Walter Ibarra

PosSS

B/TS/R

Born1987-11-01

Age (2027)39

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2024

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2021	33	INTLNaranjeros de…	179	.247/.273/.373	4	2	73	—
2022	34	INTLAguilas de Me…	162	.181/.266/.232	0	0	38	—
2024	36	INTLVenados de Ma…	96	.202/.264/.262	1	1	43	—

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)
2006	18	ROK	GCL Yankees	—	86	72	19	2	0	0	12	8	1	3	2	264	376	292	668	28	297	9	14	315	49	—	—	—	—	—	—
2007	19	A+	Tampa Yankees	—	30	28	5	1	0	0	2	9	0	1	0	179	233	214	448	36	263	30	7	210	-4	—	—	—	—	—	—
2007	19	ROK	GCL Yankees	—	46	39	8	2	0	0	4	8	2	0	1	205	311	256	568	51	250	17	9	266	17	—	—	—	—	—	—
2008	20	AA	Trenton Thunder	—	60	56	15	3	0	1	2	8	1	0	2	268	305	375	680	107	298	13	3	300	72	—	—	—	—	—	—
2008	20	A	Charleston RiverDogs	—	97	91	18	6	1	1	6	16	0	1	0	198	247	319	566	121	230	16	6	254	25	—	—	—	—	—	—
2009	21	A+	Tampa Yankees	—	250	234	62	10	1	0	10	23	1	11	5	265	298	316	614	51	290	9	4	273	56	—	—	—	—	—	—
2009	21	A	Charleston RiverDogs	—	32	29	7	0	0	0	2	10	0	1	0	241	290	241	532		368	31	6	242	15	—	—	—	—	—	—
2010	22	A+	Tampa Yankees	—	274	246	74	12	1	1	15	46	5	15	7	301	353	370	723	69	360	17	5	319	79	—	—	—	—	—	—
2010	22	INTL	Naranjeros de Hermosillo	—	175	155	47	8	1	1	12	37	1	5	2	303	357	387	744	84	387	21	7	323	105	—	—	—	—	—	—
2011	23	A+	Tampa Yankees	—	437	390	116	24	3	6	19	65	6	10	7	297	340	421	760	123	336	15	4	322	88	—	—	—	—	—	—
2011	23	INTL	Naranjeros de Hermosillo	—	167	151	25	5	1	0	8	34	1	2	1	166	212	212	424	46	214	20	5	189	14	—	—	—	—	—	—
2012	24	AA	Trenton Thunder	—	166	156	43	15	2	1	5	27	2	2	1	276	307	417	723	141	328	16	3	314	71	—	—	—	—	—	—
2012	24	ROK	GCL Yankees	—	22	22	4	2	0	0	0	3	0	0	0	182	182	273	455	91	211	14	0	199	-27	—	—	—	—	—	—
2012	24	INTL	Naranjeros de Hermosillo	—	78	72	16	3	0	3	2	13	2	3	1	222	263	389	652	167	232	17	3	282	77	—	—	—	—	—	—
2013	25	AAA	Scranton/Wilkes-Barre RailRiders	—	130	122	31	5	0	2	8	42	0	1	1	254	300	344	644	90	372	32	6	291	54	—	—	—	—	—	—
2013	25	AA	Trenton Thunder	—	82	77	24	2	1	1	2	21	0	2	1	312	329	403	732	91	404	26	2	314	68	—	—	—	—	—	—
2013	25	INTL	Venados de Mazatlan	—	186	172	33	9	1	0	8	35	0	1	2	192	228	256	484	64	241	19	4	213	30	—	—	—	—	—	—
2014	26	AAA	Albuquerque Isotopes	—	359	338	91	11	0	5	14	68	2	6	4	269	302	346	648	77	323	19	4	289	47	—	—	—	—	—	—
2014	26	AA	Chattanooga Lookouts	—	29	27	6	2	0	0	2	7	0	0	1	222	276	296	572	74	300	24	7	261	22	—	—	—	—	—	—
2014	26	INTL	Mexico	—	275	247	71	9	5	4	14	45	1	4	3	287	328	413	741	126	335	16	5	314	99	—	—	—	—	—	—
2015	27	AAA	Sultanes de Monterrey	—	402	361	110	20	2	3	18	57	1	14	3	305	339	396	736	91	351	14	4	312	86	—	—	—	—	—	—
2015	27	INTL	Aguilas de Mexicali	—	274	247	76	15	2	5	14	53	2	9	3	308	350	445	795	138	366	19	5	339	116	—	—	—	—	—	—
2016	28	AAA	Sultanes de Monterrey	—	450	410	135	25	3	6	24	60	2	10	4	329	368	449	817	120	370	13	5	353	88	—	—	—	—	—	—
2017	29	AAA	Sultanes de Monterrey	—	329	307	81	12	2	2	16	69	0	2	1	264	300	336	636	72	333	21	5	282	45	—	—	—	—	—	—
2017	29	INTL	Mexico	—	262	232	62	9	0	6	13	47	3	3	2	267	315	384	698	116	308	18	5	297	87	—	—	—	—	—	—
2019	31	AAA	Leones de Yucatan	—	362	302	79	16	2	2	43	84	2	6	5	262	357	348	705	86	348	23	12	312	59	—	—	—	—	—	—
2019	31	INTL	Venados de Mazatlan	—	128	120	25	3	0	0	5	32	1	0	0	208	246	233	479	25	281	25	4	219	34	—	—	—	—	—	—
2020	32	INTL	Naranjeros de Hermosillo	—	24	19	1	0	0	0	2	4	0	0	0	53	143	53	195		62	17	8	96	-49	—	—	—	—	—	—
2021	33	INTL	Naranjeros de Hermosillo	—	179	166	41	9	0	4	5	41	1	2	1	247	273	373	647	127	301	23	3	276	73	—	—	—	—	—	—
2022	34	INTL	Aguilas de Mexicali	—	162	138	25	3	2	0	16	37	0	0	3	181	266	232	498	51	243	23	10	224	38	—	—	—	—	—	—
2024	36	INTL	Venados de Mazatlan	—	96	84	17	2	0	1	6	22	1	1	0	202	264	262	526	60	250	23	6	232	43	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2006	18	ROK MLE	GCL Yankees	—	86	77	17	2	0	0	7	12	1	3	2	221	294	247	541	26	247	14	8	240	49	—	—	—	—	—	—
2007	19	A+ MLE	Tampa Yankees	—	30	28	4	1	0	0	2	13	0	1	0	143	200	179	379	36	254	43	7	163	-4	—	—	—	—	—	—
2007	19	ROK MLE	GCL Yankees	—	46	41	6	1	0	0	2	12	2	0	1	146	222	171	393	24	198	26	4	194	17	—	—	—	—	—	—
2008	20	AA MLE	Trenton Thunder	—	60	57	15	3	0	1	1	10	1	0	2	263	288	368	657	105	295	17	2	275	72	—	—	—	—	—	—
2008	20	A MLE	Charleston RiverDogs	—	97	94	16	5	1	1	3	21	0	1	0	170	196	277	472	106	212	22	3	205	25	—	—	—	—	—	—
2009	21	A+ MLE	Tampa Yankees	—	250	236	59	10	1	0	8	33	1	11	5	250	278	301	578	51	278	13	3	251	56	—	—	—	—	—	—
2009	21	A MLE	Charleston RiverDogs	—	32	30	6	0	0	0	1	13	0	1	0	200	226	200	426		339	41	3	190	15	—	—	—	—	—	—
2010	22	A+ MLE	Tampa Yankees	—	274	251	69	12	1	1	10	65	5	15	7	275	316	343	658	68	345	24	4	285	79	—	—	—	—	—	—
2011	23	A+ MLE	Tampa Yankees	—	437	394	110	24	2	6	15	89	6	10	7	279	316	396	712	117	316	20	3	298	88	—	—	—	—	—	—
2012	24	AA MLE	Trenton Thunder	—	166	157	40	12	2	1	4	33	2	2	1	255	282	376	658	121	307	20	2	273	71	—	—	—	—	—	—
2012	24	ROK MLE	GCL Yankees	—	22	22	2	1	0	0	0	4	0	0	0	91	91	136	227	45	153	18	0	129	-27	—	—	—	—	—	—
2013	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	130	124	29	4	0	2	6	50	0	1	1	234	269	315	584	81	369	38	5	248	54	—	—	—	—	—	—
2013	25	AA MLE	Trenton Thunder	—	82	78	21	1	1	1	1	26	0	2	1	269	278	346	625	77	364	32	1	269	68	—	—	—	—	—	—
2014	26	AAA MLE	Albuquerque Isotopes	—	359	343	79	9	0	3	9	92	2	6	4	230	254	283	537	52	299	26	3	237	47	—	—	—	—	—	—
2014	26	AA MLE	Chattanooga Lookouts	—	29	28	5	2	0	0	1	9	0	0	1	179	207	250	457	71	262	31	3	201	22	—	—	—	—	—	—
2015	27	AAA MLE	Sultanes de Monterrey	—	402	366	111	18	2	2	13	66	1	14	3	303	329	380	709	77	337	16	3	296	86	—	—	—	—	—	—
2016	28	AAA MLE	Sultanes de Monterrey	—	450	421	122	22	3	4	14	75	2	10	4	290	316	385	701	95	326	17	3	298	88	—	—	—	—	—	—
2017	29	AAA MLE	Sultanes de Monterrey	—	329	313	73	10	2	1	10	88	0	2	1	233	257	288	545	54	309	27	3	235	45	—	—	—	—	—	—
2019	31	AAA MLE	Leones de Yucatan	—	362	319	72	14	2	2	26	99	2	6	5	226	288	301	589	75	293	27	7	256	59	—	—	—	—	—	—
2006	18	ROK MLE	GCL Yankees	—	86	77	17	2	0	0	7	12	1	3	2	221	294	247	541	26	262	14	8	240	49	—	—	—	—	—	—
2006	18	ROK RAW	GCL Yankees	—	86	72	19	2	0	0	12	8	1	3	2	264	376	292	668	28	297	9	14	315	49	—	—	—	—	—	—
2007	19	ROK MLE	2 teams	—	76	69	10	2	0	0	4	24	2	1	1	145	213	174	387	29	217	32	5	182	9	—	—	—	—	—	—
2007	19	ROK RAW	2 teams	—	76	67	13	3	0	0	6	17	2	1	1	194	280	239	519	45	255	22	8	244	9	—	—	—	—	—	—
2008	20	A MLE	2 teams	—	157	150	31	8	1	2	5	31	1	1	2	207	237	313	551	107	248	20	3	232	43	—	—	—	—	—	—
2008	20	A RAW	2 teams	—	157	147	33	9	1	2	8	24	1	1	2	224	269	340	609	116	256	15	5	272	43	—	—	—	—	—	—
2009	21	A+ MLE	2 teams	—	282	266	65	10	1	0	9	46	1	12	5	244	272	289	561	45	291	16	3	244	51	—	—	—	—	—	—
2009	21	A+ RAW	2 teams	—	282	263	69	10	1	0	12	33	1	12	5	262	297	308	605	46	296	12	4	270	51	—	—	—	—	—	—
2010	22	A+ MLE	2 teams	—	449	412	112	20	1	1	16	107	6	20	9	272	309	333	641	61	358	24	4	285	79	—	—	—	—	—	—
2010	22	A+ RAW	2 teams	—	449	401	121	20	2	2	27	83	6	20	9	302	355	377	731	75	370	18	6	321	79	—	—	—	—	—	—
2011	23	A+ MLE	2 teams	—	604	547	151	33	3	8	21	123	7	12	8	276	311	391	703	115	337	20	3	298	88	—	—	—	—	—	—
2011	23	A+ RAW	2 teams	—	604	541	141	29	4	6	27	99	7	12	8	261	304	362	667	102	304	16	4	286	88	—	—	—	—	—	—
2012	24	AA MLE	3 teams	—	266	252	60	19	3	1	5	53	4	5	2	238	264	349	614	111	298	20	2	256	60	—	—	—	—	—	—
2012	24	AA RAW	3 teams	—	266	250	63	20	2	4	7	43	4	5	2	252	284	396	680	144	291	16	3	295	60	—	—	—	—	—	—
2013	25	INTL MLE	3 teams	—	398	376	93	10	1	5	13	142	0	4	4	247	272	319	592	72	381	36	3	256	59	—	—	—	—	—	—
2013	25	INTL RAW	3 teams	—	398	371	88	16	2	3	18	98	0	4	4	237	272	315	588	78	312	25	5	259	59	—	—	—	—	—	—
2014	26	AAA MLE	3 teams	—	663	624	144	18	0	6	18	172	3	10	8	231	256	288	544	58	307	26	3	234	45	—	—	—	—	—	—
2014	26	AAA RAW	3 teams	—	663	612	168	22	5	9	30	120	3	10	8	275	312	371	683	96	327	18	5	298	45	—	—	—	—	—	—
2015	27	AAA MLE	2 teams	—	676	618	187	30	3	4	22	110	3	23	6	303	330	380	710	78	357	16	3	296	86	—	—	—	—	—	—
2015	27	AAA RAW	2 teams	—	676	608	186	35	4	8	32	110	3	23	6	306	344	416	760	110	357	16	5	323	86	—	—	—	—	—	—
2016	28	AAA MLE	Sultanes de Monterrey	—	450	421	122	22	3	4	14	75	2	10	4	290	316	385	701	95	340	17	3	298	88	—	—	—	—	—	—
2016	28	AAA RAW	Sultanes de Monterrey	—	450	410	135	25	3	6	24	60	2	10	4	329	368	449	817	120	370	13	5	353	88	—	—	—	—	—	—
2017	29	AAA MLE	2 teams	—	591	551	131	18	3	2	17	157	3	5	3	238	264	292	557	54	326	27	3	235	45	—	—	—	—	—	—
2017	29	AAA RAW	2 teams	—	591	539	143	21	2	8	29	116	3	5	3	265	306	356	663	91	322	20	5	289	45	—	—	—	—	—	—
2019	31	AAA MLE	2 teams	—	490	435	96	19	2	2	35	134	3	6	5	221	283	287	571	67	308	27	7	256	59	—	—	—	—	—	—
2019	31	AAA RAW	2 teams	—	490	422	104	19	2	2	48	116	3	6	5	246	328	315	643	69	329	24	10	287	59	—	—	—	—	—	—
2020	32	INTL MLE	Naranjeros de Hermosillo	—	24	19	1	0	0	0	2	4	0	0	0	53	143	53	195		62	17	8	—	—	—	—	—	—	—	—
2020	32	INTL RAW	Naranjeros de Hermosillo	—	24	19	1	0	0	0	2	4	0	0	0	53	143	53	195		62	17	8	96	-49	—	—	—	—	—	—
2021	33	INTL MLE	Naranjeros de Hermosillo	—	179	166	41	9	0	4	5	41	1	2	1	247	273	373	647	127	301	23	3	—	—	—	—	—	—	—	—
2021	33	INTL RAW	Naranjeros de Hermosillo	—	179	166	41	9	0	4	5	41	1	2	1	247	273	373	647	127	301	23	3	276	73	—	—	—	—	—	—
2022	34	INTL MLE	Aguilas de Mexicali	—	162	138	25	3	2	0	16	37	0	0	3	181	266	232	498	51	243	23	10	—	—	—	—	—	—	—	—
2022	34	INTL RAW	Aguilas de Mexicali	—	162	138	25	3	2	0	16	37	0	0	3	181	266	232	498	51	243	23	10	224	38	—	—	—	—	—	—
2024	36	INTL MLE	Venados de Mazatlan	—	96	84	17	2	0	1	6	22	1	1	0	202	264	262	526	60	250	23	6	—	—	—	—	—	—	—	—
2024	36	INTL RAW	Venados de Mazatlan	—	96	84	17	2	0	1	6	22	1	1	0	202	264	262	526	60	250	23	6	232	43	—	—	—	—	—	—
2006	18	ROK MLE	GCL Yankees	—	86	78	17	2	0	0	7	12	1	3	2	218	294	244	538	26	247	14	8	240	49	—	—	—	—	—	—
2007	19	ROK MLE	2 teams	—	76	70	10	2	0	0	4	24	2	1	1	143	213	171	385	29	220	32	5	182	9	—	—	—	—	—	—
2008	20	A MLE	2 teams	—	157	150	31	8	1	2	5	31	1	1	2	207	237	313	551	107	244	20	3	232	43	—	—	—	—	—	—
2009	21	A+ MLE	2 teams	—	282	270	65	10	1	0	9	46	1	12	5	241	272	285	557	44	285	16	3	244	51	—	—	—	—	—	—
2010	22	A+ MLE	2 teams	—	449	424	112	20	1	1	16	107	6	20	9	264	309	323	632	59	345	24	4	285	79	—	—	—	—	—	—
2011	23	A+ MLE	2 teams	—	604	571	151	33	3	8	21	123	7	12	8	264	311	375	686	110	316	20	3	298	88	—	—	—	—	—	—
2012	24	AA MLE	3 teams	—	266	255	60	19	3	1	5	53	4	5	2	235	264	345	609	110	289	20	2	256	60	—	—	—	—	—	—
2013	25	INTL MLE	3 teams	—	398	382	93	10	1	5	13	142	0	4	4	243	272	314	587	71	367	36	3	256	59	—	—	—	—	—	—
2014	26	AAA MLE	3 teams	—	663	637	144	18	0	6	18	172	3	10	8	226	256	283	538	57	296	26	3	234	45	—	—	—	—	—	—
2015	27	AAA MLE	2 teams	—	676	646	187	30	3	4	22	110	3	23	6	289	330	364	693	74	337	16	3	296	86	—	—	—	—	—	—
2016	28	AAA MLE	Sultanes de Monterrey	—	450	431	122	22	3	4	14	75	2	10	4	283	316	376	692	93	326	17	3	298	88	—	—	—	—	—	—
2017	29	AAA MLE	2 teams	—	591	566	131	18	3	2	17	157	3	5	3	231	264	284	549	53	309	27	3	235	45	—	—	—	—	—	—
2019	31	AAA MLE	2 teams	—	490	449	96	19	2	2	35	134	3	6	5	214	283	278	562	65	293	27	7	256	59	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	5649	5205	1303	225	23	40	215	1290	38	115	63	250	285	325	611	75	321	23	4	243	50	-333	-2	+0	+61	+122	-15.5
/ 162G	—	MLE		—	650	599	151	26	3	5	25	148	4	13	7	252	287	331	617	78	323	23	4	243	50	-38	-0	+0	+7	+14	-1.8

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.

2019 AAALeones de Yucatan · 362 PAwOBA .304 → .256 (−48)K% 23.2% → 27.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.20%	÷1.018	×1.200	—	—	27.35%
BB% (unintentional) /PA	10.77%	÷0.986	×0.690	—	×0.952	7.18%
HBP% /PA	0.55%	—	×0.940	—	×0.952	0.49%
Singles /BIP	27.06%	÷0.992	×0.930	×0.950	×0.952	22.95%
Doubles /BIP	7.34%	÷0.910	×0.830	×0.950	×0.952	6.05%
Triples /BIP	0.92%	÷1.150	×0.920	×0.950	×0.952	0.66%
Home runs /BIP	0.92%	÷0.792	×0.700	—	×0.952	0.77%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 58, 1B 98, 2B 82, 3B 130, K 104, 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 ×0.950.

Result: wOBA .304 → .256; ISO .086 → .076; BABIP .348 → .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).

2017 AAASultanes de Monterrey · 329 PAwOBA .274 → .235 (−39)K% 21.0% → 26.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.97%	÷0.946	×1.200	—	—	26.60%
BB% (unintentional) /PA	4.56%	÷1.060	×0.690	—	×0.972	2.89%
HBP% /PA	0.00%	—	×0.940	—	×0.972	0.00%
Singles /BIP	27.31%	÷0.978	×0.930	×1.030	×0.972	26.02%
Doubles /BIP	5.04%	÷0.992	×0.830	×1.030	×0.972	4.22%
Triples /BIP	0.84%	÷1.150	×0.920	×1.030	×0.972	0.67%
Home runs /BIP	0.84%	÷1.043	×0.700	—	×0.972	0.55%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 109, 1B 96, 2B 98, 3B 130, K 89, BB 112 — 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 ×1.030.

Result: wOBA .274 → .235; ISO .072 → .055; BABIP .333 → .309. 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 AAASultanes de Monterrey · 450 PAwOBA .347 → .298 (−49)K% 13.3% → 16.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.33%	÷0.961	×1.200	—	—	16.65%
BB% (unintentional) /PA	5.11%	÷1.118	×0.690	—	×0.982	3.10%
HBP% /PA	0.44%	—	×0.940	—	×0.982	0.41%
Singles /BIP	28.86%	÷1.036	×0.930	×1.015	×0.982	25.80%
Doubles /BIP	7.14%	÷0.979	×0.830	×1.015	×0.982	6.03%
Triples /BIP	0.86%	÷0.900	×0.920	×1.015	×0.982	0.87%
Home runs /BIP	1.71%	÷1.051	×0.700	—	×0.982	1.12%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 110, 1B 107, 2B 96, 3B 80, K 92, BB 124 — 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 ×1.015.

Result: wOBA .347 → .298; ISO .120 → .098; BABIP .370 → .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).

2015 AAASultanes de Monterrey · 402 PAwOBA .307 → .296 (−10)K% 14.2% → 16.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.18%	÷1.042	×1.200	—	—	16.32%
BB% (unintentional) /PA	4.48%	÷0.964	×0.690	—	×0.992	3.18%
HBP% /PA	0.25%	—	×0.940	—	×0.992	0.23%
Singles /BIP	27.96%	÷0.977	×0.930	×1.050	×0.992	27.71%
Doubles /BIP	6.58%	÷1.018	×0.830	×1.050	×0.992	5.58%
Triples /BIP	0.66%	÷1.150	×0.920	×1.050	×0.992	0.55%
Home runs /BIP	0.99%	÷0.986	×0.700	—	×0.992	0.69%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 97, 1B 95, 2B 104, 3B 130, K 108, BB 93 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .307 → .296; ISO .091 → .078; BABIP .351 → .337. 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 AAAAlbuquerque Isotopes · 359 PAwOBA .282 → .237 (−44)K% 18.9% → 25.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.94%	÷0.955	×1.290	—	—	25.58%
BB% (unintentional) /PA	3.90%	÷1.049	×0.710	—	×1.003	2.65%
HBP% /PA	0.56%	—	×0.980	—	×1.003	0.55%
Singles /BIP	27.78%	÷1.008	×0.900	×1.050	×1.003	26.12%
Doubles /BIP	4.07%	÷0.982	×0.810	×1.050	×1.003	3.54%
Triples /BIP	0.00%	÷1.150	×0.810	×1.050	×1.003	0.00%
Home runs /BIP	1.85%	÷1.078	×0.780	—	×1.003	1.34%

Factors used: league row PCL. Park (home-season share, regressed): HR 116, 1B 102, 2B 96, 3B 130, K 91, BB 110 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .282 → .237; ISO .077 → .057; BABIP .323 → .299. 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 · 29 PAwOBA .255 → .201 (−54)K% 24.1% → 30.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.14%	÷0.972	×1.220	—	—	30.31%
BB% (unintentional) /PA	6.90%	÷1.036	×0.680	—	×0.978	4.43%
HBP% /PA	0.00%	—	×0.840	—	×0.978	0.00%
Singles /BIP	20.00%	÷1.014	×0.920	—	×0.978	17.74%
Doubles /BIP	10.00%	÷1.053	×0.910	—	×0.978	8.45%
Triples /BIP	0.00%	÷1.150	×0.880	—	×0.978	0.00%
Home runs /BIP	0.00%	÷1.026	×0.800	—	×0.978	0.00%

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 .255 → .201; ISO .074 → .059; BABIP .300 → .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).

2013 AAAScranton/Wilkes-Barre RailRiders · 130 PAwOBA .284 → .248 (−36)K% 32.3% → 38.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.31%	÷1.010	×1.200	—	—	38.38%
BB% (unintentional) /PA	6.15%	÷1.015	×0.690	—	×1.018	4.26%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	30.00%	÷0.971	×0.930	×1.049	×1.018	30.66%
Doubles /BIP	6.25%	÷1.026	×0.830	×1.049	×1.018	5.40%
Triples /BIP	0.00%	÷1.000	×0.970	×1.049	×1.018	0.00%
Home runs /BIP	2.50%	÷0.976	×0.840	—	×1.018	2.19%

Factors used: league row IL. Park (home-season share, regressed): HR 95, 1B 94, 2B 105, 3B 100, K 102, BB 103 — applied at half strength. Age: age 26 vs a level average of 27.2 → +1.8% on BB/HBP/hit rates (1.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.049.

Result: wOBA .284 → .248; ISO .090 → .073; BABIP .372 → .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).

2013 AATrenton Thunder · 82 PAwOBA .313 → .269 (−44)K% 25.6% → 31.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.61%	÷1.003	×1.220	—	—	31.16%
BB% (unintentional) /PA	2.44%	÷1.055	×0.700	—	×0.988	1.60%
HBP% /PA	0.00%	—	×0.850	—	×0.988	0.00%
Singles /BIP	35.71%	÷0.996	×0.970	×0.970	×0.988	33.35%
Doubles /BIP	3.57%	÷1.204	×0.860	×0.970	×0.988	2.45%
Triples /BIP	1.79%	÷1.140	×0.950	×0.970	×0.988	1.43%
Home runs /BIP	1.79%	÷0.979	×0.780	—	×0.988	1.41%

Factors used: league row EL. Park (home-season share, regressed): HR 96, 1B 99, 2B 141, 3B 128, K 101, BB 111 — applied at half strength. Age: age 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.970.

Result: wOBA .313 → .269; ISO .091 → .068; BABIP .404 → .364. 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 — .