Matt Holliday

PosLF

B/TR/R

Born1980-01-15

Age (2027)47

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2018

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2016	36	MLBSTL	426	.246/.322/.461	20	0	123	0.9
2017	37	AAA/A+2 orgs	51	.256/.360/.279	0	0	48	—	.221/.300/.244
2017	37	MLBNYY	427	.231/.320/.432	19	1	107	0.3
2018	38	AAACOL	62	.346/.452/.596	3	0	112	—	.250/.323/.411
2018	38	MLBCOL	65	.283/.415/.434	2	0	140	0.1
2019	39	No MLB games played
2020	40	No MLB games played
2021	41	No MLB games played
2022	42	No MLB games played
2023	43	No MLB games played
2024	44	No MLB games played
2025	45	No MLB games played
2026	46	No MLB games played

Last 3 seasons WAR 1.3

Contract

No contract data on file.

Skills · percentileStatcast 2016-2018

Avg EV84

xwOBA81

Barrel%55

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)
2004	24	MLB	Colorado Rockies	—	439	400	116	31	3	14	31	86	6	3	3	290	350	487	838	198	339	20	7	368	135	+18	-1	-6	-5	+10	1.6
2005	25	MLB	Colorado Rockies	—	526	479	147	24	7	19	36	79	7	14	3	307	364	505	869	198	332	15	7	380	142	+26	+2	-3	-6	+11	3.1
2005	25	AA	Tulsa Drillers	—	28	26	14	3	0	1	1	3	0	1	0	538	556	769	1.325	231	565	11	4	560	229	—	—	—	—	—	—
2006	26	MLB	Colorado Rockies	—	667	602	196	45	5	34	47	110	15	10	5	326	389	586	975	261	351	16	7	422	170	+55	+0	-17	-7	+14	4.7
2007	27	MLB	Colorado Rockies	—	713	636	216	50	6	36	63	126	10	11	4	340	408	607	1.015	267	377	18	9	438	178	+66	+1	-2	-8	+15	7.4
2008	28	MLB	Colorado Rockies	—	623	539	173	38	2	25	74	104	8	28	2	321	411	538	949	217	359	17	12	416	163	+47	+5	-3	-7	+13	5.6
2009	29	MLB	St. Louis Cardinals	—	670	581	182	39	3	24	72	101	10	14	7	313	398	515	913	201	341	15	11	399	151	+40	+0	-3	-7	+15	4.5
2010	30	MLB	St. Louis Cardinals	—	675	596	186	45	1	28	69	93	8	9	5	312	391	532	923	220	331	14	10	405	156	+45	-0	+0	-7	+15	5.4
2011	31	MLB	St. Louis Cardinals	—	516	446	132	36	0	22	60	93	8	2	1	296	389	525	914	229	330	18	12	401	157	+35	+0	-3	-6	+11	3.8
2012	32	MLB	St. Louis Cardinals	—	688	599	177	36	2	27	75	132	9	4	4	295	382	497	880	202	337	19	11	387	149	+40	-1	-10	-7	+15	3.8
2013	33	MLB	St. Louis Cardinals	—	602	520	156	31	1	22	69	86	9	6	1	300	391	490	882	190	322	14	11	389	149	+35	+1	-12	-6	+13	3.1
2014	34	MLB	St. Louis Cardinals	—	667	574	156	37	0	20	74	100	17	4	1	272	371	441	812	169	298	15	11	364	132	+25	+0	-12	-7	+14	2.1
2015	35	MLB	St. Louis Cardinals	—	277	229	64	16	1	4	39	49	6	2	1	279	398	410	808	131	335	18	14	365	125	+8	+0	-4	-3	+6	0.7
2016	36	MLB	St. Louis Cardinals	—	426	382	94	20	1	20	35	71	8	0	0	246	322	461	783	215	253	17	8	345	123	+12	+0	-8	-5	+9	0.9
2017	37	MLB	New York Yankees	—	427	373	86	18	0	19	46	114	3	1	0	231	320	432	752	201	273	27	11	331	107	+3	+0	-1	-9	+9	0.3
2017	37	AAA	Scranton/Wilkes-Barre RailRiders	—	21	18	5	0	0	0	3	2	0	0	0	278	381	278	659		312	10	14	315	58	—	—	—	—	—	—
2017	37	A+	Tampa Yankees	—	30	25	6	1	0	0	3	5	1	0	0	240	345	280	625	40	286	17	10	288	41	—	—	—	—	—	—
2018	38	MLB	Colorado Rockies	—	65	53	15	2	0	2	12	18	0	0	0	283	415	434	849	151	394	28	18	385	140	+3	+0	-2	-1	+1	0.1
2018	38	AAA	Albuquerque Isotopes	—	62	52	18	4	0	3	9	9	1	0	0	346	452	596	1.048	250	375	15	15	457	112	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	7981	7009	2096	468	32	316	802	1362	124	108	37	299	381	510	891	211	331	17	10	391	151	+481	+7	-87	-90	+173	49.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2004	24	MLB MLE	Colorado Rockies	—	439	400	116	31	3	14	31	86	6	3	3	290	350	487	838	198	339	20	7	368	135	+18	-1	-6	-5	+10	1.6
2005	25	MLB MLE	Colorado Rockies	—	526	480	147	24	7	19	35	79	7	14	3	306	362	504	866	198	332	15	7	378	142	+26	+2	-3	-6	+11	3.1
2005	25	AA MLE	Tulsa Drillers	—	28	26	13	3	0	1	1	4	0	1	0	500	519	731	1.249	231	505	14	4	506	229	—	—	—	—	—	—
2006	26	MLB MLE	Colorado Rockies	—	667	605	196	45	5	34	44	110	15	10	5	324	384	583	968	260	351	16	7	419	170	+55	+0	-17	-7	+14	4.7
2007	27	MLB MLE	Colorado Rockies	—	713	643	216	50	6	36	56	126	10	11	4	336	398	600	998	264	377	18	8	431	178	+66	+1	-2	-8	+15	7.4
2008	28	MLB MLE	Colorado Rockies	—	623	545	173	38	2	25	68	104	8	28	2	317	401	532	933	215	359	17	11	409	163	+47	+5	-3	-7	+13	5.6
2009	29	MLB MLE	St. Louis Cardinals	—	670	589	182	39	3	24	64	101	10	14	7	309	386	508	894	199	341	15	10	391	151	+40	+0	-3	-7	+15	4.5
2010	30	MLB MLE	St. Louis Cardinals	—	675	606	186	43	1	30	59	93	8	9	5	307	376	530	906	223	331	14	9	399	156	+45	-0	+0	-7	+15	5.4
2011	31	MLB MLE	St. Louis Cardinals	—	516	450	132	34	0	24	56	93	8	2	1	293	381	529	910	236	330	18	11	400	157	+35	+0	-3	-6	+11	3.8
2012	32	MLB MLE	St. Louis Cardinals	—	688	602	177	34	2	29	72	132	9	4	4	294	378	502	879	208	337	19	10	389	149	+40	-1	-10	-7	+15	3.8
2013	33	MLB MLE	St. Louis Cardinals	—	602	525	157	30	1	24	64	86	9	6	1	299	385	497	882	198	322	14	11	388	149	+35	+1	-12	-6	+13	3.1
2014	34	MLB MLE	St. Louis Cardinals	—	667	578	156	35	0	22	70	100	17	4	1	270	365	445	810	175	298	15	10	363	132	+25	+0	-12	-7	+14	2.1
2015	35	MLB MLE	St. Louis Cardinals	—	277	234	63	15	1	4	34	49	6	2	1	269	376	393	769	124	335	18	12	353	125	+8	+0	-4	-3	+6	0.7
2016	36	MLB MLE	St. Louis Cardinals	—	426	383	95	19	1	22	34	71	8	0	0	248	322	475	798	227	253	17	8	350	123	+12	+0	-8	-5	+9	0.9
2017	37	MLB MLE	New York Yankees	—	427	373	85	18	0	18	46	114	3	1	0	228	318	421	738	193	273	27	11	326	107	+3	+0	-1	-9	+9	0.3
2017	37	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	21	19	5	0	0	0	2	2	0	0	0	263	333	263	596		279	10	10	254	58	—	—	—	—	—	—
2017	37	A+ MLE	Tampa Yankees	—	30	26	5	1	0	0	2	7	1	0	0	192	276	231	507	38	235	23	7	229	41	—	—	—	—	—	—
2018	38	MLB MLE	Colorado Rockies	—	65	53	15	2	0	2	12	18	0	0	0	283	415	434	849	151	394	28	18	375	140	+3	+0	-2	-1	+1	0.1
2018	38	AAA MLE	Albuquerque Isotopes	—	62	56	14	3	0	2	5	12	1	0	0	250	323	411	733	161	296	19	8	333	112	—	—	—	—	—	—
2004	24	MLB MLE	Colorado Rockies	—	439	400	116	31	3	14	31	86	6	3	3	290	350	487	838	198	339	20	7	368	135	+18	-1	-6	-5	+10	1.6
2004	24	MLB RAW	Colorado Rockies	—	439	400	116	31	3	14	31	86	6	3	3	290	350	487	838	198	339	20	7	368	135	+18	-1	-6	-5	+10	1.6
2005	25	MLB MLE	2 teams	—	554	506	160	27	7	20	36	83	7	15	3	316	370	516	886	200	343	15	6	385	147	+31	+2	-3	-6	+12	3.6
2005	25	MLB RAW	2 teams	—	554	505	161	27	7	20	37	82	7	15	3	319	373	519	892	200	346	15	7	389	147	+31	+2	-3	-6	+12	3.6
2006	26	MLB MLE	Colorado Rockies	—	667	605	196	45	5	34	44	110	15	10	5	324	384	583	968	260	349	16	7	419	170	+55	+0	-17	-7	+14	4.7
2006	26	MLB RAW	Colorado Rockies	—	667	602	196	45	5	34	47	110	15	10	5	326	389	586	975	261	351	16	7	422	170	+55	+0	-17	-7	+14	4.7
2007	27	MLB MLE	Colorado Rockies	—	713	643	216	50	6	36	56	126	10	11	4	336	398	600	998	264	371	18	8	431	178	+66	+1	-2	-8	+15	7.4
2007	27	MLB RAW	Colorado Rockies	—	713	636	216	50	6	36	63	126	10	11	4	340	408	607	1.015	267	377	18	9	438	178	+66	+1	-2	-8	+15	7.4
2008	28	MLB MLE	Colorado Rockies	—	623	545	173	38	2	25	68	104	8	28	2	317	401	532	933	215	354	17	11	409	163	+47	+5	-3	-7	+13	5.6
2008	28	MLB RAW	Colorado Rockies	—	623	539	173	38	2	25	74	104	8	28	2	321	411	538	949	217	359	17	12	416	163	+47	+5	-3	-7	+13	5.6
2009	29	MLB MLE	St. Louis Cardinals	—	670	589	182	39	3	24	64	101	10	14	7	309	386	508	894	199	335	15	10	391	151	+40	+0	-3	-7	+15	4.5
2009	29	MLB RAW	St. Louis Cardinals	—	670	581	182	39	3	24	72	101	10	14	7	313	398	515	913	201	341	15	11	399	151	+40	+0	-3	-7	+15	4.5
2010	30	MLB MLE	St. Louis Cardinals	—	675	606	186	43	1	30	59	93	8	9	5	307	376	530	906	223	322	14	9	399	156	+45	-0	+0	-7	+15	5.4
2010	30	MLB RAW	St. Louis Cardinals	—	675	596	186	45	1	28	69	93	8	9	5	312	391	532	923	220	331	14	10	405	156	+45	-0	+0	-7	+15	5.4
2011	31	MLB MLE	St. Louis Cardinals	—	516	450	132	34	0	24	56	93	8	2	1	293	381	529	910	236	322	18	11	400	157	+35	+0	-3	-6	+11	3.8
2011	31	MLB RAW	St. Louis Cardinals	—	516	446	132	36	0	22	60	93	8	2	1	296	389	525	914	229	330	18	12	401	157	+35	+0	-3	-6	+11	3.8
2012	32	MLB MLE	St. Louis Cardinals	—	688	602	177	34	2	29	72	132	9	4	4	294	378	502	879	208	332	19	10	389	149	+40	-1	-10	-7	+15	3.8
2012	32	MLB RAW	St. Louis Cardinals	—	688	599	177	36	2	27	75	132	9	4	4	295	382	497	880	202	337	19	11	387	149	+40	-1	-10	-7	+15	3.8
2013	33	MLB MLE	St. Louis Cardinals	—	602	525	157	30	1	24	64	86	9	6	1	299	385	497	882	198	317	14	11	388	149	+35	+1	-12	-6	+13	3.1
2013	33	MLB RAW	St. Louis Cardinals	—	602	520	156	31	1	22	69	86	9	6	1	300	391	490	882	190	322	14	11	389	149	+35	+1	-12	-6	+13	3.1
2014	34	MLB MLE	St. Louis Cardinals	—	667	578	156	35	0	22	70	100	17	4	1	270	365	445	810	175	293	15	10	363	132	+25	+0	-12	-7	+14	2.1
2014	34	MLB RAW	St. Louis Cardinals	—	667	574	156	37	0	20	74	100	17	4	1	272	371	441	812	169	298	15	11	364	132	+25	+0	-12	-7	+14	2.1
2015	35	MLB MLE	St. Louis Cardinals	—	277	234	63	15	1	4	34	49	6	2	1	269	376	393	769	124	321	18	12	353	125	+8	+0	-4	-3	+6	0.7
2015	35	MLB RAW	St. Louis Cardinals	—	277	229	64	16	1	4	39	49	6	2	1	279	398	410	808	131	335	18	14	365	125	+8	+0	-4	-3	+6	0.7
2016	36	MLB MLE	St. Louis Cardinals	—	426	383	95	19	1	22	34	71	8	0	0	248	322	475	798	227	251	17	8	350	123	+12	+0	-8	-5	+9	0.9
2016	36	MLB RAW	St. Louis Cardinals	—	426	382	94	20	1	20	35	71	8	0	0	246	322	461	783	215	253	17	8	345	123	+12	+0	-8	-5	+9	0.9
2017	37	MLB MLE	3 teams	—	478	418	95	19	0	18	50	124	4	1	0	227	316	402	718	175	273	26	10	316	100	+0	+0	-1	-9	+10	0.1
2017	37	MLB RAW	3 teams	—	478	416	97	19	0	19	52	121	4	1	0	233	324	416	740	183	277	25	11	328	100	+0	+0	-1	-9	+10	0.1
2018	38	MLB MLE	2 teams	—	127	109	29	5	0	4	17	30	1	0	0	266	370	422	792	156	333	24	13	355	126	+4	+0	-2	-1	+3	0.3
2018	38	MLB RAW	2 teams	—	127	105	33	6	0	5	21	27	1	0	0	314	433	514	947	200	384	21	17	421	126	+4	+0	-2	-1	+3	0.3
2004	24	MLB MLE	Colorado Rockies	—	439	399	116	31	3	14	31	86	6	3	3	291	350	489	839	198	339	20	7	368	135	—	—	—	—	—	—
2005	25	MLB MLE	2 teams	—	554	506	160	27	7	20	36	83	7	15	3	316	370	516	886	200	341	15	6	385	147	—	—	—	—	—	—
2006	26	MLB MLE	Colorado Rockies	—	667	603	196	45	5	34	44	110	15	10	5	325	384	585	969	260	351	16	7	419	170	—	—	—	—	—	—
2007	27	MLB MLE	Colorado Rockies	—	713	641	216	50	6	36	56	126	10	11	4	337	398	602	1.000	265	377	18	8	431	178	—	—	—	—	—	—
2008	28	MLB MLE	Colorado Rockies	—	623	542	173	38	2	25	68	104	8	28	2	319	401	535	936	216	359	17	11	409	163	—	—	—	—	—	—
2009	29	MLB MLE	St. Louis Cardinals	—	670	591	182	39	3	24	64	101	10	14	7	308	386	506	892	198	341	15	10	391	151	—	—	—	—	—	—
2010	30	MLB MLE	St. Louis Cardinals	—	675	603	186	43	1	30	59	93	8	9	5	308	376	532	908	224	331	14	9	399	156	—	—	—	—	—	—
2011	31	MLB MLE	St. Louis Cardinals	—	516	447	132	34	0	24	56	93	8	2	1	295	381	532	914	237	330	18	11	400	157	—	—	—	—	—	—
2012	32	MLB MLE	St. Louis Cardinals	—	688	602	177	34	2	29	72	132	9	4	4	294	378	502	879	208	337	19	10	389	149	—	—	—	—	—	—
2013	33	MLB MLE	St. Louis Cardinals	—	602	524	157	30	1	24	64	86	9	6	1	300	385	498	883	198	322	14	11	388	149	—	—	—	—	—	—
2014	34	MLB MLE	St. Louis Cardinals	—	667	575	156	35	0	22	70	100	17	4	1	271	365	447	812	176	298	15	10	363	132	—	—	—	—	—	—
2015	35	MLB MLE	St. Louis Cardinals	—	277	235	63	15	1	4	34	49	6	2	1	268	376	391	767	123	335	18	12	353	125	—	—	—	—	—	—
2016	36	MLB MLE	St. Louis Cardinals	—	426	381	95	19	1	22	34	71	8	0	0	249	322	478	800	228	253	17	8	350	123	—	—	—	—	—	—
2017	37	MLB MLE	3 teams	—	478	421	95	19	0	18	50	124	4	1	0	226	316	399	715	173	271	26	10	316	100	—	—	—	—	—	—
2018	38	MLB MLE	2 teams	—	127	108	29	5	0	4	17	30	1	0	0	269	370	426	796	157	346	24	13	355	126	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	7981	7009	2096	468	32	316	802	1362	124	108	37	299	381	510	891	211	331	17	10	391	148	+481	+7	-87	-90	+173	49.3
/ 162G	—	A+C		—	650	571	171	38	3	26	65	111	10	9	3	299	381	513	894	214	331	17	10	391	148	+39	+1	-7	-7	+14	4.0
Career	—	MLE		—	8122	7193	2133	464	32	330	755	1388	126	109	37	297	373	508	881	211	327	17	9	387	148	+481	+7	-87	-90	+173	49.3
/ 162G	—	MLE		—	650	576	171	37	3	26	60	111	10	9	3	297	373	507	880	210	327	17	9	387	148	+39	+1	-7	-7	+14	4.0

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 AAAAlbuquerque Isotopes · 62 PAwOBA .441 → .333 (−109)K% 14.5% → 19.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.52%	÷0.978	×1.290	—	—	19.16%
BB% (unintentional) /PA	12.90%	÷1.024	×0.710	—	×0.940	8.41%
HBP% /PA	1.61%	—	×0.980	—	×0.940	1.49%
Singles /BIP	25.58%	÷1.034	×0.900	—	×0.940	20.93%
Doubles /BIP	9.30%	÷0.960	×0.810	—	×0.940	7.38%
Triples /BIP	0.00%	÷0.973	×0.810	—	×0.940	0.00%
Home runs /BIP	6.98%	÷1.162	×0.780	—	×0.940	4.40%

Factors used: league row PCL. Park (home-season share, regressed): HR 132, 1B 107, 2B 92, 3B 95, K 96, BB 105 — applied at half strength. Age: age 38 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (10.8 yr older than average).

Result: wOBA .441 → .333; ISO .250 → .174; BABIP .375 → .296. 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 A+Tampa Yankees · 30 PAwOBA .291 → .229 (−61)K% 16.7% → 24.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.67%	÷0.949	×1.420	—	—	24.94%
BB% (unintentional) /PA	10.00%	÷1.007	×0.750	—	×0.940	7.00%
HBP% /PA	3.33%	—	×0.930	—	×0.940	2.91%
Singles /BIP	25.00%	÷1.071	×0.920	—	×0.940	20.18%
Doubles /BIP	5.00%	÷0.995	×0.960	—	×0.940	4.54%
Triples /BIP	0.00%	÷1.031	×0.810	—	×0.940	0.00%
Home runs /BIP	0.00%	÷0.949	×0.880	—	×0.940	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 90, 1B 114, 2B 99, 3B 106, K 90, BB 101 — applied at half strength. Age: age 37 vs a level average of 22.8 → −6.0% on BB/HBP/hit rates (14.2 yr older than average).

Result: wOBA .291 → .229; ISO .040 → .035; BABIP .286 → .235. 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 AAAScranton/Wilkes-Barre RailRiders · 21 PAwOBA .308 → .254 (−54)K% 9.5% → 11.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.52%	÷0.995	×1.200	—	—	11.49%
BB% (unintentional) /PA	14.29%	÷1.105	×0.690	—	×0.940	8.39%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	31.25%	÷0.980	×0.930	—	×0.940	27.88%
Doubles /BIP	0.00%	÷0.951	×0.830	—	×0.940	0.00%
Triples /BIP	0.00%	÷1.150	×0.970	—	×0.940	0.00%
Home runs /BIP	0.00%	÷1.247	×0.840	—	×0.940	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 149, 1B 96, 2B 90, 3B 130, K 99, BB 121 — applied at half strength. Age: age 37 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (9.8 yr older than average).

Result: wOBA .308 → .254; ISO .000 → .000; BABIP .312 → .279. 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 AATulsa Drillers · 28 PAwOBA .564 → .506 (−58)K% 10.7% → 13.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.71%	÷1.000	×1.220	—	—	13.07%
BB% (unintentional) /PA	3.57%	÷1.000	×0.700	—	×0.998	2.49%
HBP% /PA	0.00%	—	×0.870	—	×0.998	0.00%
Singles /BIP	43.48%	÷1.000	×0.920	—	×0.998	39.92%
Doubles /BIP	13.04%	÷1.000	×0.840	—	×0.998	10.93%
Triples /BIP	0.00%	÷1.000	×0.940	—	×0.998	0.00%
Home runs /BIP	4.35%	÷1.000	×0.800	—	×0.998	3.47%

Factors used: league row TL. 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 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average).

Result: wOBA .564 → .506; ISO .231 → .194; BABIP .565 → .505. 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).