Starlin Castro

PosSS

B/TR/R

Born1990-03-24

Age (2027)37

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2024

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	wRC+	WAR
2022	32	INTLLeones del Es…	168	.219/.251/.250	1	41	—
2023	33	INTLAguilas Cibae…	137	.319/.400/.429	2	136	—
2024	34	INTLAguilas Cibae…	83	.234/.262/.351	1	64	—

Contract

No contract data on file.

Skills · percentileStatcast 2019-2021

xwOBA57

Avg EV40

Barrel%32

Speed23

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)
2007	17	ROK	DSL Cubs	—	253	221	66	6	2	2	23	24	4	13	2	299	375	371	746	72	323	9	9	335	46	—	—	—	—	—	—
2008	18	ROK	AZL Cubs	—	215	196	61	11	5	3	14	33	3	6	5	311	366	464	830	153	360	15	7	365	68	—	—	—	—	—	—
2009	19	AA	Tennessee Smokies	—	122	111	32	6	3	0	10	12	0	6	0	288	347	396	744	108	323	10	8	331	97	—	—	—	—	—	—
2009	19	A+	Daytona Cubs	—	387	358	108	17	3	3	19	41	3	22	11	302	342	391	733	89	332	11	5	324	91	—	—	—	—	—	—
2010	20	MLB	Chicago Cubs	—	506	463	139	31	5	3	29	71	6	10	8	300	349	408	758	108	346	14	6	335	103	+2	-1	+4	+7	+11	2.3
2010	20	AA	Tennessee Smokies	—	121	109	41	8	5	1	9	11	1	4	5	376	429	569	997	193	404	9	7	429	140	—	—	—	—	—	—
2010	20	INTL	Leones del Escogido	—	66	60	19	3	1	0	4	10	1	1	1	317	369	400	769	83	373	15	6	342	118	—	—	—	—	—	—
2011	21	MLB	Chicago Cubs	—	715	674	207	36	9	10	35	96	2	22	9	307	343	432	775	125	344	13	5	343	114	+12	+1	-0	+8	+15	3.6
2012	22	MLB	Chicago Cubs	—	691	646	183	29	12	14	36	100	4	25	13	283	325	430	755	147	315	14	5	332	105	+4	-0	+11	+7	+15	3.7
2013	23	MLB	Chicago Cubs	—	705	666	163	34	2	10	30	129	7	9	6	245	284	347	631	102	290	18	4	283	77	-20	-1	+3	+8	+15	0.6
2014	24	MLB	Chicago Cubs	—	569	528	154	33	1	14	35	100	4	4	4	292	340	438	778	146	337	18	6	345	116	+11	-1	+6	+6	+12	3.5
2015	25	MLB	Chicago Cubs	—	578	547	145	23	2	11	21	91	5	5	5	265	298	375	673	110	298	16	4	299	83	-12	-1	+4	+6	+13	1.0
2016	26	MLB	New York Yankees	—	610	577	156	29	1	21	24	118	3	4	0	270	303	433	736	163	305	19	4	322	101	+1	+1	+11	+2	+13	2.8
2017	27	MLB	New York Yankees	—	473	443	133	18	1	16	23	93	4	2	0	300	340	454	794	153	347	20	5	350	120	+11	+0	+5	+2	+10	2.9
2017	27	AAA	Scranton/Wilkes-Barre RailRiders	—	25	24	8	0	0	1	1	4	0	0	0	333	360	458	818	125	368	16	4	365	89	—	—	—	—	—	—
2018	28	MLB	Miami Marlins	—	647	593	165	32	2	12	48	124	0	6	4	278	332	400	732	121	330	19	7	325	111	+9	-0	+6	+2	+14	3.1
2019	29	MLB	Miami Marlins	—	676	636	172	31	4	22	28	111	3	2	2	270	304	436	740	165	293	16	4	322	111	+9	-0	+9	+2	+15	3.5
2020	30	MLB	Washington Nationals	—	63	60	16	3	1	2	3	13	0	0	0	267	302	450	752	183	311	21	5	330	112	+1	+0	-0	+0	+1	0.2
2021	31	MLB	Washington Nationals	—	346	315	89	20	0	3	26	62	0	0	1	283	336	375	711	92	339	18	8	317	99	-1	-0	+1	+1	+7	0.9
2022	32	INTL	Leones del Escogido	—	168	160	35	2	0	1	7	31	0	0	0	219	251	250	501	31	264	18	4	229	41	—	—	—	—	—	—
2023	33	INTL	Aguilas Cibaenas	—	137	119	38	5	1	2	15	21	1	0	1	319	400	429	829	109	367	15	11	369	136	—	—	—	—	—	—
2024	34	INTL	Aguilas Cibaenas	—	83	77	18	4	1	1	3	13	0	0	0	234	263	351	613	117	258	16	4	262	64	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	6579	6148	1722	319	40	138	338	1108	38	89	52	280	322	412	734	132	320	17	5	324	106	+44	-3	+58	+52	+143	30.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2007	17	ROK MLE	DSL Cubs	—	253	228	48	4	1	1	16	29	4	13	2	211	274	250	524	39	228	11	6	236	46	—	—	—	—	—	—
2008	18	ROK MLE	AZL Cubs	—	215	201	48	8	4	2	9	48	3	6	5	239	282	348	630	109	293	22	4	269	68	—	—	—	—	—	—
2009	19	AA MLE	Tennessee Smokies	—	122	114	33	6	3	0	7	15	0	6	0	289	331	395	725	105	326	12	6	311	97	—	—	—	—	—	—
2009	19	A+ MLE	Daytona Cubs	—	387	363	106	17	3	3	14	58	3	22	11	292	324	380	704	88	332	15	4	303	91	—	—	—	—	—	—
2010	20	MLB MLE	Chicago Cubs	—	506	470	137	30	4	3	22	71	6	10	8	291	331	391	723	100	346	14	4	320	103	+2	-1	+4	+7	+11	2.3
2010	20	AA MLE	Tennessee Smokies	—	121	112	39	7	5	1	6	14	1	4	5	348	387	527	913	179	366	12	5	375	140	—	—	—	—	—	—
2011	21	MLB MLE	Chicago Cubs	—	715	676	205	35	8	10	33	96	2	22	9	303	338	423	761	120	344	13	5	337	114	+12	+1	-0	+8	+15	3.6
2012	22	MLB MLE	Chicago Cubs	—	691	651	181	28	10	15	31	100	4	25	13	278	315	421	736	143	315	14	4	323	105	+4	-0	+11	+7	+15	3.7
2013	23	MLB MLE	Chicago Cubs	—	705	666	162	33	2	10	30	129	7	9	6	243	283	344	627	101	290	18	4	282	77	-20	-1	+3	+8	+15	0.6
2014	24	MLB MLE	Chicago Cubs	—	569	532	154	32	1	15	31	100	4	4	4	289	333	438	771	148	337	18	5	339	116	+11	-1	+6	+6	+12	3.5
2015	25	MLB MLE	Chicago Cubs	—	578	553	144	22	2	11	15	91	5	5	5	260	286	367	653	107	298	16	3	290	83	-12	-1	+4	+6	+13	1.0
2016	26	MLB MLE	New York Yankees	—	610	578	155	29	1	20	23	118	3	4	0	268	300	426	725	157	305	19	4	317	101	+1	+1	+11	+2	+13	2.8
2017	27	MLB MLE	New York Yankees	—	473	444	132	18	1	15	22	93	4	2	0	297	336	444	780	146	347	20	5	345	120	+11	+0	+5	+2	+10	2.9
2017	27	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	25	24	8	0	0	1	1	5	0	0	0	333	360	458	818	125	345	20	4	300	89	—	—	—	—	—	—
2018	28	MLB MLE	Miami Marlins	—	647	596	171	35	2	13	45	124	0	6	4	287	337	418	755	131	330	19	7	333	111	+9	-0	+6	+2	+14	3.1
2019	29	MLB MLE	Miami Marlins	—	676	638	178	34	4	23	26	111	3	2	2	279	310	453	763	174	293	16	4	332	111	+9	-0	+9	+2	+15	3.5
2020	30	MLB MLE	Washington Nationals	—	63	60	16	3	1	2	3	13	0	0	0	267	302	450	752	183	311	21	5	334	112	+1	+0	-0	+0	+1	0.2
2021	31	MLB MLE	Washington Nationals	—	346	317	89	20	0	3	25	62	0	0	1	281	333	372	706	91	339	18	7	314	99	-1	-0	+1	+1	+7	0.9
2007	17	ROK MLE	DSL Cubs	—	253	228	48	4	1	1	16	29	4	13	2	211	274	250	524	39	234	11	6	236	46	—	—	—	—	—	—
2007	17	ROK RAW	DSL Cubs	—	253	221	66	6	2	2	23	24	4	13	2	299	375	371	746	72	323	9	9	335	46	—	—	—	—	—	—
2008	18	ROK MLE	AZL Cubs	—	215	201	48	8	4	2	9	48	3	6	5	239	282	348	630	109	303	22	4	269	68	—	—	—	—	—	—
2008	18	ROK RAW	AZL Cubs	—	215	196	61	11	5	3	14	33	3	6	5	311	366	464	830	153	360	15	7	365	68	—	—	—	—	—	—
2009	19	A+ MLE	2 teams	—	509	476	139	23	6	3	22	73	3	28	11	292	327	384	712	92	338	14	4	305	93	—	—	—	—	—	—
2009	19	A+ RAW	2 teams	—	509	469	140	23	6	3	29	53	3	28	11	299	343	392	736	94	330	10	6	325	93	—	—	—	—	—	—
2010	20	MLB MLE	3 teams	—	693	643	194	41	10	4	31	94	8	15	14	302	342	415	757	114	344	14	4	331	110	+8	-3	+4	+7	+15	3.2
2010	20	MLB RAW	3 teams	—	693	632	199	42	11	4	42	92	8	15	14	315	365	435	800	120	359	13	6	352	110	+8	-3	+4	+7	+15	3.2
2011	21	MLB MLE	Chicago Cubs	—	715	676	205	35	8	10	33	96	2	22	9	303	338	423	761	120	340	13	5	337	114	+12	+1	-0	+8	+15	3.6
2011	21	MLB RAW	Chicago Cubs	—	715	674	207	36	9	10	35	96	2	22	9	307	343	432	775	125	344	13	5	343	114	+12	+1	-0	+8	+15	3.6
2012	22	MLB MLE	Chicago Cubs	—	691	651	181	28	10	15	31	100	4	25	13	278	315	421	736	143	307	14	4	323	105	+4	-0	+11	+7	+15	3.7
2012	22	MLB RAW	Chicago Cubs	—	691	646	183	29	12	14	36	100	4	25	13	283	325	430	755	147	315	14	5	332	105	+4	-0	+11	+7	+15	3.7
2013	23	MLB MLE	Chicago Cubs	—	705	666	162	33	2	10	30	129	7	9	6	243	283	344	627	101	288	18	4	282	77	-20	-1	+3	+8	+15	0.6
2013	23	MLB RAW	Chicago Cubs	—	705	666	163	34	2	10	30	129	7	9	6	245	284	347	631	102	290	18	4	283	77	-20	-1	+3	+8	+15	0.6
2014	24	MLB MLE	Chicago Cubs	—	569	532	154	32	1	15	31	100	4	4	4	289	333	438	771	148	332	18	5	339	116	+11	-1	+6	+6	+12	3.5
2014	24	MLB RAW	Chicago Cubs	—	569	528	154	33	1	14	35	100	4	4	4	292	340	438	778	146	337	18	6	345	116	+11	-1	+6	+6	+12	3.5
2015	25	MLB MLE	Chicago Cubs	—	578	553	144	22	2	11	15	91	5	5	5	260	286	367	653	107	292	16	3	290	83	-12	-1	+4	+6	+13	1.0
2015	25	MLB RAW	Chicago Cubs	—	578	547	145	23	2	11	21	91	5	5	5	265	298	375	673	110	298	16	4	299	83	-12	-1	+4	+6	+13	1.0
2016	26	MLB MLE	New York Yankees	—	610	578	155	29	1	20	23	118	3	4	0	268	300	426	725	157	303	19	4	317	101	+1	+1	+11	+2	+13	2.8
2016	26	MLB RAW	New York Yankees	—	610	577	156	29	1	21	24	118	3	4	0	270	303	433	736	163	305	19	4	322	101	+1	+1	+11	+2	+13	2.8
2017	27	MLB MLE	2 teams	—	498	468	140	18	1	16	23	98	4	2	0	299	337	444	782	145	347	20	5	343	118	+11	+0	+5	+2	+11	2.9
2017	27	MLB RAW	2 teams	—	498	467	141	18	1	17	24	97	4	2	0	302	341	454	795	152	348	19	5	351	118	+11	+0	+5	+2	+11	2.9
2018	28	MLB MLE	Miami Marlins	—	647	596	171	35	2	13	45	124	0	6	4	287	337	418	755	131	340	19	7	333	111	+9	-0	+6	+2	+14	3.1
2018	28	MLB RAW	Miami Marlins	—	647	593	165	32	2	12	48	124	0	6	4	278	332	400	732	121	330	19	7	325	111	+9	-0	+6	+2	+14	3.1
2019	29	MLB MLE	Miami Marlins	—	676	638	178	34	4	23	26	111	3	2	2	279	310	453	763	174	302	16	4	332	111	+9	-0	+9	+2	+15	3.5
2019	29	MLB RAW	Miami Marlins	—	676	636	172	31	4	22	28	111	3	2	2	270	304	436	740	165	293	16	4	322	111	+9	-0	+9	+2	+15	3.5
2020	30	MLB MLE	Washington Nationals	—	63	60	16	3	1	2	3	13	0	0	0	267	302	450	752	183	311	21	5	334	112	+1	+0	-0	+0	+1	0.2
2020	30	MLB RAW	Washington Nationals	—	63	60	16	3	1	2	3	13	0	0	0	267	302	450	752	183	311	21	5	330	112	+1	+0	-0	+0	+1	0.2
2021	31	MLB MLE	Washington Nationals	—	346	317	89	20	0	3	25	62	0	0	1	281	333	372	706	91	336	18	7	314	99	-1	-0	+1	+1	+7	0.9
2021	31	MLB RAW	Washington Nationals	—	346	315	89	20	0	3	26	62	0	0	1	283	336	375	711	92	339	18	8	317	99	-1	-0	+1	+1	+7	0.9
2022	32	INTL MLE	Leones del Escogido	—	168	160	35	2	0	1	7	31	0	0	0	219	251	250	501	31	264	18	4	—	—	—	—	—	—	—	—
2022	32	INTL RAW	Leones del Escogido	—	168	160	35	2	0	1	7	31	0	0	0	219	251	250	501	31	264	18	4	229	41	—	—	—	—	—	—
2023	33	INTL MLE	Aguilas Cibaenas	—	137	119	38	5	1	2	15	21	1	0	1	319	400	429	829	109	367	15	11	—	—	—	—	—	—	—	—
2023	33	INTL RAW	Aguilas Cibaenas	—	137	119	38	5	1	2	15	21	1	0	1	319	400	429	829	109	367	15	11	369	136	—	—	—	—	—	—
2024	34	INTL MLE	Aguilas Cibaenas	—	83	77	18	4	1	1	3	13	0	0	0	234	263	351	613	117	258	16	4	—	—	—	—	—	—	—	—
2024	34	INTL RAW	Aguilas Cibaenas	—	83	77	18	4	1	1	3	13	0	0	0	234	263	351	613	117	258	16	4	262	64	—	—	—	—	—	—
2007	17	ROK MLE	DSL Cubs	—	253	231	48	4	1	1	16	29	4	13	2	208	274	247	521	39	228	11	6	236	46	—	—	—	—	—	—
2008	18	ROK MLE	AZL Cubs	—	215	201	48	8	4	2	9	48	3	6	5	239	282	348	630	109	293	22	4	269	68	—	—	—	—	—	—
2009	19	A+ MLE	2 teams	—	509	479	139	23	6	3	22	73	3	28	11	290	327	382	709	92	331	14	4	305	93	—	—	—	—	—	—
2010	20	MLB MLE	3 teams	—	693	649	194	41	10	4	31	94	8	15	14	299	342	411	753	112	350	14	4	331	110	—	—	—	—	—	—
2011	21	MLB MLE	Chicago Cubs	—	715	674	205	35	8	10	33	96	2	22	9	304	338	424	762	120	344	13	5	337	114	—	—	—	—	—	—
2012	22	MLB MLE	Chicago Cubs	—	691	651	181	28	10	15	31	100	4	25	13	278	315	421	736	143	315	14	4	323	105	—	—	—	—	—	—
2013	23	MLB MLE	Chicago Cubs	—	705	662	162	33	2	10	30	129	7	9	6	245	283	346	629	101	290	18	4	282	77	—	—	—	—	—	—
2014	24	MLB MLE	Chicago Cubs	—	569	529	154	32	1	15	31	100	4	4	4	291	333	440	774	149	337	18	5	339	116	—	—	—	—	—	—
2015	25	MLB MLE	Chicago Cubs	—	578	553	144	22	2	11	15	91	5	5	5	260	286	367	653	107	298	16	3	290	83	—	—	—	—	—	—
2016	26	MLB MLE	New York Yankees	—	610	579	155	29	1	20	23	118	3	4	0	268	300	425	725	157	305	19	4	317	101	—	—	—	—	—	—
2017	27	MLB MLE	2 teams	—	498	468	140	18	1	16	23	98	4	2	0	299	337	444	782	145	347	20	5	343	118	—	—	—	—	—	—
2018	28	MLB MLE	Miami Marlins	—	647	597	171	35	2	13	45	124	0	6	4	286	337	417	754	131	330	19	7	333	111	—	—	—	—	—	—
2019	29	MLB MLE	Miami Marlins	—	676	642	178	34	4	23	26	111	3	2	2	277	310	450	761	173	293	16	4	332	111	—	—	—	—	—	—
2020	30	MLB MLE	Washington Nationals	—	63	60	16	3	1	2	3	13	0	0	0	267	302	450	752	183	311	21	5	334	112	—	—	—	—	—	—
2021	31	MLB MLE	Washington Nationals	—	346	318	89	20	0	3	25	62	0	0	1	280	333	371	704	91	339	18	7	314	99	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	6579	6148	1722	319	40	138	338	1108	38	89	52	280	322	412	734	132	320	17	5	324	90	+44	-3	+58	+52	+143	30.0
/ 162G	—	A+C		—	650	607	171	32	4	14	33	109	4	9	5	282	323	417	740	135	321	17	5	324	90	+4	-0	+6	+5	+14	3.0
Career	—	MLE		—	8156	7639	2115	376	55	152	388	1351	51	141	77	277	316	400	716	123	317	17	5	302	90	+44	-3	+58	+52	+143	30.0
/ 162G	—	MLE		—	650	609	168	30	4	12	31	108	4	11	6	276	315	397	713	122	316	17	5	302	90	+4	-0	+6	+5	+14	3.0

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.

2017 AAAScranton/Wilkes-Barre RailRiders · 25 PAwOBA .354 → .300 (−55)K% 16.0% → 19.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.00%	÷0.995	×1.200	—	—	19.30%
BB% (unintentional) /PA	4.00%	÷1.105	×0.690	—	×1.003	2.51%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	35.00%	÷0.980	×0.930	—	×1.003	33.32%
Doubles /BIP	0.00%	÷0.951	×0.830	—	×1.003	0.00%
Triples /BIP	0.00%	÷1.150	×0.970	—	×1.003	0.00%
Home runs /BIP	5.00%	÷1.247	×0.840	—	×1.003	3.38%

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 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average).

Result: wOBA .354 → .300; ISO .125 → .083; BABIP .368 → .345. 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 AATennessee Smokies · 121 PAwOBA .424 → .375 (−49)K% 9.1% → 11.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.09%	÷0.960	×1.220	—	—	11.55%
BB% (unintentional) /PA	7.44%	÷1.048	×0.680	—	×1.050	5.07%
HBP% /PA	0.83%	—	×0.840	—	×1.050	0.73%
Singles /BIP	27.55%	÷0.988	×0.920	×0.961	×1.050	25.89%
Doubles /BIP	8.16%	÷1.126	×0.910	×0.961	×1.050	6.66%
Triples /BIP	5.10%	÷1.006	×0.880	×0.961	×1.050	4.50%
Home runs /BIP	1.02%	÷1.049	×0.800	—	×1.050	0.82%

Factors used: league row SL. Park (home-season share, regressed): HR 110, 1B 98, 2B 125, 3B 101, K 92, BB 110 — applied at half strength. Age: age 20 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (4.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.961.

Result: wOBA .424 → .375; ISO .193 → .166; BABIP .404 → .366. 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 A+Daytona Cubs · 387 PAwOBA .316 → .303 (−13)K% 10.6% → 15.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.59%	÷1.000	×1.420	—	—	15.04%
BB% (unintentional) /PA	4.65%	÷1.000	×0.750	—	×1.050	3.66%
HBP% /PA	0.78%	—	×0.930	—	×1.050	0.76%
Singles /BIP	26.81%	÷1.000	×0.920	×1.031	×1.050	26.71%
Doubles /BIP	5.36%	÷1.000	×0.960	×1.031	×1.050	5.57%
Triples /BIP	0.95%	÷1.000	×0.810	×1.031	×1.050	0.83%
Home runs /BIP	0.95%	÷1.000	×0.880	—	×1.050	0.87%

Factors used: league row FSL. 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 22.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.031.

Result: wOBA .316 → .303; ISO .089 → .086; BABIP .332 → .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).

2009 AATennessee Smokies · 122 PAwOBA .322 → .311 (−11)K% 9.8% → 12.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.84%	÷1.000	×1.220	—	—	12.00%
BB% (unintentional) /PA	8.20%	÷1.000	×0.680	—	×1.050	5.85%
HBP% /PA	0.00%	—	×0.840	—	×1.050	0.00%
Singles /BIP	23.23%	÷1.000	×0.920	×1.050	×1.050	23.56%
Doubles /BIP	6.06%	÷1.000	×0.910	×1.050	×1.050	6.08%
Triples /BIP	3.03%	÷1.000	×0.880	×1.050	×1.050	2.94%
Home runs /BIP	0.00%	÷1.000	×0.800	—	×1.050	0.00%

Factors used: league row SL. 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 24.8 → +5.0% on BB/HBP/hit rates (5.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .322 → .311; ISO .108 → .108; BABIP .323 → .326. 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 ROKAZL Cubs · 215 PAwOBA .357 → .269 (−88)K% 15.3% → 22.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.35%	÷1.000	×1.440	—	—	22.10%
BB% (unintentional) /PA	6.51%	÷1.000	×0.620	—	×1.022	4.13%
HBP% /PA	1.40%	—	×0.720	—	×1.022	1.03%
Singles /BIP	25.77%	÷1.000	×0.820	×1.007	×1.022	21.76%
Doubles /BIP	6.75%	÷1.000	×0.720	×1.007	×1.022	5.00%
Triples /BIP	3.07%	÷1.000	×0.720	×1.007	×1.022	2.27%
Home runs /BIP	1.84%	÷1.000	×0.780	—	×1.022	1.47%

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 ×1.007.

Result: wOBA .357 → .269; ISO .153 → .111; BABIP .360 → .293. 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 DSLDSL Cubs · 253 PAwOBA .331 → .236 (−94)K% 9.5% → 11.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.49%	÷1.000	×1.220	—	—	11.57%
BB% (unintentional) /PA	9.09%	÷1.000	×0.700	—	×1.022	6.51%
HBP% /PA	1.58%	—	×0.700	—	×1.022	1.13%
Singles /BIP	28.43%	÷1.000	×0.680	×1.032	×1.022	20.40%
Doubles /BIP	3.05%	÷1.000	×0.600	×1.032	×1.022	1.93%
Triples /BIP	1.02%	÷1.000	×0.600	×1.032	×1.022	0.64%
Home runs /BIP	1.02%	÷1.000	×0.470	—	×1.022	0.49%

Factors used: level-wide DSL 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 17 vs a level average of 18.5 → +2.2% on BB/HBP/hit rates (1.5 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.032.

Result: wOBA .331 → .236; ISO .072 → .043; BABIP .323 → .228. 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 — .