Edwin Encarnación

PosDH

B/TR/R

Born1983-01-07

Age (2027)44

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2020

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2018	35	MLBCleveland Ind…	579	.246/.339/.474	32	3	125	1.6
2019	36	MLBNYY	486	.244/.346/.531	34	0	137	1.9
2020	37	MLBCWS	181	.157/.250/.377	10	0	73	-0.5
2021	38	No MLB games played
2022	39	No MLB games played
2023	40	No MLB games played
2024	41	No MLB games played
2025	42	No MLB games played
2026	43	No MLB games played

Last 3 seasons WAR 3.0

Contract

No contract data on file.

Skills · percentileStatcast 2018-2020

xwOBA84

Barrel%77

Avg EV53

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)
2005	22	MLB	Cincinnati Reds	—	234	211	49	16	0	9	20	60	3	3	0	232	308	436	744	204	282	26	9	330	105	+1	+1	-0	+2	+5	0.9
2005	22	AAA	Louisville Bats	—	330	290	91	23	0	15	33	53	4	7	2	314	391	548	940	234	338	16	10	408	125	—	—	—	—	—	—
2006	23	MLB	Cincinnati Reds	—	467	406	112	33	1	15	41	78	13	6	3	276	358	473	831	197	307	17	9	365	130	+17	+0	-5	+2	+10	2.4
2006	23	AAA	Louisville Bats	—	39	36	11	3	0	1	2	11	0	0	0	306	333	472	806	167	417	28	5	350	90	—	—	—	—	—	—
2007	24	MLB	Cincinnati Reds	—	560	502	145	25	1	16	39	86	14	8	1	289	354	438	792	149	322	15	7	353	122	+14	+1	-13	+2	+12	1.8
2007	24	AAA	Louisville Bats	—	50	46	19	3	0	3	1	4	0	1	0	413	400	674	1.074	261	410	8	2	451	175	—	—	—	—	—	—
2008	25	MLB	Cincinnati Reds	—	582	506	127	29	1	26	61	102	10	1	0	251	343	466	810	215	264	18	10	356	126	+18	+0	-10	+2	+13	2.3
2009	26	MLB	Toronto Blue Jays	—	338	293	66	11	2	13	37	67	5	2	1	225	322	410	732	184	245	20	11	326	107	+3	+0	-6	+1	+7	0.5
2009	26	AAA	Louisville Bats	—	45	37	10	1	0	2	8	6	0	0	0	270	400	459	859	189	276	13	18	386	105	—	—	—	—	—	—
2010	27	MLB	Toronto Blue Jays	—	367	332	81	16	0	21	29	60	2	1	0	244	309	482	790	238	235	16	8	343	117	+7	+0	+2	+2	+8	1.9
2010	27	AAA	Las Vegas 51s	—	35	32	14	2	0	3	2	2	1	0	0	438	486	781	1.267	344	407	6	6	545	183	—	—	—	—	—	—
2010	27	INTL	Aguilas Cibaenas	—	64	57	14	4	1	3	5	8	2	1	0	246	328	509	837	263	239	12	8	365	133	—	—	—	—	—	—
2011	28	MLB	Toronto Blue Jays	—	530	481	131	36	0	17	43	77	3	8	2	272	336	453	789	181	292	15	8	348	120	+12	+1	-9	+2	+11	1.8
2011	28	INTL	Aguilas Cibaenas	—	21	15	2	0	0	1	6	5	0	0	0	133	381	333	714	200	111	24	29	342	117	—	—	—	—	—	—
2012	29	MLB	Toronto Blue Jays	—	644	542	152	24	0	42	84	94	11	13	3	280	388	557	945	277	266	15	13	408	153	+41	+1	-10	-12	+14	3.5
2013	30	MLB	Toronto Blue Jays	—	621	530	144	29	1	36	82	62	4	7	1	272	373	534	907	262	247	10	13	394	147	+35	+1	-9	-11	+13	2.9
2014	31	MLB	Toronto Blue Jays	—	542	477	128	27	2	34	62	82	2	2	0	268	355	547	902	279	260	15	11	392	146	+29	+0	-9	-10	+12	2.3
2015	32	MLB	Toronto Blue Jays	—	624	528	146	31	0	39	77	98	9	3	2	277	378	557	935	280	267	16	12	401	153	+40	-0	-3	-11	+14	4.0
2016	33	MLB	Toronto Blue Jays	—	702	601	158	34	0	42	87	138	5	2	0	263	360	529	889	266	270	20	12	384	144	+37	+0	-6	-13	+15	3.5
2017	34	MLB	Cleveland Indians	—	669	554	143	20	1	38	104	133	5	2	0	258	380	504	883	245	271	20	16	387	144	+35	+0	-0	-12	+14	3.9
2018	35	MLB	Cleveland Indians	—	579	500	123	16	1	32	63	132	8	3	0	246	339	474	813	228	265	23	11	355	125	+17	+1	-4	-10	+13	1.6
2019	36	MLB	New York Yankees	—	486	418	102	18	0	34	58	103	7	0	1	244	346	531	877	287	239	21	12	380	137	+21	-0	-4	-9	+11	1.9
2020	37	MLB	Chicago White Sox	—	181	159	25	5	0	10	16	54	4	0	0	157	250	377	627	220	156	30	9	278	73	-6	+0	+0	-3	+4	-0.5
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	8126	7040	1832	370	10	424	903	1426	105	61	14	260	352	496	849	236	268	18	11	371	137	+357	+7	-87	-77	+176	38.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	22	MLB MLE	Cincinnati Reds	—	234	213	49	16	0	9	18	60	3	3	0	230	299	432	731	202	282	26	8	324	105	+1	+1	-0	+2	+5	0.9
2005	22	AAA MLE	Louisville Bats	—	330	300	84	20	0	13	23	64	4	7	2	280	339	477	816	197	308	19	7	353	125	—	—	—	—	—	—
2006	23	MLB MLE	Cincinnati Reds	—	467	413	112	33	1	15	38	78	13	6	3	271	351	465	816	194	307	17	8	360	130	+17	+0	-5	+2	+10	2.4
2006	23	AAA MLE	Louisville Bats	—	39	38	11	3	0	1	1	13	0	0	0	289	308	447	755	158	392	33	3	301	90	—	—	—	—	—	—
2007	24	MLB MLE	Cincinnati Reds	—	560	510	145	25	1	16	35	86	14	8	1	284	347	431	778	147	322	15	6	348	122	+14	+1	-13	+2	+12	1.8
2007	24	AAA MLE	Louisville Bats	—	50	49	19	3	0	3	1	5	0	1	0	388	400	633	1.033	245	388	10	2	427	175	—	—	—	—	—	—
2008	25	MLB MLE	Cincinnati Reds	—	582	507	127	29	1	26	60	102	10	1	0	250	341	465	807	215	264	18	10	355	126	+18	+0	-10	+2	+13	2.3
2009	26	MLB MLE	Toronto Blue Jays	—	338	293	66	11	2	13	37	67	5	2	1	225	322	410	732	184	245	20	11	326	107	+3	+0	-6	+1	+7	0.5
2009	26	AAA MLE	Louisville Bats	—	45	39	10	1	0	2	6	7	0	0	0	256	356	436	791	179	255	16	13	324	105	—	—	—	—	—	—
2010	27	MLB MLE	Toronto Blue Jays	—	367	333	81	16	0	21	28	60	2	1	0	243	306	480	786	237	235	16	8	340	117	+7	+0	+2	+2	+8	1.9
2010	27	AAA MLE	Las Vegas 51s	—	35	33	12	2	0	2	1	3	1	0	0	364	400	606	1.006	242	352	9	3	439	183	—	—	—	—	—	—
2011	28	MLB MLE	Toronto Blue Jays	—	530	483	131	36	0	17	41	77	3	8	2	271	332	451	783	180	292	15	8	345	120	+12	+1	-9	+2	+11	1.8
2012	29	MLB MLE	Toronto Blue Jays	—	644	554	152	24	0	42	72	94	11	13	3	274	369	545	914	271	266	15	11	395	153	+41	+1	-10	-12	+14	3.5
2013	30	MLB MLE	Toronto Blue Jays	—	621	537	144	29	1	36	75	62	4	7	1	268	362	527	889	259	247	10	12	385	147	+35	+1	-9	-11	+13	2.9
2014	31	MLB MLE	Toronto Blue Jays	—	542	483	128	27	2	34	56	82	2	2	0	265	344	540	884	275	260	15	10	383	146	+29	+0	-9	-10	+12	2.3
2015	32	MLB MLE	Toronto Blue Jays	—	624	533	146	31	0	39	72	98	9	3	2	274	370	552	921	278	267	16	12	395	153	+40	-0	-3	-11	+14	4.0
2016	33	MLB MLE	Toronto Blue Jays	—	702	605	158	34	0	42	84	138	5	2	0	261	356	526	882	264	270	20	12	381	144	+37	+0	-6	-13	+15	3.5
2017	34	MLB MLE	Cleveland Indians	—	669	560	143	20	1	38	99	133	5	2	0	255	372	498	870	243	271	20	15	381	144	+35	+0	-0	-12	+14	3.9
2018	35	MLB MLE	Cleveland Indians	—	579	503	123	16	1	32	61	132	8	3	0	245	336	471	807	227	265	23	11	353	125	+17	+1	-4	-10	+13	1.6
2019	36	MLB MLE	New York Yankees	—	486	419	100	18	0	32	57	103	7	0	1	239	340	511	850	272	239	21	12	370	137	+21	-0	-4	-9	+11	1.9
2020	37	MLB MLE	Chicago White Sox	—	181	160	25	5	0	10	16	54	4	0	0	156	250	375	625	219	156	30	9	276	73	-6	+0	+0	-3	+4	-0.5
2005	22	AAA MLE	2 teams	—	564	513	133	36	0	22	41	124	7	10	2	259	323	458	781	199	300	22	7	341	117	—	—	—	—	—	—
2005	22	AAA RAW	2 teams	—	564	501	140	39	0	24	53	113	7	10	2	279	357	501	858	222	316	20	9	376	117	—	—	—	—	—	—
2006	23	MLB MLE	2 teams	—	506	451	123	36	1	16	39	91	13	6	3	273	348	463	811	191	308	18	8	356	127	+16	+0	-5	+2	+11	2.4
2006	23	MLB RAW	2 teams	—	506	442	123	36	1	16	43	89	13	6	3	278	356	473	829	195	315	18	8	364	127	+16	+0	-5	+2	+11	2.4
2007	24	MLB MLE	2 teams	—	610	559	164	28	1	19	36	91	14	9	1	293	351	449	800	156	322	15	6	355	126	+19	+1	-13	+2	+13	2.3
2007	24	MLB RAW	2 teams	—	610	548	164	28	1	19	40	90	14	9	1	299	358	458	816	159	330	15	7	361	126	+19	+1	-13	+2	+13	2.3
2008	25	MLB MLE	Cincinnati Reds	—	582	507	127	29	1	26	60	102	10	1	0	250	341	465	807	215	263	18	10	355	126	+18	+0	-10	+2	+13	2.3
2008	25	MLB RAW	Cincinnati Reds	—	582	506	127	29	1	26	61	102	10	1	0	251	343	466	810	215	264	18	10	356	126	+18	+0	-10	+2	+13	2.3
2009	26	MLB MLE	2 teams	—	383	332	76	12	2	15	43	74	5	2	1	229	326	413	739	184	248	19	11	326	106	+3	+0	-6	+1	+8	0.6
2009	26	MLB RAW	2 teams	—	383	330	76	12	2	15	45	73	5	2	1	230	332	415	747	185	249	19	12	333	106	+3	+0	-6	+1	+8	0.6
2010	27	MLB MLE	3 teams	—	466	423	107	20	0	27	34	73	5	2	0	253	316	492	808	239	245	16	7	349	122	+12	+0	+2	+2	+10	2.7
2010	27	MLB RAW	3 teams	—	466	421	109	22	1	27	36	70	5	2	0	259	325	508	833	249	250	15	8	361	122	+12	+0	+2	+2	+10	2.7
2011	28	MLB MLE	2 teams	—	551	502	137	38	0	18	43	80	3	8	2	273	334	456	790	183	292	15	8	345	120	+13	+1	-9	+2	+12	1.9
2011	28	MLB RAW	2 teams	—	551	496	133	36	0	18	49	82	3	8	2	268	338	450	787	181	288	15	9	348	120	+13	+1	-9	+2	+12	1.9
2012	29	MLB MLE	Toronto Blue Jays	—	644	554	152	24	0	42	72	94	11	13	3	274	369	545	914	271	259	15	11	395	153	+41	+1	-10	-12	+14	3.5
2012	29	MLB RAW	Toronto Blue Jays	—	644	542	152	24	0	42	84	94	11	13	3	280	388	557	945	277	266	15	13	408	153	+41	+1	-10	-12	+14	3.5
2013	30	MLB MLE	Toronto Blue Jays	—	621	537	144	29	1	36	75	62	4	7	1	268	362	527	889	259	243	10	12	385	147	+35	+1	-9	-11	+13	2.9
2013	30	MLB RAW	Toronto Blue Jays	—	621	530	144	29	1	36	82	62	4	7	1	272	373	534	907	262	247	10	13	394	147	+35	+1	-9	-11	+13	2.9
2014	31	MLB MLE	Toronto Blue Jays	—	542	483	128	27	2	34	56	82	2	2	0	265	344	540	884	275	255	15	10	383	146	+29	+0	-9	-10	+12	2.3
2014	31	MLB RAW	Toronto Blue Jays	—	542	477	128	27	2	34	62	82	2	2	0	268	355	547	902	279	260	15	11	392	146	+29	+0	-9	-10	+12	2.3
2015	32	MLB MLE	Toronto Blue Jays	—	624	533	146	31	0	39	72	98	9	3	2	274	370	552	921	278	264	16	12	395	153	+40	-0	-3	-11	+14	4.0
2015	32	MLB RAW	Toronto Blue Jays	—	624	528	146	31	0	39	77	98	9	3	2	277	378	557	935	280	267	16	12	401	153	+40	-0	-3	-11	+14	4.0
2016	33	MLB MLE	Toronto Blue Jays	—	702	605	158	34	0	42	84	138	5	2	0	261	356	526	882	264	268	20	12	381	144	+37	+0	-6	-13	+15	3.5
2016	33	MLB RAW	Toronto Blue Jays	—	702	601	158	34	0	42	87	138	5	2	0	263	360	529	889	266	270	20	12	384	144	+37	+0	-6	-13	+15	3.5
2017	34	MLB MLE	Cleveland Indians	—	669	560	143	20	1	38	99	133	5	2	0	255	372	498	870	243	266	20	15	381	144	+35	+0	-0	-12	+14	3.9
2017	34	MLB RAW	Cleveland Indians	—	669	554	143	20	1	38	104	133	5	2	0	258	380	504	883	245	271	20	16	387	144	+35	+0	-0	-12	+14	3.9
2018	35	MLB MLE	Cleveland Indians	—	579	503	123	16	1	32	61	132	8	3	0	245	336	471	807	227	263	23	11	353	125	+17	+1	-4	-10	+13	1.6
2018	35	MLB RAW	Cleveland Indians	—	579	500	123	16	1	32	63	132	8	3	0	246	339	474	813	228	265	23	11	355	125	+17	+1	-4	-10	+13	1.6
2019	36	MLB MLE	New York Yankees	—	486	419	100	18	0	32	57	103	7	0	1	239	340	511	850	272	237	21	12	370	137	+21	-0	-4	-9	+11	1.9
2019	36	MLB RAW	New York Yankees	—	486	418	102	18	0	34	58	103	7	0	1	244	346	531	877	287	239	21	12	380	137	+21	-0	-4	-9	+11	1.9
2020	37	MLB MLE	Chicago White Sox	—	181	160	25	5	0	10	16	54	4	0	0	156	250	375	625	219	155	30	9	276	73	-6	+0	+0	-3	+4	-0.5
2020	37	MLB RAW	Chicago White Sox	—	181	159	25	5	0	10	16	54	4	0	0	157	250	377	627	220	156	30	9	278	73	-6	+0	+0	-3	+4	-0.5
2005	22	AAA MLE	2 teams	—	564	511	133	36	0	22	41	124	7	10	2	260	323	460	783	200	297	22	7	341	117	—	—	—	—	—	—
2006	23	MLB MLE	2 teams	—	506	449	123	36	1	16	39	91	13	6	3	274	348	465	813	192	314	18	8	356	127	—	—	—	—	—	—
2007	24	MLB MLE	2 teams	—	610	555	164	28	1	19	36	91	14	9	1	295	351	452	804	157	327	15	6	355	126	—	—	—	—	—	—
2008	25	MLB MLE	Cincinnati Reds	—	582	507	127	29	1	26	60	102	10	1	0	250	341	465	807	215	264	18	10	355	126	—	—	—	—	—	—
2009	26	MLB MLE	2 teams	—	383	332	76	12	2	15	43	74	5	2	1	229	326	413	739	184	247	19	11	326	106	—	—	—	—	—	—
2010	27	MLB MLE	3 teams	—	466	424	107	20	0	27	34	73	5	2	0	252	316	491	807	238	245	16	7	349	122	—	—	—	—	—	—
2011	28	MLB MLE	2 teams	—	551	500	137	38	0	18	43	80	3	8	2	274	334	458	792	184	292	15	8	345	120	—	—	—	—	—	—
2012	29	MLB MLE	Toronto Blue Jays	—	644	556	152	24	0	42	72	94	11	13	3	273	369	543	912	270	266	15	11	395	153	—	—	—	—	—	—
2013	30	MLB MLE	Toronto Blue Jays	—	621	537	144	29	1	36	75	62	4	7	1	268	362	527	889	259	247	10	12	385	147	—	—	—	—	—	—
2014	31	MLB MLE	Toronto Blue Jays	—	542	479	128	27	2	34	56	82	2	2	0	267	344	545	889	278	260	15	10	383	146	—	—	—	—	—	—
2015	32	MLB MLE	Toronto Blue Jays	—	624	538	146	31	0	39	72	98	9	3	2	271	370	546	916	275	267	16	12	395	153	—	—	—	—	—	—
2016	33	MLB MLE	Toronto Blue Jays	—	702	607	158	34	0	42	84	138	5	2	0	260	356	524	880	264	270	20	12	381	144	—	—	—	—	—	—
2017	34	MLB MLE	Cleveland Indians	—	669	560	143	20	1	38	99	133	5	2	0	255	372	498	870	243	271	20	15	381	144	—	—	—	—	—	—
2018	35	MLB MLE	Cleveland Indians	—	579	505	123	16	1	32	61	132	8	3	0	244	336	469	805	226	265	23	11	353	125	—	—	—	—	—	—
2019	36	MLB MLE	New York Yankees	—	486	419	100	18	0	32	57	103	7	0	1	239	340	511	850	272	239	21	12	370	137	—	—	—	—	—	—
2020	37	MLB MLE	Chicago White Sox	—	181	159	25	5	0	10	16	54	4	0	0	157	250	377	627	220	156	30	9	276	73	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	8126	7040	1832	370	10	424	903	1426	105	61	14	260	352	496	849	236	268	18	11	371	133	+357	+7	-87	-77	+176	38.3
/ 162G	—	A+C		—	650	563	147	30	1	34	72	114	8	5	1	261	352	499	851	238	269	18	11	371	133	+29	+1	-7	-6	+14	3.1
Career	—	MLE		—	8710	7641	1986	403	10	448	888	1531	112	70	16	260	346	491	837	231	268	18	10	365	133	+357	+7	-87	-77	+176	38.3
/ 162G	—	MLE		—	650	570	148	30	1	33	66	114	8	5	1	260	344	489	834	230	269	18	10	365	133	+29	+1	-7	-6	+14	3.1

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.

2010 AAALas Vegas 51s · 35 PAwOBA .529 → .439 (−90)K% 5.7% → 7.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.71%	÷0.959	×1.290	—	—	7.69%
BB% (unintentional) /PA	5.71%	÷0.988	×0.710	—	×1.003	4.12%
HBP% /PA	2.86%	—	×0.980	—	×1.003	2.81%
Singles /BIP	30.00%	÷0.985	×0.900	—	×1.003	27.49%
Doubles /BIP	6.67%	÷1.077	×0.810	—	×1.003	5.03%
Triples /BIP	0.00%	÷1.150	×0.810	—	×1.003	0.00%
Home runs /BIP	10.00%	÷1.024	×0.780	—	×1.003	7.64%

Factors used: league row PCL. Park (home-season share, regressed): HR 105, 1B 97, 2B 115, 3B 130, K 92, BB 98 — 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 .529 → .439; ISO .344 → .261; BABIP .407 → .352. 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 AAALouisville Bats · 45 PAwOBA .376 → .324 (−52)K% 13.3% → 16.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.33%	÷1.000	×1.200	—	—	16.00%
BB% (unintentional) /PA	17.78%	÷1.000	×0.690	—	×1.018	12.49%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	22.58%	÷1.000	×0.930	—	×1.018	21.38%
Doubles /BIP	3.23%	÷1.000	×0.830	—	×1.018	2.73%
Triples /BIP	0.00%	÷1.000	×0.970	—	×1.018	0.00%
Home runs /BIP	6.45%	÷1.000	×0.840	—	×1.018	5.52%

Factors used: league row IL. 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).

Result: wOBA .376 → .324; ISO .189 → .168; BABIP .276 → .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).

2007 AAALouisville Bats · 50 PAwOBA .438 → .427 (−11)K% 8.0% → 9.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.00%	÷1.000	×1.200	—	—	9.60%
BB% (unintentional) /PA	2.00%	÷1.000	×0.690	—	×1.048	1.45%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	30.95%	÷1.000	×0.930	—	×1.048	30.17%
Doubles /BIP	7.14%	÷1.000	×0.830	—	×1.048	6.21%
Triples /BIP	0.00%	÷1.000	×0.970	—	×1.048	0.00%
Home runs /BIP	7.14%	÷1.000	×0.840	—	×1.048	6.29%

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).

Result: wOBA .438 → .427; ISO .261 → .242; BABIP .410 → .388. 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 AAALouisville Bats · 39 PAwOBA .340 → .301 (−39)K% 28.2% → 33.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.21%	÷1.000	×1.200	—	—	33.85%
BB% (unintentional) /PA	5.13%	÷1.000	×0.690	—	×1.050	3.72%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	28.00%	÷1.000	×0.930	—	×1.050	27.34%
Doubles /BIP	12.00%	÷1.000	×0.830	—	×1.050	10.46%
Triples /BIP	0.00%	÷1.000	×0.970	—	×1.050	0.00%
Home runs /BIP	4.00%	÷1.000	×0.840	—	×1.050	3.53%

Factors used: league row IL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average).

Result: wOBA .340 → .301; ISO .167 → .142; BABIP .417 → .392. 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 AAALouisville Bats · 330 PAwOBA .400 → .353 (−47)K% 16.1% → 19.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.06%	÷1.000	×1.200	—	—	19.27%
BB% (unintentional) /PA	9.70%	÷1.000	×0.690	—	×1.050	7.03%
HBP% /PA	1.21%	—	×0.940	—	×1.050	1.20%
Singles /BIP	22.36%	÷1.000	×0.930	×0.974	×1.050	21.27%
Doubles /BIP	9.70%	÷1.000	×0.830	×0.974	×1.050	8.24%
Triples /BIP	0.00%	÷1.000	×0.970	×0.974	×1.050	0.00%
Home runs /BIP	6.33%	÷1.000	×0.840	—	×1.050	5.58%

Factors used: league row IL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.974.

Result: wOBA .400 → .353; ISO .234 → .206; BABIP .338 → .308. 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 — .