José Marmolejos

Pos1B

B/TL/L

Born1993-01-02

Age (2027)34

No MLB projection yet. Career stats below are historical.

Overview

INTL

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	31	INTLDominican Rep…	142	.256/.316/.360	1	0	84	—
2025	32	INTLLeones del Es…	85	.269/.417/.373	0	2	132	—
2026	33	INTLLeones del Es…	34	.400/.471/.600	1	0	204	—

Contract

No contract data on file.

Skills · percentileStatcast 2020-2021

Barrel%70

Avg EV62

xwOBA43

Speed13

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	18	ROK	DSL Nationals	—	215	184	41	6	3	1	23	32	7	1	1	223	332	304	636	82	263	15	11	297	21	—	—	—	—	—	—
2012	19	ROK	DSL Nationals	—	282	255	76	21	8	4	23	34	3	1	2	298	363	490	853	192	330	12	8	374	42	—	—	—	—	—	—
2013	20	ROK	GCL Nationals	—	158	141	44	11	0	2	14	27	1	1	1	312	378	433	811	121	368	17	9	360	63	—	—	—	—	—	—
2015	22	A	Hagerstown Suns	—	521	468	145	39	5	11	35	89	9	3	1	310	369	485	854	175	355	17	7	371	90	—	—	—	—	—	—
2016	23	AA	Harrisburg Senators	—	135	127	38	9	0	2	5	29	2	0	0	299	336	417	753	118	371	21	4	334	80	—	—	—	—	—	—
2016	23	A+	Potomac Nationals	—	444	378	108	36	5	11	59	84	2	2	3	286	385	495	880	209	337	19	13	384	93	—	—	—	—	—	—
2016	23	INTL	Tigres del Licey	—	98	88	19	3	1	1	8	20	1	0	0	216	289	307	595	91	265	20	8	271	69	—	—	—	—	—	—
2017	24	AA	Harrisburg Senators	—	454	400	115	18	4	14	44	79	5	0	2	287	365	458	823	170	324	17	10	362	104	—	—	—	—	—	—
2017	24	INTL	Tigres del Licey	—	89	79	18	2	0	2	10	18	0	0	0	228	315	329	644	101	271	20	11	296	87	—	—	—	—	—	—
2018	25	AAA	Syracuse Chiefs	—	539	493	131	25	1	8	39	97	2	0	0	266	322	369	691	103	313	18	7	310	66	—	—	—	—	—	—
2018	25	INTL	Aguilas Cibaenas	—	64	59	11	1	1	0	4	13	0	0	0	186	238	237	475	51	234	20	6	216	32	—	—	—	—	—	—
2019	26	AAA	Fresno Grizzlies	—	382	352	111	29	2	16	28	80	1	1	0	315	367	545	913	230	370	21	7	398	92	—	—	—	—	—	—
2019	26	AA	Harrisburg Senators	—	43	39	12	2	0	2	4	6	0	0	0	308	372	513	885	205	323	14	9	390	99	—	—	—	—	—	—
2019	26	INTL	Estrellas Orientales	—	65	62	13	3	0	0	3	12	0	0	0	210	246	258	504	48	260	18	5	231	42	—	—	—	—	—	—
2020	27	MLB	Seattle Mariners	—	115	107	22	4	0	6	7	32	1	0	1	206	261	411	672	206	232	28	6	297	90	-1	-0	-2	-1	+2	-0.3
2021	28	MLB	Seattle Mariners	—	122	106	17	4	0	4	15	39	0	0	0	160	264	311	576	151	203	32	12	263	66	-5	+0	-2	-8	+3	-1.3
2021	28	AAA	Tacoma Rainiers	—	353	293	99	16	2	26	54	69	2	0	0	338	444	672	1.116	334	361	20	15	473	146	—	—	—	—	—	—
2023	30	INTL	Leones del Escogido	—	108	91	19	7	0	2	16	21	1	0	1	209	333	352	685	143	250	19	15	316	100	—	—	—	—	—	—
2024	31	INTL	Dominican Republic	—	142	125	32	10	0	1	11	27	0	0	1	256	316	360	676	104	301	19	8	293	84	—	—	—	—	—	—
2025	32	INTL	Leones del Escogido	—	85	67	18	7	0	0	15	19	2	2	0	269	417	373	790	104	367	22	18	363	132	—	—	—	—	—	—
2026	33	INTL	Leones del Escogido	—	34	30	12	3	0	1	4	5	0	0	0	400	471	600	1.071	200	458	15	12	470	204	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	237	213	39	8	0	10	22	71	1	0	1	183	263	362	624	178	218	30	9	279	75	-7	-0	-4	-10	+5	-1.7
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2011	18	ROK MLE	DSL Nationals	—	215	191	28	4	2	0	16	39	7	1	1	147	238	188	427	42	177	18	7	199	21	—	—	—	—	—	—
2012	19	ROK MLE	DSL Nationals	—	282	263	49	13	5	2	15	41	3	1	2	186	238	297	535	110	210	15	5	231	42	—	—	—	—	—	—
2013	20	ROK MLE	GCL Nationals	—	158	147	35	8	0	2	8	39	1	1	1	238	282	333	615	95	292	25	5	261	63	—	—	—	—	—	—
2015	22	A MLE	Hagerstown Suns	—	521	482	124	32	4	9	21	123	9	3	1	257	301	396	697	139	312	24	4	301	90	—	—	—	—	—	—
2016	23	AA MLE	Harrisburg Senators	—	135	128	34	8	0	1	4	36	2	0	0	266	299	352	650	86	359	27	3	287	80	—	—	—	—	—	—
2016	23	A+ MLE	Potomac Nationals	—	444	404	96	29	4	9	33	123	2	2	3	238	298	396	694	158	310	28	7	306	93	—	—	—	—	—	—
2017	24	AA MLE	Harrisburg Senators	—	454	414	111	16	4	12	30	94	5	0	2	268	325	413	738	145	313	21	7	322	104	—	—	—	—	—	—
2018	25	AAA MLE	Syracuse Chiefs	—	539	503	120	23	1	6	29	112	2	0	0	239	283	324	607	85	287	21	5	266	66	—	—	—	—	—	—
2019	26	AAA MLE	Fresno Grizzlies	—	382	361	89	22	1	12	19	108	1	1	0	247	286	413	699	166	318	28	5	304	92	—	—	—	—	—	—
2019	26	AA MLE	Harrisburg Senators	—	43	40	11	2	0	1	3	7	0	0	0	275	326	400	726	125	299	16	7	315	99	—	—	—	—	—	—
2020	27	MLB MLE	Seattle Mariners	—	115	107	22	4	0	6	7	32	1	0	1	206	261	411	672	206	232	28	6	301	90	-1	-0	-2	-1	+2	-0.3
2021	28	MLB MLE	Seattle Mariners	—	122	106	17	4	0	4	15	39	0	0	0	160	264	311	576	151	203	32	12	266	66	-5	+0	-2	-8	+3	-1.3
2021	28	AAA MLE	Tacoma Rainiers	—	353	315	92	14	2	20	32	83	2	0	0	292	361	540	901	248	324	24	9	384	146	—	—	—	—	—	—
2011	18	ROK MLE	DSL Nationals	—	215	191	28	4	2	0	16	39	7	1	1	147	238	188	427	42	183	18	7	199	21	—	—	—	—	—	—
2011	18	ROK RAW	DSL Nationals	—	215	184	41	6	3	1	23	32	7	1	1	223	332	304	636	82	263	15	11	297	21	—	—	—	—	—	—
2012	19	ROK MLE	DSL Nationals	—	282	263	49	13	5	2	15	41	3	1	2	186	238	297	535	110	213	15	5	231	42	—	—	—	—	—	—
2012	19	ROK RAW	DSL Nationals	—	282	255	76	21	8	4	23	34	3	1	2	298	363	490	853	192	330	12	8	374	42	—	—	—	—	—	—
2013	20	ROK MLE	GCL Nationals	—	158	147	35	8	0	2	8	39	1	1	1	238	282	333	615	95	306	25	5	261	63	—	—	—	—	—	—
2013	20	ROK RAW	GCL Nationals	—	158	141	44	11	0	2	14	27	1	1	1	312	378	433	811	121	368	17	9	360	63	—	—	—	—	—	—
2015	22	A MLE	Hagerstown Suns	—	521	482	124	32	4	9	21	123	9	3	1	257	301	396	697	139	320	24	4	301	90	—	—	—	—	—	—
2015	22	A RAW	Hagerstown Suns	—	521	468	145	39	5	11	35	89	9	3	1	310	369	485	854	175	355	17	7	371	90	—	—	—	—	—	—
2016	23	A+ MLE	3 teams	—	677	622	154	44	5	12	43	185	5	2	3	248	301	392	694	145	329	27	6	302	90	—	—	—	—	—	—
2016	23	A+ RAW	3 teams	—	677	593	165	48	6	14	72	133	5	2	3	278	361	450	811	172	333	20	11	358	90	—	—	—	—	—	—
2017	24	AA MLE	2 teams	—	543	497	133	19	5	14	36	113	5	0	2	268	323	410	734	143	317	21	7	322	104	—	—	—	—	—	—
2017	24	AA RAW	2 teams	—	543	479	133	20	4	16	54	97	5	0	2	278	357	436	793	159	315	18	10	352	104	—	—	—	—	—	—
2018	25	AAA MLE	2 teams	—	603	563	133	26	1	6	32	125	2	0	0	236	280	318	598	82	290	21	5	266	66	—	—	—	—	—	—
2018	25	AAA RAW	2 teams	—	603	552	142	26	2	8	43	110	2	0	0	257	313	355	668	98	305	18	7	300	66	—	—	—	—	—	—
2019	26	AAA MLE	3 teams	—	490	463	115	27	1	16	25	134	1	1	0	248	288	415	703	166	315	27	5	305	93	—	—	—	—	—	—
2019	26	AAA RAW	3 teams	—	490	453	136	34	2	18	35	98	1	1	0	300	352	503	855	203	349	20	7	375	93	—	—	—	—	—	—
2020	27	MLB MLE	Seattle Mariners	—	115	107	22	4	0	6	7	32	1	0	1	206	261	411	672	206	232	28	6	301	90	-1	-0	-2	-1	+2	-0.3
2020	27	MLB RAW	Seattle Mariners	—	115	107	22	4	0	6	7	32	1	0	1	206	261	411	672	206	232	28	6	297	90	-1	-0	-2	-1	+2	-0.3
2021	28	AAA MLE	2 teams	—	475	421	109	18	2	24	47	122	2	0	0	259	336	482	818	223	304	26	10	354	125	—	—	—	—	—	—
2021	28	AAA RAW	2 teams	—	475	399	116	20	2	30	69	108	2	0	0	291	398	576	974	286	323	23	15	419	125	—	—	—	—	—	—
2023	30	INTL MLE	Leones del Escogido	—	108	91	19	7	0	2	16	21	1	0	1	209	333	352	685	143	250	19	15	—	—	—	—	—	—	—	—
2023	30	INTL RAW	Leones del Escogido	—	108	91	19	7	0	2	16	21	1	0	1	209	333	352	685	143	250	19	15	316	100	—	—	—	—	—	—
2024	31	INTL MLE	Dominican Republic	—	142	125	32	10	0	1	11	27	0	0	1	256	316	360	676	104	301	19	8	—	—	—	—	—	—	—	—
2024	31	INTL RAW	Dominican Republic	—	142	125	32	10	0	1	11	27	0	0	1	256	316	360	676	104	301	19	8	293	84	—	—	—	—	—	—
2025	32	INTL MLE	Leones del Escogido	—	85	67	18	7	0	0	15	19	2	2	0	269	417	373	790	104	367	22	18	—	—	—	—	—	—	—	—
2025	32	INTL RAW	Leones del Escogido	—	85	67	18	7	0	0	15	19	2	2	0	269	417	373	790	104	367	22	18	363	132	—	—	—	—	—	—
2026	33	INTL MLE	Leones del Escogido	—	34	30	12	3	0	1	4	5	0	0	0	400	471	600	1.071	200	458	15	12	—	—	—	—	—	—	—	—
2026	33	INTL RAW	Leones del Escogido	—	34	30	12	3	0	1	4	5	0	0	0	400	471	600	1.071	200	458	15	12	470	204	—	—	—	—	—	—
2011	18	ROK MLE	DSL Nationals	—	215	190	28	4	2	0	16	39	7	1	1	147	238	189	428	42	177	18	7	199	21	—	—	—	—	—	—
2012	19	ROK MLE	DSL Nationals	—	282	262	49	13	5	2	15	41	3	1	2	187	238	298	536	111	210	15	5	231	42	—	—	—	—	—	—
2013	20	ROK MLE	GCL Nationals	—	158	148	35	8	0	2	8	39	1	1	1	236	282	331	613	95	292	25	5	261	63	—	—	—	—	—	—
2015	22	A MLE	Hagerstown Suns	—	521	486	124	32	4	9	21	123	9	3	1	255	301	393	694	138	312	24	4	301	90	—	—	—	—	—	—
2016	23	A+ MLE	3 teams	—	677	624	154	44	5	12	43	185	5	2	3	247	301	391	693	144	321	27	6	302	90	—	—	—	—	—	—
2017	24	AA MLE	2 teams	—	543	497	133	19	5	14	36	113	5	0	2	268	323	410	734	143	313	21	7	322	104	—	—	—	—	—	—
2018	25	AAA MLE	2 teams	—	603	564	133	26	1	6	32	125	2	0	0	236	280	317	597	82	287	21	5	266	66	—	—	—	—	—	—
2019	26	AAA MLE	3 teams	—	490	461	115	27	1	16	25	134	1	1	0	249	288	416	705	167	316	27	5	305	93	—	—	—	—	—	—
2020	27	MLB MLE	Seattle Mariners	—	115	106	22	4	0	6	7	32	1	0	1	208	261	415	676	208	232	28	6	301	90	—	—	—	—	—	—
2021	28	AAA MLE	2 teams	—	475	423	109	18	2	24	47	122	2	0	0	258	336	480	816	222	293	26	10	354	125	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	237	213	39	8	0	10	22	71	1	0	1	183	263	362	624	178	218	30	9	279	68	-7	-0	-4	-10	+5	-1.7
/ 162G	—	A+C		—	650	584	107	22	0	27	60	195	3	0	3	183	263	360	622	176	219	30	9	279	68	-19	-1	-12	-27	+14	-4.6
Career	—	MLE		—	4448	4069	983	222	25	95	296	1025	39	11	13	242	299	378	678	137	297	23	7	269	68	-7	-0	-4	-10	+5	-1.7
/ 162G	—	MLE		—	650	595	144	32	4	14	43	150	6	2	2	242	300	380	680	138	297	23	7	269	68	-19	-1	-12	-27	+14	-4.6

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.

2021 AAATacoma Rainiers · 353 PAwOBA .462 → .384 (−78)K% 19.5% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.55%	÷0.994	×1.200	—	—	23.61%
BB% (unintentional) /PA	13.88%	÷1.045	×0.690	—	×0.992	9.10%
HBP% /PA	0.57%	—	×0.940	—	×0.992	0.53%
Singles /BIP	24.55%	÷0.952	×0.930	×0.991	×0.992	23.57%
Doubles /BIP	7.14%	÷0.989	×0.830	×0.991	×0.992	5.89%
Triples /BIP	0.89%	÷0.977	×0.920	×0.991	×0.992	0.83%
Home runs /BIP	11.61%	÷0.970	×0.700	—	×0.992	8.31%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 94, 1B 90, 2B 98, 3B 95, K 99, BB 109 — 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 ×0.991.

Result: wOBA .462 → .384; ISO .334 → .261; BABIP .361 → .324. 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).

2019 AAAFresno Grizzlies · 382 PAwOBA .386 → .304 (−82)K% 20.9% → 28.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.94%	÷0.953	×1.290	—	—	28.35%
BB% (unintentional) /PA	6.81%	÷0.990	×0.710	—	×1.018	4.97%
HBP% /PA	0.26%	—	×0.980	—	×1.018	0.26%
Singles /BIP	23.53%	÷0.959	×0.900	×0.950	×1.018	21.35%
Doubles /BIP	10.66%	÷0.976	×0.810	×0.950	×1.018	8.56%
Triples /BIP	0.74%	÷1.140	×0.810	×0.950	×1.018	0.51%
Home runs /BIP	5.88%	÷0.962	×0.780	—	×1.018	4.86%

Factors used: league row PCL. Park (home-season share, regressed): HR 92, 1B 92, 2B 95, 3B 128, K 91, BB 98 — 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 ×0.950.

Result: wOBA .386 → .304; ISO .230 → .174; BABIP .370 → .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).

2019 AAHarrisburg Senators · 43 PAwOBA .379 → .315 (−64)K% 14.0% → 17.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.95%	÷0.996	×1.220	—	—	17.09%
BB% (unintentional) /PA	9.30%	÷1.054	×0.700	—	×0.988	6.10%
HBP% /PA	0.00%	—	×0.850	—	×0.988	0.00%
Singles /BIP	24.24%	÷0.991	×0.970	—	×0.988	23.44%
Doubles /BIP	6.06%	÷0.985	×0.860	—	×0.988	5.23%
Triples /BIP	0.00%	÷1.150	×0.950	—	×0.988	0.00%
Home runs /BIP	6.06%	÷1.111	×0.780	—	×0.988	4.20%

Factors used: league row EL. Park (home-season share, regressed): HR 122, 1B 98, 2B 97, 3B 130, K 99, BB 111 — 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).

Result: wOBA .379 → .315; ISO .205 → .151; BABIP .323 → .299. 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 AAASyracuse Chiefs · 539 PAwOBA .303 → .266 (−37)K% 18.0% → 20.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.00%	÷1.044	×1.200	—	—	20.68%
BB% (unintentional) /PA	7.05%	÷0.956	×0.690	—	×1.033	5.25%
HBP% /PA	0.37%	—	×0.940	—	×1.033	0.36%
Singles /BIP	24.49%	÷1.044	×0.930	×1.001	×1.033	22.56%
Doubles /BIP	6.31%	÷0.933	×0.830	×1.001	×1.033	5.81%
Triples /BIP	0.25%	÷0.900	×0.970	×1.001	×1.033	0.28%
Home runs /BIP	2.02%	÷1.205	×0.840	—	×1.033	1.46%

Factors used: league row IL. Park (home-season share, regressed): HR 141, 1B 109, 2B 87, 3B 80, K 109, BB 91 — 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 ×1.001.

Result: wOBA .303 → .266; ISO .103 → .087; BABIP .313 → .287. 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 AAHarrisburg Senators · 454 PAwOBA .355 → .322 (−33)K% 17.4% → 20.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.40%	÷1.022	×1.220	—	—	20.77%
BB% (unintentional) /PA	9.25%	÷0.974	×0.700	—	×1.012	6.73%
HBP% /PA	1.10%	—	×0.850	—	×1.012	0.95%
Singles /BIP	24.61%	÷1.016	×0.970	×1.024	×1.012	24.33%
Doubles /BIP	5.61%	÷0.998	×0.860	×1.024	×1.012	5.00%
Triples /BIP	1.25%	÷0.906	×0.950	×1.024	×1.012	1.35%
Home runs /BIP	4.36%	÷0.970	×0.780	—	×1.012	3.55%

Factors used: league row EL. Park (home-season share, regressed): HR 94, 1B 103, 2B 100, 3B 81, K 104, BB 95 — 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 ×1.024.

Result: wOBA .355 → .322; ISO .170 → .149; BABIP .324 → .313. 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+Potomac Nationals · 444 PAwOBA .376 → .306 (−70)K% 18.9% → 27.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.92%	÷0.974	×1.420	—	—	27.58%
BB% (unintentional) /PA	12.61%	÷1.061	×0.630	—	×0.998	7.47%
HBP% /PA	0.45%	—	×0.860	—	×0.998	0.39%
Singles /BIP	19.05%	÷0.966	×0.940	×1.021	×0.998	18.87%
Doubles /BIP	12.24%	÷1.010	×0.830	×1.021	×0.998	10.24%
Triples /BIP	1.70%	÷0.975	×0.800	×1.021	×0.998	1.42%
Home runs /BIP	3.74%	÷1.025	×0.900	—	×0.998	3.28%

Factors used: league row CAR. Park (home-season share, regressed): HR 105, 1B 93, 2B 102, 3B 95, K 95, BB 112 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.021.

Result: wOBA .376 → .306; ISO .209 → .174; BABIP .337 → .310. 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 AAHarrisburg Senators · 135 PAwOBA .327 → .287 (−40)K% 21.5% → 26.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.48%	÷0.980	×1.220	—	—	26.74%
BB% (unintentional) /PA	3.70%	÷0.992	×0.700	—	×1.027	2.68%
HBP% /PA	1.48%	—	×0.850	—	×1.027	1.29%
Singles /BIP	27.55%	÷1.029	×0.970	×1.013	×1.027	27.00%
Doubles /BIP	9.18%	÷0.922	×0.860	×1.013	×1.027	8.91%
Triples /BIP	0.00%	÷1.137	×0.950	×1.013	×1.027	0.00%
Home runs /BIP	2.04%	÷1.445	×0.780	—	×1.027	1.13%

Factors used: league row EL. Park (home-season share, regressed): HR 189, 1B 106, 2B 84, 3B 127, K 96, BB 98 — 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 ×1.013.

Result: wOBA .327 → .287; ISO .118 → .091; BABIP .371 → .359. 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 AHagerstown Suns · 521 PAwOBA .366 → .301 (−65)K% 17.1% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.08%	÷0.971	×1.340	—	—	23.58%
BB% (unintentional) /PA	6.33%	÷1.054	×0.660	—	—	3.97%
HBP% /PA	1.73%	—	×0.770	—	—	1.33%
Singles /BIP	23.75%	÷1.047	×0.920	×1.024	—	21.37%
Doubles /BIP	10.29%	÷0.992	×0.820	×1.024	—	8.71%
Triples /BIP	1.32%	÷1.150	×0.940	×1.024	—	1.10%
Home runs /BIP	2.90%	÷0.979	×0.820	—	—	2.43%

Factors used: league row SAL. Park (home-season share, regressed): HR 96, 1B 109, 2B 98, 3B 130, K 94, BB 111 — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.024.

Result: wOBA .366 → .301; ISO .175 → .144; BABIP .355 → .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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .