Jonathan Diaz

PosSS

B/TR/R

Born1985-04-10

Age (2027)42

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2017

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2015	30	AAATOR	430	.223/.329/.284	2	7	51	—	.212/.286/.268
2015	30	MLBTOR	16	.154/.267/.154	0	0	23	0.4
2016	31	AAAScranton/Wilk…	371	.207/.316/.249	1	4	35	—	.194/.271/.231
2017	32	AAA/AA2 orgs	226	.214/.382/.306	3	2	61	—	.192/.309/.263
2018	33	No MLB games played
2019	34	No MLB games played
2020	35	No MLB games played
2021	36	No MLB games played
2022	37	No MLB games played
2023	38	No MLB games played
2024	39	No MLB games played
2025	40	No MLB games played
2026	41	No MLB games played

Last 3 seasons WAR 0.4

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	22	A	Lansing Lugnuts	—	473	357	88	19	6	1	82	55	15	8	2	246	407	342	749	95	287	12	17	339	80	—	—	—	—	—	—
2008	23	AA	New Hampshire Fisher Cats	—	81	60	12	1	1	0	18	15	0	0	0	200	385	250	635	50	261	19	22	303	72	—	—	—	—	—	—
2008	23	A+	Dunedin Blue Jays	—	141	105	18	2	0	1	25	23	7	1	6	171	365	219	584	48	205	16	18	289	56	—	—	—	—	—	—
2009	24	AAA	Las Vegas 51s	—	104	80	12	0	0	0	14	13	3	0	0	150	299	150	449		179	12	13	220	19	—	—	—	—	—	—
2009	24	AA	New Hampshire Fisher Cats	—	223	182	39	9	0	1	34	32	3	3	4	214	347	280	627	66	255	14	15	295	59	—	—	—	—	—	—
2010	25	AAA	Las Vegas 51s	—	113	94	25	3	0	2	8	18	0	1	0	266	324	362	685	96	307	16	7	280	66	—	—	—	—	—	—
2010	25	AA	New Hampshire Fisher Cats	—	385	312	72	20	1	0	53	48	9	4	2	231	358	301	660	71	270	12	14	304	69	—	—	—	—	—	—
2011	26	AAA	Las Vegas 51s	—	80	64	19	3	0	1	15	15	0	2	1	297	430	391	821	94	367	19	19	375	95	—	—	—	—	—	—
2011	26	AA	New Hampshire Fisher Cats	—	262	218	55	11	0	1	28	48	9	7	5	252	361	317	677	64	318	18	11	310	71	—	—	—	—	—	—
2012	27	AAA	Las Vegas 51s	—	400	312	75	11	2	3	62	56	7	12	4	240	378	317	695	77	280	14	16	313	68	—	—	—	—	—	—
2012	27	AA	New Hampshire Fisher Cats	—	163	145	26	2	0	1	13	28	2	6	2	179	256	214	470	34	214	17	8	221	20	—	—	—	—	—	—
2013	28	AAA	Pawtucket Red Sox	—	399	332	84	11	2	2	47	67	8	10	3	253	359	316	675	63	311	17	12	307	66	—	—	—	—	—	—
2013	28	INTL	Gigantes del Cibao	—	185	134	35	6	0	1	33	26	12	2	2	261	447	328	775	67	315	14	18	362	131	—	—	—	—	—	—
2014	29	MLB	Toronto Blue Jays	—	45	38	6	1	0	0	3	14	2	1	0	158	256	184	440	26	250	31	7	208	27	-4	+0	+2	+5	+1	0.4
2014	29	AAA	Buffalo Bisons	—	303	244	50	13	3	1	37	43	5	4	4	205	322	295	617	90	243	14	12	274	51	—	—	—	—	—	—
2014	29	INTL	Gigantes del Cibao	—	129	101	25	1	0	2	20	27	5	1	1	248	397	317	714	69	315	21	16	333	112	—	—	—	—	—	—
2015	30	MLB	Toronto Blue Jays	—	16	13	2	0	0	0	1	3	1	0	0	154	267	154	421		200	19	6	203	23	-1	+0	+0	+5	+0	0.4
2015	30	AAA	Buffalo Bisons	—	430	359	80	12	2	2	51	64	6	7	3	223	329	284	613	61	264	15	12	281	51	—	—	—	—	—	—
2016	31	AAA	Scranton/Wilkes-Barre RailRiders	—	371	305	63	8	1	1	47	63	2	4	2	207	316	249	566	43	256	17	13	259	35	—	—	—	—	—	—
2017	32	AAA	Scranton/Wilkes-Barre RailRiders	—	208	162	34	5	1	2	32	38	8	2	2	210	366	290	656	80	256	18	15	307	55	—	—	—	—	—	—
2017	32	AA	New Hampshire Fisher Cats	—	18	11	3	0	0	1	7	3	0	0	0	273	556	545	1.101	273	286	17	39	487	136	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	61	51	8	1	0	0	4	17	3	1	0	157	259	176	435	20	235	28	7	207	26	-5	+0	+2	+10	+1	0.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2007	22	A MLE	Lansing Lugnuts	—	473	382	86	17	6	1	57	75	15	8	2	225	348	309	657	84	257	16	12	286	80	—	—	—	—	—	—
2008	23	AA MLE	New Hampshire Fisher Cats	—	81	65	13	1	1	0	13	18	0	0	0	200	333	246	579	46	267	22	16	275	72	—	—	—	—	—	—
2008	23	A+ MLE	Dunedin Blue Jays	—	141	111	18	2	0	1	19	33	7	1	6	162	321	207	528	45	198	23	13	251	56	—	—	—	—	—	—
2009	24	AAA MLE	Las Vegas 51s	—	104	84	13	0	0	0	10	17	3	0	0	155	268	155	423		170	16	10	197	19	—	—	—	—	—	—
2009	24	AA MLE	New Hampshire Fisher Cats	—	223	192	39	8	0	1	24	39	3	3	4	203	301	260	562	57	245	17	11	255	59	—	—	—	—	—	—
2010	25	AAA MLE	Las Vegas 51s	—	113	96	27	3	0	2	6	24	0	1	0	281	324	375	699	94	295	21	5	266	66	—	—	—	—	—	—
2010	25	AA MLE	New Hampshire Fisher Cats	—	385	328	73	20	1	0	37	59	9	4	2	223	318	290	608	67	256	15	10	270	69	—	—	—	—	—	—
2011	26	AAA MLE	Las Vegas 51s	—	80	68	17	2	0	1	11	20	0	2	1	250	354	324	678	74	334	25	14	309	95	—	—	—	—	—	—
2011	26	AA MLE	New Hampshire Fisher Cats	—	262	228	55	10	0	1	18	57	9	7	5	241	322	298	620	57	305	22	7	273	71	—	—	—	—	—	—
2012	27	AAA MLE	Las Vegas 51s	—	400	329	72	9	2	2	45	72	7	12	4	219	325	277	602	58	251	18	11	269	68	—	—	—	—	—	—
2012	27	AA MLE	New Hampshire Fisher Cats	—	163	149	26	2	0	1	9	33	2	6	2	174	231	208	439	34	212	20	6	198	20	—	—	—	—	—	—
2013	28	AAA MLE	Pawtucket Red Sox	—	399	349	83	9	2	2	30	79	8	10	3	238	313	292	605	54	289	20	8	266	66	—	—	—	—	—	—
2014	29	MLB MLE	Toronto Blue Jays	—	45	38	6	1	0	0	3	14	2	1	0	158	256	184	440	26	250	31	7	208	27	-4	+0	+2	+5	+1	0.4
2014	29	AAA MLE	Buffalo Bisons	—	303	257	52	12	3	1	24	55	5	4	4	202	283	284	567	82	231	18	8	243	51	—	—	—	—	—	—
2015	30	MLB MLE	Toronto Blue Jays	—	16	13	2	0	0	0	1	3	1	0	0	154	267	154	421		200	19	6	202	23	-1	+0	+0	+5	+0	0.4
2015	30	AAA MLE	Buffalo Bisons	—	430	377	80	11	2	2	33	76	6	7	3	212	286	268	554	56	247	18	8	244	51	—	—	—	—	—	—
2016	31	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	371	320	62	7	1	1	32	76	2	4	2	194	271	231	502	38	231	20	9	220	35	—	—	—	—	—	—
2017	32	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	208	175	33	5	1	1	19	46	8	2	2	189	297	246	543	57	230	22	9	250	55	—	—	—	—	—	—
2017	32	AA MLE	New Hampshire Fisher Cats	—	18	13	3	0	0	1	5	4	0	0	0	231	444	462	906	231	242	22	28	369	136	—	—	—	—	—	—
2007	22	A MLE	Lansing Lugnuts	—	473	382	86	17	6	1	57	75	15	8	2	225	348	309	657	84	276	16	12	286	80	—	—	—	—	—	—
2007	22	A RAW	Lansing Lugnuts	—	473	357	88	19	6	1	82	55	15	8	2	246	407	342	749	95	287	12	17	339	80	—	—	—	—	—	—
2008	23	A+ MLE	2 teams	—	222	176	31	3	1	1	32	51	7	1	6	176	326	222	547	45	236	23	14	260	62	—	—	—	—	—	—
2008	23	A+ RAW	2 teams	—	222	165	30	3	1	1	43	38	7	1	6	182	372	230	602	48	225	17	19	294	62	—	—	—	—	—	—
2009	24	AA MLE	2 teams	—	327	276	52	8	0	1	34	56	6	3	4	188	291	228	519	40	233	17	10	237	46	—	—	—	—	—	—
2009	24	AA RAW	2 teams	—	327	262	51	9	0	1	48	45	6	3	4	195	332	240	573	46	231	14	15	271	46	—	—	—	—	—	—
2010	25	AA MLE	2 teams	—	498	424	99	23	1	2	43	83	9	5	2	233	317	307	624	73	283	17	9	269	68	—	—	—	—	—	—
2010	25	AA RAW	2 teams	—	498	406	97	23	1	2	61	66	9	5	2	239	351	315	666	76	278	13	12	299	68	—	—	—	—	—	—
2011	26	AA MLE	2 teams	—	342	297	73	13	0	1	28	77	9	9	6	246	329	300	629	54	326	23	8	281	77	—	—	—	—	—	—
2011	26	AA RAW	2 teams	—	342	282	74	14	0	2	43	63	9	9	6	262	377	333	711	71	329	18	13	325	77	—	—	—	—	—	—
2012	27	AAA MLE	2 teams	—	563	478	98	11	2	3	54	105	9	18	6	205	298	255	553	50	253	19	10	248	54	—	—	—	—	—	—
2012	27	AAA RAW	2 teams	—	563	457	101	13	2	4	75	84	9	18	6	221	342	284	626	63	259	15	13	287	54	—	—	—	—	—	—
2013	28	AAA MLE	2 teams	—	584	502	121	13	3	2	44	116	20	12	5	241	327	291	618	50	308	20	8	266	66	—	—	—	—	—	—
2013	28	AAA RAW	2 teams	—	584	466	119	17	2	3	80	93	20	12	5	255	387	320	707	64	312	16	14	325	66	—	—	—	—	—	—
2014	29	AAA MLE	3 teams	—	477	406	79	18	4	1	37	94	12	6	5	195	281	266	547	71	248	20	8	238	48	—	—	—	—	—	—
2014	29	AAA RAW	3 teams	—	477	383	81	15	3	3	60	84	12	6	5	211	336	290	626	78	261	18	13	284	48	—	—	—	—	—	—
2015	30	AAA MLE	2 teams	—	446	390	81	11	2	2	34	79	7	7	3	208	283	262	545	54	254	18	8	242	50	—	—	—	—	—	—
2015	30	AAA RAW	2 teams	—	446	372	82	12	2	2	52	67	7	7	3	220	327	280	607	59	262	15	12	278	50	—	—	—	—	—	—
2016	31	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	371	320	62	7	1	1	32	76	2	4	2	194	271	231	502	38	250	20	9	220	35	—	—	—	—	—	—
2016	31	AAA RAW	Scranton/Wilkes-Barre RailRiders	—	371	305	63	8	1	1	47	63	2	4	2	207	316	249	566	43	256	17	13	259	35	—	—	—	—	—	—
2017	32	AAA MLE	2 teams	—	226	188	36	5	1	2	24	49	8	2	2	191	309	261	570	69	243	22	11	259	62	—	—	—	—	—	—
2017	32	AAA RAW	2 teams	—	226	173	37	5	1	3	39	41	8	2	2	214	382	306	688	92	258	18	17	322	62	—	—	—	—	—	—
2007	22	A MLE	Lansing Lugnuts	—	473	398	86	17	6	1	57	75	15	8	2	216	348	296	645	80	257	16	12	286	80	—	—	—	—	—	—
2008	23	A+ MLE	2 teams	—	222	181	31	3	1	1	32	51	7	1	6	171	326	215	541	44	223	23	14	260	62	—	—	—	—	—	—
2009	24	AA MLE	2 teams	—	327	284	52	8	0	1	34	56	6	3	4	183	291	222	513	39	221	17	10	237	46	—	—	—	—	—	—
2010	25	AA MLE	2 teams	—	498	443	99	23	1	2	43	83	9	5	2	223	317	293	611	70	265	17	9	269	68	—	—	—	—	—	—
2011	26	AA MLE	2 teams	—	342	302	73	13	0	1	28	77	9	9	6	242	329	295	624	53	312	23	8	281	77	—	—	—	—	—	—
2012	27	AAA MLE	2 teams	—	563	495	98	11	2	3	54	105	9	18	6	198	298	246	544	48	240	19	10	248	54	—	—	—	—	—	—
2013	28	AAA MLE	2 teams	—	584	515	121	13	3	2	44	116	20	12	5	235	327	283	610	49	289	20	8	266	66	—	—	—	—	—	—
2014	29	AAA MLE	3 teams	—	477	425	79	18	4	1	37	94	12	6	5	186	281	254	535	68	233	20	8	238	48	—	—	—	—	—	—
2015	30	AAA MLE	2 teams	—	446	402	81	11	2	2	34	79	7	7	3	201	283	254	537	52	245	18	8	242	50	—	—	—	—	—	—
2016	31	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	371	334	62	7	1	1	32	76	2	4	2	186	271	222	493	36	231	20	9	220	35	—	—	—	—	—	—
2017	32	AAA MLE	2 teams	—	226	192	36	5	1	2	24	49	8	2	2	188	309	255	564	68	231	22	11	259	62	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	61	51	8	1	0	0	4	17	3	1	0	157	259	176	435	20	235	28	7	207	59	-5	+0	+2	+10	+1	0.8
/ 162G	—	A+C		—	650	543	86	11	0	0	43	181	32	11	0	158	261	179	439	20	238	28	7	207	59	-57	+2	+21	+105	+14	8.7
Career	—	MLE		—	4529	3839	818	129	21	17	419	861	104	75	43	213	307	271	578	58	268	19	9	256	59	-5	+0	+2	+10	+1	0.8
/ 162G	—	MLE		—	650	551	117	19	3	2	60	124	15	11	6	212	307	269	575	56	268	19	9	256	59	-57	+2	+21	+105	+14	8.7

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 · 208 PAwOBA .305 → .250 (−55)K% 18.3% → 22.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.27%	÷0.995	×1.200	—	—	22.04%
BB% (unintentional) /PA	15.38%	÷1.105	×0.690	—	×0.952	9.15%
HBP% /PA	3.85%	—	×0.940	—	×0.952	3.44%
Singles /BIP	20.97%	÷0.980	×0.930	×1.013	×0.952	19.19%
Doubles /BIP	4.03%	÷0.951	×0.830	×1.013	×0.952	3.39%
Triples /BIP	0.81%	÷1.150	×0.970	×1.013	×0.952	0.66%
Home runs /BIP	1.61%	÷1.247	×0.840	—	×0.952	1.03%

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 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 ×1.013.

Result: wOBA .305 → .250; ISO .080 → .066; BABIP .256 → .230. 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 AANew Hampshire Fisher Cats · 18 PAwOBA .477 → .369 (−109)K% 16.7% → 20.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.67%	÷1.007	×1.220	—	—	20.20%
BB% (unintentional) /PA	38.89%	÷0.995	×0.700	—	×0.940	25.73%
HBP% /PA	0.00%	—	×0.850	—	×0.940	0.00%
Singles /BIP	25.00%	÷1.024	×0.970	—	×0.940	22.26%
Doubles /BIP	0.00%	÷1.024	×0.860	—	×0.940	0.00%
Triples /BIP	0.00%	÷0.900	×0.950	—	×0.940	0.00%
Home runs /BIP	12.50%	÷1.165	×0.780	—	×0.940	7.87%

Factors used: league row EL. Park (home-season share, regressed): HR 133, 1B 105, 2B 105, 3B 80, K 101, BB 99 — applied at half strength. Age: age 32 vs a level average of 24.8 → −6.0% on BB/HBP/hit rates (7.2 yr older than average).

Result: wOBA .477 → .369; ISO .273 → .209; BABIP .286 → .242. 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 AAAScranton/Wilkes-Barre RailRiders · 371 PAwOBA .254 → .220 (−34)K% 17.0% → 20.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.98%	÷0.994	×1.200	—	—	20.50%
BB% (unintentional) /PA	12.67%	÷0.977	×0.690	—	×0.962	8.61%
HBP% /PA	0.54%	—	×0.940	—	×0.962	0.49%
Singles /BIP	21.90%	÷0.991	×0.930	×1.017	×0.962	20.12%
Doubles /BIP	3.31%	÷1.059	×0.830	×1.017	×0.962	2.54%
Triples /BIP	0.41%	÷0.900	×0.970	×1.017	×0.962	0.44%
Home runs /BIP	0.41%	÷0.996	×0.840	—	×0.962	0.34%

Factors used: league row IL. Park (home-season share, regressed): HR 99, 1B 98, 2B 112, 3B 80, K 99, BB 95 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.017.

Result: wOBA .254 → .220; ISO .043 → .038; BABIP .256 → .231. 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 AAABuffalo Bisons · 430 PAwOBA .276 → .244 (−31)K% 14.9% → 17.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.88%	÷1.008	×1.200	—	—	17.72%
BB% (unintentional) /PA	11.86%	÷1.040	×0.690	—	×0.972	7.65%
HBP% /PA	1.40%	—	×0.940	—	×0.972	1.27%
Singles /BIP	21.69%	÷0.981	×0.930	×1.023	×0.972	20.45%
Doubles /BIP	4.07%	÷0.944	×0.830	×1.023	×0.972	3.56%
Triples /BIP	0.68%	÷0.900	×0.970	×1.023	×0.972	0.73%
Home runs /BIP	0.68%	÷0.966	×0.840	—	×0.972	0.57%

Factors used: league row IL. Park (home-season share, regressed): HR 93, 1B 96, 2B 89, 3B 80, K 102, BB 108 — 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 ×1.023.

Result: wOBA .276 → .244; ISO .061 → .059; BABIP .264 → .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).

2014 AAABuffalo Bisons · 303 PAwOBA .269 → .243 (−27)K% 14.2% → 18.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.19%	÷0.942	×1.200	—	—	18.08%
BB% (unintentional) /PA	12.21%	÷1.041	×0.690	—	×0.982	7.95%
HBP% /PA	1.65%	—	×0.940	—	×0.982	1.52%
Singles /BIP	16.42%	÷0.968	×0.930	×1.050	×0.982	16.27%
Doubles /BIP	6.47%	÷0.985	×0.830	×1.050	×0.982	5.62%
Triples /BIP	1.49%	÷1.150	×0.970	×1.050	×0.982	1.30%
Home runs /BIP	0.50%	÷1.006	×0.840	—	×0.982	0.41%

Factors used: league row IL. Park (home-season share, regressed): HR 101, 1B 94, 2B 97, 3B 130, K 88, BB 108 — 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 .269 → .243; ISO .090 → .085; BABIP .243 → .231. 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 AAAPawtucket Red Sox · 399 PAwOBA .301 → .266 (−35)K% 16.8% → 19.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.79%	÷1.018	×1.200	—	—	19.80%
BB% (unintentional) /PA	11.78%	÷1.069	×0.690	—	×0.992	7.55%
HBP% /PA	2.01%	—	×0.940	—	×0.992	1.87%
Singles /BIP	26.04%	÷0.964	×0.930	×1.000	×0.992	24.91%
Doubles /BIP	4.15%	÷1.083	×0.830	×1.000	×0.992	3.16%
Triples /BIP	0.75%	÷0.957	×0.970	×1.000	×0.992	0.76%
Home runs /BIP	0.75%	÷1.068	×0.840	—	×0.992	0.59%

Factors used: league row IL. Park (home-season share, regressed): HR 114, 1B 93, 2B 117, 3B 91, K 104, BB 114 — 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 ×1.000.

Result: wOBA .301 → .266; ISO .063 → .055; BABIP .311 → .289. 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 AAALas Vegas 51s · 400 PAwOBA .310 → .269 (−40)K% 14.0% → 18.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.00%	÷1.004	×1.290	—	—	17.98%
BB% (unintentional) /PA	15.50%	÷0.985	×0.710	—	×1.003	11.21%
HBP% /PA	1.75%	—	×0.980	—	×1.003	1.72%
Singles /BIP	23.05%	÷0.985	×0.900	×1.010	×1.003	21.33%
Doubles /BIP	4.30%	÷1.085	×0.810	×1.010	×1.003	3.25%
Triples /BIP	0.78%	÷0.994	×0.810	×1.010	×1.003	0.64%
Home runs /BIP	1.17%	÷1.059	×0.780	—	×1.003	0.87%

Factors used: league row PCL. Park (home-season share, regressed): HR 112, 1B 97, 2B 117, 3B 99, K 101, BB 97 — 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 ×1.010.

Result: wOBA .310 → .269; ISO .077 → .063; BABIP .280 → .251. 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 AANew Hampshire Fisher Cats · 163 PAwOBA .217 → .198 (−19)K% 17.2% → 20.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.18%	÷1.037	×1.220	—	—	20.22%
BB% (unintentional) /PA	7.98%	÷0.943	×0.700	—	×0.978	5.79%
HBP% /PA	1.23%	—	×0.850	—	×0.978	1.02%
Singles /BIP	19.66%	÷0.994	×0.970	×1.049	×0.978	19.67%
Doubles /BIP	1.71%	÷0.987	×0.860	×1.049	×0.978	1.53%
Triples /BIP	0.00%	÷0.900	×0.950	×1.049	×0.978	0.00%
Home runs /BIP	0.85%	÷1.019	×0.780	—	×0.978	0.64%

Factors used: league row EL. Park (home-season share, regressed): HR 104, 1B 99, 2B 97, 3B 80, K 107, BB 89 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.049.

Result: wOBA .217 → .198; ISO .034 → .028; BABIP .214 → .212. 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 — .