Avisaíl García

PosRF

B/TR/R

Born1991-06-12

Age (2027)36

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2024

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2022	31	AAAMIA	34	.250/.364/.321	0	2	56	—	.200/.273/.267
2022	31	MLBMIA	380	.224/.267/.317	8	4	69	-1.3
2023	32	AAA/AAMIA	53	.227/.358/.568	4	0	76	—	.191/.283/.446
2023	32	MLBMIA	118	.185/.237/.315	3	2	55	-0.5
2024	33	MLBMIA	51	.240/.255/.380	2	0	82	-0.0
2025	34	No MLB games played
2026	35	No MLB games played

Last 3 seasons WAR -1.8

Contract

No contract data on file.

Skills · percentileStatcast 2022-2024

Speed63

Avg EV47

Barrel%46

xwOBA33

Bat Spd28

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)
2008	17	ROK	VSL Tigers	—	263	245	73	12	2	7	15	39	2	7	5	298	344	449	792	151	330	15	6	351	36	—	—	—	—	—	—
2009	18	A	West Michigan Whitecaps	—	315	299	79	11	2	1	8	70	4	8	7	264	293	324	617	60	336	22	3	275	51	—	—	—	—	—	—
2010	19	A	West Michigan Whitecaps	—	524	494	139	17	4	4	20	113	5	20	4	281	316	356	672	75	353	22	4	300	53	—	—	—	—	—	—
2011	20	A+	Lakeland Flying Tigers	—	515	488	129	16	6	11	18	132	6	14	5	264	299	389	688	125	339	26	3	305	53	—	—	—	—	—	—
2012	21	MLB	Detroit Tigers	—	51	47	15	0	0	0	3	10	1	0	2	319	373	319	692		405	20	6	322	97	-0	-1	-1	-7	+1	-0.7
2012	21	AA	Erie SeaWolves	—	226	215	67	9	3	6	7	38	4	9	4	312	345	465	810	153	357	17	3	359	102	—	—	—	—	—	—
2012	21	A+	Lakeland Flying Tigers	—	283	262	74	7	5	8	11	57	5	14	4	282	324	439	763	156	327	20	4	332	74	—	—	—	—	—	—
2012	21	INTL	Caribes de Anzoategui	—	60	54	10	2	0	0	5	15	1	1	1	185	267	222	489	37	256	25	8	234	44	—	—	—	—	—	—
2013	22	MLB	Chicago White Sox	—	256	244	69	7	3	7	9	59	1	3	3	283	311	422	733	139	344	23	4	322	103	+1	-1	-7	-5	+6	-0.6
2013	22	AAA	Charlotte Knights	—	188	174	65	7	2	6	12	36	2	4	2	374	420	540	960	167	447	19	6	424	151	—	—	—	—	—	—
2013	22	A+	Lakeland Flying Tigers	—	28	24	10	0	2	1	4	1	0	2	0	417	500	708	1.208	292	409	4	14	516	173	—	—	—	—	—	—
2014	23	MLB	Chicago White Sox	—	190	172	42	8	0	7	14	44	2	4	1	244	309	413	721	169	285	23	7	318	98	-0	+0	-6	-4	+4	-0.6
2014	23	AAA	Charlotte Knights	—	53	50	17	3	0	1	1	16	2	0	0	340	377	460	837	120	485	30	2	375	100	—	—	—	—	—	—
2014	23	INTL	Tigres de Aragua	—	142	125	39	8	2	5	11	34	2	4	1	312	377	528	905	216	378	24	8	386	147	—	—	—	—	—	—
2015	24	MLB	Chicago White Sox	—	601	553	142	17	2	13	36	141	8	7	7	257	312	365	677	108	320	23	6	304	89	-8	-1	-6	-6	+13	-0.9
2016	25	MLB	Chicago White Sox	—	453	413	101	18	2	12	34	115	4	4	4	245	308	385	693	140	309	25	8	310	95	-3	-1	-2	-6	+10	-0.2
2016	25	INTL	Tigres de Aragua	—	136	113	33	6	0	5	18	25	5	2	1	292	412	478	890	186	337	18	13	399	156	—	—	—	—	—	—
2017	26	MLB	Chicago White Sox	—	561	518	171	27	5	18	33	111	9	5	3	330	380	506	886	176	392	20	6	391	145	+30	-0	-2	-6	+12	3.5
2018	27	MLB	Chicago White Sox	—	385	356	84	11	2	19	20	102	4	3	1	236	284	438	722	202	271	26	5	314	95	-2	+0	+1	-4	+8	0.3
2018	27	AAA	Charlotte Knights	—	28	25	9	3	0	3	3	9	0	0	0	360	429	840	1.269	480	462	32	11	532	127	—	—	—	—	—	—
2019	28	MLB	Tampa Bay Rays	—	530	489	138	25	2	20	31	125	7	10	4	282	334	464	798	182	340	24	6	351	122	+14	+0	-1	-6	+11	1.9
2020	29	MLB	Milwaukee Brewers	—	207	181	43	10	0	2	20	49	6	1	3	238	333	326	659	88	315	24	10	306	92	-2	-1	+1	+1	+4	0.4
2021	30	MLB	Milwaukee Brewers	—	515	461	121	18	0	29	38	121	11	8	4	262	333	490	824	228	291	23	7	359	123	+14	+0	-3	-6	+11	1.8
2022	31	MLB	Miami Marlins	—	380	357	80	9	0	8	17	109	4	4	0	224	267	317	584	92	298	29	4	263	69	-14	+1	-3	-4	+8	-1.3
2022	31	AAA	Jacksonville Jumbo Shrimp	—	34	28	7	2	0	0	5	11	0	2	0	250	364	321	685	71	389	32	15	311	56	—	—	—	—	—	—
2023	32	MLB	Miami Marlins	—	118	108	20	3	1	3	6	39	2	2	0	185	237	315	552	130	258	33	5	247	55	-6	+0	-0	-2	+3	-0.5
2023	32	AAA	Jacksonville Jumbo Shrimp	—	32	27	7	2	0	3	5	11	0	0	0	259	375	667	1.042	407	308	34	16	441	93	—	—	—	—	—	—
2023	32	AA	Pensacola Blue Wahoos	—	21	17	3	1	0	1	3	5	1	0	0	176	333	412	745	235	182	24	14	338	51	—	—	—	—	—	—
2024	33	MLB	Miami Marlins	—	51	50	12	1	0	2	1	13	0	0	0	240	255	380	635	140	286	25	2	280	82	-1	+0	+0	-1	+1	-0.0
2024	33	AAA	Jacksonville Jumbo Shrimp	—	21	19	2	0	1	0	2	7	0	0	0	105	190	211	401	105	167	33	10	186	-18	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	4298	3949	1038	154	17	140	262	1038	59	51	32	263	318	417	735	154	321	24	6	326	107	+34	-3	-27	-57	+93	4.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2008	17	ROK MLE	VSL Tigers	—	263	250	48	7	1	3	10	48	2	7	5	192	229	264	493	72	224	18	4	222	36	—	—	—	—	—	—
2009	18	A MLE	West Michigan Whitecaps	—	315	301	73	9	2	1	6	95	4	8	7	243	267	296	563	53	335	30	2	244	51	—	—	—	—	—	—
2010	19	A MLE	West Michigan Whitecaps	—	524	499	118	13	3	3	15	158	5	20	4	236	266	293	558	56	330	30	3	246	53	—	—	—	—	—	—
2011	20	A+ MLE	Lakeland Flying Tigers	—	515	494	109	15	4	9	12	198	6	14	5	221	248	322	570	101	340	38	2	247	53	—	—	—	—	—	—
2012	21	MLB MLE	Detroit Tigers	—	51	48	15	0	0	0	2	10	1	0	2	312	353	312	665		405	20	4	311	97	-0	-1	-1	-7	+1	-0.7
2012	21	AA MLE	Erie SeaWolves	—	226	217	65	8	3	4	5	49	4	9	4	300	327	419	747	120	369	22	2	319	102	—	—	—	—	—	—
2012	21	A+ MLE	Lakeland Flying Tigers	—	283	265	65	7	4	6	8	81	5	14	4	245	281	370	650	125	308	29	3	278	74	—	—	—	—	—	—
2013	22	MLB MLE	Chicago White Sox	—	256	244	69	7	3	7	9	59	1	3	3	283	311	422	733	139	344	23	4	321	103	+1	-1	-7	-5	+6	-0.6
2013	22	AAA MLE	Charlotte Knights	—	188	177	63	6	2	5	9	42	2	4	2	356	394	497	891	141	451	22	5	392	151	—	—	—	—	—	—
2013	22	A+ MLE	Lakeland Flying Tigers	—	28	25	9	0	1	1	3	1	0	2	0	360	429	560	989	200	355	4	11	424	173	—	—	—	—	—	—
2014	23	MLB MLE	Chicago White Sox	—	190	173	42	8	0	7	13	44	2	4	1	243	303	410	714	168	285	23	7	313	98	-0	+0	-6	-4	+4	-0.6
2014	23	AAA MLE	Charlotte Knights	—	53	50	15	2	0	1	1	20	2	0	0	300	340	400	740	100	476	38	2	316	100	—	—	—	—	—	—
2015	24	MLB MLE	Chicago White Sox	—	601	556	142	17	2	13	33	141	8	7	7	255	307	363	670	108	320	23	5	299	89	-8	-1	-6	-6	+13	-0.9
2016	25	MLB MLE	Chicago White Sox	—	453	413	101	18	2	12	34	115	4	4	4	245	308	385	693	140	309	25	8	309	95	-3	-1	-2	-6	+10	-0.2
2017	26	MLB MLE	Chicago White Sox	—	561	523	171	27	5	18	28	111	9	5	3	327	371	501	872	174	392	20	5	383	145	+30	-0	-2	-6	+12	3.5
2018	27	MLB MLE	Chicago White Sox	—	385	358	84	11	2	19	18	102	4	3	1	235	279	436	715	201	271	26	5	308	95	-2	+0	+1	-4	+8	0.3
2018	27	AAA MLE	Charlotte Knights	—	28	26	7	2	0	2	2	11	0	0	0	269	321	577	898	308	358	39	7	356	127	—	—	—	—	—	—
2019	28	MLB MLE	Tampa Bay Rays	—	530	491	138	26	2	21	29	125	7	10	4	281	330	470	801	189	340	24	5	349	122	+14	+0	-1	-6	+11	1.9
2020	29	MLB MLE	Milwaukee Brewers	—	207	183	44	11	0	2	18	49	6	1	3	240	329	333	662	93	315	24	9	304	92	-2	-1	+1	+1	+4	0.4
2021	30	MLB MLE	Milwaukee Brewers	—	515	466	121	19	0	28	33	121	11	8	4	260	324	481	804	221	291	23	6	351	123	+14	+0	-3	-6	+11	1.8
2022	31	MLB MLE	Miami Marlins	—	380	357	82	10	0	8	17	109	4	4	0	230	272	325	597	95	298	29	4	271	69	-14	+1	-3	-4	+8	-1.3
2022	31	AAA MLE	Jacksonville Jumbo Shrimp	—	34	30	6	2	0	0	3	14	0	2	0	200	273	267	539	67	335	41	9	251	56	—	—	—	—	—	—
2023	32	MLB MLE	Miami Marlins	—	118	111	20	3	1	3	5	39	2	2	0	180	229	306	535	126	258	33	4	249	55	-6	+0	-0	-2	+3	-0.5
2023	32	AAA MLE	Jacksonville Jumbo Shrimp	—	32	29	6	2	0	2	3	13	0	0	0	207	281	483	764	276	242	41	9	305	93	—	—	—	—	—	—
2023	32	AA MLE	Pensacola Blue Wahoos	—	21	18	3	1	0	1	2	6	1	0	0	167	286	389	675	222	153	29	10	244	51	—	—	—	—	—	—
2024	33	MLB MLE	Miami Marlins	—	51	50	12	1	0	2	1	13	0	0	0	240	255	380	635	140	286	25	2	289	82	-1	+0	+0	-1	+1	-0.0
2024	33	AAA MLE	Jacksonville Jumbo Shrimp	—	21	20	2	0	1	0	1	8	0	0	0	100	143	200	343	100	149	38	5	142	-18	—	—	—	—	—	—
2008	17	ROK MLE	VSL Tigers	—	263	250	48	7	1	3	10	48	2	7	5	192	229	264	493	72	225	18	4	222	36	—	—	—	—	—	—
2008	17	ROK RAW	VSL Tigers	—	263	245	73	12	2	7	15	39	2	7	5	298	344	449	792	151	330	15	6	351	36	—	—	—	—	—	—
2009	18	A MLE	West Michigan Whitecaps	—	315	301	73	9	2	1	6	95	4	8	7	243	267	296	563	53	344	30	2	244	51	—	—	—	—	—	—
2009	18	A RAW	West Michigan Whitecaps	—	315	299	79	11	2	1	8	70	4	8	7	264	293	324	617	60	336	22	3	275	51	—	—	—	—	—	—
2010	19	A MLE	West Michigan Whitecaps	—	524	499	118	13	3	3	15	158	5	20	4	236	266	293	558	56	335	30	3	246	53	—	—	—	—	—	—
2010	19	A RAW	West Michigan Whitecaps	—	524	494	139	17	4	4	20	113	5	20	4	281	316	356	672	75	353	22	4	300	53	—	—	—	—	—	—
2011	20	A+ MLE	Lakeland Flying Tigers	—	515	494	109	15	4	9	12	198	6	14	5	221	248	322	570	101	345	38	2	247	53	—	—	—	—	—	—
2011	20	A+ RAW	Lakeland Flying Tigers	—	515	488	129	16	6	11	18	132	6	14	5	264	299	389	688	125	339	26	3	305	53	—	—	—	—	—	—
2012	21	A+ MLE	4 teams	—	620	588	160	16	8	11	16	154	11	24	11	272	304	383	687	111	348	25	3	298	88	—	—	—	—	—	—
2012	21	A+ RAW	4 teams	—	620	578	166	18	8	14	26	120	11	24	11	287	330	419	749	131	339	19	4	331	88	—	—	—	—	—	—
2013	22	MLB MLE	3 teams	—	472	446	141	13	7	13	21	103	3	9	5	316	351	464	815	148	386	22	4	355	127	+15	-0	-7	-5	+10	1.3
2013	22	MLB RAW	3 teams	—	472	442	144	14	7	14	25	96	3	9	5	326	366	484	850	158	389	20	5	374	127	+15	-0	-7	-5	+10	1.3
2014	23	MLB MLE	3 teams	—	385	351	90	16	0	12	22	101	6	8	2	256	311	405	716	148	320	26	6	314	98	-1	+1	-6	-4	+8	-0.1
2014	23	MLB RAW	3 teams	—	385	347	98	19	2	13	26	94	6	8	2	282	343	461	804	179	346	24	7	351	98	-1	+1	-6	-4	+8	-0.1
2015	24	MLB MLE	Chicago White Sox	—	601	556	142	17	2	13	33	141	8	7	7	255	307	363	670	108	318	23	5	299	89	-8	-1	-6	-6	+13	-0.9
2015	24	MLB RAW	Chicago White Sox	—	601	553	142	17	2	13	36	141	8	7	7	257	312	365	677	108	320	23	6	304	89	-8	-1	-6	-6	+13	-0.9
2016	25	MLB MLE	2 teams	—	589	534	131	23	3	15	44	150	9	6	5	245	313	384	697	139	313	25	7	309	95	-4	-1	-2	-6	+13	0.0
2016	25	MLB RAW	2 teams	—	589	526	134	24	2	17	52	140	9	6	5	255	332	405	737	150	315	24	9	331	95	-4	-1	-2	-6	+13	0.0
2017	26	MLB MLE	Chicago White Sox	—	561	523	171	27	5	18	28	111	9	5	3	327	371	501	872	174	387	20	5	383	145	+30	-0	-2	-6	+12	3.5
2017	26	MLB RAW	Chicago White Sox	—	561	518	171	27	5	18	33	111	9	5	3	330	380	506	886	176	392	20	6	391	145	+30	-0	-2	-6	+12	3.5
2018	27	MLB MLE	2 teams	—	413	384	90	13	2	20	20	113	4	3	1	234	279	435	714	201	273	27	5	311	97	-2	+0	+1	-4	+9	0.5
2018	27	MLB RAW	2 teams	—	413	381	93	14	2	22	23	111	4	3	1	244	294	465	759	220	281	27	6	329	97	-2	+0	+1	-4	+9	0.5
2019	28	MLB MLE	Tampa Bay Rays	—	530	491	138	26	2	21	29	125	7	10	4	281	330	470	801	189	336	24	5	349	122	+14	+0	-1	-6	+11	1.9
2019	28	MLB RAW	Tampa Bay Rays	—	530	489	138	25	2	20	31	125	7	10	4	282	334	464	798	182	340	24	6	351	122	+14	+0	-1	-6	+11	1.9
2020	29	MLB MLE	Milwaukee Brewers	—	207	183	44	11	0	2	18	49	6	1	3	240	329	333	662	93	318	24	9	304	92	-2	-1	+1	+1	+4	0.4
2020	29	MLB RAW	Milwaukee Brewers	—	207	181	43	10	0	2	20	49	6	1	3	238	333	326	659	88	315	24	10	306	92	-2	-1	+1	+1	+4	0.4
2021	30	MLB MLE	Milwaukee Brewers	—	515	466	121	19	0	28	33	121	11	8	4	260	324	481	804	221	289	23	6	351	123	+14	+0	-3	-6	+11	1.8
2021	30	MLB RAW	Milwaukee Brewers	—	515	461	121	18	0	29	38	121	11	8	4	262	333	490	824	228	291	23	7	359	123	+14	+0	-3	-6	+11	1.8
2022	31	MLB MLE	2 teams	—	414	387	88	12	0	8	20	123	4	6	0	227	273	320	593	93	309	30	5	269	68	-16	+1	-3	-4	+9	-1.3
2022	31	MLB RAW	2 teams	—	414	385	87	11	0	8	22	120	4	6	0	226	275	317	592	91	304	29	5	267	68	-16	+1	-3	-4	+9	-1.3
2023	32	MLB MLE	3 teams	—	171	158	29	6	1	6	10	58	3	2	0	184	246	348	594	165	245	34	6	259	61	-8	+0	-0	-2	+4	-0.6
2023	32	MLB RAW	3 teams	—	171	152	30	6	1	7	14	55	3	2	0	197	275	388	663	191	256	32	8	294	61	-8	+0	-0	-2	+4	-0.6
2024	33	MLB MLE	2 teams	—	72	70	14	1	1	2	2	21	0	0	0	200	222	329	551	129	255	29	3	246	53	-4	+0	+0	-1	+2	-0.3
2024	33	MLB RAW	2 teams	—	72	69	14	1	1	2	3	20	0	0	0	203	236	333	569	130	255	28	4	253	53	-4	+0	+0	-1	+2	-0.3
2008	17	ROK MLE	VSL Tigers	—	263	249	48	7	1	3	10	48	2	7	5	193	229	265	494	72	224	18	4	222	36	—	—	—	—	—	—
2009	18	A MLE	West Michigan Whitecaps	—	315	302	73	9	2	1	6	95	4	8	7	242	267	295	562	53	335	30	2	244	51	—	—	—	—	—	—
2010	19	A MLE	West Michigan Whitecaps	—	524	499	118	13	3	3	15	158	5	20	4	236	266	293	558	56	330	30	3	246	53	—	—	—	—	—	—
2011	20	A+ MLE	Lakeland Flying Tigers	—	515	492	109	15	4	9	12	198	6	14	5	222	248	323	571	102	340	38	2	247	53	—	—	—	—	—	—
2012	21	A+ MLE	4 teams	—	620	588	160	16	8	11	16	154	11	24	11	272	304	383	687	111	341	25	3	298	88	—	—	—	—	—	—
2013	22	MLB MLE	3 teams	—	472	445	141	13	7	13	21	103	3	9	5	317	351	465	816	148	388	22	4	355	127	—	—	—	—	—	—
2014	23	MLB MLE	3 teams	—	385	354	90	16	0	12	22	101	6	8	2	254	311	401	712	147	326	26	6	314	98	—	—	—	—	—	—
2015	24	MLB MLE	Chicago White Sox	—	601	555	142	17	2	13	33	141	8	7	7	256	307	364	670	108	320	23	5	299	89	—	—	—	—	—	—
2016	25	MLB MLE	2 teams	—	589	531	131	23	3	15	44	150	9	6	5	247	313	386	700	139	309	25	7	309	95	—	—	—	—	—	—
2017	26	MLB MLE	Chicago White Sox	—	561	519	171	27	5	18	28	111	9	5	3	329	371	505	876	175	392	20	5	383	145	—	—	—	—	—	—
2018	27	MLB MLE	2 teams	—	413	386	90	13	2	20	20	113	4	3	1	233	279	433	712	199	277	27	5	311	97	—	—	—	—	—	—
2019	28	MLB MLE	Tampa Bay Rays	—	530	489	138	26	2	21	29	125	7	10	4	282	330	472	803	190	340	24	5	349	122	—	—	—	—	—	—
2020	29	MLB MLE	Milwaukee Brewers	—	207	181	44	11	0	2	18	49	6	1	3	243	329	337	666	94	315	24	9	304	92	—	—	—	—	—	—
2021	30	MLB MLE	Milwaukee Brewers	—	515	466	121	19	0	28	33	121	11	8	4	260	324	481	804	221	291	23	6	351	123	—	—	—	—	—	—
2022	31	MLB MLE	2 teams	—	414	387	88	12	0	8	20	123	4	6	0	227	273	320	593	93	301	30	5	269	68	—	—	—	—	—	—
2023	32	MLB MLE	3 teams	—	171	156	29	6	1	6	10	58	3	2	0	186	246	353	598	167	242	34	6	259	61	—	—	—	—	—	—
2024	33	MLB MLE	2 teams	—	72	70	14	1	1	2	2	21	0	0	0	200	222	329	551	129	246	29	3	246	53	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	33	MLB MLE	2 teams	—	72	70	14	1	1	2	2	21	0	0	0	200	222	329	551	129	246	29	3	246	53	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	4298	3949	1038	154	17	140	262	1038	59	51	32	263	318	417	735	154	321	24	6	326	91	+34	-3	-27	-57	+93	4.2
/ 162G	—	A+C		—	650	597	157	23	3	21	40	157	9	8	5	263	319	417	736	154	322	24	6	326	91	+5	-0	-4	-9	+14	0.6
Career	—	MLE		—	7167	6681	1707	244	41	185	339	1869	98	138	66	256	301	387	689	132	325	26	5	303	91	+34	-3	-27	-57	+93	4.2
/ 162G	—	MLE		—	650	606	155	22	4	17	31	170	9	13	6	256	302	389	691	134	326	26	5	303	91	+5	-0	-4	-9	+14	0.6

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.

2024 AAAJacksonville Jumbo Shrimp · 21 PAwOBA .182 → .142 (−41)K% 33.3% → 40.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷0.999	×1.200	—	—	40.04%
BB% (unintentional) /PA	9.52%	÷1.005	×0.690	—	×0.942	6.16%
HBP% /PA	0.00%	—	×0.940	—	×0.942	0.00%
Singles /BIP	8.33%	÷1.016	×0.930	—	×0.942	7.18%
Doubles /BIP	0.00%	÷0.970	×0.830	—	×0.942	0.00%
Triples /BIP	8.33%	÷0.985	×0.970	—	×0.942	7.73%
Home runs /BIP	0.00%	÷0.925	×0.700	—	×0.942	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 85, 1B 103, 2B 94, 3B 97, K 100, BB 101 — 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).

Result: wOBA .182 → .142; ISO .105 → .092; BABIP .167 → .149. 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).

2023 AAAJacksonville Jumbo Shrimp · 32 PAwOBA .428 → .305 (−124)K% 34.4% → 39.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	34.38%	÷1.040	×1.200	—	—	39.65%
BB% (unintentional) /PA	15.62%	÷1.008	×0.690	—	×0.952	10.18%
HBP% /PA	0.00%	—	×0.940	—	×0.952	0.00%
Singles /BIP	12.50%	÷1.016	×0.930	—	×0.952	10.89%
Doubles /BIP	12.50%	÷0.955	×0.830	—	×0.952	10.34%
Triples /BIP	0.00%	÷1.039	×0.970	—	×0.952	0.00%
Home runs /BIP	18.75%	÷1.031	×0.700	—	×0.952	12.12%

Factors used: league row International League. Park (home-season share, regressed): HR 106, 1B 103, 2B 91, 3B 108, K 108, BB 102 — 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 .428 → .305; ISO .407 → .278; BABIP .308 → .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).

2023 AAPensacola Blue Wahoos · 21 PAwOBA .330 → .244 (−86)K% 23.8% → 29.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.81%	÷0.990	×1.220	—	—	29.34%
BB% (unintentional) /PA	14.29%	÷1.056	×0.680	—	×0.940	8.65%
HBP% /PA	4.76%	—	×0.840	—	×0.940	3.76%
Singles /BIP	8.33%	÷1.052	×0.920	—	×0.940	6.85%
Doubles /BIP	8.33%	÷0.947	×0.910	—	×0.940	7.53%
Triples /BIP	0.00%	÷1.097	×0.880	—	×0.940	0.00%
Home runs /BIP	8.33%	÷1.091	×0.800	—	×0.940	5.74%

Factors used: league row SL. Park (home-season share, regressed): HR 118, 1B 110, 2B 89, 3B 119, K 98, BB 111 — 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 .330 → .244; ISO .235 → .178; BABIP .182 → .153. 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 AAAJacksonville Jumbo Shrimp · 34 PAwOBA .313 → .251 (−63)K% 32.4% → 40.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.35%	÷0.966	×1.200	—	—	40.21%
BB% (unintentional) /PA	14.71%	÷0.978	×0.690	—	×0.962	9.98%
HBP% /PA	0.00%	—	×0.940	—	×0.962	0.00%
Singles /BIP	29.41%	÷1.054	×0.930	—	×0.962	24.97%
Doubles /BIP	11.76%	÷0.898	×0.830	—	×0.962	10.46%
Triples /BIP	0.00%	÷0.930	×0.970	—	×0.962	0.00%
Home runs /BIP	0.00%	÷1.032	×0.700	—	×0.962	0.00%

Factors used: league row International League. Park (home-season share, regressed): HR 106, 1B 111, 2B 80, 3B 86, K 93, BB 96 — 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 .313 → .251; ISO .071 → .063; BABIP .389 → .335. 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 AAACharlotte Knights · 28 PAwOBA .516 → .356 (−161)K% 32.1% → 39.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	32.14%	÷0.986	×1.200	—	—	39.10%
BB% (unintentional) /PA	10.71%	÷1.030	×0.690	—	×1.003	7.20%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	18.75%	÷1.030	×0.930	—	×1.003	16.98%
Doubles /BIP	18.75%	÷1.077	×0.830	—	×1.003	14.50%
Triples /BIP	0.00%	÷1.150	×0.970	—	×1.003	0.00%
Home runs /BIP	18.75%	÷1.319	×0.840	—	×1.003	11.98%

Factors used: league row IL. Park (home-season share, regressed): HR 164, 1B 106, 2B 115, 3B 130, K 97, BB 106 — 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).

Result: wOBA .516 → .356; ISO .480 → .303; BABIP .462 → .358. 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 AAACharlotte Knights · 53 PAwOBA .364 → .316 (−48)K% 30.2% → 37.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.19%	÷0.975	×1.200	—	—	37.14%
BB% (unintentional) /PA	1.89%	÷1.012	×0.690	—	×1.050	1.35%
HBP% /PA	3.77%	—	×0.940	—	×1.050	3.72%
Singles /BIP	38.24%	÷0.966	×0.930	—	×1.050	38.67%
Doubles /BIP	8.82%	÷0.977	×0.830	—	×1.050	7.87%
Triples /BIP	0.00%	÷0.910	×0.970	—	×1.050	0.00%
Home runs /BIP	2.94%	÷1.118	×0.840	—	×1.050	2.32%

Factors used: league row IL. Park (home-season share, regressed): HR 124, 1B 93, 2B 95, 3B 82, K 95, BB 102 — 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).

Result: wOBA .364 → .316; ISO .120 → .091; BABIP .485 → .476. 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 AAACharlotte Knights · 188 PAwOBA .413 → .392 (−21)K% 19.1% → 22.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.15%	÷1.023	×1.200	—	—	22.47%
BB% (unintentional) /PA	6.38%	÷0.939	×0.690	—	×1.050	4.93%
HBP% /PA	1.06%	—	×0.940	—	×1.050	1.05%
Singles /BIP	36.23%	÷1.004	×0.930	×1.050	×1.050	37.01%
Doubles /BIP	5.07%	÷1.006	×0.830	×1.050	×1.050	4.62%
Triples /BIP	1.45%	÷0.900	×0.970	×1.050	×1.050	1.72%
Home runs /BIP	4.35%	÷0.972	×0.840	—	×1.050	3.95%

Factors used: league row IL. Park (home-season share, regressed): HR 94, 1B 101, 2B 101, 3B 80, K 105, BB 88 — applied at half strength. Age: age 22 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (5.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .413 → .392; ISO .167 → .154; BABIP .447 → .451. 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 A+Lakeland Flying Tigers · 28 PAwOBA .502 → .424 (−78)K% 3.6% → 5.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	3.57%	÷1.018	×1.420	—	—	4.98%
BB% (unintentional) /PA	14.29%	÷1.045	×0.750	—	×1.012	10.38%
HBP% /PA	0.00%	—	×0.930	—	×1.012	0.00%
Singles /BIP	30.43%	÷1.011	×0.920	—	×1.012	28.03%
Doubles /BIP	0.00%	÷0.944	×0.960	—	×1.012	0.00%
Triples /BIP	8.70%	÷1.150	×0.810	—	×1.012	6.20%
Home runs /BIP	4.35%	÷1.067	×0.880	—	×1.012	3.63%

Factors used: league row FSL. Park (home-season share, regressed): HR 113, 1B 102, 2B 89, 3B 130, K 104, BB 109 — applied at half strength. Age: age 22 vs a level average of 22.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average).

Result: wOBA .502 → .424; ISO .292 → .230; BABIP .409 → .355. 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 — .