Alberto Rosario

PosC

B/TR/R

Born1987-01-10

Age (2027)40

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2019

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2017	30	AAA/INTL2 orgs	287	.215/.260/.242	0	3	19	—	.212/.248/.238
2018	31	AAA/AA2 orgs	179	.253/.291/.313	2	0	37	—	.224/.251/.284
2019	32	AAA/INTL2 orgs	172	.252/.322/.316	1	0	35	—	.192/.244/.240

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. 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)
2006	19	ROK	DSL Angels	—	205	178	49	5	4	0	18	21	4	3	5	275	355	348	703	73	308	10	9	315	34	—	—	—	—	—	—
2007	20	ROK	AZL Angels	—	81	73	22	4	0	1	5	9	1	2	2	301	354	397	752	96	328	11	6	331	61	—	—	—	—	—	—
2008	21	A+	Rancho Cucamonga Quakes	—	134	124	27	5	0	0	8	18	0	3	1	218	265	258	523	40	250	13	6	238	30	—	—	—	—	—	—
2008	21	A	Cedar Rapids Kernels	—	49	46	11	2	0	0	1	11	0	1	1	239	255	283	538	43	314	22	2	233	17	—	—	—	—	—	—
2008	21	ROK	Orem Owlz	—	57	55	13	5	1	0	1	13	1	0	0	236	263	364	627	127	310	23	2	277	7	—	—	—	—	—	—
2009	22	A+	Rancho Cucamonga Quakes	—	343	314	73	15	4	0	13	43	8	9	4	232	281	306	586	73	267	13	4	261	40	—	—	—	—	—	—
2010	23	AA	Arkansas Travelers	—	179	166	32	3	0	0	7	31	0	2	2	193	225	211	436	18	235	17	4	195	1	—	—	—	—	—	—
2010	23	A+	Rancho Cucamonga Quakes	—	210	181	55	9	1	4	11	25	5	8	1	304	360	431	791	127	329	12	5	333	103	—	—	—	—	—	—
2010	23	INTL	Dominican Republic	—	81	71	16	2	0	0	2	14	1	1	1	225	257	254	510	28	281	17	2	214	31	—	—	—	—	—	—
2011	24	AA	Arkansas Travelers	—	320	290	66	6	1	3	23	40	4	5	1	228	293	286	580	59	252	12	7	266	42	—	—	—	—	—	—
2011	24	INTL	Toros del Este	—	85	76	7	1	0	0	7	19	1	1	0	92	179	105	284	13	121	22	8	145	-16	—	—	—	—	—	—
2012	25	AAA	Salt Lake Bees	—	83	77	17	3	0	1	4	17	1	4	1	221	268	299	567	78	271	20	5	256	25	—	—	—	—	—	—
2012	25	AA	Arkansas Travelers	—	174	163	36	7	0	1	6	32	3	1	3	221	262	282	544	61	267	18	3	246	30	—	—	—	—	—	—
2012	25	INTL	Dominican Republic	—	91	80	21	5	0	1	9	13	1	0	1	263	344	362	707	100	303	14	10	320	102	—	—	—	—	—	—
2013	26	AAA	Pawtucket Red Sox	—	102	90	21	3	0	2	7	22	2	0	0	233	303	333	636	100	288	22	7	283	55	—	—	—	—	—	—
2013	26	AA	Portland Sea Dogs	—	41	36	6	0	0	0	3	4	1	0	0	167	250	167	417		182	10	7	201	11	—	—	—	—	—	—
2013	26	INTL	Estrellas de Oriente	—	53	51	13	3	0	0	0	9	0	0	1	255	255	314	569	59	310	17	0	243	51	—	—	—	—	—	—
2014	27	AA	Chattanooga Lookouts	—	50	47	13	1	0	1	3	15	0	0	0	277	320	362	682	85	387	30	6	308	42	—	—	—	—	—	—
2014	27	INTL	Estrellas de Oriente	—	69	61	25	4	0	1	5	13	1	2	1	410	463	525	987	115	511	19	7	428	176	—	—	—	—	—	—
2015	28	AAA	Memphis Redbirds	—	16	16	5	2	0	0	0	2	0	0	1	312	312	438	750	125	357	12	0	330	63	—	—	—	—	—	—
2015	28	AA	Springfield Cardinals	—	164	148	27	8	0	1	9	19	3	0	0	182	244	257	501	74	203	12	5	226	11	—	—	—	—	—	—
2015	28	INTL	Estrellas de Oriente	—	70	66	15	3	0	0	2	17	1	0	2	227	261	273	534	45	306	24	3	241	49	—	—	—	—	—	—
2016	29	MLB	St. Louis Cardinals	—	41	38	7	2	0	0	2	5	0	0	0	184	225	237	462	53	212	12	5	207	25	-4	+0	+1	+4	+1	0.2
2016	29	AAA	Memphis Redbirds	—	124	114	32	5	0	0	6	20	2	0	0	281	328	325	652	44	333	16	5	294	61	—	—	—	—	—	—
2016	29	INTL	Estrellas Orientales	—	54	47	5	1	0	0	5	14	0	0	0	106	192	128	320	21	147	26	9	155	-9	—	—	—	—	—	—
2017	30	AAA	Memphis Redbirds	—	204	190	47	6	0	0	11	31	1	3	0	247	292	279	571	32	294	15	5	261	32	—	—	—	—	—	—
2017	30	INTL	Estrellas Orientales	—	83	75	10	1	0	0	3	12	1	0	0	133	177	147	324	13	159	14	4	148	-14	—	—	—	—	—	—
2018	31	AAA	Reno Aces	—	47	42	9	1	0	1	1	8	1	0	0	214	250	310	560	95	235	17	2	237	17	—	—	—	—	—	—
2018	31	AA	Jackson Generals	—	132	124	33	3	0	1	7	20	0	0	2	266	305	315	620	48	308	15	5	281	44	—	—	—	—	—	—
2019	32	AAA	Reno Aces	—	157	140	35	3	1	1	15	27	1	0	1	250	327	307	634	57	301	17	10	292	30	—	—	—	—	—	—
2019	32	INTL	Estrellas Orientales	—	15	15	4	2	0	0	0	4	0	0	0	267	267	400	667	133	364	27	0	292	84	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	41	38	7	2	0	0	2	5	0	0	0	184	225	237	462	53	212	12	5	207	26	-4	+0	+1	+4	+1	0.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2006	19	ROK MLE	DSL Angels	—	205	184	35	3	3	0	12	26	4	3	5	190	255	239	494	49	211	13	6	219	34	—	—	—	—	—	—
2007	20	ROK MLE	AZL Angels	—	81	75	18	3	0	1	3	13	1	2	2	240	278	320	598	80	271	16	4	258	61	—	—	—	—	—	—
2008	21	A+ MLE	Rancho Cucamonga Quakes	—	134	126	25	4	0	0	6	24	0	3	1	198	235	230	465	32	240	18	4	212	30	—	—	—	—	—	—
2008	21	A MLE	Cedar Rapids Kernels	—	49	46	10	2	0	0	1	15	0	1	1	217	234	261	495	43	288	31	2	194	17	—	—	—	—	—	—
2008	21	ROK MLE	Orem Owlz	—	57	55	9	3	1	0	1	19	1	0	0	164	193	255	448	91	236	33	2	178	7	—	—	—	—	—	—
2009	22	A+ MLE	Rancho Cucamonga Quakes	—	343	318	68	13	3	0	9	58	8	9	4	214	254	274	527	60	250	17	3	228	40	—	—	—	—	—	—
2010	23	AA MLE	Arkansas Travelers	—	179	168	29	3	0	0	5	36	0	2	2	173	197	190	387	18	210	20	3	169	1	—	—	—	—	—	—
2010	23	A+ MLE	Rancho Cucamonga Quakes	—	210	184	56	8	1	4	8	34	5	8	1	304	350	424	774	120	320	16	4	320	103	—	—	—	—	—	—
2011	24	AA MLE	Arkansas Travelers	—	320	299	62	5	1	3	14	49	4	5	1	207	252	261	513	54	233	15	4	230	42	—	—	—	—	—	—
2012	25	AAA MLE	Salt Lake Bees	—	83	78	14	2	0	1	3	22	1	4	1	179	220	244	463	64	237	27	4	205	25	—	—	—	—	—	—
2012	25	AA MLE	Arkansas Travelers	—	174	165	33	6	0	1	4	39	3	1	3	200	233	255	487	55	248	22	2	212	30	—	—	—	—	—	—
2013	26	AAA MLE	Pawtucket Red Sox	—	102	92	20	2	0	2	5	26	2	0	0	217	273	304	577	87	279	25	5	249	55	—	—	—	—	—	—
2013	26	AA MLE	Portland Sea Dogs	—	41	37	6	0	0	0	2	5	1	0	0	162	225	162	387		178	12	5	185	11	—	—	—	—	—	—
2014	27	AA MLE	Chattanooga Lookouts	—	50	48	11	1	0	1	2	19	0	0	0	229	260	312	573	83	339	38	4	231	42	—	—	—	—	—	—
2015	28	AAA MLE	Memphis Redbirds	—	16	16	4	2	0	0	0	3	0	0	1	250	250	375	625	125	307	19	0	262	63	—	—	—	—	—	—
2015	28	AA MLE	Springfield Cardinals	—	164	152	25	7	0	1	5	24	3	0	0	164	206	230	437	66	180	15	3	185	11	—	—	—	—	—	—
2016	29	MLB MLE	St. Louis Cardinals	—	41	38	7	2	0	0	2	5	0	0	0	184	225	237	462	53	212	12	5	205	25	-4	+0	+1	+4	+1	0.2
2016	29	AAA MLE	Memphis Redbirds	—	124	116	29	4	0	0	4	26	2	0	0	250	287	284	571	34	310	21	3	258	61	—	—	—	—	—	—
2017	30	AAA MLE	Memphis Redbirds	—	204	193	41	5	0	0	8	40	1	3	0	212	248	238	486	26	262	20	4	216	32	—	—	—	—	—	—
2018	31	AAA MLE	Reno Aces	—	47	42	8	1	0	1	1	10	1	0	0	190	227	286	513	95	193	21	2	193	17	—	—	—	—	—	—
2018	31	AA MLE	Jackson Generals	—	132	127	30	3	0	1	4	25	0	0	2	236	260	283	543	47	276	19	3	233	44	—	—	—	—	—	—
2019	32	AAA MLE	Reno Aces	—	157	146	28	2	1	1	9	36	1	0	1	192	244	240	483	48	239	23	6	213	30	—	—	—	—	—	—
2006	19	ROK MLE	DSL Angels	—	205	184	35	3	3	0	12	26	4	3	5	190	255	239	494	49	219	13	6	219	34	—	—	—	—	—	—
2006	19	ROK RAW	DSL Angels	—	205	178	49	5	4	0	18	21	4	3	5	275	355	348	703	73	308	10	9	315	34	—	—	—	—	—	—
2007	20	ROK MLE	AZL Angels	—	81	75	18	3	0	1	3	13	1	2	2	240	278	320	598	80	274	16	4	258	61	—	—	—	—	—	—
2007	20	ROK RAW	AZL Angels	—	81	73	22	4	0	1	5	9	1	2	2	301	354	397	752	96	328	11	6	331	61	—	—	—	—	—	—
2008	21	A+ MLE	3 teams	—	240	228	44	9	1	0	7	58	1	4	2	193	220	241	462	48	256	24	3	200	22	—	—	—	—	—	—
2008	21	A+ RAW	3 teams	—	240	225	51	12	1	0	10	42	1	4	2	227	263	289	552	62	276	18	4	246	22	—	—	—	—	—	—
2009	22	A+ MLE	Rancho Cucamonga Quakes	—	343	318	68	13	3	0	9	58	8	9	4	214	254	274	527	60	260	17	3	228	40	—	—	—	—	—	—
2009	22	A+ RAW	Rancho Cucamonga Quakes	—	343	314	73	15	4	0	13	43	8	9	4	232	281	306	586	73	267	13	4	261	40	—	—	—	—	—	—
2010	23	A+ MLE	3 teams	—	470	423	104	14	1	5	15	84	6	11	4	246	282	319	601	73	293	18	3	251	56	—	—	—	—	—	—
2010	23	A+ RAW	3 teams	—	470	418	103	14	1	4	20	70	6	11	4	246	291	313	604	67	284	15	4	260	56	—	—	—	—	—	—
2011	24	AA MLE	2 teams	—	405	378	79	7	1	4	18	62	5	6	1	209	254	265	519	56	237	15	4	230	42	—	—	—	—	—	—
2011	24	AA RAW	2 teams	—	405	366	73	7	1	3	30	59	5	6	1	199	269	249	518	49	227	15	7	241	42	—	—	—	—	—	—
2012	25	AA MLE	3 teams	—	348	329	63	11	0	2	10	82	5	5	5	191	227	243	470	52	248	24	3	210	28	—	—	—	—	—	—
2012	25	AA RAW	3 teams	—	348	320	74	15	0	3	19	62	5	5	5	231	285	306	591	75	277	18	5	268	28	—	—	—	—	—	—
2013	26	AAA MLE	3 teams	—	196	178	36	3	0	2	9	42	3	0	1	202	253	253	505	51	252	21	5	231	42	—	—	—	—	—	—
2013	26	AAA RAW	3 teams	—	196	177	40	6	0	2	10	35	3	0	1	226	279	294	573	68	270	18	5	255	42	—	—	—	—	—	—
2014	27	INTL MLE	2 teams	—	119	111	25	2	0	2	5	45	1	2	1	225	265	297	562	72	359	38	4	231	42	—	—	—	—	—	—
2014	27	INTL RAW	2 teams	—	119	108	38	5	0	2	8	28	1	2	1	352	402	454	855	102	462	24	7	378	42	—	—	—	—	—	—
2015	28	AA MLE	3 teams	—	250	234	40	12	0	1	7	37	4	0	3	171	208	235	443	64	199	15	3	192	16	—	—	—	—	—	—
2015	28	AA RAW	3 teams	—	250	230	47	13	0	1	11	38	4	0	3	204	253	274	527	70	241	15	4	237	16	—	—	—	—	—	—
2016	29	AAA MLE	3 teams	—	219	204	47	8	0	0	8	41	2	0	0	230	266	270	536	39	283	19	4	245	52	—	—	—	—	—	—
2016	29	AAA RAW	3 teams	—	219	199	44	8	0	0	13	39	2	0	0	221	276	261	537	40	270	18	6	244	52	—	—	—	—	—	—
2017	30	AAA MLE	2 teams	—	287	268	58	7	0	0	11	56	2	3	0	216	253	243	495	26	272	20	4	216	32	—	—	—	—	—	—
2017	30	AAA RAW	2 teams	—	287	265	57	7	0	0	14	43	2	3	0	215	260	242	501	26	256	15	5	228	32	—	—	—	—	—	—
2018	31	AA MLE	2 teams	—	179	169	37	3	0	2	5	36	1	0	2	219	246	272	518	53	263	20	3	222	37	—	—	—	—	—	—
2018	31	AA RAW	2 teams	—	179	166	42	4	0	2	8	28	1	0	2	253	291	313	605	60	290	16	4	269	37	—	—	—	—	—	—
2019	32	AAA MLE	2 teams	—	172	160	30	2	1	1	10	39	1	0	1	188	240	231	471	44	240	23	6	213	30	—	—	—	—	—	—
2019	32	AAA RAW	2 teams	—	172	155	39	5	1	1	15	31	1	0	1	252	322	316	638	65	306	18	9	292	30	—	—	—	—	—	—
2006	19	ROK MLE	DSL Angels	—	205	187	35	3	3	0	12	26	4	3	5	187	255	235	490	48	211	13	6	219	34	—	—	—	—	—	—
2007	20	ROK MLE	AZL Angels	—	81	77	18	3	0	1	3	13	1	2	2	234	278	312	590	78	271	16	4	258	61	—	—	—	—	—	—
2008	21	A+ MLE	3 teams	—	240	230	44	9	1	0	7	58	1	4	2	191	220	239	459	48	249	24	3	200	22	—	—	—	—	—	—
2009	22	A+ MLE	Rancho Cucamonga Quakes	—	343	323	68	13	3	0	9	58	8	9	4	211	254	269	523	59	250	17	3	228	40	—	—	—	—	—	—
2010	23	A+ MLE	3 teams	—	470	446	104	14	1	5	15	84	6	11	4	233	282	303	584	70	269	18	3	251	56	—	—	—	—	—	—
2011	24	AA MLE	2 teams	—	405	379	79	7	1	4	18	62	5	6	1	208	254	264	518	55	233	15	4	230	42	—	—	—	—	—	—
2012	25	AA MLE	3 teams	—	348	330	63	11	0	2	10	82	5	5	5	191	227	242	469	52	244	24	3	210	28	—	—	—	—	—	—
2013	26	AAA MLE	3 teams	—	196	182	36	3	0	2	9	42	3	0	1	198	253	247	500	49	250	21	5	231	42	—	—	—	—	—	—
2014	27	INTL MLE	2 teams	—	119	112	25	2	0	2	5	45	1	2	1	223	265	295	560	71	339	38	4	231	42	—	—	—	—	—	—
2015	28	AA MLE	3 teams	—	250	237	40	12	0	1	7	37	4	0	3	169	208	232	440	63	191	15	3	192	16	—	—	—	—	—	—
2016	29	AAA MLE	3 teams	—	219	207	47	8	0	0	8	41	2	0	0	227	266	266	532	39	286	19	4	245	52	—	—	—	—	—	—
2017	30	AAA MLE	2 teams	—	287	272	58	7	0	0	11	56	2	3	0	213	253	239	492	26	262	20	4	216	32	—	—	—	—	—	—
2018	31	AA MLE	2 teams	—	179	171	37	3	0	2	5	36	1	0	2	216	246	269	515	53	254	20	3	222	37	—	—	—	—	—	—
2019	32	AAA MLE	2 teams	—	172	159	30	2	1	1	10	39	1	0	1	189	240	233	472	44	239	23	6	213	30	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	41	38	7	2	0	0	2	5	0	0	0	184	225	237	462	53	212	12	5	207	38	-4	+0	+1	+4	+1	0.2
/ 162G	—	A+C		—	650	602	111	32	0	0	32	79	0	0	0	184	226	238	463	53	212	12	5	207	38	-57	+0	+12	+62	+14	3.2
Career	—	MLE		—	3514	3259	684	97	10	20	129	679	44	45	31	210	250	264	514	54	257	19	4	224	38	-4	+0	+1	+4	+1	0.2
/ 162G	—	MLE		—	650	603	127	18	2	4	24	126	8	8	6	211	250	267	517	56	258	19	4	224	38	-57	+0	+12	+62	+14	3.2

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.

2019 AAAReno Aces · 157 PAwOBA .282 → .213 (−68)K% 17.2% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.20%	÷0.970	×1.290	—	—	22.88%
BB% (unintentional) /PA	8.28%	÷0.986	×0.710	—	×0.952	5.68%
HBP% /PA	0.64%	—	×0.980	—	×0.952	0.59%
Singles /BIP	26.55%	÷1.035	×0.900	×0.975	×0.952	21.43%
Doubles /BIP	2.65%	÷1.025	×0.810	×0.975	×0.952	1.95%
Triples /BIP	0.88%	÷1.150	×0.810	×0.975	×0.952	0.58%
Home runs /BIP	0.88%	÷1.077	×0.780	—	×0.952	0.61%

Factors used: league row PCL. Park (home-season share, regressed): HR 115, 1B 107, 2B 105, 3B 130, K 94, BB 97 — 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 ×0.975.

Result: wOBA .282 → .213; ISO .057 → .039; BABIP .301 → .239. 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 AAJackson Generals · 132 PAwOBA .275 → .233 (−43)K% 15.2% → 19.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.15%	÷0.972	×1.220	—	—	19.01%
BB% (unintentional) /PA	5.30%	÷1.003	×0.680	—	×0.940	3.38%
HBP% /PA	0.00%	—	×0.840	—	×0.940	0.00%
Singles /BIP	27.88%	÷0.982	×0.920	×1.026	×0.940	25.19%
Doubles /BIP	2.88%	÷1.022	×0.910	×1.026	×0.940	2.48%
Triples /BIP	0.00%	÷1.145	×0.880	×1.026	×0.940	0.00%
Home runs /BIP	0.96%	÷0.954	×0.800	—	×0.940	0.76%

Factors used: league row SL. Park (home-season share, regressed): HR 91, 1B 96, 2B 104, 3B 129, K 94, BB 101 — applied at half strength. Age: age 31 vs a level average of 24.8 → −6.0% on BB/HBP/hit rates (6.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.026.

Result: wOBA .275 → .233; ISO .048 → .039; BABIP .308 → .276. 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 · 47 PAwOBA .235 → .193 (−43)K% 17.0% → 22.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.02%	÷0.991	×1.290	—	—	22.16%
BB% (unintentional) /PA	2.13%	÷1.069	×0.710	—	×0.962	1.36%
HBP% /PA	2.13%	—	×0.980	—	×0.962	2.01%
Singles /BIP	20.59%	÷1.024	×0.900	—	×0.962	17.41%
Doubles /BIP	2.94%	÷1.117	×0.810	—	×0.962	2.05%
Triples /BIP	0.00%	÷1.150	×0.810	—	×0.962	0.00%
Home runs /BIP	2.94%	÷1.044	×0.780	—	×0.962	2.11%

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 31 vs a level average of 27.2 → −3.8% on BB/HBP/hit rates (3.8 yr older than average).

Result: wOBA .235 → .193; ISO .095 → .070; BABIP .235 → .193. 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 AAAMemphis Redbirds · 204 PAwOBA .255 → .216 (−39)K% 15.2% → 19.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.20%	÷1.010	×1.290	—	—	19.41%
BB% (unintentional) /PA	5.39%	÷0.997	×0.710	—	×0.972	3.73%
HBP% /PA	0.49%	—	×0.980	—	×0.972	0.47%
Singles /BIP	25.79%	÷1.001	×0.900	×1.038	×0.972	23.38%
Doubles /BIP	3.77%	÷1.021	×0.810	×1.038	×0.972	3.02%
Triples /BIP	0.00%	÷1.135	×0.810	×1.038	×0.972	0.00%
Home runs /BIP	0.00%	÷0.980	×0.780	—	×0.972	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 96, 1B 100, 2B 104, 3B 127, K 102, BB 99 — 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 ×1.038.

Result: wOBA .255 → .216; ISO .032 → .025; BABIP .294 → .262. 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 AAAMemphis Redbirds · 124 PAwOBA .292 → .258 (−34)K% 16.1% → 21.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.13%	÷0.988	×1.290	—	—	21.05%
BB% (unintentional) /PA	4.84%	÷0.983	×0.710	—	×0.982	3.43%
HBP% /PA	1.61%	—	×0.980	—	×0.982	1.55%
Singles /BIP	28.72%	÷0.989	×0.900	×1.050	×0.982	26.94%
Doubles /BIP	5.32%	÷0.941	×0.810	×1.050	×0.982	4.72%
Triples /BIP	0.00%	÷0.951	×0.810	×1.050	×0.982	0.00%
Home runs /BIP	0.00%	÷0.931	×0.780	—	×0.982	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 86, 1B 98, 2B 88, 3B 90, K 98, BB 97 — 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 ×1.050.

Result: wOBA .292 → .258; ISO .044 → .038; BABIP .333 → .310. 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 AASpringfield Cardinals · 164 PAwOBA .215 → .185 (−30)K% 11.6% → 14.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.59%	÷0.978	×1.220	—	—	14.46%
BB% (unintentional) /PA	4.27%	÷1.000	×0.700	—	×0.968	2.89%
HBP% /PA	1.83%	—	×0.870	—	×0.968	1.54%
Singles /BIP	13.95%	÷0.982	×0.920	×1.014	×0.968	12.83%
Doubles /BIP	6.20%	÷1.003	×0.840	×1.014	×0.968	5.10%
Triples /BIP	0.00%	÷1.003	×0.940	×1.014	×0.968	0.00%
Home runs /BIP	0.78%	÷1.140	×0.800	—	×0.968	0.53%

Factors used: league row TL. Park (home-season share, regressed): HR 128, 1B 96, 2B 101, 3B 101, K 96, BB 100 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.014.

Result: wOBA .215 → .185; ISO .074 → .060; BABIP .203 → .180. 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 AAAMemphis Redbirds · 16 PAwOBA .321 → .262 (−58)K% 12.5% → 16.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.50%	÷0.967	×1.290	—	—	16.67%
BB% (unintentional) /PA	0.00%	÷1.013	×0.710	—	×0.992	0.00%
HBP% /PA	0.00%	—	×0.980	—	×0.992	0.00%
Singles /BIP	21.43%	÷1.030	×0.900	—	×0.992	18.57%
Doubles /BIP	14.29%	÷0.946	×0.810	—	×0.992	12.14%
Triples /BIP	0.00%	÷0.900	×0.810	—	×0.992	0.00%
Home runs /BIP	0.00%	÷1.224	×0.780	—	×0.992	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 145, 1B 106, 2B 89, 3B 80, K 93, BB 103 — 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 .321 → .262; ISO .125 → .101; BABIP .357 → .307. 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 AAChattanooga Lookouts · 50 PAwOBA .300 → .231 (−69)K% 30.0% → 37.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.00%	÷0.972	×1.220	—	—	37.67%
BB% (unintentional) /PA	6.00%	÷1.036	×0.680	—	×0.978	3.85%
HBP% /PA	0.00%	—	×0.840	—	×0.978	0.00%
Singles /BIP	34.38%	÷1.014	×0.920	—	×0.978	30.49%
Doubles /BIP	3.12%	÷1.053	×0.910	—	×0.978	2.64%
Triples /BIP	0.00%	÷1.150	×0.880	—	×0.978	0.00%
Home runs /BIP	3.12%	÷1.026	×0.800	—	×0.978	2.38%

Factors used: league row SL. Park (home-season share, regressed): HR 105, 1B 103, 2B 111, 3B 130, K 94, BB 107 — applied at half strength. Age: age 27 vs a level average of 24.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average).

Result: wOBA .300 → .231; ISO .085 → .061; BABIP .387 → .339. 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 — .