Gregorio Petit

Pos2B

B/TR/R

Born1984-12-10

Age (2027)42

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2018

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2016	31	AAA/INTL2 orgs	201	.270/.335/.339	0	2	68	—	.246/.283/.281
2016	31	MLBLAA	223	.245/.300/.348	2	1	82	0.1
2017	32	AAA/INTL2 orgs	421	.265/.303/.392	7	5	66	—	.214/.230/.309
2018	33	AAA/INTL2 orgs	382	.256/.305/.311	1	5	43	—	.228/.263/.279
2018	33	MLBMIN	67	.246/.313/.279	0	3	73	0.3
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.

Skills · percentileStatcast 2015-2018

Speed23

Avg EV16

Barrel%10

xwOBA10

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)
2005	20	A	Kane County Cougars	—	318	287	83	10	4	9	26	44	1	8	2	289	350	446	796	157	315	14	8	350	84	—	—	—	—	—	—
2006	21	A+	Stockton Ports	—	576	519	133	25	7	8	38	96	5	22	13	256	313	378	691	121	298	17	7	303	63	—	—	—	—	—	—
2007	22	AAA	Sacramento River Cats	—	260	235	65	12	0	2	16	48	3	1	2	277	331	353	684	77	335	18	6	304	70	—	—	—	—	—	—
2007	22	AA	Midland RockHounds	—	299	268	82	14	0	4	25	44	1	9	3	306	367	403	770	97	353	15	8	342	90	—	—	—	—	—	—
2008	23	MLB	Oakland Athletics	—	25	23	8	2	0	0	2	9	0	0	0	348	400	435	835	87	571	36	8	376	140	+1	+0	+0	+1	+1	0.3
2008	23	AAA	Sacramento River Cats	—	339	308	83	14	3	1	23	60	1	3	5	269	322	344	666	75	332	18	7	296	64	—	—	—	—	—	—
2009	24	MLB	Oakland Athletics	—	31	31	7	1	0	0	0	6	0	0	0	226	226	258	484	32	280	19	0	217	33	-2	+0	-2	+2	+1	-0.2
2009	24	AAA	Sacramento River Cats	—	398	357	87	18	0	5	26	83	1	0	2	244	297	336	633	92	297	21	7	277	48	—	—	—	—	—	—
2010	25	AAA	Oklahoma City RedHawks	—	525	471	118	20	1	7	40	96	6	13	3	251	317	342	659	91	300	18	8	296	47	—	—	—	—	—	—
2010	25	INTL	Leones del Caracas	—	134	110	25	8	0	0	17	21	2	2	4	227	341	300	641	73	278	16	13	291	83	—	—	—	—	—	—
2011	26	INTL	Leones del Caracas	—	103	95	18	6	0	0	5	15	1	0	1	189	238	253	490	63	225	15	5	221	36	—	—	—	—	—	—
2012	27	AAA	Columbus Clippers	—	422	377	98	24	0	10	29	75	6	1	2	260	323	403	726	143	297	18	7	318	62	—	—	—	—	—	—
2012	27	INTL	Leones del Caracas	—	100	87	23	8	0	0	5	12	5	3	2	264	340	356	697	92	307	12	5	310	96	—	—	—	—	—	—
2013	28	AAA	Tucson Padres	—	555	503	147	26	3	4	40	75	2	5	3	292	347	380	727	87	334	14	7	323	63	—	—	—	—	—	—
2013	28	INTL	Leones del Caracas	—	172	154	48	12	0	10	12	42	0	0	0	312	361	584	946	273	355	24	7	396	154	—	—	—	—	—	—
2014	29	MLB	Houston Astros	—	100	97	27	8	0	2	1	25	2	0	1	278	300	423	723	144	357	25	1	320	99	-0	-0	+0	+6	+2	0.8
2014	29	AAA	Oklahoma City RedHawks	—	347	317	94	19	1	10	20	52	3	1	3	297	344	457	802	161	324	15	6	348	78	—	—	—	—	—	—
2014	29	INTL	Leones del Caracas	—	123	113	28	5	0	0	8	24	2	0	0	248	309	292	601	44	315	20	7	279	75	—	—	—	—	—	—
2015	30	MLB	New York Yankees	—	47	42	7	3	0	0	3	16	0	0	0	167	222	238	460	71	259	34	6	204	15	-5	+0	-2	+1	+1	-0.5
2015	30	AAA	Scranton/Wilkes-Barre RailRiders	—	183	174	40	10	0	2	8	22	0	0	0	230	264	322	586	92	253	12	4	262	33	—	—	—	—	—	—
2016	31	MLB	Los Angeles Angels	—	223	204	50	13	1	2	15	51	1	1	1	245	300	348	648	103	316	23	7	289	82	-5	-0	-0	+2	+5	0.1
2016	31	AAA	Salt Lake Bees	—	62	55	18	3	0	0	5	13	0	2	0	327	383	382	765	55	419	21	8	337	62	—	—	—	—	—	—
2016	31	INTL	Leones del Caracas	—	139	119	29	9	0	0	11	29	1	0	1	244	313	319	632	76	315	21	8	274	71	—	—	—	—	—	—
2017	32	AAA	Buffalo Bisons	—	297	281	71	19	1	4	10	48	0	2	1	253	278	370	648	117	288	16	3	282	44	—	—	—	—	—	—
2017	32	INTL	Leones del Caracas	—	124	107	32	7	0	3	11	17	0	3	0	299	364	449	813	150	326	14	9	345	120	—	—	—	—	—	—
2018	33	MLB	Minnesota Twins	—	67	61	15	2	0	0	6	14	0	3	1	246	313	279	592	33	319	21	9	276	73	-2	+0	+2	+2	+1	0.3
2018	33	AAA	Rochester Red Wings	—	312	284	76	12	1	1	17	47	3	4	1	268	316	327	643	60	314	15	5	286	45	—	—	—	—	—	—
2018	33	INTL	Leones del Caracas	—	70	63	13	2	0	0	4	7	0	1	0	206	254	238	492	32	232	10	6	219	34	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	493	458	114	29	1	4	27	121	3	4	3	249	295	343	638	94	328	25	5	285	79	-12	-0	-2	+13	+11	1.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	20	A MLE	Kane County Cougars	—	318	295	75	8	4	7	18	60	1	8	2	254	299	380	679	125	292	19	6	293	84	—	—	—	—	—	—
2006	21	A+ MLE	Stockton Ports	—	576	530	122	21	6	7	27	128	5	22	13	230	274	332	606	102	278	22	5	261	63	—	—	—	—	—	—
2007	22	AAA MLE	Sacramento River Cats	—	260	239	61	10	0	2	12	62	3	1	2	255	299	322	621	67	321	24	5	271	70	—	—	—	—	—	—
2007	22	AA MLE	Midland RockHounds	—	299	275	77	12	0	3	18	54	1	9	3	280	327	356	683	76	332	18	6	301	90	—	—	—	—	—	—
2008	23	MLB MLE	Oakland Athletics	—	25	23	8	2	0	0	2	9	0	0	0	348	400	435	835	87	571	36	8	376	140	+1	+0	+0	+1	+1	0.3
2008	23	AAA MLE	Sacramento River Cats	—	339	314	79	12	3	1	17	77	1	3	5	252	292	318	611	67	322	23	5	263	64	—	—	—	—	—	—
2009	24	MLB MLE	Oakland Athletics	—	31	31	7	1	0	0	0	6	0	0	0	226	226	258	484	32	280	19	0	217	33	-2	+0	-2	+2	+1	-0.2
2009	24	AAA MLE	Sacramento River Cats	—	398	365	79	15	0	4	18	107	1	0	2	216	255	290	546	74	275	27	5	239	48	—	—	—	—	—	—
2010	25	AAA MLE	Oklahoma City RedHawks	—	525	483	99	16	1	6	28	127	6	13	3	205	257	280	537	75	259	24	5	237	47	—	—	—	—	—	—
2012	27	AAA MLE	Columbus Clippers	—	422	386	86	20	0	7	20	92	6	1	2	223	272	329	601	106	262	22	5	260	62	—	—	—	—	—	—
2013	28	AAA MLE	Tucson Padres	—	555	517	127	22	2	3	26	104	2	5	3	246	284	313	598	68	291	19	5	262	63	—	—	—	—	—	—
2014	29	MLB MLE	Houston Astros	—	100	97	27	8	0	2	1	25	2	0	1	278	300	423	723	144	357	25	1	315	99	-0	-0	+0	+6	+2	0.8
2014	29	AAA MLE	Oklahoma City RedHawks	—	347	324	82	17	1	7	13	68	3	1	3	253	288	377	665	123	284	20	4	284	78	—	—	—	—	—	—
2015	30	MLB MLE	New York Yankees	—	47	43	7	3	0	0	2	16	0	0	0	163	200	233	433	70	259	34	4	190	15	-5	+0	-2	+1	+1	-0.5
2015	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	—	183	178	36	9	0	2	4	27	0	0	0	202	220	287	506	84	224	15	2	217	33	—	—	—	—	—	—
2016	31	MLB MLE	Los Angeles Angels	—	223	205	51	14	1	2	14	51	1	1	1	249	300	356	656	107	316	23	6	289	82	-5	-0	-0	+2	+5	0.1
2016	31	AAA MLE	Salt Lake Bees	—	62	57	14	2	0	0	3	17	0	2	0	246	283	281	564	35	342	27	5	260	62	—	—	—	—	—	—
2017	32	AAA MLE	Buffalo Bisons	—	297	285	61	16	1	3	6	61	0	2	1	214	230	309	539	95	249	21	2	233	44	—	—	—	—	—	—
2018	33	MLB MLE	Minnesota Twins	—	67	61	15	2	0	0	6	14	0	3	1	246	313	279	592	33	319	21	9	276	73	-2	+0	+2	+2	+1	0.3
2018	33	AAA MLE	Rochester Red Wings	—	312	290	66	10	1	1	11	58	3	4	1	228	263	279	542	52	267	19	4	234	45	—	—	—	—	—	—
2005	20	A MLE	Kane County Cougars	—	318	295	75	8	4	7	18	60	1	8	2	254	299	380	679	125	297	19	6	293	84	—	—	—	—	—	—
2005	20	A RAW	Kane County Cougars	—	318	287	83	10	4	9	26	44	1	8	2	289	350	446	796	157	315	14	8	350	84	—	—	—	—	—	—
2006	21	A+ MLE	Stockton Ports	—	576	530	122	21	6	7	27	128	5	22	13	230	274	332	606	102	287	22	5	261	63	—	—	—	—	—	—
2006	21	A+ RAW	Stockton Ports	—	576	519	133	25	7	8	38	96	5	22	13	256	313	378	691	121	298	17	7	303	63	—	—	—	—	—	—
2007	22	AA MLE	2 teams	—	559	514	139	23	0	5	30	116	4	10	5	270	316	344	660	74	338	21	5	287	80	—	—	—	—	—	—
2007	22	AA RAW	2 teams	—	559	503	147	26	0	6	41	92	4	10	5	292	350	380	730	87	345	16	7	325	80	—	—	—	—	—	—
2008	23	AAA MLE	2 teams	—	364	337	87	14	3	1	19	86	1	3	5	258	300	326	626	68	344	24	5	271	69	—	—	—	—	—	—
2008	23	AAA RAW	2 teams	—	364	331	91	16	3	1	25	69	1	3	5	275	328	350	678	76	345	19	7	302	69	—	—	—	—	—	—
2009	24	AAA MLE	2 teams	—	429	396	86	16	0	4	18	113	1	0	2	217	253	288	541	71	287	26	4	237	47	—	—	—	—	—	—
2009	24	AAA RAW	2 teams	—	429	388	94	19	0	5	26	89	1	0	2	242	292	330	621	88	296	21	6	273	47	—	—	—	—	—	—
2010	25	AAA MLE	2 teams	—	659	602	124	21	1	7	36	159	8	15	7	206	260	279	539	73	267	24	5	237	47	—	—	—	—	—	—
2010	25	AAA RAW	2 teams	—	659	581	143	28	1	7	57	117	8	15	7	246	322	334	656	88	296	18	9	295	47	—	—	—	—	—	—
2011	26	INTL MLE	Leones del Caracas	—	103	95	18	6	0	0	5	15	1	0	1	189	238	253	490	63	225	15	5	—	—	—	—	—	—	—	—
2011	26	INTL RAW	Leones del Caracas	—	103	95	18	6	0	0	5	15	1	0	1	189	238	253	490	63	225	15	5	221	36	—	—	—	—	—	—
2012	27	AAA MLE	2 teams	—	522	473	107	25	0	9	25	114	11	4	4	226	281	336	617	110	277	22	5	260	62	—	—	—	—	—	—
2012	27	AAA RAW	2 teams	—	522	464	121	32	0	10	34	87	11	4	4	261	326	394	721	134	299	17	7	316	62	—	—	—	—	—	—
2013	28	AAA MLE	2 teams	—	727	676	167	29	3	4	33	136	2	5	3	247	284	317	601	70	299	19	5	262	63	—	—	—	—	—	—
2013	28	AAA RAW	2 teams	—	727	657	195	38	3	14	52	117	2	5	3	297	350	428	778	131	338	16	7	340	63	—	—	—	—	—	—
2014	29	AAA MLE	3 teams	—	570	538	138	31	1	12	18	118	7	1	4	257	290	385	674	128	306	21	3	291	83	—	—	—	—	—	—
2014	29	AAA RAW	3 teams	—	570	527	149	32	1	12	29	101	7	1	4	283	329	416	744	133	328	18	5	328	83	—	—	—	—	—	—
2015	30	AAA MLE	2 teams	—	230	221	43	12	0	2	6	43	0	0	0	195	216	276	492	81	232	19	3	211	29	—	—	—	—	—	—
2015	30	AAA RAW	2 teams	—	230	216	47	13	0	2	11	38	0	0	0	218	256	306	561	88	254	17	5	250	29	—	—	—	—	—	—
2016	31	MLB MLE	3 teams	—	424	384	98	24	2	3	25	102	2	3	2	255	304	352	656	96	336	24	6	282	77	-11	-0	-0	+2	+9	-0.1
2016	31	MLB RAW	3 teams	—	424	378	97	25	1	2	31	93	2	3	2	257	316	344	660	87	331	22	7	291	77	-11	-0	-0	+2	+9	-0.1
2017	32	AAA MLE	2 teams	—	421	400	87	23	1	5	9	86	0	5	1	217	235	318	552	100	260	20	2	233	44	—	—	—	—	—	—
2017	32	AAA RAW	2 teams	—	421	388	103	26	1	7	21	65	0	5	1	265	303	392	695	126	298	15	5	301	44	—	—	—	—	—	—
2018	33	AAA MLE	3 teams	—	449	415	96	14	1	1	20	85	3	8	2	231	272	277	549	46	286	19	4	241	50	—	—	—	—	—	—
2018	33	AAA RAW	3 teams	—	449	408	104	16	1	1	27	68	3	8	2	255	306	306	612	51	301	15	6	274	50	—	—	—	—	—	—
2005	20	A MLE	Kane County Cougars	—	318	296	75	8	4	7	18	60	1	8	2	253	299	378	678	125	292	19	6	293	84	—	—	—	—	—	—
2006	21	A+ MLE	Stockton Ports	—	576	539	122	21	6	7	27	128	5	22	13	226	274	327	601	100	278	22	5	261	63	—	—	—	—	—	—
2007	22	AA MLE	2 teams	—	559	520	139	23	0	5	30	116	4	10	5	267	316	340	656	73	327	21	5	287	80	—	—	—	—	—	—
2008	23	AAA MLE	2 teams	—	364	341	87	14	3	1	19	86	1	3	5	255	300	323	622	67	339	24	5	271	69	—	—	—	—	—	—
2009	24	AAA MLE	2 teams	—	429	407	86	16	0	4	18	113	1	0	2	211	253	280	533	69	275	26	4	237	47	—	—	—	—	—	—
2010	25	AAA MLE	2 teams	—	659	610	124	21	1	7	36	159	8	15	7	203	260	275	535	72	259	24	5	237	47	—	—	—	—	—	—
2012	27	AAA MLE	2 teams	—	522	481	107	25	0	9	25	114	11	4	4	222	281	331	612	108	262	22	5	260	62	—	—	—	—	—	—
2013	28	AAA MLE	2 teams	—	727	686	167	29	3	4	33	136	2	5	3	243	284	312	596	69	291	19	5	262	63	—	—	—	—	—	—
2014	29	AAA MLE	3 teams	—	570	540	138	31	1	12	18	118	7	1	4	256	290	383	673	128	300	21	3	291	83	—	—	—	—	—	—
2015	30	AAA MLE	2 teams	—	230	222	43	12	0	2	6	43	0	0	0	194	216	275	491	81	231	19	3	211	29	—	—	—	—	—	—
2016	31	MLB MLE	3 teams	—	424	394	98	24	2	3	25	102	2	3	2	249	304	343	647	94	321	24	6	282	77	—	—	—	—	—	—
2017	32	AAA MLE	2 teams	—	421	409	87	23	1	5	9	86	0	5	1	213	235	311	545	98	249	20	2	233	44	—	—	—	—	—	—
2018	33	AAA MLE	3 teams	—	449	423	96	14	1	1	20	85	3	8	2	227	272	272	544	45	276	19	4	241	50	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	493	458	114	29	1	4	27	121	3	4	3	249	295	343	638	94	328	25	5	285	60	-12	-0	-2	+13	+11	1.0
/ 162G	—	A+C		—	650	604	149	38	1	5	36	160	4	5	4	247	294	338	632	91	326	25	6	285	60	-16	-1	-2	+17	+14	1.3
Career	—	MLE		—	6351	5876	1387	267	22	67	289	1361	46	84	51	236	277	323	600	87	293	21	5	256	60	-12	-0	-2	+13	+11	1.0
/ 162G	—	MLE		—	650	601	142	27	2	7	30	139	5	9	5	236	278	323	601	87	293	21	5	256	60	-16	-1	-2	+17	+14	1.3

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.

2018 AAARochester Red Wings · 312 PAwOBA .281 → .234 (−48)K% 15.1% → 18.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.06%	÷0.978	×1.200	—	—	18.49%
BB% (unintentional) /PA	5.45%	÷1.008	×0.690	—	×0.940	3.50%
HBP% /PA	0.96%	—	×0.940	—	×0.940	0.85%
Singles /BIP	26.16%	÷1.023	×0.930	×1.011	×0.940	22.59%
Doubles /BIP	5.06%	÷1.009	×0.830	×1.011	×0.940	3.96%
Triples /BIP	0.42%	÷1.150	×0.970	×1.011	×0.940	0.34%
Home runs /BIP	0.42%	÷0.879	×0.840	—	×0.940	0.38%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 105, 2B 102, 3B 130, K 96, BB 102 — applied at half strength. Age: age 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.011.

Result: wOBA .281 → .234; ISO .060 → .049; BABIP .314 → .267. 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 AAABuffalo Bisons · 297 PAwOBA .278 → .233 (−45)K% 16.2% → 20.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.16%	÷0.950	×1.200	—	—	20.41%
BB% (unintentional) /PA	3.37%	÷1.027	×0.690	—	×0.942	2.13%
HBP% /PA	0.00%	—	×0.940	—	×0.942	0.00%
Singles /BIP	20.17%	÷1.021	×0.930	×1.020	×0.942	17.66%
Doubles /BIP	8.15%	÷0.940	×0.830	×1.020	×0.942	6.92%
Triples /BIP	0.43%	÷0.961	×0.970	×1.020	×0.942	0.42%
Home runs /BIP	1.72%	÷0.903	×0.840	—	×0.942	1.51%

Factors used: league row IL. Park (home-season share, regressed): HR 80, 1B 104, 2B 88, 3B 92, K 90, BB 106 — 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 ×1.020.

Result: wOBA .278 → .233; ISO .117 → .100; BABIP .288 → .249. 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 AAASalt Lake Bees · 62 PAwOBA .328 → .260 (−68)K% 21.0% → 27.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.97%	÷0.969	×1.290	—	—	27.92%
BB% (unintentional) /PA	6.45%	÷1.021	×0.710	—	×0.952	4.27%
HBP% /PA	0.00%	—	×0.980	—	×0.952	0.00%
Singles /BIP	35.71%	÷1.033	×0.900	—	×0.952	29.62%
Doubles /BIP	7.14%	÷1.020	×0.810	—	×0.952	5.40%
Triples /BIP	0.00%	÷1.137	×0.810	—	×0.952	0.00%
Home runs /BIP	0.00%	÷1.035	×0.780	—	×0.952	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 107, 1B 107, 2B 104, 3B 127, K 94, BB 104 — 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).

Result: wOBA .328 → .260; ISO .055 → .041; BABIP .419 → .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).

2015 AAAScranton/Wilkes-Barre RailRiders · 183 PAwOBA .252 → .217 (−36)K% 12.0% → 14.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.02%	÷0.991	×1.200	—	—	14.56%
BB% (unintentional) /PA	3.83%	÷1.139	×0.690	—	×0.962	2.23%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	18.42%	÷1.011	×0.930	×1.001	×0.962	16.32%
Doubles /BIP	6.58%	÷0.903	×0.830	×1.001	×0.962	5.82%
Triples /BIP	0.00%	÷1.150	×0.970	×1.001	×0.962	0.00%
Home runs /BIP	1.32%	÷0.878	×0.840	—	×0.962	1.21%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 102, 2B 81, 3B 130, K 98, BB 128 — 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 ×1.001.

Result: wOBA .252 → .217; ISO .092 → .083; BABIP .253 → .224. 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 AAAOklahoma City RedHawks · 347 PAwOBA .341 → .284 (−56)K% 15.0% → 19.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.99%	÷0.994	×1.290	—	—	19.46%
BB% (unintentional) /PA	5.19%	÷0.977	×0.710	—	×0.972	3.67%
HBP% /PA	0.86%	—	×0.980	—	×0.972	0.82%
Singles /BIP	24.15%	÷1.018	×0.900	×1.036	×0.972	21.51%
Doubles /BIP	7.17%	÷0.935	×0.810	×1.036	×0.972	6.26%
Triples /BIP	0.38%	÷1.150	×0.810	×1.036	×0.972	0.27%
Home runs /BIP	3.77%	÷1.042	×0.780	—	×0.972	2.74%

Factors used: league row PCL. Park (home-season share, regressed): HR 108, 1B 104, 2B 87, 3B 130, K 99, BB 95 — 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 ×1.036.

Result: wOBA .341 → .284; ISO .161 → .125; BABIP .324 → .284. 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 AAATucson Padres · 555 PAwOBA .315 → .262 (−53)K% 13.5% → 18.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.51%	÷0.933	×1.290	—	—	18.68%
BB% (unintentional) /PA	6.85%	÷1.045	×0.710	—	×0.982	4.57%
HBP% /PA	0.36%	—	×0.980	—	×0.982	0.35%
Singles /BIP	26.64%	÷1.023	×0.900	×1.024	×0.982	23.55%
Doubles /BIP	6.07%	÷0.963	×0.810	×1.024	×0.982	5.14%
Triples /BIP	0.70%	÷1.150	×0.810	×1.024	×0.982	0.50%
Home runs /BIP	0.93%	÷0.901	×0.780	—	×0.982	0.79%

Factors used: league row PCL. Park (home-season share, regressed): HR 80, 1B 105, 2B 93, 3B 130, K 87, BB 109 — 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 ×1.024.

Result: wOBA .315 → .262; ISO .087 → .072; BABIP .334 → .291. 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 AAAColumbus Clippers · 422 PAwOBA .312 → .260 (−52)K% 17.8% → 21.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.77%	÷0.974	×1.200	—	—	21.89%
BB% (unintentional) /PA	6.87%	÷0.998	×0.690	—	×0.992	4.71%
HBP% /PA	1.42%	—	×0.940	—	×0.992	1.33%
Singles /BIP	21.19%	÷1.002	×0.930	×0.995	×0.992	19.41%
Doubles /BIP	7.95%	÷0.999	×0.830	×0.995	×0.992	6.52%
Triples /BIP	0.00%	÷1.101	×0.970	×0.995	×0.992	0.00%
Home runs /BIP	3.31%	÷1.178	×0.840	—	×0.992	2.34%

Factors used: league row IL. Park (home-season share, regressed): HR 136, 1B 100, 2B 100, 3B 120, K 95, BB 100 — 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 ×0.995.

Result: wOBA .312 → .260; ISO .143 → .109; BABIP .297 → .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).

2010 AAAOklahoma City RedHawks · 525 PAwOBA .290 → .237 (−53)K% 18.3% → 24.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.29%	÷0.974	×1.290	—	—	24.21%
BB% (unintentional) /PA	7.62%	÷1.015	×0.710	—	×1.018	5.43%
HBP% /PA	1.14%	—	×0.980	—	×1.018	1.14%
Singles /BIP	24.00%	÷1.070	×0.900	×1.018	×1.018	20.92%
Doubles /BIP	5.33%	÷0.996	×0.810	×1.018	×1.018	4.50%
Triples /BIP	0.27%	÷1.150	×0.810	×1.018	×1.018	0.19%
Home runs /BIP	1.87%	÷0.936	×0.780	—	×1.018	1.58%

Factors used: league row PCL. Park (home-season share, regressed): HR 87, 1B 114, 2B 99, 3B 130, K 95, 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 ×1.018.

Result: wOBA .290 → .237; ISO .091 → .074; BABIP .300 → .259. 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 — .