Adam Lind

Pos1B

B/TL/L

Born1983-07-17

Age (2027)44

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2018

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2016	33	MLBSEA	430	.239/.287/.431	20	0	99	-0.4
2017	34	MLBWSH	301	.303/.369/.513	14	1	135	0.8
2018	35	AAA/A+2 orgs	283	.245/.305/.424	11	0	42	—	.191/.225/.307
2019	36	No MLB games played
2020	37	No MLB games played
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 0.3

Contract

No contract data on file.

Skills · percentileStatcast 2015-2017

xwOBA74

Avg EV68

Barrel%48

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	A+	Dunedin Blue Jays	—	555	497	156	43	4	12	48	76	4	2	1	314	379	489	868	175	347	14	9	380	107	—	—	—	—	—	—
2006	23	MLB	Toronto Blue Jays	—	65	60	22	8	0	2	5	12	0	0	0	367	415	600	1.015	233	435	18	8	443	186	+7	+0	-0	-6	+1	0.2
2006	23	AAA	Syracuse SkyChiefs	—	137	109	43	7	0	5	23	18	2	1	0	394	507	596	1.104	202	427	13	17	474	181	—	—	—	—	—	—
2006	23	AA	New Hampshire Fisher Cats	—	378	348	108	24	0	19	25	87	2	2	1	310	360	543	903	233	363	23	7	392	116	—	—	—	—	—	—
2007	24	MLB	Toronto Blue Jays	—	311	290	69	14	0	11	16	65	1	1	2	238	280	400	680	162	269	21	5	298	88	-5	-1	+3	-5	+7	-0.1
2007	24	AAA	Syracuse Chiefs	—	190	174	52	8	2	6	14	42	1	0	0	299	354	471	826	172	362	22	7	364	106	—	—	—	—	—	—
2008	25	MLB	Toronto Blue Jays	—	349	326	92	16	4	9	16	59	2	2	0	282	320	439	758	156	317	17	5	331	106	+2	+0	-10	-6	+8	-0.5
2008	25	AAA	Syracuse Chiefs	—	213	189	62	17	2	6	19	36	3	1	1	328	398	534	932	206	376	17	9	406	126	—	—	—	—	—	—
2009	26	MLB	Toronto Blue Jays	—	654	587	179	46	0	35	58	110	5	1	1	305	372	562	934	257	323	17	9	405	155	+43	-0	-12	-7	+14	3.8
2010	27	MLB	Toronto Blue Jays	—	613	569	135	32	3	23	38	144	3	0	0	237	289	425	714	188	277	23	6	314	96	-3	+0	-4	-7	+13	-0.1
2011	28	MLB	Toronto Blue Jays	—	542	499	125	16	0	26	32	107	3	1	1	251	300	439	739	188	265	20	6	322	100	-0	-0	-10	-10	+12	-0.9
2012	29	MLB	Toronto Blue Jays	—	353	321	82	14	2	11	29	61	0	0	0	255	317	414	731	159	282	17	8	323	103	+1	+0	-4	-9	+8	-0.4
2012	29	AAA	Las Vegas 51s	—	143	125	49	10	0	8	15	26	0	1	0	392	457	664	1.121	272	436	18	10	476	148	—	—	—	—	—	—
2013	30	MLB	Toronto Blue Jays	—	521	465	134	26	1	23	51	103	1	1	0	288	360	497	857	209	324	20	10	375	135	+22	+0	-8	-9	+11	1.6
2014	31	MLB	Toronto Blue Jays	—	318	290	93	24	2	6	28	48	0	0	0	321	381	479	860	159	369	15	9	381	139	+15	+0	-6	-6	+7	1.0
2014	31	A+	Dunedin Blue Jays	—	16	14	4	2	0	0	2	3	0	0	0	286	375	429	804	143	364	19	12	361	73	—	—	—	—	—	—
2015	32	MLB	Milwaukee Brewers	—	572	502	139	32	0	20	66	100	1	0	0	277	362	460	822	183	309	17	12	364	125	+17	+0	-9	-10	+12	1.0
2016	33	MLB	Seattle Mariners	—	430	401	96	17	0	20	26	89	1	0	1	239	287	431	719	192	259	21	6	316	99	-0	-0	-5	-8	+9	-0.4
2017	34	MLB	Washington Nationals	—	301	267	81	14	0	14	28	47	0	1	0	303	369	513	883	210	316	16	9	381	135	+13	+0	-7	-5	+7	0.8
2018	35	AAA	Pawtucket Red Sox	—	252	229	51	11	0	10	19	49	0	0	1	223	282	402	684	179	236	19	8	299	29	—	—	—	—	—	—
2018	35	A+	Tampa Tarpons	—	31	28	12	2	0	1	3	4	0	0	0	429	484	607	1.091	179	478	13	10	480	145	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	5029	4577	1247	259	12	200	393	945	17	7	5	272	332	465	798	193	302	19	8	349	123	+135	-1	-72	-88	+109	8.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	22	A+ MLE	Dunedin Blue Jays	—	555	514	140	40	3	10	31	108	4	2	1	272	319	420	739	148	321	19	6	327	107	—	—	—	—	—	—
2006	23	MLB MLE	Toronto Blue Jays	—	65	60	22	8	0	2	5	12	0	0	0	367	415	600	1.015	233	435	18	8	443	186	+7	+0	-0	-6	+1	0.2
2006	23	AAA MLE	Syracuse SkyChiefs	—	137	119	43	6	0	5	13	22	2	1	0	361	433	538	971	176	388	16	9	435	181	—	—	—	—	—	—
2006	23	AA MLE	New Hampshire Fisher Cats	—	378	356	103	22	0	15	17	106	2	2	1	289	325	478	803	188	361	28	4	340	116	—	—	—	—	—	—
2007	24	MLB MLE	Toronto Blue Jays	—	311	290	69	14	0	11	16	65	1	1	2	238	280	400	680	162	269	21	5	298	88	-5	-1	+3	-5	+7	-0.1
2007	24	AAA MLE	Syracuse Chiefs	—	190	180	50	7	2	5	8	50	1	0	0	278	312	422	734	144	357	26	4	325	106	—	—	—	—	—	—
2008	25	MLB MLE	Toronto Blue Jays	—	349	329	92	16	4	9	13	59	2	2	0	280	311	435	746	155	317	17	4	325	106	+2	+0	-10	-6	+8	-0.5
2008	25	AAA MLE	Syracuse Chiefs	—	213	196	58	15	2	5	12	43	3	1	1	296	346	469	815	173	349	20	6	355	126	—	—	—	—	—	—
2009	26	MLB MLE	Toronto Blue Jays	—	654	594	179	46	0	35	51	110	5	1	1	301	362	556	917	254	323	17	8	397	155	+43	-0	-12	-7	+14	3.8
2010	27	MLB MLE	Toronto Blue Jays	—	613	572	135	32	3	23	35	144	3	0	0	236	284	423	707	187	277	23	6	310	96	-3	+0	-4	-7	+13	-0.1
2011	28	MLB MLE	Toronto Blue Jays	—	542	503	125	16	0	26	28	107	3	1	1	249	292	435	728	187	265	20	5	316	100	-0	-0	-10	-10	+12	-0.9
2012	29	MLB MLE	Toronto Blue Jays	—	353	322	82	14	2	11	28	61	0	0	0	255	314	413	727	158	282	17	8	320	103	+1	+0	-4	-9	+8	-0.4
2012	29	AAA MLE	Las Vegas 51s	—	143	129	43	8	0	6	11	33	0	1	0	333	386	535	921	202	384	23	8	387	148	—	—	—	—	—	—
2013	30	MLB MLE	Toronto Blue Jays	—	521	470	134	26	1	23	46	103	1	1	0	285	350	491	842	206	324	20	9	367	135	+22	+0	-8	-9	+11	1.6
2014	31	MLB MLE	Toronto Blue Jays	—	318	293	93	24	2	6	25	48	0	0	0	317	371	474	845	157	369	15	8	374	139	+15	+0	-6	-6	+7	1.0
2014	31	A+ MLE	Dunedin Blue Jays	—	16	15	4	2	0	0	1	4	0	0	0	267	312	400	713	133	312	25	6	276	73	—	—	—	—	—	—
2015	32	MLB MLE	Milwaukee Brewers	—	572	513	140	34	0	19	55	100	1	0	0	273	344	450	795	177	309	17	10	353	125	+17	+0	-9	-10	+12	1.0
2016	33	MLB MLE	Seattle Mariners	—	430	404	97	17	0	21	23	89	1	0	1	240	283	438	721	198	259	21	5	315	99	-0	-0	-5	-8	+9	-0.4
2017	34	MLB MLE	Washington Nationals	—	301	272	81	14	0	14	23	47	0	1	0	298	353	504	856	206	316	16	8	368	135	+13	+0	-7	-5	+7	0.8
2018	35	AAA MLE	Pawtucket Red Sox	—	252	238	40	8	0	6	10	59	0	0	1	168	202	277	479	109	189	23	4	211	29	—	—	—	—	—	—
2018	35	A+ MLE	Tampa Tarpons	—	31	29	11	2	0	1	2	6	0	0	0	379	419	552	971	172	420	19	6	382	145	—	—	—	—	—	—
2005	22	A+ MLE	Dunedin Blue Jays	—	555	514	140	40	3	10	31	108	4	2	1	272	319	420	739	148	323	19	6	327	107	—	—	—	—	—	—
2005	22	A+ RAW	Dunedin Blue Jays	—	555	497	156	43	4	12	48	76	4	2	1	314	379	489	868	175	347	14	9	380	107	—	—	—	—	—	—
2006	23	AA MLE	3 teams	—	580	535	167	36	0	22	35	140	4	3	1	312	359	503	862	191	383	24	6	374	139	—	—	—	—	—	—
2006	23	AA RAW	3 teams	—	580	517	173	39	0	26	53	117	4	3	1	335	401	561	962	226	387	20	9	417	139	—	—	—	—	—	—
2007	24	MLB MLE	2 teams	—	501	470	119	21	2	16	24	115	2	1	2	253	292	409	701	155	301	23	5	308	95	-3	-1	+3	-5	+11	0.5
2007	24	MLB RAW	2 teams	—	501	464	121	22	2	17	30	107	2	1	2	261	308	427	735	166	303	21	6	323	95	-3	-1	+3	-5	+11	0.5
2008	25	MLB MLE	2 teams	—	562	525	150	31	6	14	25	102	5	3	1	286	324	448	772	162	328	18	4	336	114	+9	+0	-10	-6	+12	0.6
2008	25	MLB RAW	2 teams	—	562	515	154	33	6	15	35	95	5	3	1	299	350	474	823	175	338	17	6	359	114	+9	+0	-10	-6	+12	0.6
2009	26	MLB MLE	Toronto Blue Jays	—	654	594	179	46	0	35	51	110	5	1	1	301	362	556	917	254	318	17	8	397	155	+43	-0	-12	-7	+14	3.8
2009	26	MLB RAW	Toronto Blue Jays	—	654	587	179	46	0	35	58	110	5	1	1	305	372	562	934	257	323	17	9	405	155	+43	-0	-12	-7	+14	3.8
2010	27	MLB MLE	Toronto Blue Jays	—	613	572	135	32	3	23	35	144	3	0	0	236	284	423	707	187	275	23	6	310	96	-3	+0	-4	-7	+13	-0.1
2010	27	MLB RAW	Toronto Blue Jays	—	613	569	135	32	3	23	38	144	3	0	0	237	289	425	714	188	277	23	6	314	96	-3	+0	-4	-7	+13	-0.1
2011	28	MLB MLE	Toronto Blue Jays	—	542	503	125	16	0	26	28	107	3	1	1	249	292	435	728	187	262	20	5	316	100	-0	-0	-10	-10	+12	-0.9
2011	28	MLB RAW	Toronto Blue Jays	—	542	499	125	16	0	26	32	107	3	1	1	251	300	439	739	188	265	20	6	322	100	-0	-0	-10	-10	+12	-0.9
2012	29	MLB MLE	2 teams	—	496	451	125	22	2	17	39	94	0	1	0	277	335	448	783	171	312	19	8	340	116	+9	+0	-4	-9	+11	0.8
2012	29	MLB RAW	2 teams	—	496	446	131	24	2	19	44	87	0	1	0	294	357	484	841	191	324	18	9	367	116	+9	+0	-4	-9	+11	0.8
2013	30	MLB MLE	Toronto Blue Jays	—	521	470	134	26	1	23	46	103	1	1	0	285	350	491	842	206	319	20	9	367	135	+22	+0	-8	-9	+11	1.6
2013	30	MLB RAW	Toronto Blue Jays	—	521	465	134	26	1	23	51	103	1	1	0	288	360	497	857	209	324	20	10	375	135	+22	+0	-8	-9	+11	1.6
2014	31	MLB MLE	2 teams	—	334	308	96	26	2	6	26	52	0	0	0	312	365	468	833	156	360	16	8	369	136	+14	+0	-6	-6	+7	1.0
2014	31	MLB RAW	2 teams	—	334	304	97	26	2	6	30	51	0	0	0	319	380	477	857	158	368	15	9	380	136	+14	+0	-6	-6	+7	1.0
2015	32	MLB MLE	Milwaukee Brewers	—	572	513	140	34	0	19	55	100	1	0	0	273	344	450	795	177	305	17	10	353	125	+17	+0	-9	-10	+12	1.0
2015	32	MLB RAW	Milwaukee Brewers	—	572	502	139	32	0	20	66	100	1	0	0	277	362	460	822	183	309	17	12	364	125	+17	+0	-9	-10	+12	1.0
2016	33	MLB MLE	Seattle Mariners	—	430	404	97	17	0	21	23	89	1	0	1	240	283	438	721	198	257	21	5	315	99	-0	-0	-5	-8	+9	-0.4
2016	33	MLB RAW	Seattle Mariners	—	430	401	96	17	0	20	26	89	1	0	1	239	287	431	719	192	259	21	6	316	99	-0	-0	-5	-8	+9	-0.4
2017	34	MLB MLE	Washington Nationals	—	301	272	81	14	0	14	23	47	0	1	0	298	353	504	856	206	309	16	8	368	135	+13	+0	-7	-5	+7	0.8
2017	34	MLB RAW	Washington Nationals	—	301	267	81	14	0	14	28	47	0	1	0	303	369	513	883	210	316	16	9	381	135	+13	+0	-7	-5	+7	0.8
2018	35	AAA MLE	2 teams	—	283	267	51	10	0	7	12	65	0	0	1	191	226	307	533	116	221	23	4	230	42	—	—	—	—	—	—
2018	35	AAA RAW	2 teams	—	283	257	63	13	0	11	22	53	0	0	1	245	305	424	729	179	264	19	8	319	42	—	—	—	—	—	—
2005	22	A+ MLE	Dunedin Blue Jays	—	555	515	140	40	3	10	31	108	4	2	1	272	319	419	738	148	321	19	6	327	107	—	—	—	—	—	—
2006	23	AA MLE	3 teams	—	580	536	167	36	0	22	35	140	4	3	1	312	359	502	861	190	376	24	6	374	139	—	—	—	—	—	—
2007	24	MLB MLE	2 teams	—	501	470	119	21	2	16	24	115	2	1	2	253	292	409	701	155	302	23	5	308	95	—	—	—	—	—	—
2008	25	MLB MLE	2 teams	—	562	527	150	31	6	14	25	102	5	3	1	285	324	446	770	161	329	18	4	336	114	—	—	—	—	—	—
2009	26	MLB MLE	Toronto Blue Jays	—	654	593	179	46	0	35	51	110	5	1	1	302	362	556	918	255	323	17	8	397	155	—	—	—	—	—	—
2010	27	MLB MLE	Toronto Blue Jays	—	613	570	135	32	3	23	35	144	3	0	0	237	284	425	708	188	277	23	6	310	96	—	—	—	—	—	—
2011	28	MLB MLE	Toronto Blue Jays	—	542	506	125	16	0	26	28	107	3	1	1	247	292	433	725	186	265	20	5	316	100	—	—	—	—	—	—
2012	29	MLB MLE	2 teams	—	496	454	125	22	2	17	39	94	0	1	0	275	335	445	780	170	311	19	8	340	116	—	—	—	—	—	—
2013	30	MLB MLE	Toronto Blue Jays	—	521	469	134	26	1	23	46	103	1	1	0	286	350	493	843	207	324	20	9	367	135	—	—	—	—	—	—
2014	31	MLB MLE	2 teams	—	334	305	96	26	2	6	26	52	0	0	0	315	365	472	837	157	366	16	8	369	136	—	—	—	—	—	—
2015	32	MLB MLE	Milwaukee Brewers	—	572	511	140	34	0	19	55	100	1	0	0	274	344	452	797	178	309	17	10	353	125	—	—	—	—	—	—
2016	33	MLB MLE	Seattle Mariners	—	430	403	97	17	0	21	23	89	1	0	1	241	283	439	722	199	259	21	5	315	99	—	—	—	—	—	—
2017	34	MLB MLE	Washington Nationals	—	301	275	81	14	0	14	23	47	0	1	0	295	353	498	851	204	316	16	8	368	135	—	—	—	—	—	—
2018	35	AAA MLE	2 teams	—	283	269	51	10	0	7	12	65	0	0	1	190	226	305	531	115	214	23	4	230	42	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	5029	4577	1247	259	12	200	393	945	17	7	5	272	332	465	798	193	302	19	8	349	116	+135	-1	-72	-88	+109	8.5
/ 162G	—	A+C		—	650	592	161	33	2	26	51	122	2	1	1	272	332	466	798	194	301	19	8	349	116	+17	-0	-9	-11	+14	1.1
Career	—	MLE		—	6944	6398	1739	371	19	253	453	1376	29	14	9	272	323	454	777	183	308	20	7	340	116	+135	-1	-72	-88	+109	8.5
/ 162G	—	MLE		—	650	599	164	35	2	24	42	129	3	1	1	274	325	459	784	185	310	20	6	340	116	+17	-0	-9	-11	+14	1.1

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.

2018 AAAPawtucket Red Sox · 252 PAwOBA .292 → .211 (−81)K% 19.4% → 23.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.44%	÷0.994	×1.200	—	—	23.47%
BB% (unintentional) /PA	6.75%	÷1.082	×0.690	—	×0.940	4.04%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	16.67%	÷1.000	×0.930	×0.981	×0.940	14.30%
Doubles /BIP	6.11%	÷1.067	×0.830	×0.981	×0.940	4.38%
Triples /BIP	0.00%	÷0.900	×0.970	×0.981	×0.940	0.00%
Home runs /BIP	5.56%	÷1.342	×0.840	—	×0.940	3.27%

Factors used: league row IL. Park (home-season share, regressed): HR 168, 1B 100, 2B 113, 3B 80, K 99, BB 116 — applied at half strength. Age: age 35 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (7.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.981.

Result: wOBA .292 → .211; ISO .179 → .113; BABIP .236 → .189. 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 A+Tampa Tarpons · 31 PAwOBA .467 → .382 (−85)K% 12.9% → 18.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.90%	÷1.004	×1.420	—	—	18.24%
BB% (unintentional) /PA	9.68%	÷1.015	×0.750	—	×0.940	6.72%
HBP% /PA	0.00%	—	×0.930	—	×0.940	0.00%
Singles /BIP	37.50%	÷1.003	×0.920	—	×0.940	32.34%
Doubles /BIP	8.33%	÷0.891	×0.960	—	×0.940	8.44%
Triples /BIP	0.00%	÷0.983	×0.810	—	×0.940	0.00%
Home runs /BIP	4.17%	÷1.205	×0.880	—	×0.940	2.86%

Factors used: league row FSL. Park (home-season share, regressed): HR 141, 1B 101, 2B 78, 3B 97, K 101, BB 103 — applied at half strength. Age: age 35 vs a level average of 22.8 → −6.0% on BB/HBP/hit rates (12.2 yr older than average).

Result: wOBA .467 → .382; ISO .179 → .141; BABIP .478 → .420. 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 A+Dunedin Blue Jays · 16 PAwOBA .352 → .276 (−76)K% 18.8% → 26.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.75%	÷1.016	×1.420	—	—	26.20%
BB% (unintentional) /PA	12.50%	÷0.979	×0.750	—	×0.940	9.00%
HBP% /PA	0.00%	—	×0.930	—	×0.940	0.00%
Singles /BIP	18.18%	÷0.982	×0.920	—	×0.940	16.01%
Doubles /BIP	18.18%	÷1.083	×0.960	—	×0.940	15.15%
Triples /BIP	0.00%	÷0.900	×0.810	—	×0.940	0.00%
Home runs /BIP	0.00%	÷1.309	×0.880	—	×0.940	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 162, 1B 96, 2B 117, 3B 80, K 103, BB 96 — applied at half strength. Age: age 31 vs a level average of 22.8 → −6.0% on BB/HBP/hit rates (8.2 yr older than average).

Result: wOBA .352 → .276; ISO .143 → .112; BABIP .364 → .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).

2012 AAALas Vegas 51s · 143 PAwOBA .472 → .387 (−85)K% 18.2% → 23.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.18%	÷1.004	×1.290	—	—	23.35%
BB% (unintentional) /PA	10.49%	÷0.985	×0.710	—	×0.982	7.43%
HBP% /PA	0.00%	—	×0.980	—	×0.982	0.00%
Singles /BIP	31.31%	÷0.985	×0.900	×1.050	×0.982	29.50%
Doubles /BIP	10.10%	÷1.085	×0.810	×1.050	×0.982	7.78%
Triples /BIP	0.00%	÷0.994	×0.810	×1.050	×0.982	0.00%
Home runs /BIP	8.08%	÷1.059	×0.780	—	×0.982	5.85%

Factors used: league row PCL. Park (home-season share, regressed): HR 112, 1B 97, 2B 117, 3B 99, K 101, BB 97 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .472 → .387; ISO .272 → .200; BABIP .436 → .384. 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).

2008 AAASyracuse Chiefs · 213 PAwOBA .396 → .355 (−41)K% 16.9% → 20.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.90%	÷1.000	×1.200	—	—	20.28%
BB% (unintentional) /PA	7.98%	÷1.000	×0.690	—	×1.033	5.69%
HBP% /PA	1.41%	—	×0.940	—	×1.033	1.37%
Singles /BIP	24.18%	÷1.000	×0.930	×1.001	×1.033	23.27%
Doubles /BIP	11.11%	÷1.000	×0.830	×1.001	×1.033	9.54%
Triples /BIP	1.31%	÷1.000	×0.970	×1.001	×1.033	1.31%
Home runs /BIP	3.92%	÷1.000	×0.840	—	×1.033	3.40%

Factors used: league row IL. 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 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 .396 → .355; ISO .206 → .183; BABIP .376 → .349. 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 AAASyracuse Chiefs · 190 PAwOBA .350 → .325 (−25)K% 22.1% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.11%	÷1.000	×1.200	—	—	26.53%
BB% (unintentional) /PA	5.79%	÷1.000	×0.690	—	×1.048	4.19%
HBP% /PA	0.53%	—	×0.940	—	×1.048	0.52%
Singles /BIP	27.27%	÷1.000	×0.930	×1.034	×1.048	27.50%
Doubles /BIP	6.06%	÷1.000	×0.830	×1.034	×1.048	5.45%
Triples /BIP	1.52%	÷1.000	×0.970	×1.034	×1.048	1.59%
Home runs /BIP	4.55%	÷1.000	×0.840	—	×1.048	4.00%

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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.034.

Result: wOBA .350 → .325; ISO .172 → .155; BABIP .362 → .357. 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 AANew Hampshire Fisher Cats · 378 PAwOBA .382 → .340 (−42)K% 23.0% → 28.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.02%	÷1.000	×1.220	—	—	28.08%
BB% (unintentional) /PA	6.08%	÷1.000	×0.700	—	×1.027	4.37%
HBP% /PA	0.53%	—	×0.850	—	×1.027	0.46%
Singles /BIP	24.90%	÷1.000	×0.970	×1.044	×1.027	25.90%
Doubles /BIP	9.20%	÷1.000	×0.860	×1.044	×1.027	8.48%
Triples /BIP	0.00%	÷1.000	×0.950	×1.044	×1.027	0.00%
Home runs /BIP	7.28%	÷1.000	×0.780	—	×1.027	5.83%

Factors used: league row EL. 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 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 ×1.044.

Result: wOBA .382 → .340; ISO .233 → .189; BABIP .363 → .361. 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 AAASyracuse SkyChiefs · 137 PAwOBA .464 → .435 (−29)K% 13.1% → 15.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.14%	÷1.000	×1.200	—	—	15.77%
BB% (unintentional) /PA	13.14%	÷1.000	×0.690	—	×1.050	9.52%
HBP% /PA	1.46%	—	×0.940	—	×1.050	1.44%
Singles /BIP	34.07%	÷1.000	×0.930	×0.952	×1.050	31.66%
Doubles /BIP	7.69%	÷1.000	×0.830	×0.952	×1.050	6.38%
Triples /BIP	0.00%	÷1.000	×0.970	×0.952	×1.050	0.00%
Home runs /BIP	5.49%	÷1.000	×0.840	—	×1.050	4.85%

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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.952.

Result: wOBA .464 → .435; ISO .202 → .193; BABIP .427 → .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).