Austin Jackson

PosCF

B/TR/R

Born1987-02-01

Age (2027)40

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	29	MLBCWS	203	.254/.322/.343	0	2	86	0.3
2017	30	AAACLE	29	.333/.379/.556	1	2	99	—	.286/.310/.464
2017	30	MLBCleveland Ind…	318	.318/.392/.482	7	3	146	2.3
2018	31	MLBNYM	375	.245/.299/.326	3	3	81	-0.3
2019	32	No MLB games played
2020	33	No MLB games played
2021	34	No MLB games played
2022	35	No MLB games played
2023	36	No MLB games played
2024	37	No MLB games played
2025	38	No MLB games played
2026	39	No MLB games played

Last 3 seasons WAR 2.3

Contract

No contract data on file.

Skills · percentileStatcast 2016-2018

Speed50

xwOBA40

Avg EV35

Barrel%13

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	18	ROK	GCL Yankees	—	171	148	45	11	2	0	18	26	1	11	2	304	383	405	789	101	357	15	11	349	61	—	—	—	—	—	—
2006	19	A	Charleston RiverDogs	—	611	535	139	24	5	4	61	151	6	37	12	260	342	346	688	86	352	25	10	311	58	—	—	—	—	—	—
2007	20	A+	Tampa Yankees	—	284	258	89	15	6	10	22	48	2	13	5	345	401	566	967	221	391	17	8	419	136	—	—	—	—	—	—
2007	20	A	Charleston RiverDogs	—	266	235	61	16	1	3	24	59	4	19	6	260	338	374	713	115	331	22	9	320	59	—	—	—	—	—	—
2008	21	AA	Trenton Thunder	—	584	520	148	33	5	9	56	113	2	19	6	285	356	419	776	135	346	19	10	344	95	—	—	—	—	—	—
2009	22	AAA	Scranton/Wilkes-Barre Yankees	—	557	504	151	23	9	4	40	123	6	24	4	300	358	405	763	105	384	22	7	339	91	—	—	—	—	—	—
2010	23	MLB	Detroit Tigers	—	675	618	181	34	10	4	47	170	4	27	6	293	347	400	746	107	396	25	7	332	111	+9	+3	+7	+2	+15	3.7
2011	24	MLB	Detroit Tigers	—	668	591	147	22	11	10	56	181	4	22	5	249	318	374	692	125	340	27	8	304	93	-6	+2	+10	+2	+14	2.4
2012	25	MLB	Detroit Tigers	—	617	543	163	29	10	16	67	134	2	12	9	300	379	479	858	179	371	22	11	377	145	+33	-1	+3	+2	+13	5.1
2013	26	MLB	Detroit Tigers	—	614	552	150	30	7	12	52	129	4	8	4	272	339	417	755	145	333	21	8	335	116	+12	+0	+1	+2	+13	2.9
2014	27	MLB	Seattle Mariners	—	656	597	153	30	6	4	47	144	2	20	6	256	313	347	659	90	325	22	7	294	87	-10	+2	-4	+2	+14	0.4
2015	28	MLB	Chicago Cubs	—	527	491	131	25	3	9	29	126	3	17	10	267	312	385	697	118	342	24	6	310	94	-4	-1	+4	+2	+11	1.3
2015	28	AAA	Tacoma Rainiers	—	42	38	10	1	0	0	4	12	0	1	0	263	333	289	623	26	385	29	10	291	41	—	—	—	—	—	—
2016	29	MLB	Chicago White Sox	—	203	181	46	12	2	0	17	39	1	2	1	254	322	343	664	88	319	19	8	297	86	-3	+0	+1	+1	+4	0.3
2017	30	MLB	Cleveland Indians	—	318	280	89	19	3	7	33	64	1	3	1	318	392	482	874	164	385	20	10	383	146	+18	+0	-3	+1	+7	2.3
2017	30	AAA	Columbus Clippers	—	29	27	9	3	0	1	2	6	0	2	0	333	379	556	935	222	400	21	7	409	99	—	—	—	—	—	—
2018	31	MLB	New York Mets	—	375	347	85	17	1	3	26	133	1	3	3	245	299	326	625	81	387	35	7	284	81	-8	-1	-3	+1	+8	-0.3
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4653	4200	1145	218	53	65	374	1120	22	114	45	273	335	396	731	124	355	24	8	325	106	+32	+5	+15	+17	+101	17.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	18	ROK MLE	GCL Yankees	—	171	155	35	8	1	0	11	37	1	11	2	226	281	290	572	65	281	22	6	259	61	—	—	—	—	—	—
2006	19	A MLE	Charleston RiverDogs	—	611	554	122	19	5	3	42	202	6	37	12	220	282	289	571	69	329	33	7	254	58	—	—	—	—	—	—
2007	20	A+ MLE	Tampa Yankees	—	284	263	83	15	5	9	17	68	2	13	5	316	362	513	875	198	388	24	6	369	136	—	—	—	—	—	—
2007	20	A MLE	Charleston RiverDogs	—	266	243	52	13	1	2	16	79	4	19	6	214	274	300	574	86	297	30	6	255	59	—	—	—	—	—	—
2008	21	AA MLE	Trenton Thunder	—	584	537	145	30	5	7	39	138	2	19	6	270	322	384	705	114	342	24	7	309	95	—	—	—	—	—	—
2009	22	AAA MLE	Scranton/Wilkes-Barre Yankees	—	557	516	143	20	9	3	28	148	6	24	4	277	322	368	690	91	369	27	5	303	91	—	—	—	—	—	—
2010	23	MLB MLE	Detroit Tigers	—	675	622	184	35	10	4	43	170	4	27	6	296	345	404	749	108	396	25	6	333	111	+9	+3	+7	+2	+15	3.7
2011	24	MLB MLE	Detroit Tigers	—	668	594	149	23	11	10	53	181	4	22	5	251	316	377	694	126	340	27	8	305	93	-6	+2	+10	+2	+14	2.4
2012	25	MLB MLE	Detroit Tigers	—	617	543	166	30	10	17	67	134	2	12	9	306	384	492	876	186	371	22	11	383	145	+33	-1	+3	+2	+13	5.1
2013	26	MLB MLE	Detroit Tigers	—	614	552	153	31	7	13	52	129	4	8	4	277	344	429	773	152	333	21	8	340	116	+12	+0	+1	+2	+13	2.9
2014	27	MLB MLE	Seattle Mariners	—	656	597	154	30	6	4	47	144	2	20	6	258	314	348	663	90	325	22	7	297	87	-10	+2	-4	+2	+14	0.4
2015	28	MLB MLE	Chicago Cubs	—	527	491	130	24	3	9	29	126	3	17	10	265	310	381	691	116	342	24	6	308	94	-4	-1	+4	+2	+11	1.3
2015	28	AAA MLE	Tacoma Rainiers	—	42	39	9	1	0	0	3	15	0	1	0	231	286	256	542	26	344	36	7	229	41	—	—	—	—	—	—
2016	29	MLB MLE	Chicago White Sox	—	203	181	46	12	2	0	17	39	1	2	1	254	322	343	664	88	319	19	8	296	86	-3	+0	+1	+1	+4	0.3
2017	30	MLB MLE	Cleveland Indians	—	318	280	90	19	4	7	33	64	1	3	1	321	395	493	888	171	385	20	10	384	146	+18	+0	-3	+1	+7	2.3
2017	30	AAA MLE	Columbus Clippers	—	29	28	8	2	0	1	1	7	0	2	0	286	310	464	775	179	352	24	3	315	99	—	—	—	—	—	—
2018	31	MLB MLE	New York Mets	—	375	349	88	18	1	3	24	133	1	3	3	252	302	335	637	83	387	35	6	288	81	-8	-1	-3	+1	+8	-0.3
2005	18	ROK MLE	GCL Yankees	—	171	155	35	8	1	0	11	37	1	11	2	226	281	290	572	65	287	22	6	259	61	—	—	—	—	—	—
2005	18	ROK RAW	GCL Yankees	—	171	148	45	11	2	0	18	26	1	11	2	304	383	405	789	101	357	15	11	349	61	—	—	—	—	—	—
2006	19	A MLE	Charleston RiverDogs	—	611	554	122	19	5	3	42	202	6	37	12	220	282	289	571	69	337	33	7	254	58	—	—	—	—	—	—
2006	19	A RAW	Charleston RiverDogs	—	611	535	139	24	5	4	61	151	6	37	12	260	342	346	688	86	352	25	10	311	58	—	—	—	—	—	—
2007	20	A+ MLE	2 teams	—	550	505	134	27	6	11	34	147	6	32	11	265	319	408	727	143	350	27	6	314	99	—	—	—	—	—	—
2007	20	A+ RAW	2 teams	—	550	493	150	31	7	13	46	107	6	32	11	304	371	475	845	170	363	19	8	371	99	—	—	—	—	—	—
2008	21	AA MLE	Trenton Thunder	—	584	537	145	30	5	7	39	138	2	19	6	270	322	384	705	114	348	24	7	309	95	—	—	—	—	—	—
2008	21	AA RAW	Trenton Thunder	—	584	520	148	33	5	9	56	113	2	19	6	285	356	419	776	135	346	19	10	344	95	—	—	—	—	—	—
2009	22	AAA MLE	Scranton/Wilkes-Barre Yankees	—	557	516	143	20	9	3	28	148	6	24	4	277	322	368	690	91	377	27	5	303	91	—	—	—	—	—	—
2009	22	AAA RAW	Scranton/Wilkes-Barre Yankees	—	557	504	151	23	9	4	40	123	6	24	4	300	358	405	763	105	384	22	7	339	91	—	—	—	—	—	—
2010	23	MLB MLE	Detroit Tigers	—	675	622	184	35	10	4	43	170	4	27	6	296	345	404	749	108	399	25	6	333	111	+9	+3	+7	+2	+15	3.7
2010	23	MLB RAW	Detroit Tigers	—	675	618	181	34	10	4	47	170	4	27	6	293	347	400	746	107	396	25	7	332	111	+9	+3	+7	+2	+15	3.7
2011	24	MLB MLE	Detroit Tigers	—	668	594	149	23	11	10	53	181	4	22	5	251	316	377	694	126	342	27	8	305	93	-6	+2	+10	+2	+14	2.4
2011	24	MLB RAW	Detroit Tigers	—	668	591	147	22	11	10	56	181	4	22	5	249	318	374	692	125	340	27	8	304	93	-6	+2	+10	+2	+14	2.4
2012	25	MLB MLE	Detroit Tigers	—	617	543	166	30	10	17	67	134	2	12	9	306	384	492	876	186	377	22	11	383	145	+33	-1	+3	+2	+13	5.1
2012	25	MLB RAW	Detroit Tigers	—	617	543	163	29	10	16	67	134	2	12	9	300	379	479	858	179	371	22	11	377	145	+33	-1	+3	+2	+13	5.1
2013	26	MLB MLE	Detroit Tigers	—	614	552	153	31	7	13	52	129	4	8	4	277	344	429	773	152	339	21	8	340	116	+12	+0	+1	+2	+13	2.9
2013	26	MLB RAW	Detroit Tigers	—	614	552	150	30	7	12	52	129	4	8	4	272	339	417	755	145	333	21	8	335	116	+12	+0	+1	+2	+13	2.9
2014	27	MLB MLE	Seattle Mariners	—	656	597	154	30	6	4	47	144	2	20	6	258	314	348	663	90	328	22	7	297	87	-10	+2	-4	+2	+14	0.4
2014	27	MLB RAW	Seattle Mariners	—	656	597	153	30	6	4	47	144	2	20	6	256	313	347	659	90	325	22	7	294	87	-10	+2	-4	+2	+14	0.4
2015	28	MLB MLE	2 teams	—	569	530	138	25	3	9	32	141	3	18	10	260	306	370	676	109	339	25	6	302	90	-7	-0	+4	+2	+12	1.1
2015	28	MLB RAW	2 teams	—	569	529	141	26	3	9	33	138	3	18	10	267	313	378	691	112	345	24	6	308	90	-7	-0	+4	+2	+12	1.1
2016	29	MLB MLE	Chicago White Sox	—	203	181	46	12	2	0	17	39	1	2	1	254	322	343	664	88	319	19	8	296	86	-3	+0	+1	+1	+4	0.3
2016	29	MLB RAW	Chicago White Sox	—	203	181	46	12	2	0	17	39	1	2	1	254	322	343	664	88	319	19	8	297	86	-3	+0	+1	+1	+4	0.3
2017	30	MLB MLE	2 teams	—	347	308	98	21	4	8	34	71	1	5	1	318	388	490	878	172	386	20	10	379	142	+17	+1	-3	+1	+8	2.4
2017	30	MLB RAW	2 teams	—	347	307	98	22	3	8	35	70	1	5	1	319	391	489	879	169	386	20	10	385	142	+17	+1	-3	+1	+8	2.4
2018	31	MLB MLE	New York Mets	—	375	349	88	18	1	3	24	133	1	3	3	252	302	335	637	83	397	35	6	288	81	-8	-1	-3	+1	+8	-0.3
2018	31	MLB RAW	New York Mets	—	375	347	85	17	1	3	26	133	1	3	3	245	299	326	625	81	387	35	7	284	81	-8	-1	-3	+1	+8	-0.3
2005	18	ROK MLE	GCL Yankees	—	171	157	35	8	1	0	11	37	1	11	2	223	281	287	568	64	281	22	6	259	61	—	—	—	—	—	—
2006	19	A MLE	Charleston RiverDogs	—	611	558	122	19	5	3	42	202	6	37	12	219	282	287	569	68	329	33	7	254	58	—	—	—	—	—	—
2007	20	A+ MLE	2 teams	—	550	505	134	27	6	11	34	147	6	32	11	265	319	408	727	143	344	27	6	314	99	—	—	—	—	—	—
2008	21	AA MLE	Trenton Thunder	—	584	538	145	30	5	7	39	138	2	19	6	270	322	383	705	113	342	24	7	309	95	—	—	—	—	—	—
2009	22	AAA MLE	Scranton/Wilkes-Barre Yankees	—	557	518	143	20	9	3	28	148	6	24	4	276	322	367	689	91	369	27	5	303	91	—	—	—	—	—	—
2010	23	MLB MLE	Detroit Tigers	—	675	623	184	35	10	4	43	170	4	27	6	295	345	403	748	108	396	25	6	333	111	—	—	—	—	—	—
2011	24	MLB MLE	Detroit Tigers	—	668	606	149	23	11	10	53	181	4	22	5	246	316	370	686	124	340	27	8	305	93	—	—	—	—	—	—
2012	25	MLB MLE	Detroit Tigers	—	617	543	166	30	10	17	67	134	2	12	9	306	384	492	876	186	371	22	11	383	145	—	—	—	—	—	—
2013	26	MLB MLE	Detroit Tigers	—	614	553	153	31	7	13	52	129	4	8	4	277	344	429	772	152	333	21	8	340	116	—	—	—	—	—	—
2014	27	MLB MLE	Seattle Mariners	—	656	602	154	30	6	4	47	144	2	20	6	256	314	346	660	90	325	22	7	297	87	—	—	—	—	—	—
2015	28	MLB MLE	2 teams	—	569	529	138	25	3	9	32	141	3	18	10	261	306	371	677	110	342	25	6	302	90	—	—	—	—	—	—
2016	29	MLB MLE	Chicago White Sox	—	203	183	46	12	2	0	17	39	1	2	1	251	322	339	660	87	319	19	8	296	86	—	—	—	—	—	—
2017	30	MLB MLE	2 teams	—	347	309	98	21	4	8	34	71	1	5	1	317	388	489	876	172	382	20	10	379	142	—	—	—	—	—	—
2018	31	MLB MLE	New York Mets	—	375	347	88	18	1	3	24	133	1	3	3	254	302	337	639	84	387	35	6	288	81	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4653	4200	1145	218	53	65	374	1120	22	114	45	273	335	396	731	124	355	24	8	325	99	+32	+5	+15	+17	+101	17.3
/ 162G	—	A+C		—	650	587	159	30	7	9	52	156	3	16	6	271	333	392	725	121	352	24	8	325	99	+4	+1	+2	+2	+14	2.4
Career	—	MLE		—	7197	6543	1755	329	80	92	523	1814	43	240	80	268	326	385	712	117	355	25	7	314	99	+32	+5	+15	+17	+101	17.3
/ 162G	—	MLE		—	650	591	158	30	7	8	47	164	4	22	7	267	326	382	708	115	354	25	7	314	99	+4	+1	+2	+2	+14	2.4

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.

2017 AAAColumbus Clippers · 29 PAwOBA .397 → .315 (−82)K% 20.7% → 25.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.69%	÷0.989	×1.200	—	—	25.10%
BB% (unintentional) /PA	6.90%	÷1.089	×0.690	—	×0.972	4.25%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	23.81%	÷0.945	×0.930	—	×0.972	22.77%
Doubles /BIP	14.29%	÷1.018	×0.830	—	×0.972	11.32%
Triples /BIP	0.00%	÷0.900	×0.970	—	×0.972	0.00%
Home runs /BIP	4.76%	÷1.231	×0.840	—	×0.972	3.16%

Factors used: league row IL. Park (home-season share, regressed): HR 146, 1B 89, 2B 104, 3B 80, K 98, BB 118 — applied at half strength. Age: age 30 vs a level average of 27.2 → −2.8% on BB/HBP/hit rates (2.8 yr older than average).

Result: wOBA .397 → .315; ISO .222 → .158; BABIP .400 → .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).

2015 AAATacoma Rainiers · 42 PAwOBA .284 → .229 (−55)K% 28.6% → 35.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.57%	÷1.049	×1.290	—	—	35.13%
BB% (unintentional) /PA	9.52%	÷1.046	×0.710	—	×0.992	6.41%
HBP% /PA	0.00%	—	×0.980	—	×0.992	0.00%
Singles /BIP	34.62%	÷0.995	×0.900	—	×0.992	31.05%
Doubles /BIP	3.85%	÷0.910	×0.810	—	×0.992	3.40%
Triples /BIP	0.00%	÷0.900	×0.810	—	×0.992	0.00%
Home runs /BIP	0.00%	÷1.127	×0.780	—	×0.992	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 125, 1B 99, 2B 82, 3B 80, K 110, BB 109 — 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 .284 → .229; ISO .026 → .022; BABIP .385 → .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).

2009 AAAScranton/Wilkes-Barre Yankees · 557 PAwOBA .333 → .303 (−30)K% 22.1% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.08%	÷1.000	×1.200	—	—	26.50%
BB% (unintentional) /PA	7.00%	÷1.000	×0.690	—	×1.050	5.07%
HBP% /PA	1.08%	—	×0.940	—	×1.050	1.06%
Singles /BIP	30.18%	÷1.000	×0.930	×1.000	×1.050	29.48%
Doubles /BIP	6.04%	÷1.000	×0.830	×1.000	×1.050	5.26%
Triples /BIP	2.36%	÷1.000	×0.970	×1.000	×1.050	2.41%
Home runs /BIP	1.05%	÷1.000	×0.840	—	×1.050	0.93%

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 ×1.000.

Result: wOBA .333 → .303; ISO .105 → .096; BABIP .384 → .369. 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 AATrenton Thunder · 584 PAwOBA .336 → .309 (−27)K% 19.3% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.35%	÷1.000	×1.220	—	—	23.61%
BB% (unintentional) /PA	9.08%	÷1.000	×0.700	—	×1.050	6.67%
HBP% /PA	0.34%	—	×0.850	—	×1.050	0.31%
Singles /BIP	24.82%	÷1.000	×0.970	×1.003	×1.050	25.34%
Doubles /BIP	8.11%	÷1.000	×0.860	×1.003	×1.050	7.34%
Triples /BIP	1.23%	÷1.000	×0.950	×1.003	×1.050	1.23%
Home runs /BIP	2.21%	÷1.000	×0.780	—	×1.050	1.81%

Factors used: league row EL. 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 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.003.

Result: wOBA .336 → .309; ISO .135 → .119; BABIP .346 → .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).

2007 A+Tampa Yankees · 284 PAwOBA .411 → .369 (−42)K% 16.9% → 24.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.90%	÷1.000	×1.420	—	—	24.00%
BB% (unintentional) /PA	7.75%	÷1.000	×0.750	—	×1.042	6.05%
HBP% /PA	0.70%	—	×0.930	—	×1.042	0.68%
Singles /BIP	27.62%	÷1.000	×0.920	×1.040	×1.042	27.53%
Doubles /BIP	7.14%	÷1.000	×0.960	×1.040	×1.042	7.43%
Triples /BIP	2.86%	÷1.000	×0.810	×1.040	×1.042	2.51%
Home runs /BIP	4.76%	÷1.000	×0.880	—	×1.042	4.37%

Factors used: league row FSL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.040.

Result: wOBA .411 → .369; ISO .221 → .195; BABIP .391 → .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).

2007 ACharleston RiverDogs · 266 PAwOBA .315 → .255 (−60)K% 22.2% → 29.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.18%	÷1.000	×1.340	—	—	29.72%
BB% (unintentional) /PA	9.02%	÷1.000	×0.660	—	×1.030	6.13%
HBP% /PA	1.50%	—	×0.770	—	×1.030	1.19%
Singles /BIP	23.30%	÷1.000	×0.920	×0.978	×1.030	21.58%
Doubles /BIP	9.09%	÷1.000	×0.820	×0.978	×1.030	7.51%
Triples /BIP	0.57%	÷1.000	×0.940	×0.978	×1.030	0.54%
Home runs /BIP	1.70%	÷1.000	×0.820	—	×1.030	1.44%

Factors used: league row SAL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 20 vs a level average of 22.0 → +3.0% on BB/HBP/hit rates (2.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.978.

Result: wOBA .315 → .255; ISO .115 → .092; BABIP .331 → .297. 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 ACharleston RiverDogs · 611 PAwOBA .306 → .254 (−52)K% 24.7% → 33.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.71%	÷1.000	×1.340	—	—	33.12%
BB% (unintentional) /PA	9.98%	÷1.000	×0.660	—	×1.045	6.89%
HBP% /PA	0.98%	—	×0.770	—	×1.045	0.79%
Singles /BIP	27.60%	÷1.000	×0.920	×0.993	×1.045	26.34%
Doubles /BIP	6.25%	÷1.000	×0.820	×0.993	×1.045	5.32%
Triples /BIP	1.30%	÷1.000	×0.940	×0.993	×1.045	1.27%
Home runs /BIP	1.04%	÷1.000	×0.820	—	×1.045	0.89%

Factors used: league row SAL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 19 vs a level average of 22.0 → +4.5% on BB/HBP/hit rates (3.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.

Result: wOBA .306 → .254; ISO .086 → .071; BABIP .352 → .329. 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 ROKGCL Yankees · 171 PAwOBA .348 → .259 (−89)K% 15.2% → 21.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.20%	÷1.000	×1.440	—	—	21.89%
BB% (unintentional) /PA	10.53%	÷1.000	×0.620	—	×1.022	6.67%
HBP% /PA	0.58%	—	×0.720	—	×1.022	0.43%
Singles /BIP	26.23%	÷1.000	×0.820	×0.971	×1.022	21.36%
Doubles /BIP	9.02%	÷1.000	×0.720	×0.971	×1.022	6.45%
Triples /BIP	1.64%	÷1.000	×0.720	×0.971	×1.022	1.17%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×1.022	0.00%

Factors used: level-wide ROK 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 18 vs a level average of 19.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.971.

Result: wOBA .348 → .259; ISO .101 → .072; BABIP .357 → .281. 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).