	—	—	—	—	—	—
2007	19	ROK RAW	GCL Braves	—	114	104	23	5	0	0	7	10	0	1	1	221	270	269	540	48	240	9	6	242	14	—	—	—	—	—	—
2008	20	ROK MLE	Danville Braves	—	163	157	22	1	0	2	4	34	1	1	1	140	167	185	351	45	165	21	2	162	-4	—	—	—	—	—	—
2008	20	ROK RAW	Danville Braves	—	163	154	28	2	0	3	7	24	1	1	1	182	222	253	475	71	197	15	4	216	-4	—	—	—	—	—	—
2009	21	A+ MLE	2 teams	—	382	371	97	19	1	5	9	69	1	4	5	261	281	358	639	97	309	18	2	277	74	—	—	—	—	—	—
2009	21	A+ RAW	2 teams	—	382	366	106	23	1	6	14	50	1	4	5	290	318	407	725	117	322	13	4	322	74	—	—	—	—	—	—
2010	22	A+ MLE	2 teams	—	347	340	77	18	1	6	4	59	1	1	2	226	238	338	576	112	258	17	1	247	53	—	—	—	—	—	—
2010	22	A+ RAW	2 teams	—	347	336	85	20	1	7	8	43	1	1	2	253	272	381	653	128	273	12	2	287	53	—	—	—	—	—	—
2011	23	AA MLE	2 teams	—	291	271	59	9	0	1	9	28	4	0	3	218	254	262	516	44	239	10	3	219	34	—	—	—	—	—	—
2011	23	AA RAW	2 teams	—	291	265	57	9	0	1	15	25	4	0	3	215	268	260	528	45	233	9	5	239	34	—	—	—	—	—	—
2012	24	AA MLE	2 teams	—	403	377	101	10	0	1	15	56	3	1	2	268	301	302	604	34	310	14	4	265	65	—	—	—	—	—	—
2012	24	AA RAW	2 teams	—	403	367	98	13	0	1	25	48	3	1	2	267	319	311	630	44	302	12	6	284	65	—	—	—	—	—	—
2013	25	AAA MLE	4 teams	—	193	180	46	4	0	0	10	22	0	1	1	256	295	278	573	22	289	11	5	256	59	—	—	—	—	—	—
2013	25	AAA RAW	4 teams	—	193	177	45	4	0	0	13	20	0	1	1	254	305	277	582	23	285	10	7	266	59	—	—	—	—	—	—
2014	26	AAA MLE	3 teams	—	263	255	57	8	1	2	3	58	1	0	1	224	236	286	522	63	281	22	1	226	39	—	—	—	—	—	—
2014	26	AAA RAW	3 teams	—	263	254	63	9	1	2	4	48	1	0	1	248	263	315	578	67	298	18	2	255	39	—	—	—	—	—	—
2015	27	MLB MLE	3 teams	—	213	193	32	8	0	1	10	39	0	0	0	166	207	223	430	57	203	18	5	190	15	-22	+0	+11	+4	+5	-0.2
2015	27	MLB RAW	3 teams	—	213	190	40	6	0	1	13	31	0	0	0	211	261	258	519	47	247	15	6	229	15	-22	+0	+11	+4	+5	-0.2
2016	28	INTL MLE	3 teams	—	282	267	77	12	2	2	8	50	3	0	1	288	317	371	687	82	346	18	3	307	94	—	—	—	—	—	—
2016	28	INTL RAW	3 teams	—	282	253	69	15	1	1	22	40	3	0	1	273	338	352	690	79	318	14	8	311	94	—	—	—	—	—	—
2017	29	MLB MLE	2 teams	—	302	278	70	10	0	11	11	55	5	2	0	252	293	406	699	155	273	18	4	304	92	-3	+0	+6	+5	+7	1.6
2017	29	MLB RAW	2 teams	—	302	279	77	8	0	10	10	48	5	2	0	276	313	412	725	136	298	16	3	315	92	-3	+0	+6	+5	+7	1.6
2018	30	MLB MLE	2 teams	—	291	271	56	8	0	2	10	43	1	1	0	207	238	258	496	52	236	15	3	216	32	-23	+0	-0	+5	+6	-1.2
2018	30	MLB RAW	2 teams	—	291	265	59	7	1	1	16	35	1	1	0	223	270	268	537	45	250	12	5	240	32	-23	+0	-0	+5	+6	-1.2
2019	31	AAA MLE	3 teams	—	294	278	60	15	0	0	12	54	4	0	0	216	259	270	528	54	268	18	4	237	47	—	—	—	—	—	—
2019	31	AAA RAW	3 teams	—	294	273	72	17	0	0	17	45	4	0	0	264	316	326	642	62	316	15	6	294	47	—	—	—	—	—	—
2020	32	INTL MLE	Venezuela	—	120	113	37	7	0	2	4	11	0	0	0	327	350	442	793	115	350	9	3	—	—	—	—	—	—	—	—
2020	32	INTL RAW	Venezuela	—	120	113	37	7	0	2	4	11	0	0	0	327	350	442	793	115	350	9	3	344	119	—	—	—	—	—	—
2021	33	INTL MLE	Caribes de Anzoategui	—	108	97	27	2	0	1	10	11	0	0	0	278	346	330	676	52	306	10	9	—	—	—	—	—	—	—	—
2021	33	INTL RAW	Caribes de Anzoategui	—	108	97	27	2	0	1	10	11	0	0	0	278	346	330	676	52	306	10	9	309	95	—	—	—	—	—	—
2022	34	INTL MLE	Caribes de Anzoategui	—	153	142	38	5	1	3	6	12	2	0	0	268	307	380	687	113	271	8	4	—	—	—	—	—	—	—	—
2022	34	INTL RAW	Caribes de Anzoategui	—	153	142	38	5	1	3	6	12	2	0	0	268	307	380	687	113	271	8	4	302	90	—	—	—	—	—	—
2023	35	INTL MLE	Aguilas del Zulia	—	103	93	24	6	0	2	7	10	1	0	0	258	317	387	704	129	272	10	7	—	—	—	—	—	—	—	—
2023	35	INTL RAW	Aguilas del Zulia	—	103	93	24	6	0	2	7	10	1	0	0	258	317	387	704	129	272	10	7	310	96	—	—	—	—	—	—
2024	36	INTL MLE	Tigres de Aragua	—	128	117	40	5	0	2	9	6	0	0	0	342	389	436	825	94	342	5	7	—	—	—	—	—	—	—	—
2024	36	INTL RAW	Tigres de Aragua	—	128	117	40	5	0	2	9	6	0	0	0	342	389	436	825	94	342	5	7	365	133	—	—	—	—	—	—
2025	37	INTL MLE	Caribes de Anzoategui	—	118	103	31	7	0	1	10	20	2	0	0	301	374	398	772	97	361	17	8	—	—	—	—	—	—	—	—
2025	37	INTL RAW	Caribes de Anzoategui	—	118	103	31	7	0	1	10	20	2	0	0	301	374	398	772	97	361	17	8	342	117	—	—	—	—	—	—
2006	18	ROK MLE	DSL Braves	—	145	136	25	5	1	0	6	15	2	1	1	184	229	235	464	51	202	10	4	212	30	—	—	—	—	—	—
2007	19	ROK MLE	GCL Braves	—	114	109	19	4	0	0	4	14	0	1	1	174	207	211	418	37	197	12	4	189	14	—	—	—	—	—	—
2008	20	ROK MLE	Danville Braves	—	163	157	22	1	0	2	4	34	1	1	1	140	167	185	351	45	166	21	2	162	-4	—	—	—	—	—	—
2009	21	A+ MLE	2 teams	—	382	369	97	19	1	5	9	69	1	4	5	263	281	360	641	98	306	18	2	277	74	—	—	—	—	—	—
2010	22	A+ MLE	2 teams	—	347	339	77	18	1	6	4	59	1	1	2	227	238	339	577	112	256	17	1	247	53	—	—	—	—	—	—
2011	23	AA MLE	2 teams	—	291	276	59	9	0	1	9	28	4	0	3	214	254	257	511	43	230	10	3	219	34	—	—	—	—	—	—
2012	24	AA MLE	2 teams	—	403	382	101	10	0	1	15	56	3	1	2	264	301	298	600	34	304	14	4	265	65	—	—	—	—	—	—
2013	25	AAA MLE	4 teams	—	193	181	46	4	0	0	10	22	0	1	1	254	295	276	571	22	288	11	5	256	59	—	—	—	—	—	—
2014	26	AAA MLE	3 teams	—	263	257	57	8	1	2	3	58	1	0	1	222	236	284	520	62	282	22	1	226	39	—	—	—	—	—	—
2015	27	MLB MLE	3 teams	—	213	201	32	8	0	1	10	39	0	0	0	159	207	214	421	55	209	18	5	190	15	—	—	—	—	—	—
2016	28	INTL MLE	3 teams	—	282	269	77	12	2	2	8	50	3	0	1	286	317	368	685	82	355	18	3	307	94	—	—	—	—	—	—
2017	29	MLB MLE	2 teams	—	302	283	70	10	0	11	11	55	5	2	0	247	293	399	692	152	275	18	4	304	92	—	—	—	—	—	—
2018	30	MLB MLE	2 teams	—	291	278	56	8	0	2	10	43	1	1	0	201	238	252	489	50	240	15	3	216	32	—	—	—	—	—	—
2019	31	AAA MLE	3 teams	—	294	276	60	15	0	0	12	54	4	0	0	217	259	272	530	54	270	18	4	237	47	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	721	659	146	23	0	10	30	121	7	3	0	222	263	302	565	80	254	17	4	248	24	-40	+1	+25	+33	+16	3.5
/ 162G	—	A+C		—	650	594	132	21	0	9	27	109	6	3	0	222	263	303	566	81	255	17	4	248	24	-36	+1	+23	+30	+14	3.2
Career	—	MLE		—	4413	4146	995	163	7	44	161	666	31	13	18	240	274	315	588	75	275	15	4	204	24	-40	+1	+25	+33	+16	3.5
/ 162G	—	MLE		—	650	611	146	24	1	6	24	98	5	2	3	239	274	311	585	72	274	15	4	204	24	-36	+1	+23	+30	+14	3.2

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.

2019 AAANorfolk Tides · 198 PAwOBA .308 → .237 (−71)K% 14.6% → 18.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.65%	÷0.973	×1.200	—	—	18.06%
BB% (unintentional) /PA	6.06%	÷1.103	×0.690	—	×0.962	3.65%
HBP% /PA	1.01%	—	×0.940	—	×0.962	0.91%
Singles /BIP	23.87%	÷1.033	×0.930	×0.950	×0.962	19.65%
Doubles /BIP	9.68%	÷0.990	×0.830	×0.950	×0.962	7.42%
Triples /BIP	0.00%	÷0.954	×0.970	×0.950	×0.962	0.00%
Home runs /BIP	0.00%	÷0.889	×0.840	—	×0.962	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 78, 1B 107, 2B 98, 3B 91, K 95, BB 121 — 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 ×0.950.

Result: wOBA .308 → .237; ISO .082 → .062; BABIP .335 → .271. 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 AAATacoma Rainiers · 104 PAwOBA .276 → .241 (−35)K% 14.4% → 17.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.42%	÷1.041	×1.290	—	—	17.88%
BB% (unintentional) /PA	2.88%	÷1.115	×0.710	—	×0.992	1.82%
HBP% /PA	0.96%	—	×0.980	—	×0.992	0.93%
Singles /BIP	26.19%	÷0.987	×0.900	×1.014	×0.992	24.03%
Doubles /BIP	4.76%	÷0.901	×0.810	×1.014	×0.992	4.31%
Triples /BIP	1.19%	÷1.063	×0.810	×1.014	×0.992	0.91%
Home runs /BIP	0.00%	÷0.896	×0.780	—	×0.992	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 79, 1B 97, 2B 80, 3B 113, K 108, BB 123 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.014.

Result: wOBA .276 → .241; ISO .061 → .051; BABIP .321 → .293. 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 AAATacoma Rainiers · 26 PAwOBA .283 → .228 (−55)K% 30.8% → 37.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.77%	÷1.049	×1.290	—	—	37.83%
BB% (unintentional) /PA	11.54%	÷1.046	×0.710	—	×1.003	7.85%
HBP% /PA	0.00%	—	×0.980	—	×1.003	0.00%
Singles /BIP	40.00%	÷0.995	×0.900	—	×1.003	36.28%
Doubles /BIP	0.00%	÷0.910	×0.810	—	×1.003	0.00%
Triples /BIP	0.00%	÷0.900	×0.810	—	×1.003	0.00%
Home runs /BIP	0.00%	÷1.127	×0.780	—	×1.003	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 125, 1B 99, 2B 82, 3B 80, K 110, BB 109 — 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).

Result: wOBA .283 → .228; ISO .000 → .000; BABIP .400 → .363. 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 AAATacoma Rainiers · 181 PAwOBA .285 → .236 (−48)K% 16.0% → 20.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.02%	÷1.017	×1.290	—	—	20.32%
BB% (unintentional) /PA	2.21%	÷1.052	×0.710	—	×1.018	1.52%
HBP% /PA	0.55%	—	×0.980	—	×1.018	0.55%
Singles /BIP	26.03%	÷1.016	×0.900	×0.975	×1.018	22.88%
Doubles /BIP	4.79%	÷0.937	×0.810	×0.975	×1.018	4.11%
Triples /BIP	0.68%	÷0.971	×0.810	×0.975	×1.018	0.57%
Home runs /BIP	1.37%	÷0.963	×0.780	—	×1.018	1.13%

Factors used: league row PCL. Park (home-season share, regressed): HR 93, 1B 103, 2B 87, 3B 94, K 103, BB 110 — 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 ×0.975.

Result: wOBA .285 → .236; ISO .086 → .069; BABIP .317 → .277. 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 AAATacoma Rainiers · 95 PAwOBA .303 → .277 (−26)K% 10.5% → 13.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.53%	÷1.030	×1.290	—	—	13.19%
BB% (unintentional) /PA	7.37%	÷1.049	×0.710	—	×1.033	5.15%
HBP% /PA	0.00%	—	×0.980	—	×1.033	0.00%
Singles /BIP	29.87%	÷0.983	×0.900	×1.016	×1.033	28.69%
Doubles /BIP	3.90%	÷0.957	×0.810	×1.016	×1.033	3.46%
Triples /BIP	0.00%	÷0.900	×0.810	×1.016	×1.033	0.00%
Home runs /BIP	0.00%	÷0.938	×0.780	—	×1.033	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 88, 1B 97, 2B 91, 3B 80, K 106, BB 110 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.016.

Result: wOBA .303 → .277; ISO .034 → .031; BABIP .338 → .322. 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 ROKAZL Mariners · 20 PAwOBA .317 → .227 (−90)K% 10.0% → 14.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.00%	÷1.000	×1.440	—	—	14.40%
BB% (unintentional) /PA	5.00%	÷1.000	×0.620	—	×0.945	2.93%
HBP% /PA	0.00%	—	×0.720	—	×0.945	0.00%
Singles /BIP	29.41%	÷1.000	×0.820	—	×0.945	22.79%
Doubles /BIP	5.88%	÷1.000	×0.720	—	×0.945	4.00%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.945	0.00%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×0.945	0.00%

Factors used: level-wide ROK 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 25 vs a level average of 19.5 → −5.5% on BB/HBP/hit rates (5.5 yr older than average).

Result: wOBA .317 → .227; ISO .053 → .035; BABIP .353 → .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).

2012 AAJackson Generals · 349 PAwOBA .278 → .265 (−14)K% 11.2% → 14.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.17%	÷0.974	×1.220	—	—	14.00%
BB% (unintentional) /PA	5.16%	÷0.997	×0.680	—	×1.012	3.56%
HBP% /PA	0.86%	—	×0.840	—	×1.012	0.73%
Singles /BIP	26.60%	÷0.943	×0.920	×1.041	×1.012	27.34%
Doubles /BIP	3.90%	÷1.228	×0.910	×1.041	×1.012	3.05%
Triples /BIP	0.00%	÷1.150	×0.880	×1.041	×1.012	0.00%
Home runs /BIP	0.35%	÷0.957	×0.800	—	×1.012	0.30%

Factors used: league row SL. Park (home-season share, regressed): HR 91, 1B 89, 2B 146, 3B 130, K 95, BB 99 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.041.

Result: wOBA .278 → .265; ISO .044 → .035; BABIP .305 → .304. 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 AAJackson Generals · 237 PAwOBA .231 → .219 (−12)K% 8.0% → 9.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.02%	÷1.031	×1.220	—	—	9.49%
BB% (unintentional) /PA	4.64%	÷1.063	×0.680	—	×1.027	3.05%
HBP% /PA	0.42%	—	×0.840	—	×1.027	0.36%
Singles /BIP	19.31%	÷0.986	×0.920	×1.041	×1.027	19.25%
Doubles /BIP	3.96%	÷1.028	×0.910	×1.041	×1.027	3.75%
Triples /BIP	0.00%	÷1.150	×0.880	×1.041	×1.027	0.00%
Home runs /BIP	0.50%	÷1.130	×0.800	—	×1.027	0.36%

Factors used: league row SL. Park (home-season share, regressed): HR 126, 1B 97, 2B 106, 3B 130, K 106, BB 113 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.041.

Result: wOBA .231 → .219; ISO .050 → .045; BABIP .233 → .230. 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 — .