Pedro Severino

PosC

B/TR/R

Born1993-07-20

Age (2027)34

No MLB projection yet. Career stats below are historical.

Overview

INTL

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2024	31	INTLLeones del Es…	64	.241/.328/.315	0	1	78	—
2025	32	INTLLeones del Es…	78	.206/.333/.270	1	1	75	—
2026	33	INTLToros del Este	20	.316/.350/.526	1	2	146	—

Contract

No contract data on file.

Skills · percentileStatcast 2020-2022

xwOBA56

Barrel%43

Avg EV35

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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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)
2011	18	ROK	GCL Nationals	—	130	115	21	4	1	2	10	27	2	0	0	183	258	287	545	104	221	21	8	246	6	—	—	—	—	—	—
2012	19	ROK	GCL Nationals	—	125	109	24	3	1	0	9	9	4	0	0	220	303	266	569	46	238	7	7	262	22	—	—	—	—	—	—
2013	20	A	Hagerstown Suns	—	302	282	68	19	2	1	13	54	1	1	0	241	277	333	610	92	291	18	4	269	32	—	—	—	—	—	—
2014	21	A+	Potomac Nationals	—	326	291	72	15	1	9	21	57	5	2	0	247	309	399	708	151	276	17	6	308	58	—	—	—	—	—	—
2014	21	INTL	Mesa Solar Sox	—	48	44	11	2	1	0	2	7	1	0	0	250	298	341	639	91	289	15	4	282	77	—	—	—	—	—	—
2015	22	AA	Harrisburg Senators	—	357	329	81	13	0	5	19	51	1	1	2	246	289	331	621	85	276	14	5	275	57	—	—	—	—	—	—
2015	22	INTL	Aguilas Cibaenas	—	61	58	12	4	0	2	2	14	0	0	0	207	233	379	613	172	238	23	3	264	65	—	—	—	—	—	—
2016	23	MLB	Washington Nationals	—	34	28	9	2	0	2	5	3	1	0	0	321	441	607	1.048	286	304	9	15	455	193	+4	+0	+0	+7	+1	1.2
2016	23	AAA	Syracuse Chiefs	—	317	291	79	13	0	2	19	45	2	3	4	271	321	337	657	65	310	14	6	295	55	—	—	—	—	—	—
2016	23	INTL	Aguilas Cibaenas	—	18	17	4	0	1	0	0	5	0	0	0	235	235	353	588	118	308	28	0	241	49	—	—	—	—	—	—
2017	24	MLB	Washington Nationals	—	31	29	5	1	0	0	2	10	0	0	0	172	226	207	433	34	263	32	6	203	8	-3	+0	+0	+6	+1	0.4
2017	24	AAA	Syracuse Chiefs	—	227	211	51	4	0	5	15	43	0	1	1	242	292	332	624	90	280	19	7	282	49	—	—	—	—	—	—
2017	24	INTL	Aguilas Cibaenas	—	65	55	15	1	1	1	7	8	0	1	0	273	355	382	737	109	298	12	11	319	102	—	—	—	—	—	—
2018	25	MLB	Washington Nationals	—	213	190	32	9	0	2	18	47	4	1	0	168	255	247	502	79	211	22	8	236	36	-16	+0	+6	+6	+5	0.0
2018	25	AAA	Syracuse Chiefs	—	136	130	35	5	1	6	5	23	0	0	0	269	296	462	758	192	284	17	4	330	68	—	—	—	—	—	—
2019	26	MLB	Baltimore Orioles	—	341	305	76	13	0	13	29	73	4	3	1	249	322	420	742	170	285	21	9	329	103	+1	+0	-7	+6	+7	0.8
2020	27	MLB	Baltimore Orioles	—	178	160	40	5	1	5	16	40	1	1	0	250	322	388	710	138	304	22	9	318	97	-1	+0	-3	+3	+4	0.4
2021	28	MLB	Baltimore Orioles	—	419	379	94	18	0	11	34	109	1	0	0	248	312	383	694	135	314	26	8	309	90	-5	+0	-11	+7	+9	0.1
2022	29	MLB	Milwaukee Brewers	—	21	18	4	2	0	0	3	7	0	0	0	222	333	333	667	111	364	33	14	308	101	+0	+0	+0	+5	+0	0.6
2022	29	AAA	Nashville Sounds	—	126	117	36	10	0	4	6	27	2	2	0	308	352	496	848	188	368	21	5	371	86	—	—	—	—	—	—
2022	29	AA	Biloxi Shuckers	—	27	23	10	0	0	1	4	4	0	1	0	435	519	565	1.084	130	500	15	15	482	138	—	—	—	—	—	—
2022	29	INTL	Leones del Escogido	—	102	91	24	5	1	1	6	20	1	3	1	264	316	374	690	110	311	20	6	298	88	—	—	—	—	—	—
2023	30	AAA	Tacoma Rainiers	—	267	241	59	12	0	10	25	55	1	7	0	245	318	419	737	174	278	21	9	329	49	—	—	—	—	—	—
2023	30	INTL	Leones del Escogido	—	31	28	5	0	0	0	2	4	0	0	0	179	233	179	412		200	13	6	191	15	—	—	—	—	—	—
2024	31	INTL	Leones del Escogido	—	64	54	13	4	0	0	7	11	0	1	1	241	328	315	643	74	289	17	11	284	78	—	—	—	—	—	—
2025	32	INTL	Leones del Escogido	—	78	63	13	1	0	1	11	15	1	1	0	206	333	270	603	63	255	19	14	279	75	—	—	—	—	—	—
2026	33	INTL	Toros del Este	—	20	19	6	1	0	1	1	4	0	2	0	316	350	526	876	211	357	20	5	384	146	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1237	1109	260	50	1	33	107	289	11	5	1	234	308	371	679	136	286	23	9	304	92	-12	+1	-14	+40	+27	4.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2011	18	ROK MLE	GCL Nationals	—	130	120	17	3	1	2	6	39	2	0	0	142	195	233	429	92	181	30	5	177	6	—	—	—	—	—	—
2012	19	ROK MLE	GCL Nationals	—	125	112	20	2	1	0	6	13	4	0	0	179	246	214	460	36	191	10	5	201	22	—	—	—	—	—	—
2013	20	A MLE	Hagerstown Suns	—	302	286	57	14	2	1	9	72	1	1	0	199	226	273	499	73	253	24	3	216	32	—	—	—	—	—	—
2014	21	A+ MLE	Potomac Nationals	—	326	298	63	12	1	8	14	81	5	2	0	211	259	339	598	128	247	25	4	254	58	—	—	—	—	—	—
2015	22	AA MLE	Harrisburg Senators	—	357	336	81	11	0	4	12	61	1	1	2	241	269	310	579	68	275	17	3	253	57	—	—	—	—	—	—
2016	23	MLB MLE	Washington Nationals	—	34	28	9	2	0	2	5	3	1	0	0	321	441	607	1.048	286	304	9	15	454	193	+4	+0	+0	+7	+1	1.2
2016	23	AAA MLE	Syracuse Chiefs	—	317	298	70	11	0	2	12	57	2	3	4	235	269	292	561	57	277	18	4	250	55	—	—	—	—	—	—
2017	24	MLB MLE	Washington Nationals	—	31	30	5	1	0	0	1	10	0	0	0	167	194	200	394	33	263	32	3	180	8	-3	+0	+0	+6	+1	0.4
2017	24	AAA MLE	Syracuse Chiefs	—	227	216	46	3	0	4	10	51	0	1	1	213	248	282	530	69	261	22	4	240	49	—	—	—	—	—	—
2018	25	MLB MLE	Washington Nationals	—	213	194	32	9	0	2	14	47	4	1	0	165	236	242	478	77	211	22	7	222	36	-16	+0	+6	+6	+5	0.0
2018	25	AAA MLE	Syracuse Chiefs	—	136	131	29	4	1	4	4	26	0	0	0	221	244	359	603	137	252	19	3	268	68	—	—	—	—	—	—
2019	26	MLB MLE	Baltimore Orioles	—	341	305	75	13	0	12	29	73	4	3	1	246	320	407	726	161	285	21	9	321	103	+1	+0	-7	+6	+7	0.8
2020	27	MLB MLE	Baltimore Orioles	—	178	160	40	5	1	5	16	40	1	1	0	250	322	388	710	138	304	22	9	311	97	-1	+0	-3	+3	+4	0.4
2021	28	MLB MLE	Baltimore Orioles	—	419	380	92	18	0	10	33	109	1	0	0	242	304	368	673	126	314	26	8	301	90	-5	+0	-11	+7	+9	0.1
2022	29	MLB MLE	Milwaukee Brewers	—	21	18	4	2	0	0	3	7	0	0	0	222	333	333	667	111	364	33	14	317	101	+0	+0	+0	+5	+0	0.6
2022	29	AAA MLE	Nashville Sounds	—	126	119	30	8	0	3	4	33	2	2	0	252	288	395	683	143	324	26	3	296	86	—	—	—	—	—	—
2022	29	AA MLE	Biloxi Shuckers	—	27	24	9	0	0	1	3	5	0	1	0	375	444	500	944	125	410	19	11	372	138	—	—	—	—	—	—
2023	30	AAA MLE	Tacoma Rainiers	—	267	249	48	10	0	6	17	64	1	7	0	193	247	305	552	112	234	24	6	241	49	—	—	—	—	—	—
2011	18	ROK MLE	GCL Nationals	—	130	120	17	3	1	2	6	39	2	0	0	142	195	233	429	92	190	30	5	177	6	—	—	—	—	—	—
2011	18	ROK RAW	GCL Nationals	—	130	115	21	4	1	2	10	27	2	0	0	183	258	287	545	104	221	21	8	246	6	—	—	—	—	—	—
2012	19	ROK MLE	GCL Nationals	—	125	112	20	2	1	0	6	13	4	0	0	179	246	214	460	36	200	10	5	201	22	—	—	—	—	—	—
2012	19	ROK RAW	GCL Nationals	—	125	109	24	3	1	0	9	9	4	0	0	220	303	266	569	46	238	7	7	262	22	—	—	—	—	—	—
2013	20	A MLE	Hagerstown Suns	—	302	286	57	14	2	1	9	72	1	1	0	199	226	273	499	73	259	24	3	216	32	—	—	—	—	—	—
2013	20	A RAW	Hagerstown Suns	—	302	282	68	19	2	1	13	54	1	1	0	241	277	333	610	92	291	18	4	269	32	—	—	—	—	—	—
2014	21	A+ MLE	2 teams	—	374	342	71	13	1	9	16	93	6	2	0	208	255	330	586	123	254	25	4	254	58	—	—	—	—	—	—
2014	21	A+ RAW	2 teams	—	374	335	83	17	2	9	23	64	6	2	0	248	308	391	699	143	278	17	6	305	58	—	—	—	—	—	—
2015	22	AA MLE	2 teams	—	418	393	96	13	0	5	15	71	1	1	2	244	274	316	589	71	285	17	4	253	57	—	—	—	—	—	—
2015	22	AA RAW	2 teams	—	418	387	93	17	0	7	21	65	1	1	2	240	281	339	620	98	271	16	5	273	57	—	—	—	—	—	—
2016	23	AAA MLE	3 teams	—	369	342	84	14	0	4	18	63	3	3	4	246	289	322	611	76	286	17	5	270	69	—	—	—	—	—	—
2016	23	AAA RAW	3 teams	—	369	336	92	15	1	4	24	53	3	3	4	274	328	360	688	86	310	14	7	307	69	—	—	—	—	—	—
2017	24	AAA MLE	3 teams	—	323	305	65	5	0	6	14	77	0	2	1	213	248	289	536	75	263	24	4	233	44	—	—	—	—	—	—
2017	24	AAA RAW	3 teams	—	323	295	71	6	1	6	24	61	0	2	1	241	298	329	627	88	283	19	7	282	44	—	—	—	—	—	—
2018	25	MLB MLE	2 teams	—	349	325	61	13	1	6	18	73	4	1	0	188	239	289	528	102	222	21	5	240	48	-21	+0	+6	+6	+8	-0.2
2018	25	MLB RAW	2 teams	—	349	320	67	14	1	8	23	70	4	1	0	209	271	334	605	125	242	20	7	272	48	-21	+0	+6	+6	+8	-0.2
2019	26	MLB MLE	Baltimore Orioles	—	341	305	75	13	0	12	29	73	4	3	1	246	320	407	726	161	284	21	9	321	103	+1	+0	-7	+6	+7	0.8
2019	26	MLB RAW	Baltimore Orioles	—	341	305	76	13	0	13	29	73	4	3	1	249	322	420	742	170	285	21	9	329	103	+1	+0	-7	+6	+7	0.8
2020	27	MLB MLE	Baltimore Orioles	—	178	160	40	5	1	5	16	40	1	1	0	250	322	388	710	138	304	22	9	311	97	-1	+0	-3	+3	+4	0.4
2020	27	MLB RAW	Baltimore Orioles	—	178	160	40	5	1	5	16	40	1	1	0	250	322	388	710	138	304	22	9	318	97	-1	+0	-3	+3	+4	0.4
2021	28	MLB MLE	Baltimore Orioles	—	419	380	92	18	0	10	33	109	1	0	0	242	304	368	673	126	308	26	8	301	90	-5	+0	-11	+7	+9	0.1
2021	28	MLB RAW	Baltimore Orioles	—	419	379	94	18	0	11	34	109	1	0	0	248	312	383	694	135	314	26	8	309	90	-5	+0	-11	+7	+9	0.1
2022	29	AAA MLE	4 teams	—	276	253	68	16	0	6	15	72	3	6	1	269	317	403	721	134	344	26	5	310	96	—	—	—	—	—	—
2022	29	AAA RAW	4 teams	—	276	249	74	17	1	6	19	58	3	6	1	297	354	446	800	149	358	21	7	350	96	—	—	—	—	—	—
2023	30	AAA MLE	2 teams	—	298	278	54	11	0	7	18	72	1	7	0	194	246	309	555	115	235	24	6	241	49	—	—	—	—	—	—
2023	30	AAA RAW	2 teams	—	298	269	64	12	0	10	27	59	1	7	0	238	310	394	704	156	269	20	9	315	49	—	—	—	—	—	—
2024	31	INTL MLE	Leones del Escogido	—	64	54	13	4	0	0	7	11	0	1	1	241	328	315	643	74	289	17	11	—	—	—	—	—	—	—	—
2024	31	INTL RAW	Leones del Escogido	—	64	54	13	4	0	0	7	11	0	1	1	241	328	315	643	74	289	17	11	284	78	—	—	—	—	—	—
2025	32	INTL MLE	Leones del Escogido	—	78	63	13	1	0	1	11	15	1	1	0	206	333	270	603	63	255	19	14	—	—	—	—	—	—	—	—
2025	32	INTL RAW	Leones del Escogido	—	78	63	13	1	0	1	11	15	1	1	0	206	333	270	603	63	255	19	14	279	75	—	—	—	—	—	—
2026	33	INTL MLE	Toros del Este	—	20	19	6	1	0	1	1	4	0	2	0	316	350	526	876	211	357	20	5	—	—	—	—	—	—	—	—
2026	33	INTL RAW	Toros del Este	—	20	19	6	1	0	1	1	4	0	2	0	316	350	526	876	211	357	20	5	384	146	—	—	—	—	—	—
2011	18	ROK MLE	GCL Nationals	—	130	121	17	3	1	2	6	39	2	0	0	140	195	231	427	91	181	30	5	177	6	—	—	—	—	—	—
2012	19	ROK MLE	GCL Nationals	—	125	114	20	2	1	0	6	13	4	0	0	175	246	211	456	35	191	10	5	201	22	—	—	—	—	—	—
2013	20	A MLE	Hagerstown Suns	—	302	289	57	14	2	1	9	72	1	1	0	197	226	270	496	73	253	24	3	216	32	—	—	—	—	—	—
2014	21	A+ MLE	2 teams	—	374	349	71	13	1	9	16	93	6	2	0	203	255	324	579	120	247	25	4	254	58	—	—	—	—	—	—
2015	22	AA MLE	2 teams	—	418	399	96	13	0	5	15	71	1	1	2	241	274	311	585	70	275	17	4	253	57	—	—	—	—	—	—
2016	23	AAA MLE	3 teams	—	369	345	84	14	0	4	18	63	3	3	4	243	289	319	608	75	280	17	5	270	69	—	—	—	—	—	—
2017	24	AAA MLE	3 teams	—	323	306	65	5	0	6	14	77	0	2	1	212	248	288	535	75	261	24	4	233	44	—	—	—	—	—	—
2018	25	MLB MLE	2 teams	—	349	324	61	13	1	6	18	73	4	1	0	188	239	290	529	102	227	21	5	240	48	—	—	—	—	—	—
2019	26	MLB MLE	Baltimore Orioles	—	341	305	75	13	0	12	29	73	4	3	1	246	320	407	726	161	285	21	9	321	103	—	—	—	—	—	—
2020	27	MLB MLE	Baltimore Orioles	—	178	159	40	5	1	5	16	40	1	1	0	252	322	390	712	138	304	22	9	311	97	—	—	—	—	—	—
2021	28	MLB MLE	Baltimore Orioles	—	419	382	92	18	0	10	33	109	1	0	0	241	304	366	671	126	314	26	8	301	90	—	—	—	—	—	—
2022	29	AAA MLE	4 teams	—	276	256	68	16	0	6	15	72	3	6	1	266	317	398	716	133	342	26	5	310	96	—	—	—	—	—	—
2023	30	AAA MLE	2 teams	—	298	277	54	11	0	7	18	72	1	7	0	195	246	310	556	116	234	24	6	241	49	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1237	1109	260	50	1	33	107	289	11	5	1	234	308	371	679	136	286	23	9	304	56	-12	+1	-14	+40	+27	4.3
/ 162G	—	A+C		—	650	583	136	26	1	17	56	152	6	3	1	233	307	369	676	136	285	23	9	304	56	-6	+0	-7	+21	+14	2.3
Career	—	MLE		—	4064	3737	832	146	7	75	232	897	32	31	10	223	274	326	600	103	270	22	6	251	56	-12	+1	-14	+40	+27	4.3
/ 162G	—	MLE		—	650	598	133	23	1	12	37	143	5	5	2	222	273	324	598	102	270	22	6	251	56	-6	+0	-7	+21	+14	2.3

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.

2023 AAATacoma Rainiers · 267 PAwOBA .320 → .241 (−79)K% 20.6% → 24.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.60%	÷1.024	×1.200	—	—	24.14%
BB% (unintentional) /PA	9.36%	÷1.013	×0.690	—	×0.972	6.20%
HBP% /PA	0.37%	—	×0.940	—	×0.972	0.34%
Singles /BIP	19.89%	÷0.989	×0.930	×0.956	×0.972	17.38%
Doubles /BIP	6.45%	÷0.940	×0.830	×0.956	×0.972	5.29%
Triples /BIP	0.00%	÷0.900	×0.970	×0.956	×0.972	0.00%
Home runs /BIP	5.38%	÷1.157	×0.700	—	×0.972	3.16%

Factors used: league row International League. Park (home-season share, regressed): HR 131, 1B 98, 2B 88, 3B 80, K 105, BB 103 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.956.

Result: wOBA .320 → .241; ISO .174 → .113; BABIP .278 → .234. 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).

2022 AAANashville Sounds · 126 PAwOBA .363 → .296 (−67)K% 21.4% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.43%	÷0.971	×1.200	—	—	26.49%
BB% (unintentional) /PA	4.76%	÷0.994	×0.690	—	×0.982	3.24%
HBP% /PA	1.59%	—	×0.940	—	×0.982	1.47%
Singles /BIP	24.44%	÷0.996	×0.930	×0.995	×0.982	22.31%
Doubles /BIP	11.11%	÷0.952	×0.830	×0.995	×0.982	9.46%
Triples /BIP	0.00%	÷1.150	×0.970	×0.995	×0.982	0.00%
Home runs /BIP	4.44%	÷0.946	×0.700	—	×0.982	3.23%

Factors used: league row International League. Park (home-season share, regressed): HR 89, 1B 99, 2B 90, 3B 130, K 94, BB 99 — 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 ×0.995.

Result: wOBA .363 → .296; ISO .188 → .142; BABIP .368 → .324. 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).

2022 AABiloxi Shuckers · 27 PAwOBA .470 → .372 (−98)K% 14.8% → 18.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.81%	÷0.976	×1.220	—	—	18.51%
BB% (unintentional) /PA	14.81%	÷1.027	×0.680	—	×0.958	9.40%
HBP% /PA	0.00%	—	×0.840	—	×0.958	0.00%
Singles /BIP	47.37%	÷1.060	×0.920	—	×0.958	39.37%
Doubles /BIP	0.00%	÷0.973	×0.910	—	×0.958	0.00%
Triples /BIP	0.00%	÷0.900	×0.880	—	×0.958	0.00%
Home runs /BIP	5.26%	÷1.012	×0.800	—	×0.958	3.99%

Factors used: league row SL. Park (home-season share, regressed): HR 102, 1B 112, 2B 95, 3B 80, K 95, BB 105 — applied at half strength. Age: age 29 vs a level average of 24.8 → −4.2% on BB/HBP/hit rates (4.2 yr older than average).

Result: wOBA .470 → .372; ISO .130 → .101; BABIP .500 → .410. 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 AAASyracuse Chiefs · 136 PAwOBA .322 → .268 (−54)K% 16.9% → 19.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.91%	÷1.044	×1.200	—	—	19.44%
BB% (unintentional) /PA	3.68%	÷0.956	×0.690	—	×1.033	2.74%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	21.50%	÷1.044	×0.930	×0.972	×1.033	19.23%
Doubles /BIP	4.67%	÷0.933	×0.830	×0.972	×1.033	4.17%
Triples /BIP	0.93%	÷0.900	×0.970	×0.972	×1.033	1.01%
Home runs /BIP	5.61%	÷1.205	×0.840	—	×1.033	4.04%

Factors used: league row IL. Park (home-season share, regressed): HR 141, 1B 109, 2B 87, 3B 80, K 109, BB 91 — 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 ×0.972.

Result: wOBA .322 → .268; ISO .192 → .149; BABIP .284 → .252. 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).

2017 AAASyracuse Chiefs · 227 PAwOBA .276 → .240 (−35)K% 18.9% → 22.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.94%	÷1.005	×1.200	—	—	22.62%
BB% (unintentional) /PA	6.61%	÷1.033	×0.690	—	×1.048	4.63%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	25.00%	÷0.997	×0.930	×0.969	×1.048	23.68%
Doubles /BIP	2.38%	÷1.081	×0.830	×0.969	×1.048	1.86%
Triples /BIP	0.00%	÷1.150	×0.970	×0.969	×1.048	0.00%
Home runs /BIP	2.98%	÷0.980	×0.840	—	×1.048	2.67%

Factors used: league row IL. Park (home-season share, regressed): HR 96, 1B 99, 2B 116, 3B 130, K 101, BB 107 — 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 ×0.969.

Result: wOBA .276 → .240; ISO .090 → .077; BABIP .280 → .261. 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 AAASyracuse Chiefs · 317 PAwOBA .291 → .250 (−41)K% 14.2% → 17.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.20%	÷0.949	×1.200	—	—	17.95%
BB% (unintentional) /PA	5.99%	÷1.110	×0.690	—	×1.050	3.91%
HBP% /PA	0.63%	—	×0.940	—	×1.050	0.62%
Singles /BIP	26.02%	÷1.048	×0.930	×0.963	×1.050	23.36%
Doubles /BIP	5.28%	÷0.959	×0.830	×0.963	×1.050	4.63%
Triples /BIP	0.00%	÷0.900	×0.970	×0.963	×1.050	0.00%
Home runs /BIP	0.81%	÷0.978	×0.840	—	×1.050	0.73%

Factors used: league row IL. Park (home-season share, regressed): HR 96, 1B 110, 2B 92, 3B 80, K 90, BB 122 — 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 ×0.963.

Result: wOBA .291 → .250; ISO .065 → .058; BABIP .310 → .277. 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 AAHarrisburg Senators · 357 PAwOBA .268 → .253 (−15)K% 14.3% → 17.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.29%	÷1.018	×1.220	—	—	17.12%
BB% (unintentional) /PA	5.04%	÷1.052	×0.700	—	×1.042	3.50%
HBP% /PA	0.28%	—	×0.850	—	×1.042	0.25%
Singles /BIP	22.66%	÷0.962	×0.970	×0.986	×1.042	23.47%
Doubles /BIP	4.68%	÷1.070	×0.860	×0.986	×1.042	3.86%
Triples /BIP	0.00%	÷0.916	×0.950	×0.986	×1.042	0.00%
Home runs /BIP	1.80%	÷0.986	×0.780	—	×1.042	1.48%

Factors used: league row EL. Park (home-season share, regressed): HR 97, 1B 92, 2B 114, 3B 83, K 104, BB 110 — 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 ×0.986.

Result: wOBA .268 → .253; ISO .085 → .071; BABIP .276 → .275. 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+Potomac Nationals · 326 PAwOBA .303 → .254 (−49)K% 17.5% → 24.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.48%	÷0.996	×1.420	—	—	24.93%
BB% (unintentional) /PA	6.44%	÷0.943	×0.630	—	×1.027	4.42%
HBP% /PA	1.53%	—	×0.860	—	×1.027	1.35%
Singles /BIP	20.09%	÷1.012	×0.940	×0.974	×1.027	18.67%
Doubles /BIP	6.41%	÷1.037	×0.830	×0.974	×1.027	5.14%
Triples /BIP	0.43%	÷1.150	×0.800	×0.974	×1.027	0.30%
Home runs /BIP	3.85%	÷0.988	×0.900	—	×1.027	3.60%

Factors used: league row CAR. Park (home-season share, regressed): HR 98, 1B 102, 2B 107, 3B 130, K 99, BB 89 — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.974.

Result: wOBA .303 → .254; ISO .151 → .128; BABIP .276 → .247. 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 — .