Steven Souza Jr.

PosRF

B/TR/R

Born1989-04-24

Age (2027)38

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2022

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2020	31	INTLGigantes del …	40	.147/.275/.147	0	0	34	—
2020	31	MLBCHC	31	.148/.258/.333	1	1	68	-0.2
2021	32	AAAOklahoma City…	225	.274/.397/.554	12	4	91	—	.206/.295/.392
2021	32	MLBLAD	36	.152/.222/.333	1	0	61	-0.4
2022	33	AAASEA	96	.267/.421/.533	5	3	91	—	.207/.316/.378
2022	33	MLBSEA	19	.158/.158/.158	0	0	-17	-0.4
2023	34	No MLB games played
2024	35	No MLB games played
2025	36	No MLB games played
2026	37	No MLB games played

Last 3 seasons WAR -1.0

Contract

No contract data on file.

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	18	ROK	GCL Nationals	—	167	144	28	9	0	4	18	46	4	4	1	194	301	340	641	146	253	28	11	293	17	—	—	—	—	—	—
2008	19	A	Hagerstown Suns	—	89	79	21	4	0	2	8	26	2	8	2	266	348	392	741	127	373	29	9	336	62	—	—	—	—	—	—
2009	20	A	Hagerstown Suns	—	514	447	106	18	3	4	54	116	7	25	10	237	329	318	646	81	306	23	11	297	48	—	—	—	—	—	—
2010	21	A	Hagerstown Suns	—	344	303	70	16	6	11	27	85	8	18	4	231	311	432	743	201	278	25	8	324	61	—	—	—	—	—	—
2011	22	A+	Potomac Nationals	—	478	390	89	17	2	11	75	131	8	25	9	228	364	367	730	138	308	27	16	334	51	—	—	—	—	—	—
2012	23	A+	Potomac Nationals	—	107	91	29	2	1	6	13	25	3	7	1	319	421	560	981	242	383	23	12	430	91	—	—	—	—	—	—
2012	23	A	Hagerstown Suns	—	293	262	76	20	2	17	22	49	3	7	7	290	352	576	928	286	294	17	8	394	85	—	—	—	—	—	—
2013	24	AA	Harrisburg Senators	—	323	273	82	23	1	15	41	76	5	20	6	300	401	557	958	256	360	24	13	413	128	—	—	—	—	—	—
2013	24	ROK	GCL Nationals	—	15	10	2	1	0	0	3	4	1	2	0	200	429	300	729	100	286	27	20	334	54	—	—	—	—	—	—
2013	24	INTL	Mesa Solar Sox	—	47	42	15	2	0	1	5	11	0	10	1	357	426	476	902	119	467	23	11	404	160	—	—	—	—	—	—
2014	25	MLB	Washington Nationals	—	26	23	3	0	0	2	3	7	0	0	0	130	231	391	622	261	71	27	12	275	73	-1	+0	-1	-5	+1	-0.6
2014	25	AAA	Syracuse Chiefs	—	407	346	121	25	2	18	52	75	3	26	7	350	439	590	1.028	240	398	18	13	442	145	—	—	—	—	—	—
2015	26	MLB	Tampa Bay Rays	—	426	373	84	15	1	16	46	144	5	12	6	225	318	399	718	174	318	34	11	322	104	+2	+0	-5	-5	+9	0.2
2016	27	MLB	Tampa Bay Rays	—	468	430	106	17	1	17	31	159	5	7	6	247	305	409	714	163	348	34	7	317	101	+1	-1	+0	-5	+10	0.5
2017	28	MLB	Tampa Bay Rays	—	617	523	125	21	2	30	84	179	7	16	4	239	352	459	811	220	302	29	14	359	129	+21	+2	+2	-7	+13	3.2
2018	29	MLB	Arizona Diamondbacks	—	272	241	53	15	3	5	28	75	3	6	1	220	309	369	678	149	298	28	10	307	87	-4	+1	-2	-3	+6	-0.3
2018	29	AAA	Reno Aces	—	18	16	7	0	2	3	2	3	0	2	0	438	500	1.250	1.750	812	400	17	11	704	220	—	—	—	—	—	—
2020	31	MLB	Chicago Cubs	—	31	27	4	2	0	1	4	15	0	1	0	148	258	333	591	185	273	48	13	269	68	-1	+0	-1	-1	+1	-0.2
2020	31	INTL	Gigantes del Cibao	—	40	34	5	0	0	0	5	16	1	0	0	147	275	147	422		278	40	12	219	34	—	—	—	—	—	—
2021	32	MLB	Los Angeles Dodgers	—	36	33	5	1	1	1	2	14	1	0	0	152	222	333	556	182	222	39	6	248	61	-2	+0	-0	-3	+1	-0.4
2021	32	AAA	Oklahoma City Dodgers	—	225	186	51	14	1	12	34	61	4	4	0	274	397	554	951	280	342	27	15	413	91	—	—	—	—	—	—
2022	33	MLB	Seattle Mariners	—	19	19	3	0	0	0	0	8	0	0	0	158	158	158	316		273	42	0	143	-17	-3	+0	-0	-1	+0	-0.4
2022	33	AAA	Tacoma Rainiers	—	96	75	20	5	0	5	19	25	1	3	1	267	421	533	954	267	326	26	20	415	91	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1895	1669	383	71	8	72	198	601	21	42	17	229	319	411	730	182	311	32	10	326	107	+15	+2	-7	-29	+41	2.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2007	18	ROK MLE	GCL Nationals	—	167	151	20	6	0	3	11	66	4	4	1	132	211	232	443	99	194	40	7	194	17	—	—	—	—	—	—
2008	19	A MLE	Hagerstown Suns	—	89	81	18	3	0	2	6	35	2	8	2	222	292	333	625	111	350	39	7	260	62	—	—	—	—	—	—
2009	20	A MLE	Hagerstown Suns	—	514	465	92	14	3	3	36	155	7	25	10	198	266	260	526	62	280	30	7	239	48	—	—	—	—	—	—
2010	21	A MLE	Hagerstown Suns	—	344	311	60	13	6	8	19	110	8	18	4	193	257	350	608	158	251	32	6	259	61	—	—	—	—	—	—
2011	22	A+ MLE	Potomac Nationals	—	478	418	70	12	2	9	47	191	8	25	9	167	264	270	535	103	266	40	10	243	51	—	—	—	—	—	—
2012	23	A+ MLE	Potomac Nationals	—	107	96	22	1	1	4	8	36	3	7	1	229	308	385	694	156	313	34	7	303	91	—	—	—	—	—	—
2012	23	A MLE	Hagerstown Suns	—	293	271	61	15	2	12	13	68	3	7	7	225	268	428	696	203	240	23	4	294	85	—	—	—	—	—	—
2013	24	AA MLE	Harrisburg Senators	—	323	285	78	23	1	12	29	89	5	20	6	274	351	488	839	214	342	28	9	358	128	—	—	—	—	—	—
2013	24	ROK MLE	GCL Nationals	—	15	11	2	1	0	0	2	6	1	2	0	182	357	273	630	91	214	40	13	248	54	—	—	—	—	—	—
2014	25	MLB MLE	Washington Nationals	—	26	23	3	0	0	2	3	7	0	0	0	130	231	391	622	261	71	27	12	275	73	-1	+0	-1	-5	+1	-0.6
2014	25	AAA MLE	Syracuse Chiefs	—	407	362	112	21	2	16	36	93	3	26	7	309	377	511	888	202	363	23	9	383	145	—	—	—	—	—	—
2015	26	MLB MLE	Tampa Bay Rays	—	426	373	83	15	1	16	46	144	5	12	6	223	316	397	713	174	318	34	11	322	104	+2	+0	-5	-5	+9	0.2
2016	27	MLB MLE	Tampa Bay Rays	—	468	430	105	17	1	17	31	159	5	7	6	244	303	407	710	163	348	34	7	317	101	+1	-1	+0	-5	+10	0.5
2017	28	MLB MLE	Tampa Bay Rays	—	617	525	125	21	2	31	82	179	7	16	4	238	349	463	811	225	302	29	13	358	129	+21	+2	+2	-7	+13	3.2
2018	29	MLB MLE	Arizona Diamondbacks	—	272	241	50	13	2	5	28	75	3	6	1	207	298	340	638	133	298	28	10	297	87	-4	+1	-2	-3	+6	-0.3
2018	29	AAA MLE	Reno Aces	—	18	17	5	0	1	2	1	4	0	2	0	294	333	765	1.098	471	288	22	6	493	220	—	—	—	—	—	—
2020	31	MLB MLE	Chicago Cubs	—	31	27	4	2	0	1	4	15	0	1	0	148	258	333	591	185	273	48	13	269	68	-1	+0	-1	-1	+1	-0.2
2021	32	MLB MLE	Los Angeles Dodgers	—	36	33	5	1	1	1	2	14	1	0	0	152	222	333	556	182	222	39	6	259	61	-2	+0	-0	-3	+1	-0.4
2021	32	AAA MLE	Oklahoma City Dodgers	—	225	199	41	11	1	8	21	74	4	4	0	206	295	392	687	186	281	33	9	303	91	—	—	—	—	—	—
2022	33	MLB MLE	Seattle Mariners	—	19	19	3	0	0	0	0	8	0	0	0	158	158	158	316		273	42	0	144	-17	-3	+0	-0	-1	+0	-0.4
2022	33	AAA MLE	Tacoma Rainiers	—	96	82	17	5	0	3	12	29	1	3	1	207	316	378	694	171	263	30	12	302	91	—	—	—	—	—	—
2007	18	ROK MLE	GCL Nationals	—	167	151	20	6	0	3	11	66	4	4	1	132	211	232	443	99	205	40	7	194	17	—	—	—	—	—	—
2007	18	ROK RAW	GCL Nationals	—	167	144	28	9	0	4	18	46	4	4	1	194	301	340	641	146	253	28	11	293	17	—	—	—	—	—	—
2008	19	A MLE	Hagerstown Suns	—	89	81	18	3	0	2	6	35	2	8	2	222	292	333	625	111	364	39	7	260	62	—	—	—	—	—	—
2008	19	A RAW	Hagerstown Suns	—	89	79	21	4	0	2	8	26	2	8	2	266	348	392	741	127	373	29	9	336	62	—	—	—	—	—	—
2009	20	A MLE	Hagerstown Suns	—	514	465	92	14	3	3	36	155	7	25	10	198	266	260	526	62	284	30	7	239	48	—	—	—	—	—	—
2009	20	A RAW	Hagerstown Suns	—	514	447	106	18	3	4	54	116	7	25	10	237	329	318	646	81	306	23	11	297	48	—	—	—	—	—	—
2010	21	A MLE	Hagerstown Suns	—	344	311	60	13	6	8	19	110	8	18	4	193	257	350	608	158	263	32	6	259	61	—	—	—	—	—	—
2010	21	A RAW	Hagerstown Suns	—	344	303	70	16	6	11	27	85	8	18	4	231	311	432	743	201	278	25	8	324	61	—	—	—	—	—	—
2011	22	A+ MLE	Potomac Nationals	—	478	418	70	12	2	9	47	191	8	25	9	167	264	270	535	103	274	40	10	243	51	—	—	—	—	—	—
2011	22	A+ RAW	Potomac Nationals	—	478	390	89	17	2	11	75	131	8	25	9	228	364	367	730	138	308	27	16	334	51	—	—	—	—	—	—
2012	23	A MLE	2 teams	—	400	367	83	17	2	16	21	104	6	14	8	226	279	414	693	188	266	26	5	296	87	—	—	—	—	—	—
2012	23	A RAW	2 teams	—	400	353	105	22	3	23	35	74	6	14	8	297	371	572	943	275	314	18	9	403	87	—	—	—	—	—	—
2013	24	AA MLE	3 teams	—	385	339	91	27	1	14	35	108	6	32	7	268	347	478	825	209	347	28	9	353	125	—	—	—	—	—	—
2013	24	AA RAW	3 teams	—	385	325	99	26	1	16	49	91	6	32	7	305	405	538	944	234	372	24	13	409	125	—	—	—	—	—	—
2014	25	AAA MLE	2 teams	—	433	385	115	21	2	18	39	100	3	26	7	299	368	504	872	205	355	23	9	377	141	—	—	—	—	—	—
2014	25	AAA RAW	2 teams	—	433	369	124	25	2	20	55	82	3	26	7	336	426	577	1.003	241	381	19	13	432	141	—	—	—	—	—	—
2015	26	MLB MLE	Tampa Bay Rays	—	426	373	83	15	1	16	46	144	5	12	6	223	316	397	713	174	313	34	11	322	104	+2	+0	-5	-5	+9	0.2
2015	26	MLB RAW	Tampa Bay Rays	—	426	373	84	15	1	16	46	144	5	12	6	225	318	399	718	174	318	34	11	322	104	+2	+0	-5	-5	+9	0.2
2016	27	MLB MLE	Tampa Bay Rays	—	468	430	105	17	1	17	31	159	5	7	6	244	303	407	710	163	344	34	7	317	101	+1	-1	+0	-5	+10	0.5
2016	27	MLB RAW	Tampa Bay Rays	—	468	430	106	17	1	17	31	159	5	7	6	247	305	409	714	163	348	34	7	317	101	+1	-1	+0	-5	+10	0.5
2017	28	MLB MLE	Tampa Bay Rays	—	617	525	125	21	2	31	82	179	7	16	4	238	349	463	811	225	297	29	13	358	129	+21	+2	+2	-7	+13	3.2
2017	28	MLB RAW	Tampa Bay Rays	—	617	523	125	21	2	30	84	179	7	16	4	239	352	459	811	220	302	29	14	359	129	+21	+2	+2	-7	+13	3.2
2018	29	MLB MLE	2 teams	—	290	258	56	13	4	7	29	79	3	8	1	217	303	380	683	163	285	27	10	309	95	-2	+1	-2	-3	+6	0.1
2018	29	MLB RAW	2 teams	—	290	257	60	15	5	8	30	78	3	8	1	233	321	424	745	191	304	27	10	331	95	-2	+1	-2	-3	+6	0.1
2020	31	INTL MLE	2 teams	—	71	61	8	4	0	2	9	34	1	1	0	131	254	295	549	164	240	48	13	269	68	—	—	—	—	—	—
2020	31	INTL RAW	2 teams	—	71	61	9	2	0	1	9	31	1	1	0	148	268	230	497	82	276	44	13	241	68	—	—	—	—	—	—
2021	32	AAA MLE	2 teams	—	261	232	46	12	2	9	23	88	5	4	0	198	285	384	668	185	272	34	9	297	87	—	—	—	—	—	—
2021	32	AAA RAW	2 teams	—	261	219	56	15	2	13	36	75	5	4	0	256	373	521	894	265	326	29	14	390	87	—	—	—	—	—	—
2022	33	AAA MLE	2 teams	—	115	101	20	5	0	3	12	37	1	3	1	198	289	337	626	139	274	32	10	276	73	—	—	—	—	—	—
2022	33	AAA RAW	2 teams	—	115	94	23	5	0	5	19	33	1	3	1	245	377	457	835	213	316	29	17	370	73	—	—	—	—	—	—
2007	18	ROK MLE	GCL Nationals	—	167	150	20	6	0	3	11	66	4	4	1	133	211	233	444	100	194	40	7	194	17	—	—	—	—	—	—
2008	19	A MLE	Hagerstown Suns	—	89	81	18	3	0	2	6	35	2	8	2	222	292	333	625	111	350	39	7	260	62	—	—	—	—	—	—
2009	20	A MLE	Hagerstown Suns	—	514	466	92	14	3	3	36	155	7	25	10	197	266	260	525	62	280	30	7	239	48	—	—	—	—	—	—
2010	21	A MLE	Hagerstown Suns	—	344	314	60	13	6	8	19	110	8	18	4	191	257	347	605	156	251	32	6	259	61	—	—	—	—	—	—
2011	22	A+ MLE	Potomac Nationals	—	478	420	70	12	2	9	47	191	8	25	9	167	264	269	533	102	266	40	10	243	51	—	—	—	—	—	—
2012	23	A MLE	2 teams	—	400	370	83	17	2	16	21	104	6	14	8	224	279	411	690	186	260	26	5	296	87	—	—	—	—	—	—
2013	24	AA MLE	3 teams	—	385	341	91	27	1	14	35	108	6	32	7	267	347	475	822	208	336	28	9	353	125	—	—	—	—	—	—
2014	25	AAA MLE	2 teams	—	433	388	115	21	2	18	39	100	3	26	7	296	368	500	868	204	345	23	9	377	141	—	—	—	—	—	—
2015	26	MLB MLE	Tampa Bay Rays	—	426	372	83	15	1	16	46	144	5	12	6	223	316	398	714	175	318	34	11	322	104	—	—	—	—	—	—
2016	27	MLB MLE	Tampa Bay Rays	—	468	429	105	17	1	17	31	159	5	7	6	245	303	408	711	163	348	34	7	317	101	—	—	—	—	—	—
2017	28	MLB MLE	Tampa Bay Rays	—	617	523	125	21	2	31	82	179	7	16	4	239	349	465	813	226	302	29	13	358	129	—	—	—	—	—	—
2018	29	MLB MLE	2 teams	—	290	256	56	13	4	7	29	79	3	8	1	219	303	383	686	164	298	27	10	309	95	—	—	—	—	—	—
2020	31	INTL MLE	2 teams	—	71	61	8	4	0	2	9	34	1	1	0	131	254	295	549	164	273	48	13	269	68	—	—	—	—	—	—
2021	32	AAA MLE	2 teams	—	261	231	46	12	2	9	23	88	5	4	0	199	285	385	670	186	273	34	9	297	87	—	—	—	—	—	—
2022	33	AAA MLE	2 teams	—	115	101	20	5	0	3	12	37	1	3	1	198	289	337	626	139	265	32	10	276	73	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1895	1669	383	71	8	72	198	601	21	42	17	229	319	411	730	182	311	32	10	326	90	+15	+2	-7	-29	+41	2.2
/ 162G	—	A+C		—	650	572	132	24	3	25	68	206	7	14	6	231	319	414	734	184	313	32	10	326	90	+5	+1	-2	-10	+14	0.8
Career	—	MLE		—	5058	4497	992	200	26	158	446	1589	71	203	66	221	301	382	683	161	299	31	9	302	90	+15	+2	-7	-29	+41	2.2
/ 162G	—	MLE		—	650	578	127	26	3	20	57	204	9	26	8	220	300	379	679	159	298	31	9	302	90	+5	+1	-2	-10	+14	0.8

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 AAATacoma Rainiers · 96 PAwOBA .409 → .302 (−107)K% 26.0% → 30.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.04%	÷1.020	×1.200	—	—	30.65%
BB% (unintentional) /PA	19.79%	÷1.048	×0.690	—	×0.942	12.27%
HBP% /PA	1.04%	—	×0.940	—	×0.942	0.92%
Singles /BIP	20.00%	÷1.013	×0.930	×0.950	×0.942	16.43%
Doubles /BIP	10.00%	÷0.839	×0.830	×0.950	×0.942	8.85%
Triples /BIP	0.00%	÷0.902	×0.970	×0.950	×0.942	0.00%
Home runs /BIP	10.00%	÷1.144	×0.700	—	×0.942	5.77%

Factors used: league row International League. Park (home-season share, regressed): HR 129, 1B 103, 2B 68, 3B 80, K 104, BB 110 — 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 ×0.950.

Result: wOBA .409 → .302; ISO .267 → .188; BABIP .326 → .263. 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 AAAOklahoma City Dodgers · 225 PAwOBA .403 → .303 (−100)K% 27.1% → 32.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.11%	÷0.994	×1.200	—	—	32.72%
BB% (unintentional) /PA	14.67%	÷1.015	×0.690	—	×0.952	9.50%
HBP% /PA	1.78%	—	×0.940	—	×0.952	1.59%
Singles /BIP	19.20%	÷0.958	×0.930	×0.950	×0.952	16.86%
Doubles /BIP	11.20%	÷0.941	×0.830	×0.950	×0.952	8.94%
Triples /BIP	0.80%	÷0.900	×0.920	×0.950	×0.952	0.74%
Home runs /BIP	9.60%	÷1.016	×0.700	—	×0.952	6.30%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 103, 1B 92, 2B 88, 3B 80, K 99, BB 103 — applied at half strength. Age: age 32 vs a level average of 27.2 → −4.8% on BB/HBP/hit rates (4.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .403 → .303; ISO .280 → .199; BABIP .342 → .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).

2018 AAAReno Aces · 18 PAwOBA .683 → .493 (−190)K% 16.7% → 21.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.67%	÷0.991	×1.290	—	—	21.70%
BB% (unintentional) /PA	11.11%	÷1.069	×0.710	—	×0.982	7.24%
HBP% /PA	0.00%	—	×0.980	—	×0.982	0.00%
Singles /BIP	15.38%	÷1.024	×0.900	—	×0.982	13.28%
Doubles /BIP	0.00%	÷1.117	×0.810	—	×0.982	0.00%
Triples /BIP	15.38%	÷1.150	×0.810	—	×0.982	10.64%
Home runs /BIP	23.08%	÷1.044	×0.780	—	×0.982	16.93%

Factors used: league row PCL. Park (home-season share, regressed): HR 109, 1B 105, 2B 123, 3B 130, K 98, BB 114 — 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).

Result: wOBA .683 → .493; ISO .812 → .576; BABIP .400 → .288. 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 AAASyracuse Chiefs · 407 PAwOBA .435 → .383 (−52)K% 18.4% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.43%	÷0.965	×1.200	—	—	22.91%
BB% (unintentional) /PA	12.04%	÷0.972	×0.690	—	×1.033	8.83%
HBP% /PA	0.74%	—	×0.940	—	×1.033	0.72%
Singles /BIP	28.04%	÷1.003	×0.930	×0.991	×1.033	26.61%
Doubles /BIP	9.23%	÷1.027	×0.830	×0.991	×1.033	7.63%
Triples /BIP	0.74%	÷1.063	×0.970	×0.991	×1.033	0.69%
Home runs /BIP	6.64%	÷0.985	×0.840	—	×1.033	5.85%

Factors used: league row IL. Park (home-season share, regressed): HR 97, 1B 101, 2B 105, 3B 113, K 93, BB 94 — 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 ×0.991.

Result: wOBA .435 → .383; ISO .240 → .211; BABIP .398 → .363. 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 AAHarrisburg Senators · 323 PAwOBA .407 → .358 (−48)K% 23.5% → 27.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.53%	÷1.043	×1.220	—	—	27.52%
BB% (unintentional) /PA	12.38%	÷0.990	×0.700	—	×1.012	8.86%
HBP% /PA	1.55%	—	×0.850	—	×1.012	1.33%
Singles /BIP	21.83%	÷1.011	×0.970	×0.993	×1.012	21.04%
Doubles /BIP	11.68%	÷0.883	×0.860	×0.993	×1.012	11.42%
Triples /BIP	0.51%	÷1.150	×0.950	×0.993	×1.012	0.42%
Home runs /BIP	7.61%	÷1.012	×0.780	—	×1.012	5.94%

Factors used: league row EL. Park (home-season share, regressed): HR 102, 1B 102, 2B 77, 3B 130, K 109, BB 98 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.

Result: wOBA .407 → .358; ISO .256 → .222; BABIP .360 → .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).

2013 ROKGCL Nationals · 15 PAwOBA .351 → .248 (−104)K% 26.7% → 38.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.67%	÷1.000	×1.440	—	—	38.40%
BB% (unintentional) /PA	20.00%	÷1.000	×0.620	—	×0.955	11.84%
HBP% /PA	6.67%	—	×0.720	—	×0.955	4.58%
Singles /BIP	16.67%	÷1.000	×0.820	—	×0.955	13.05%
Doubles /BIP	16.67%	÷1.000	×0.720	—	×0.955	11.46%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.955	0.00%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×0.955	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 24 vs a level average of 19.5 → −4.5% on BB/HBP/hit rates (4.5 yr older than average).

Result: wOBA .351 → .248; ISO .100 → .078; BABIP .286 → .214. 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 AHagerstown Suns · 293 PAwOBA .386 → .294 (−92)K% 16.7% → 23.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.72%	÷0.970	×1.340	—	—	23.11%
BB% (unintentional) /PA	6.48%	÷0.960	×0.660	—	×0.990	4.41%
HBP% /PA	1.02%	—	×0.770	—	×0.990	0.78%
Singles /BIP	17.37%	÷0.987	×0.920	×0.954	×0.990	15.30%
Doubles /BIP	9.39%	÷1.009	×0.820	×0.954	×0.990	7.21%
Triples /BIP	0.94%	÷1.150	×0.940	×0.954	×0.990	0.72%
Home runs /BIP	7.98%	÷1.150	×0.820	—	×0.990	5.64%

Factors used: league row SAL. Park (home-season share, regressed): HR 130, 1B 97, 2B 102, 3B 130, K 94, BB 92 — applied at half strength. Age: age 23 vs a level average of 22.0 → −1.0% on BB/HBP/hit rates (1.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.954.

Result: wOBA .386 → .294; ISO .286 → .205; BABIP .294 → .240. 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 A+Potomac Nationals · 107 PAwOBA .419 → .303 (−116)K% 23.4% → 33.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.36%	÷0.991	×1.420	—	—	33.49%
BB% (unintentional) /PA	12.15%	÷1.029	×0.630	—	×0.998	7.42%
HBP% /PA	2.80%	—	×0.860	—	×0.998	2.41%
Singles /BIP	30.30%	÷1.086	×0.940	×0.981	×0.998	25.67%
Doubles /BIP	3.03%	÷1.028	×0.830	×0.981	×0.998	2.39%
Triples /BIP	1.52%	÷1.150	×0.800	×0.981	×0.998	1.03%
Home runs /BIP	9.09%	÷1.159	×0.900	—	×0.998	7.05%

Factors used: league row CAR. Park (home-season share, regressed): HR 132, 1B 117, 2B 106, 3B 130, K 98, BB 106 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.981.

Result: wOBA .419 → .303; ISO .242 → .171; BABIP .383 → .313. 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 — .