Dee Strange-Gordon

Pos2B

B/TL/R

Born1988-04-22

Age (2027)39

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2022

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2020	32	MLBSEA	82	.200/.268/.213	0	3	43	-0.8
2021	33	AAAPIT	244	.248/.288/.370	5	6	38	—	.205/.235/.291
2022	34	MLBWSH	59	.305/.305/.356	0	3	89	-0.3
2023	35	No MLB games played
2024	36	No MLB games played
2025	37	No MLB games played
2026	38	No MLB games played

Last 3 seasons WAR -1.1

Contract

No contract data on file.

Skills · percentileStatcast 2019-2022

Speed73

xwOBA10

Avg EV10

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)
2008	20	ROK	Ogden Raptors	—	274	251	83	13	3	2	16	29	2	18	5	331	375	430	806	100	363	11	6	355	73	—	—	—	—	—	—
2009	21	A	Great Lakes Loons	—	601	538	162	17	12	3	43	90	10	73	25	301	364	394	758	93	355	15	7	337	86	—	—	—	—	—	—
2010	22	AA	Chattanooga Lookouts	—	614	555	154	17	10	2	40	89	7	53	20	277	334	355	689	77	325	14	7	307	78	—	—	—	—	—	—
2010	22	INTL	Gigantes de Carolina	—	158	144	52	4	6	1	5	15	4	8	7	361	399	493	892	132	395	9	3	383	145	—	—	—	—	—	—
2011	23	MLB	Los Angeles Dodgers	—	233	224	68	9	2	0	7	27	0	24	7	304	325	362	686	58	345	12	3	306	99	-0	+2	-4	+6	+5	0.9
2011	23	AAA	Albuquerque Isotopes	—	313	288	96	10	6	0	18	40	2	30	4	333	377	410	786	76	382	13	6	348	84	—	—	—	—	—	—
2012	24	MLB	Los Angeles Dodgers	—	330	303	69	9	2	1	20	62	3	32	10	228	282	281	563	53	281	19	6	256	64	-14	+2	-8	+5	+7	-0.8
2012	24	AAA	Albuquerque Isotopes	—	32	30	8	0	1	0	2	3	0	2	1	267	312	333	646	67	296	9	6	292	51	—	—	—	—	—	—
2012	24	INTL	Tigres del Licey	—	123	108	29	3	6	0	11	22	3	9	6	269	352	407	760	139	333	18	9	338	115	—	—	—	—	—	—
2013	25	MLB	Los Angeles Dodgers	—	106	94	22	1	1	1	10	21	1	10	2	234	314	298	612	64	292	20	9	282	73	-3	+1	-3	+7	+2	0.4
2013	25	AAA	Albuquerque Isotopes	—	433	374	111	17	9	0	51	70	3	49	11	297	386	390	776	94	364	16	12	349	80	—	—	—	—	—	—
2013	25	INTL	Indios de Mayaguez	—	69	63	24	1	0	0	5	12	0	4	4	381	426	397	823	16	471	17	7	371	137	—	—	—	—	—	—
2014	26	MLB	Los Angeles Dodgers	—	650	609	176	24	12	2	31	107	4	64	19	289	328	378	705	89	346	16	5	314	106	+5	+5	+1	+2	+14	2.8
2015	27	MLB	Miami Marlins	—	653	615	205	24	8	4	25	91	2	58	20	333	361	418	779	85	383	14	4	343	124	+18	+4	+8	+2	+14	4.8
2016	28	MLB	Miami Marlins	—	346	325	87	7	6	1	18	55	0	30	7	268	305	335	641	68	319	16	5	287	84	-6	+3	+1	+1	+7	0.7
2016	28	AAA	New Orleans Zephyrs	—	36	35	9	1	1	0	1	5	0	3	0	257	278	343	621	86	300	14	3	276	33	—	—	—	—	—	—
2017	29	MLB	Miami Marlins	—	695	653	201	20	9	2	25	93	10	60	16	308	343	375	718	67	354	13	4	321	109	+8	+6	-2	+2	+15	3.0
2018	30	MLB	Seattle Mariners	—	588	556	149	17	8	4	9	80	9	30	12	268	291	349	640	81	304	14	2	280	77	-16	+1	-6	+2	+13	-0.6
2019	31	MLB	Seattle Mariners	—	421	393	108	12	6	3	18	61	1	22	5	275	308	359	667	84	313	14	4	293	85	-8	+2	-1	+2	+9	0.4
2020	32	MLB	Seattle Mariners	—	82	75	15	1	0	0	5	13	2	3	2	200	268	213	482	13	242	16	6	231	43	-6	-0	-3	-1	+2	-0.8
2021	33	AAA	Indianapolis Indians	—	244	230	57	11	1	5	11	35	2	6	1	248	288	370	658	122	274	14	5	293	38	—	—	—	—	—	—
2022	34	MLB	Washington Nationals	—	59	59	18	1	1	0	0	8	0	3	2	305	305	356	661	51	353	14	0	295	89	-1	-0	-5	+1	+1	-0.3
2022	34	AAA	Rochester Red Wings	—	24	21	4	1	0	0	3	1	0	0	0	190	292	238	530	48	200	4	12	254	23	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4163	3906	1118	125	55	18	168	618	32	336	102	286	321	360	681	74	334	15	4	303	91	-45	+26	-21	+30	+90	8.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2008	20	ROK MLE	Ogden Raptors	—	274	257	68	10	2	1	10	42	2	18	5	265	297	331	628	66	301	15	4	276	73	—	—	—	—	—	—
2009	21	A MLE	Great Lakes Loons	—	601	554	153	15	11	2	27	123	10	73	25	276	321	354	675	78	340	20	4	295	86	—	—	—	—	—	—
2010	22	AA MLE	Chattanooga Lookouts	—	614	569	156	17	9	2	26	108	7	53	20	274	314	346	660	72	323	18	4	284	78	—	—	—	—	—	—
2011	23	MLB MLE	Los Angeles Dodgers	—	233	224	70	10	2	0	7	27	0	24	7	312	333	375	708	62	345	12	3	315	99	-0	+2	-4	+6	+5	0.9
2011	23	AAA MLE	Albuquerque Isotopes	—	313	293	85	9	5	0	13	56	2	30	4	290	325	355	680	65	342	18	4	293	84	—	—	—	—	—	—
2012	24	MLB MLE	Los Angeles Dodgers	—	330	303	71	10	2	1	20	62	3	32	10	234	288	290	579	56	281	19	6	263	64	-14	+2	-8	+5	+7	-0.8
2012	24	AAA MLE	Albuquerque Isotopes	—	32	30	7	0	1	0	2	4	0	2	1	233	281	300	581	67	266	12	6	243	51	—	—	—	—	—	—
2013	25	MLB MLE	Los Angeles Dodgers	—	106	96	22	1	1	1	8	21	1	10	2	229	295	292	587	63	292	20	8	276	73	-3	+1	-3	+7	+2	0.4
2013	25	AAA MLE	Albuquerque Isotopes	—	433	391	100	14	7	0	34	96	3	49	11	256	320	327	647	72	332	22	8	286	80	—	—	—	—	—	—
2014	26	MLB MLE	Los Angeles Dodgers	—	650	609	180	25	14	2	31	107	4	64	19	296	334	392	726	97	346	16	5	325	106	+5	+5	+1	+2	+14	2.8
2015	27	MLB MLE	Miami Marlins	—	653	617	211	26	9	4	23	91	2	58	20	342	368	433	800	91	383	14	4	351	124	+18	+4	+8	+2	+14	4.8
2016	28	MLB MLE	Miami Marlins	—	346	327	89	8	6	1	17	55	0	30	7	272	308	343	651	70	319	16	5	293	84	-6	+3	+1	+1	+7	0.7
2016	28	AAA MLE	New Orleans Zephyrs	—	36	35	8	1	1	0	1	6	0	3	0	229	250	314	564	86	254	17	3	217	33	—	—	—	—	—	—
2017	29	MLB MLE	Miami Marlins	—	695	654	207	22	10	2	25	93	10	60	16	317	351	390	741	73	354	13	4	330	109	+8	+6	-2	+2	+15	3.0
2018	30	MLB MLE	Seattle Mariners	—	588	556	150	17	8	4	9	80	9	30	12	270	293	351	643	81	304	14	2	282	77	-16	+1	-6	+2	+13	-0.6
2019	31	MLB MLE	Seattle Mariners	—	421	394	108	12	6	3	17	61	1	22	5	274	306	358	664	84	313	14	4	294	85	-8	+2	-1	+2	+9	0.4
2020	32	MLB MLE	Seattle Mariners	—	82	75	15	1	0	0	5	13	2	3	2	200	268	213	482	13	242	16	6	232	43	-6	-0	-3	-1	+2	-0.8
2021	33	AAA MLE	Indianapolis Indians	—	244	234	48	9	1	3	7	44	2	6	1	205	235	291	525	85	235	18	3	224	38	—	—	—	—	—	—
2022	34	MLB MLE	Washington Nationals	—	59	59	18	1	1	0	0	8	0	3	2	305	305	356	661	51	353	14	0	300	89	-1	-0	-5	+1	+1	-0.3
2022	34	AAA MLE	Rochester Red Wings	—	24	22	4	1	0	0	2	1	0	0	0	182	250	227	477	45	172	4	8	202	23	—	—	—	—	—	—
2008	20	ROK MLE	Ogden Raptors	—	274	257	68	10	2	1	10	42	2	18	5	265	297	331	628	66	309	15	4	276	73	—	—	—	—	—	—
2008	20	ROK RAW	Ogden Raptors	—	274	251	83	13	3	2	16	29	2	18	5	331	375	430	806	100	363	11	6	355	73	—	—	—	—	—	—
2009	21	A MLE	Great Lakes Loons	—	601	554	153	15	11	2	27	123	10	73	25	276	321	354	675	78	350	20	4	295	86	—	—	—	—	—	—
2009	21	A RAW	Great Lakes Loons	—	601	538	162	17	12	3	43	90	10	73	25	301	364	394	758	93	355	15	7	337	86	—	—	—	—	—	—
2010	22	AA MLE	2 teams	—	772	711	195	21	11	2	33	136	11	61	27	274	317	343	660	69	334	18	4	284	78	—	—	—	—	—	—
2010	22	AA RAW	2 teams	—	772	699	206	21	16	3	45	104	11	61	27	295	347	383	730	89	341	13	6	322	78	—	—	—	—	—	—
2011	23	AAA MLE	2 teams	—	546	517	153	18	7	0	20	83	2	54	11	296	325	358	683	62	350	15	4	302	91	—	—	—	—	—	—
2011	23	AAA RAW	2 teams	—	546	512	164	19	8	0	25	67	2	54	11	320	354	389	743	68	366	12	5	330	91	—	—	—	—	—	—
2012	24	MLB MLE	3 teams	—	485	445	103	13	4	1	29	89	6	43	17	231	287	285	573	54	285	18	6	262	63	-21	+2	-8	+5	+11	-1.2
2012	24	MLB RAW	3 teams	—	485	441	106	12	9	1	33	87	6	43	17	240	302	315	617	75	295	18	7	279	63	-21	+2	-8	+5	+11	-1.2
2013	25	AAA MLE	3 teams	—	608	549	138	17	9	1	48	132	4	63	17	251	316	321	637	69	329	22	8	284	78	—	—	—	—	—	—
2013	25	AAA RAW	3 teams	—	608	531	157	19	10	1	66	103	4	63	17	296	378	375	752	79	364	17	11	340	78	—	—	—	—	—	—
2014	26	MLB MLE	Los Angeles Dodgers	—	650	609	180	25	14	2	31	107	4	64	19	296	334	392	726	97	354	16	5	325	106	+5	+5	+1	+2	+14	2.8
2014	26	MLB RAW	Los Angeles Dodgers	—	650	609	176	24	12	2	31	107	4	64	19	289	328	378	705	89	346	16	5	314	106	+5	+5	+1	+2	+14	2.8
2015	27	MLB MLE	Miami Marlins	—	653	617	211	26	9	4	23	91	2	58	20	342	368	433	800	91	393	14	4	351	124	+18	+4	+8	+2	+14	4.8
2015	27	MLB RAW	Miami Marlins	—	653	615	205	24	8	4	25	91	2	58	20	333	361	418	779	85	383	14	4	343	124	+18	+4	+8	+2	+14	4.8
2016	28	MLB MLE	2 teams	—	382	362	96	8	7	1	18	61	0	33	7	265	300	334	634	69	316	16	5	286	80	-9	+4	+1	+1	+8	0.5
2016	28	MLB RAW	2 teams	—	382	360	96	8	7	1	19	60	0	33	7	267	303	336	639	69	317	16	5	286	80	-9	+4	+1	+1	+8	0.5
2017	29	MLB MLE	Miami Marlins	—	695	654	207	22	10	2	25	93	10	60	16	317	351	390	741	73	364	13	4	330	109	+8	+6	-2	+2	+15	3.0
2017	29	MLB RAW	Miami Marlins	—	695	653	201	20	9	2	25	93	10	60	16	308	343	375	718	67	354	13	4	321	109	+8	+6	-2	+2	+15	3.0
2018	30	MLB MLE	Seattle Mariners	—	588	556	150	17	8	4	9	80	9	30	12	270	293	351	643	81	306	14	2	282	77	-16	+1	-6	+2	+13	-0.6
2018	30	MLB RAW	Seattle Mariners	—	588	556	149	17	8	4	9	80	9	30	12	268	291	349	640	81	304	14	2	280	77	-16	+1	-6	+2	+13	-0.6
2019	31	MLB MLE	Seattle Mariners	—	421	394	108	12	6	3	17	61	1	22	5	274	306	358	664	84	312	14	4	294	85	-8	+2	-1	+2	+9	0.4
2019	31	MLB RAW	Seattle Mariners	—	421	393	108	12	6	3	18	61	1	22	5	275	308	359	667	84	313	14	4	293	85	-8	+2	-1	+2	+9	0.4
2020	32	MLB MLE	Seattle Mariners	—	82	75	15	1	0	0	5	13	2	3	2	200	268	213	482	13	242	16	6	232	43	-6	-0	-3	-1	+2	-0.8
2020	32	MLB RAW	Seattle Mariners	—	82	75	15	1	0	0	5	13	2	3	2	200	268	213	482	13	242	16	6	231	43	-6	-0	-3	-1	+2	-0.8
2021	33	AAA MLE	Indianapolis Indians	—	244	234	48	9	1	3	7	44	2	6	1	205	235	291	525	85	241	18	3	224	38	—	—	—	—	—	—
2021	33	AAA RAW	Indianapolis Indians	—	244	230	57	11	1	5	11	35	2	6	1	248	288	370	658	122	274	14	5	293	38	—	—	—	—	—	—
2022	34	MLB MLE	2 teams	—	83	81	22	2	1	0	2	9	0	3	2	272	289	321	610	49	306	11	2	272	70	-3	-0	-5	+1	+2	-0.5
2022	34	MLB RAW	2 teams	—	83	80	22	2	1	0	3	9	0	3	2	275	301	325	626	50	310	11	4	283	70	-3	-0	-5	+1	+2	-0.5
2008	20	ROK MLE	Ogden Raptors	—	274	260	68	10	2	1	10	42	2	18	5	262	297	327	624	65	301	15	4	276	73	—	—	—	—	—	—
2009	21	A MLE	Great Lakes Loons	—	601	559	153	15	11	2	27	123	10	73	25	274	321	351	672	77	340	20	4	295	86	—	—	—	—	—	—
2010	22	AA MLE	2 teams	—	772	722	195	21	11	2	33	136	11	61	27	270	317	338	655	68	323	18	4	284	78	—	—	—	—	—	—
2011	23	AAA MLE	2 teams	—	546	519	153	18	7	0	20	83	2	54	11	295	325	356	681	62	343	15	4	302	91	—	—	—	—	—	—
2012	24	MLB MLE	3 teams	—	485	447	103	13	4	1	29	89	6	43	17	230	287	284	572	54	280	18	6	262	63	—	—	—	—	—	—
2013	25	AAA MLE	3 teams	—	608	551	138	17	9	1	48	132	4	63	17	250	316	319	636	69	324	22	8	284	78	—	—	—	—	—	—
2014	26	MLB MLE	Los Angeles Dodgers	—	650	610	180	25	14	2	31	107	4	64	19	295	334	392	726	97	346	16	5	325	106	—	—	—	—	—	—
2015	27	MLB MLE	Miami Marlins	—	653	623	211	26	9	4	23	91	2	58	20	339	368	429	796	90	383	14	4	351	124	—	—	—	—	—	—
2016	28	MLB MLE	2 teams	—	382	361	96	8	7	1	18	61	0	33	7	266	300	335	635	69	312	16	5	286	80	—	—	—	—	—	—
2017	29	MLB MLE	Miami Marlins	—	695	655	207	22	10	2	25	93	10	60	16	316	351	389	741	73	354	13	4	330	109	—	—	—	—	—	—
2018	30	MLB MLE	Seattle Mariners	—	588	565	150	17	8	4	9	80	9	30	12	265	293	345	638	80	304	14	2	282	77	—	—	—	—	—	—
2019	31	MLB MLE	Seattle Mariners	—	421	400	108	12	6	3	17	61	1	22	5	270	306	352	658	82	313	14	4	294	85	—	—	—	—	—	—
2020	32	MLB MLE	Seattle Mariners	—	82	75	15	1	0	0	5	13	2	3	2	200	268	213	482	13	242	16	6	232	43	—	—	—	—	—	—
2021	33	AAA MLE	Indianapolis Indians	—	244	233	48	9	1	3	7	44	2	6	1	206	235	292	526	86	235	18	3	224	38	—	—	—	—	—	—
2022	34	MLB MLE	2 teams	—	83	81	22	2	1	0	2	9	0	3	2	272	289	321	610	49	301	11	2	272	70	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4163	3906	1118	125	55	18	168	618	32	336	102	286	321	360	681	74	334	15	4	303	87	-45	+26	-21	+30	+90	8.2
/ 162G	—	A+C		—	650	610	176	20	9	3	26	96	5	52	16	289	323	366	689	77	336	15	4	303	87	-7	+4	-3	+5	+14	1.3
Career	—	MLE		—	7084	6615	1847	216	100	26	304	1164	65	591	186	279	317	354	671	75	333	16	4	297	87	-45	+26	-21	+30	+90	8.2
/ 162G	—	MLE		—	650	607	169	20	9	2	28	107	6	54	17	278	317	351	668	72	333	16	4	297	87	-7	+4	-3	+5	+14	1.3

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.

2022 AAARochester Red Wings · 24 PAwOBA .248 → .202 (−46)K% 4.2% → 4.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	4.17%	÷1.049	×1.200	—	—	4.77%
BB% (unintentional) /PA	12.50%	÷0.973	×0.690	—	×0.940	8.34%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	15.00%	÷1.011	×0.930	—	×0.940	12.97%
Doubles /BIP	5.00%	÷0.930	×0.830	—	×0.940	4.19%
Triples /BIP	0.00%	÷0.913	×0.970	—	×0.940	0.00%
Home runs /BIP	0.00%	÷1.084	×0.700	—	×0.940	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 117, 1B 102, 2B 86, 3B 83, K 110, BB 95 — applied at half strength. Age: age 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average).

Result: wOBA .248 → .202; ISO .048 → .042; BABIP .200 → .172. 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).

2021 AAAIndianapolis Indians · 244 PAwOBA .285 → .224 (−61)K% 14.3% → 17.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.34%	÷0.961	×1.200	—	—	17.92%
BB% (unintentional) /PA	4.51%	÷1.100	×0.690	—	×0.942	2.66%
HBP% /PA	0.82%	—	×0.940	—	×0.942	0.73%
Singles /BIP	20.51%	÷1.011	×0.930	×1.020	×0.942	18.12%
Doubles /BIP	5.64%	÷0.986	×0.830	×1.020	×0.942	4.56%
Triples /BIP	0.51%	÷0.914	×0.920	×1.020	×0.942	0.50%
Home runs /BIP	2.56%	÷1.096	×0.700	—	×0.942	1.54%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 119, 1B 102, 2B 97, 3B 83, K 92, BB 120 — applied at half strength. Age: age 33 vs a level average of 27.2 → −5.8% on BB/HBP/hit rates (5.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.020.

Result: wOBA .285 → .224; ISO .122 → .085; BABIP .274 → .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).

2016 AAANew Orleans Zephyrs · 36 PAwOBA .268 → .217 (−52)K% 13.9% → 17.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.89%	÷1.027	×1.290	—	—	17.44%
BB% (unintentional) /PA	2.78%	÷0.964	×0.710	—	×0.992	2.03%
HBP% /PA	0.00%	—	×0.980	—	×0.992	0.00%
Singles /BIP	23.33%	÷1.041	×0.900	—	×0.992	20.00%
Doubles /BIP	3.33%	÷0.929	×0.810	—	×0.992	2.88%
Triples /BIP	3.33%	÷1.057	×0.810	—	×0.992	2.53%
Home runs /BIP	0.00%	÷0.919	×0.780	—	×0.992	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 84, 1B 108, 2B 86, 3B 111, K 105, BB 93 — 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).

Result: wOBA .268 → .217; ISO .086 → .066; BABIP .300 → .254. 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 AAAAlbuquerque Isotopes · 433 PAwOBA .340 → .286 (−54)K% 16.2% → 22.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.17%	÷0.938	×1.290	—	—	22.23%
BB% (unintentional) /PA	11.55%	÷1.071	×0.710	—	×1.033	7.91%
HBP% /PA	0.69%	—	×0.980	—	×1.033	0.70%
Singles /BIP	27.96%	÷1.029	×0.900	×1.050	×1.033	26.53%
Doubles /BIP	5.59%	÷1.082	×0.810	×1.050	×1.033	4.54%
Triples /BIP	2.96%	÷1.150	×0.810	×1.050	×1.033	2.26%
Home runs /BIP	0.00%	÷1.004	×0.780	—	×1.033	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 101, 1B 106, 2B 116, 3B 130, K 88, BB 114 — 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 ×1.050.

Result: wOBA .340 → .286; ISO .094 → .073; BABIP .364 → .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).

2012 AAAAlbuquerque Isotopes · 32 PAwOBA .285 → .243 (−42)K% 9.4% → 12.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.38%	÷0.935	×1.290	—	—	12.93%
BB% (unintentional) /PA	6.25%	÷0.962	×0.710	—	×1.048	4.83%
HBP% /PA	0.00%	—	×0.980	—	×1.048	0.00%
Singles /BIP	25.93%	÷1.034	×0.900	—	×1.048	23.64%
Doubles /BIP	0.00%	÷1.135	×0.810	—	×1.048	0.00%
Triples /BIP	3.70%	÷1.055	×0.810	—	×1.048	2.98%
Home runs /BIP	0.00%	÷1.018	×0.780	—	×1.048	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 104, 1B 107, 2B 127, 3B 111, K 87, BB 92 — 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 .285 → .243; ISO .067 → .052; BABIP .296 → .266. 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).

2011 AAAAlbuquerque Isotopes · 313 PAwOBA .341 → .293 (−49)K% 12.8% → 17.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.78%	÷0.928	×1.290	—	—	17.77%
BB% (unintentional) /PA	5.43%	÷1.012	×0.710	—	×1.050	4.00%
HBP% /PA	0.64%	—	×0.980	—	×1.050	0.66%
Singles /BIP	32.26%	÷1.096	×0.900	×1.050	×1.050	29.20%
Doubles /BIP	4.03%	÷1.012	×0.810	×1.050	×1.050	3.56%
Triples /BIP	2.42%	÷1.150	×0.810	×1.050	×1.050	1.88%
Home runs /BIP	0.00%	÷1.173	×0.780	—	×1.050	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 135, 1B 119, 2B 102, 3B 130, K 86, BB 102 — 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 ×1.050.

Result: wOBA .341 → .293; ISO .076 → .062; BABIP .382 → .342. 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).

2010 AAChattanooga Lookouts · 614 PAwOBA .300 → .284 (−16)K% 14.5% → 17.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.50%	÷1.005	×1.220	—	—	17.59%
BB% (unintentional) /PA	6.35%	÷1.036	×0.680	—	×1.042	4.34%
HBP% /PA	1.14%	—	×0.840	—	×1.042	1.00%
Singles /BIP	26.82%	÷0.998	×0.920	×1.050	×1.042	27.06%
Doubles /BIP	3.65%	÷1.030	×0.910	×1.050	×1.042	3.53%
Triples /BIP	2.15%	÷1.131	×0.880	×1.050	×1.042	1.83%
Home runs /BIP	0.43%	÷1.001	×0.800	—	×1.042	0.36%

Factors used: league row SL. Park (home-season share, regressed): HR 100, 1B 100, 2B 106, 3B 126, K 101, BB 107 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .300 → .284; ISO .077 → .070; BABIP .325 → .323. 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 AGreat Lakes Loons · 601 PAwOBA .328 → .295 (−32)K% 15.0% → 20.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.98%	÷1.000	×1.360	—	—	20.37%
BB% (unintentional) /PA	6.49%	÷1.000	×0.690	—	×1.015	4.54%
HBP% /PA	1.66%	—	×0.780	—	×1.015	1.32%
Singles /BIP	29.02%	÷1.000	×0.920	×1.039	×1.015	28.14%
Doubles /BIP	3.79%	÷1.000	×0.830	×1.039	×1.015	3.32%
Triples /BIP	2.68%	÷1.000	×0.910	×1.039	×1.015	2.57%
Home runs /BIP	0.67%	÷1.000	×0.800	—	×1.015	0.54%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.039.

Result: wOBA .328 → .295; ISO .093 → .083; BABIP .355 → .340. 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 — .