Kennys Vargas

Pos1B

B/TS/R

Born1990-08-01

Age (2027)36

No MLB projection yet. Career stats below are historical.

Overview

INTL

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	wRC+	WAR
2023	32	INTLAguilas de Me…	286	.292/.390/.473	10	144	—
2024	33	INTLCriollos de C…	210	.190/.325/.310	5	88	—
2025	34	INTLSenadores de …	82	.232/.354/.261	0	87	—

Contract

No contract data on file.

Skills · percentileStatcast 2015-2017

Barrel%56

xwOBA45

Avg EV36

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.

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)
2009	18	ROK	GCL Twins	—	131	109	28	7	0	3	17	34	3	2	0	257	369	404	773	147	342	26	13	348	52	—	—	—	—	—	—
2010	19	ROK	GCL Twins	—	161	142	46	15	1	3	13	40	3	1	0	324	390	507	897	183	426	25	8	390	68	—	—	—	—	—	—
2010	19	INTL	Indios de Mayaguez	—	26	23	6	2	1	0	2	4	1	0	0	261	346	435	781	174	316	15	8	347	121	—	—	—	—	—	—
2011	20	ROK	Elizabethton Twins	—	191	174	56	11	0	6	15	50	1	0	0	322	379	489	867	167	420	26	8	383	62	—	—	—	—	—	—
2012	21	A	Beloit Snappers	—	186	154	49	10	1	11	28	41	1	0	0	318	426	610	1.037	292	362	22	15	441	134	—	—	—	—	—	—
2012	21	INTL	Indios de Mayaguez	—	82	72	13	2	0	3	10	21	0	0	0	181	280	333	614	153	208	26	12	281	76	—	—	—	—	—	—
2013	22	A+	Fort Myers Miracle	—	520	457	122	33	1	19	50	105	7	0	0	267	348	468	817	201	304	20	10	358	79	—	—	—	—	—	—
2013	22	INTL	Puerto Rico	—	175	156	41	7	0	5	15	42	2	1	1	263	335	404	739	141	324	24	9	329	109	—	—	—	—	—	—
2014	23	MLB	Minnesota Twins	—	234	215	59	10	1	9	12	63	3	0	0	274	322	456	778	181	340	27	5	338	110	+3	+0	-3	-14	+5	-0.9
2014	23	AA	New Britain Rock Cats	—	405	356	100	17	0	17	43	68	3	0	2	281	363	472	835	191	303	17	11	368	107	—	—	—	—	—	—
2014	23	INTL	Indios de Mayaguez	—	151	114	30	7	0	6	33	30	2	0	0	263	436	482	919	219	300	20	22	406	161	—	—	—	—	—	—
2015	24	MLB	Minnesota Twins	—	184	175	42	4	0	5	9	54	0	0	0	240	277	349	626	109	319	29	5	281	76	-5	+0	-0	-12	+4	-1.3
2015	24	AAA	Rochester Red Wings	—	151	122	34	6	0	6	26	39	2	0	0	279	413	475	889	197	359	26	17	395	116	—	—	—	—	—	—
2015	24	AA	Chattanooga Lookouts	—	151	122	35	3	2	7	26	32	2	0	0	287	420	516	936	230	333	21	17	411	99	—	—	—	—	—	—
2015	24	INTL	Puerto Rico	—	160	142	39	5	0	8	17	29	1	0	0	275	356	479	835	204	295	18	11	370	137	—	—	—	—	—	—
2016	25	MLB	Minnesota Twins	—	177	152	35	11	0	10	24	57	0	0	0	230	335	500	835	270	291	32	14	364	129	+6	+0	-1	-13	+4	-0.4
2016	25	AAA	Rochester Red Wings	—	402	330	77	16	1	15	66	89	2	1	0	233	364	424	789	191	270	22	16	352	85	—	—	—	—	—	—
2016	25	INTL	Indios de Mayaguez	—	143	117	21	5	1	3	24	31	2	0	0	179	329	316	645	137	217	22	17	303	91	—	—	—	—	—	—
2017	26	MLB	Minnesota Twins	—	264	241	61	13	0	11	20	77	2	0	0	253	316	444	760	191	325	29	8	335	111	+3	+0	+0	-11	+6	-0.1
2017	26	AAA	Rochester Red Wings	—	211	178	45	8	1	9	31	53	0	0	0	253	364	461	824	208	305	25	15	363	85	—	—	—	—	—	—
2017	26	INTL	Indios de Mayaguez	—	127	102	25	6	0	6	25	34	0	0	0	245	394	480	874	235	306	27	20	389	149	—	—	—	—	—	—
2018	27	AAA	Rochester Red Wings	—	533	463	111	23	0	21	58	133	5	0	0	240	331	425	756	186	285	25	11	334	76	—	—	—	—	—	—
2018	27	INTL	Indios de Mayaguez	—	208	170	56	10	0	6	37	46	1	0	0	329	452	494	946	165	424	22	18	423	173	—	—	—	—	—	—
2019	28	INTL	Indios de Mayaguez	—	136	103	28	9	0	5	27	33	4	0	0	272	440	505	945	233	343	24	20	415	167	—	—	—	—	—	—
2020	29	INTL	Indios de Mayaguez	—	68	50	10	1	0	1	16	20	2	0	0	200	412	280	692	80	310	29	24	342	117	—	—	—	—	—	—
2021	30	INTL	Gigantes de Carolina	—	150	126	29	7	1	5	20	45	1	0	0	230	340	421	761	190	304	30	13	335	113	—	—	—	—	—	—
2022	31	INTL	Sultanes de Monterrey	—	217	175	49	5	2	10	33	45	7	0	0	280	414	503	917	223	320	21	15	404	159	—	—	—	—	—	—
2023	32	INTL	Aguilas de Mexicali	—	286	243	71	14	0	10	32	63	7	0	0	292	390	473	863	181	351	22	11	380	144	—	—	—	—	—	—
2024	33	INTL	Criollos de Caguas	—	210	174	33	6	0	5	33	61	2	0	1	190	325	310	636	121	257	29	16	298	88	—	—	—	—	—	—
2025	34	INTL	Senadores de San Juan	—	82	69	16	2	0	0	11	30	2	0	0	232	354	261	615	29	410	37	13	297	87	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	859	783	197	38	1	35	65	251	5	0	0	252	313	437	750	185	322	29	8	330	110	+10	+0	-3	-49	+19	-2.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2009	18	ROK MLE	GCL Twins	—	131	117	21	5	0	2	10	49	3	2	0	179	262	274	535	94	280	37	8	245	52	—	—	—	—	—	—
2010	19	ROK MLE	GCL Twins	—	161	148	33	10	1	2	8	58	3	1	0	223	277	345	621	122	333	36	5	269	68	—	—	—	—	—	—
2011	20	ROK MLE	Elizabethton Twins	—	191	179	40	7	0	4	10	71	1	0	0	223	268	330	598	106	335	37	5	260	62	—	—	—	—	—	—
2012	21	A MLE	Beloit Snappers	—	186	164	44	8	1	8	18	55	1	0	0	268	344	476	820	207	344	30	10	366	134	—	—	—	—	—	—
2013	22	A+ MLE	Fort Myers Miracle	—	520	472	102	27	1	16	35	152	7	0	0	216	280	379	659	163	270	29	7	285	79	—	—	—	—	—	—
2014	23	MLB MLE	Minnesota Twins	—	234	217	59	10	1	9	10	63	3	0	0	272	313	452	765	180	340	27	4	331	110	+3	+0	-3	-14	+5	-0.9
2014	23	AA MLE	New Britain Rock Cats	—	405	374	102	16	0	14	25	84	3	0	2	273	323	428	751	155	310	21	6	327	107	—	—	—	—	—	—
2015	24	MLB MLE	Minnesota Twins	—	184	175	42	4	0	5	9	54	0	0	0	240	277	349	626	109	319	29	5	281	76	-5	+0	-0	-12	+4	-1.3
2015	24	AAA MLE	Rochester Red Wings	—	151	130	33	5	0	6	18	45	2	0	0	254	353	431	784	177	332	30	12	340	116	—	—	—	—	—	—
2015	24	AA MLE	Chattanooga Lookouts	—	151	133	32	3	2	5	15	40	2	0	0	241	327	406	733	165	287	26	10	314	99	—	—	—	—	—	—
2016	25	MLB MLE	Minnesota Twins	—	177	153	35	11	0	10	23	57	0	0	0	229	330	497	826	268	291	32	13	359	129	+6	+0	-1	-13	+4	-0.4
2016	25	AAA MLE	Rochester Red Wings	—	402	349	71	11	1	14	47	106	2	1	0	203	302	361	663	158	242	26	12	294	85	—	—	—	—	—	—
2017	26	MLB MLE	Minnesota Twins	—	264	242	61	13	0	11	19	77	2	0	0	252	312	442	754	190	325	29	7	332	111	+3	+0	+0	-11	+6	-0.1
2017	26	AAA MLE	Rochester Red Wings	—	211	190	40	6	1	8	19	64	0	0	0	211	282	379	661	168	268	30	9	294	85	—	—	—	—	—	—
2018	27	AAA MLE	Rochester Red Wings	—	533	484	101	19	0	20	37	163	5	0	0	209	272	372	644	163	257	31	7	281	76	—	—	—	—	—	—
2009	18	ROK MLE	GCL Twins	—	131	117	21	5	0	2	10	49	3	2	0	179	262	274	535	94	284	37	8	245	52	—	—	—	—	—	—
2009	18	ROK RAW	GCL Twins	—	131	109	28	7	0	3	17	34	3	2	0	257	369	404	773	147	342	26	13	348	52	—	—	—	—	—	—
2010	19	ROK MLE	2 teams	—	187	172	39	12	1	2	9	67	4	1	0	227	281	343	624	116	352	36	5	269	68	—	—	—	—	—	—
2010	19	ROK RAW	2 teams	—	187	165	52	17	2	3	15	44	4	1	0	315	384	497	881	182	408	24	8	384	68	—	—	—	—	—	—
2011	20	ROK MLE	Elizabethton Twins	—	191	179	40	7	0	4	10	71	1	0	0	223	268	330	598	106	343	37	5	260	62	—	—	—	—	—	—
2011	20	ROK RAW	Elizabethton Twins	—	191	174	56	11	0	6	15	50	1	0	0	322	379	489	867	167	420	26	8	383	62	—	—	—	—	—	—
2012	21	A MLE	2 teams	—	268	237	64	12	1	12	27	79	1	0	0	270	347	481	828	211	349	29	10	366	134	—	—	—	—	—	—
2012	21	A RAW	2 teams	—	268	226	62	12	1	14	38	62	1	0	0	274	381	522	903	248	314	23	14	392	134	—	—	—	—	—	—
2013	22	A+ MLE	2 teams	—	695	631	135	36	1	21	47	204	9	1	1	214	278	374	652	160	275	29	7	285	79	—	—	—	—	—	—
2013	22	A+ RAW	2 teams	—	695	613	163	40	1	24	65	147	9	1	1	266	345	452	797	186	309	21	9	350	79	—	—	—	—	—	—
2014	23	AA MLE	3 teams	—	790	730	199	32	1	29	43	182	8	0	2	273	320	438	758	166	322	23	5	329	109	—	—	—	—	—	—
2014	23	AA RAW	3 teams	—	790	685	189	34	1	32	88	161	8	0	2	276	365	469	834	193	313	20	11	367	109	—	—	—	—	—	—
2015	24	MLB MLE	4 teams	—	646	582	139	16	2	20	57	185	5	0	0	239	312	376	688	137	314	29	9	309	96	-3	+0	-0	-12	+14	-0.1
2015	24	MLB RAW	4 teams	—	646	561	150	18	2	26	78	154	5	0	0	267	362	446	807	178	324	24	12	360	96	-3	+0	-0	-12	+14	-0.1
2016	25	AAA MLE	3 teams	—	722	626	133	28	1	30	87	203	4	1	0	212	312	404	717	192	259	28	12	314	99	—	—	—	—	—	—
2016	25	AAA RAW	3 teams	—	722	599	133	32	2	28	114	177	4	1	0	222	350	422	772	200	263	25	16	345	99	—	—	—	—	—	—
2017	26	MLB MLE	3 teams	—	602	549	128	24	1	24	48	178	2	0	0	233	297	412	709	179	297	30	8	315	99	-0	+0	+0	-11	+13	0.2
2017	26	MLB RAW	3 teams	—	602	521	131	27	1	26	76	164	2	0	0	251	349	457	806	205	314	27	13	356	99	-0	+0	+0	-11	+13	0.2
2018	27	AAA MLE	2 teams	—	741	676	140	27	0	27	52	227	6	0	0	207	270	367	637	160	263	31	7	281	76	—	—	—	—	—	—
2018	27	AAA RAW	2 teams	—	741	633	167	33	0	27	95	179	6	0	0	264	365	444	809	180	323	24	13	359	76	—	—	—	—	—	—
2019	28	INTL MLE	Indios de Mayaguez	—	136	103	28	9	0	5	27	33	4	0	0	272	440	505	945	233	343	24	20	—	—	—	—	—	—	—	—
2019	28	INTL RAW	Indios de Mayaguez	—	136	103	28	9	0	5	27	33	4	0	0	272	440	505	945	233	343	24	20	415	167	—	—	—	—	—	—
2020	29	INTL MLE	Indios de Mayaguez	—	68	50	10	1	0	1	16	20	2	0	0	200	412	280	692	80	310	29	24	—	—	—	—	—	—	—	—
2020	29	INTL RAW	Indios de Mayaguez	—	68	50	10	1	0	1	16	20	2	0	0	200	412	280	692	80	310	29	24	342	117	—	—	—	—	—	—
2021	30	INTL MLE	Gigantes de Carolina	—	150	126	29	7	1	5	20	45	1	0	0	230	340	421	761	190	304	30	13	—	—	—	—	—	—	—	—
2021	30	INTL RAW	Gigantes de Carolina	—	150	126	29	7	1	5	20	45	1	0	0	230	340	421	761	190	304	30	13	335	113	—	—	—	—	—	—
2022	31	INTL MLE	Sultanes de Monterrey	—	217	175	49	5	2	10	33	45	7	0	0	280	414	503	917	223	320	21	15	—	—	—	—	—	—	—	—
2022	31	INTL RAW	Sultanes de Monterrey	—	217	175	49	5	2	10	33	45	7	0	0	280	414	503	917	223	320	21	15	404	159	—	—	—	—	—	—
2023	32	INTL MLE	Aguilas de Mexicali	—	286	243	71	14	0	10	32	63	7	0	0	292	390	473	863	181	351	22	11	—	—	—	—	—	—	—	—
2023	32	INTL RAW	Aguilas de Mexicali	—	286	243	71	14	0	10	32	63	7	0	0	292	390	473	863	181	351	22	11	380	144	—	—	—	—	—	—
2024	33	INTL MLE	Criollos de Caguas	—	210	174	33	6	0	5	33	61	2	0	1	190	325	310	636	121	257	29	16	—	—	—	—	—	—	—	—
2024	33	INTL RAW	Criollos de Caguas	—	210	174	33	6	0	5	33	61	2	0	1	190	325	310	636	121	257	29	16	298	88	—	—	—	—	—	—
2025	34	INTL MLE	Senadores de San Juan	—	82	69	16	2	0	0	11	30	2	0	0	232	354	261	615	29	410	37	13	—	—	—	—	—	—	—	—
2025	34	INTL RAW	Senadores de San Juan	—	82	69	16	2	0	0	11	30	2	0	0	232	354	261	615	29	410	37	13	297	87	—	—	—	—	—	—
2009	18	ROK MLE	GCL Twins	—	131	117	21	5	0	2	10	49	3	2	0	179	262	274	535	94	280	37	8	245	52	—	—	—	—	—	—
2010	19	ROK MLE	2 teams	—	187	172	39	12	1	2	9	67	4	1	0	227	281	343	624	116	333	36	5	269	68	—	—	—	—	—	—
2011	20	ROK MLE	Elizabethton Twins	—	191	178	40	7	0	4	10	71	1	0	0	225	268	331	600	107	335	37	5	260	62	—	—	—	—	—	—
2012	21	A MLE	2 teams	—	268	238	64	12	1	12	27	79	1	0	0	269	347	479	826	210	344	29	10	366	134	—	—	—	—	—	—
2013	22	A+ MLE	2 teams	—	695	634	135	36	1	21	47	204	9	1	1	213	278	372	650	159	270	29	7	285	79	—	—	—	—	—	—
2014	23	AA MLE	3 teams	—	790	733	199	32	1	29	43	182	8	0	2	271	320	437	757	165	321	23	5	329	109	—	—	—	—	—	—
2015	24	MLB MLE	4 teams	—	646	579	139	16	2	20	57	185	5	0	0	240	312	378	690	138	313	29	9	309	96	—	—	—	—	—	—
2016	25	AAA MLE	3 teams	—	722	625	133	28	1	30	87	203	4	1	0	213	312	405	717	192	257	28	12	314	99	—	—	—	—	—	—
2017	26	MLB MLE	3 teams	—	602	547	128	24	1	24	48	178	2	0	0	234	297	413	710	179	299	30	8	315	99	—	—	—	—	—	—
2018	27	AAA MLE	2 teams	—	741	677	140	27	0	27	52	227	6	0	0	207	270	366	636	160	257	31	7	281	76	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	859	783	197	38	1	35	65	251	5	0	0	252	313	437	750	185	322	29	8	330	53	+10	+0	-3	-49	+19	-2.5
/ 162G	—	A+C		—	650	592	149	29	1	26	49	190	4	0	0	252	313	436	749	184	323	29	8	330	53	+7	+0	-3	-37	+14	-1.9
Career	—	MLE		—	6122	5439	1274	243	11	207	562	1742	68	5	4	234	314	397	711	163	301	28	9	247	53	+10	+0	-3	-49	+19	-2.5
/ 162G	—	MLE		—	650	577	135	26	1	22	60	185	7	1	0	234	314	397	711	163	301	28	9	247	53	+7	+0	-3	-37	+14	-1.9

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.

2018 AAARochester Red Wings · 533 PAwOBA .327 → .281 (−47)K% 25.0% → 30.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.95%	÷0.978	×1.200	—	—	30.63%
BB% (unintentional) /PA	10.32%	÷1.008	×0.690	—	×0.992	7.00%
HBP% /PA	0.94%	—	×0.940	—	×0.992	0.87%
Singles /BIP	20.30%	÷1.023	×0.930	×1.028	×0.992	18.82%
Doubles /BIP	6.97%	÷1.009	×0.830	×1.028	×0.992	5.85%
Triples /BIP	0.00%	÷1.150	×0.970	×1.028	×0.992	0.00%
Home runs /BIP	6.36%	÷0.879	×0.840	—	×0.992	6.03%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 105, 2B 102, 3B 130, K 96, BB 102 — 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 ×1.028.

Result: wOBA .327 → .281; ISO .186 → .170; BABIP .285 → .257. 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 AAARochester Red Wings · 211 PAwOBA .356 → .294 (−62)K% 25.1% → 30.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.12%	÷0.997	×1.200	—	—	30.23%
BB% (unintentional) /PA	14.22%	÷1.080	×0.690	—	×1.003	9.11%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	21.60%	÷1.019	×0.930	×1.004	×1.003	19.86%
Doubles /BIP	6.40%	÷1.085	×0.830	×1.004	×1.003	4.93%
Triples /BIP	0.80%	÷1.085	×0.970	×1.004	×1.003	0.72%
Home runs /BIP	7.20%	÷0.956	×0.840	—	×1.003	6.35%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 104, 2B 117, 3B 117, K 99, BB 116 — 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 ×1.004.

Result: wOBA .356 → .294; ISO .208 → .183; BABIP .305 → .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).

2016 AAARochester Red Wings · 402 PAwOBA .345 → .294 (−51)K% 22.1% → 26.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.14%	÷1.007	×1.200	—	—	26.37%
BB% (unintentional) /PA	15.92%	÷0.968	×0.690	—	×1.018	11.56%
HBP% /PA	0.50%	—	×0.940	—	×1.018	0.48%
Singles /BIP	18.67%	÷0.953	×0.930	×0.986	×1.018	18.30%
Doubles /BIP	6.64%	÷1.224	×0.830	×0.986	×1.018	4.52%
Triples /BIP	0.41%	÷0.971	×0.970	×0.986	×1.018	0.42%
Home runs /BIP	6.22%	÷0.951	×0.840	—	×1.018	5.59%

Factors used: league row IL. Park (home-season share, regressed): HR 90, 1B 90, 2B 145, 3B 94, K 101, BB 94 — 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 ×0.986.

Result: wOBA .345 → .294; ISO .191 → .166; BABIP .270 → .242. 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 AAARochester Red Wings · 151 PAwOBA .386 → .340 (−46)K% 25.8% → 30.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.83%	÷1.030	×1.200	—	—	30.09%
BB% (unintentional) /PA	16.56%	÷0.980	×0.690	—	×1.033	12.04%
HBP% /PA	1.32%	—	×0.940	—	×1.033	1.29%
Singles /BIP	26.51%	÷0.979	×0.930	×0.973	×1.033	25.30%
Doubles /BIP	7.23%	÷0.987	×0.830	×0.973	×1.033	6.11%
Triples /BIP	0.00%	÷0.932	×0.970	×0.973	×1.033	0.00%
Home runs /BIP	7.23%	÷0.956	×0.840	—	×1.033	6.56%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 96, 2B 97, 3B 86, K 106, BB 96 — 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 ×0.973.

Result: wOBA .386 → .340; ISO .197 → .181; BABIP .359 → .332. 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 AAChattanooga Lookouts · 151 PAwOBA .400 → .314 (−86)K% 21.2% → 26.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.19%	÷0.988	×1.220	—	—	26.16%
BB% (unintentional) /PA	15.89%	÷1.059	×0.680	—	×0.998	10.18%
HBP% /PA	1.32%	—	×0.840	—	×0.998	1.11%
Singles /BIP	25.56%	÷0.980	×0.920	×0.955	×0.998	22.87%
Doubles /BIP	3.33%	÷0.999	×0.910	×0.955	×0.998	2.89%
Triples /BIP	2.22%	÷1.020	×0.880	×0.955	×0.998	1.83%
Home runs /BIP	7.78%	÷1.232	×0.800	—	×0.998	5.04%

Factors used: league row SL. Park (home-season share, regressed): HR 146, 1B 96, 2B 100, 3B 104, K 98, BB 112 — 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 ×0.955.

Result: wOBA .400 → .314; ISO .230 → .168; BABIP .333 → .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).

2014 AANew Britain Rock Cats · 405 PAwOBA .359 → .327 (−32)K% 16.8% → 20.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.79%	÷0.989	×1.220	—	—	20.72%
BB% (unintentional) /PA	9.88%	÷1.155	×0.700	—	×1.012	6.06%
HBP% /PA	0.74%	—	×0.850	—	×1.012	0.64%
Singles /BIP	22.92%	÷0.967	×0.970	×1.050	×1.012	24.44%
Doubles /BIP	5.90%	÷0.999	×0.860	×1.050	×1.012	5.40%
Triples /BIP	0.00%	÷1.011	×0.950	×1.050	×1.012	0.00%
Home runs /BIP	5.90%	÷0.956	×0.780	—	×1.012	4.87%

Factors used: league row EL. Park (home-season share, regressed): HR 91, 1B 93, 2B 100, 3B 102, K 98, BB 131 — 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 ×1.050.

Result: wOBA .359 → .327; ISO .191 → .165; BABIP .303 → .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).

2013 A+Fort Myers Miracle · 520 PAwOBA .350 → .285 (−65)K% 20.2% → 29.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.19%	÷0.977	×1.420	—	—	29.34%
BB% (unintentional) /PA	9.04%	÷1.009	×0.750	—	×0.998	6.71%
HBP% /PA	1.35%	—	×0.930	—	×0.998	1.25%
Singles /BIP	19.60%	÷1.038	×0.920	×1.019	×0.998	17.67%
Doubles /BIP	9.38%	÷1.105	×0.960	×1.019	×0.998	8.29%
Triples /BIP	0.28%	÷0.906	×0.810	×1.019	×0.998	0.26%
Home runs /BIP	5.40%	÷0.993	×0.880	—	×0.998	4.77%

Factors used: league row FSL. Park (home-season share, regressed): HR 99, 1B 108, 2B 121, 3B 81, K 95, BB 102 — 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 ×1.019.

Result: wOBA .350 → .285; ISO .201 → .165; BABIP .304 → .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).

2012 ABeloit Snappers · 186 PAwOBA .432 → .366 (−66)K% 22.0% → 29.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.04%	÷1.012	×1.360	—	—	29.61%
BB% (unintentional) /PA	13.44%	÷0.935	×0.690	—	—	9.91%
HBP% /PA	0.54%	—	×0.780	—	—	0.42%
Singles /BIP	23.89%	÷0.942	×0.920	×1.048	—	24.46%
Doubles /BIP	8.85%	÷1.020	×0.830	×1.048	—	7.55%
Triples /BIP	0.88%	÷1.150	×0.910	×1.048	—	0.73%
Home runs /BIP	9.73%	÷1.042	×0.800	—	—	7.47%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 108, 1B 88, 2B 104, 3B 130, K 102, BB 87 — 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 ×1.048.

Result: wOBA .432 → .366; ISO .292 → .228; BABIP .362 → .344. 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 — .