Brandon Belt

Pos1B

B/TL/L

Born1988-04-20

Age (2027)39

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2023

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2021	33	MLBSF	381	.274/.379/.597	29	3	176	3.4
2022	34	MLBSF	298	.213/.327/.350	8	1	97	-0.5
2023	35	MLBTOR	404	.254/.371/.490	19	0	141	2.1
2024	36	No MLB games played
2025	37	No MLB games played
2026	38	No MLB games played

Last 3 seasons WAR 5.0

Contract

No contract data on file.

Skills · percentileStatcast 2021-2023

Barrel%90

xwOBA82

Bat Spd62

Avg EV46

Speed23

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)
2010	22	AAA	Fresno Grizzlies	—	61	48	11	4	0	4	13	15	0	2	0	229	393	562	956	333	241	25	21	414	103	—	—	—	—	—	—
2010	22	AA	Richmond Flying Squirrels	—	201	175	59	11	6	9	22	34	2	2	1	337	417	623	1.040	286	373	17	11	444	156	—	—	—	—	—	—
2010	22	A+	San Jose Giants	—	333	269	103	28	4	10	58	50	3	18	7	383	497	628	1.125	245	439	15	17	484	158	—	—	—	—	—	—
2010	22	INTL	Scottsdale Scorpions	—	96	86	32	8	5	1	9	24	0	1	2	372	432	616	1.048	244	500	25	9	448	189	—	—	—	—	—	—
2011	23	MLB	San Francisco Giants	—	209	187	42	6	1	9	20	57	2	3	2	225	306	412	718	187	273	27	10	321	107	+2	-0	-2	-6	+5	-0.2
2011	23	AAA	Fresno Grizzlies	—	212	165	51	12	0	8	42	47	2	4	4	309	455	527	982	218	381	22	20	429	128	—	—	—	—	—	—
2011	23	A+	San Jose Giants	—	18	13	6	1	0	0	5	1	0	1	0	462	611	538	1.150	77	500	6	28	517	190	—	—	—	—	—	—
2011	23	INTL	Leones del Escogido	—	119	100	30	8	0	3	16	19	1	4	1	300	402	470	872	170	338	16	13	383	146	—	—	—	—	—	—
2012	24	MLB	San Francisco Giants	—	472	411	113	27	6	7	54	106	3	12	2	275	363	421	784	146	351	22	11	349	121	+12	+2	-8	-8	+10	0.7
2013	25	MLB	San Francisco Giants	—	571	509	147	39	4	17	52	125	6	5	2	289	362	481	843	193	351	22	9	370	138	+26	+0	-7	-10	+12	2.2
2014	26	MLB	San Francisco Giants	—	235	214	52	8	0	12	18	64	2	3	1	243	308	449	756	206	288	27	8	333	114	+4	+0	-2	-5	+5	0.2
2014	26	AAA	Fresno Grizzlies	—	20	19	10	3	0	2	1	5	0	0	1	526	550	1.000	1.550	474	667	25	5	662	233	—	—	—	—	—	—
2015	27	MLB	San Francisco Giants	—	556	492	138	33	5	18	56	147	4	9	3	280	359	478	836	197	363	26	10	367	138	+25	+1	-3	-10	+12	2.6
2016	28	MLB	San Francisco Giants	—	655	542	149	41	8	17	104	148	5	0	4	275	396	474	870	199	346	23	16	385	148	+37	-2	-7	-12	+14	3.2
2017	29	MLB	San Francisco Giants	—	451	382	92	27	3	18	66	104	2	3	2	241	356	469	824	228	284	23	15	364	136	+19	-0	+3	-8	+10	2.4
2018	30	MLB	San Francisco Giants	—	456	399	101	18	2	14	49	107	6	4	0	253	344	414	757	160	311	23	11	339	114	+8	+1	-2	-8	+10	0.9
2019	31	MLB	San Francisco Giants	—	616	526	123	32	3	17	83	127	3	4	3	234	342	403	745	169	275	21	13	334	114	+10	-0	-6	-11	+13	0.7
2020	32	MLB	San Francisco Giants	—	179	149	46	13	1	9	30	36	0	0	0	309	425	591	1.015	282	356	20	17	440	188	+19	+0	-1	-3	+4	1.8
2021	33	MLB	San Francisco Giants	—	381	325	89	14	2	29	48	103	7	3	2	274	379	597	976	323	309	27	13	420	176	+35	-0	-2	-7	+8	3.4
2021	33	AAA	Sacramento River Cats	—	15	12	3	0	0	0	2	3	0	0	0	250	357	250	607		300	20	13	274	52	—	—	—	—	—	—
2022	34	MLB	San Francisco Giants	—	298	254	54	9	1	8	37	81	6	1	0	213	327	350	677	138	277	27	12	311	97	-1	+0	-5	-5	+6	-0.5
2023	35	MLB	Toronto Blue Jays	—	404	339	86	23	0	19	61	141	2	0	0	254	371	490	860	236	370	35	15	379	141	+20	+0	-0	-7	+9	2.1
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	5483	4729	1232	290	36	194	678	1346	48	47	21	261	359	460	819	200	323	25	12	362	131	+205	+1	-43	-101	+119	18.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2010	22	AAA MLE	Fresno Grizzlies	—	61	51	10	4	0	3	10	20	0	2	0	196	328	451	779	255	225	33	16	321	103	—	—	—	—	—	—
2010	22	AA MLE	Richmond Flying Squirrels	—	201	182	57	10	6	9	15	42	2	2	1	313	372	582	954	269	350	21	7	399	156	—	—	—	—	—	—
2010	22	A+ MLE	San Jose Giants	—	333	287	92	24	3	9	40	69	3	18	7	321	409	519	928	199	384	21	12	402	158	—	—	—	—	—	—
2011	23	MLB MLE	San Francisco Giants	—	209	188	43	6	1	10	19	57	2	3	2	229	306	431	737	202	273	27	9	326	107	+2	-0	-2	-6	+5	-0.2
2011	23	AAA MLE	Fresno Grizzlies	—	212	178	47	10	0	6	29	59	2	4	4	264	373	421	795	157	350	28	14	357	128	—	—	—	—	—	—
2011	23	A+ MLE	San Jose Giants	—	18	14	6	1	0	0	4	1	0	1	0	429	556	500	1.056	71	453	6	22	449	190	—	—	—	—	—	—
2012	24	MLB MLE	San Francisco Giants	—	472	416	115	27	6	8	49	106	3	12	2	276	357	428	785	151	351	22	10	346	121	+12	+2	-8	-8	+10	0.7
2013	25	MLB MLE	San Francisco Giants	—	571	513	149	39	4	18	48	125	6	5	2	290	358	487	845	197	351	22	8	372	138	+26	+0	-7	-10	+12	2.2
2014	26	MLB MLE	San Francisco Giants	—	235	216	53	8	0	13	16	64	2	3	1	245	303	463	766	218	288	27	7	337	114	+4	+0	-2	-5	+5	0.2
2014	26	AAA MLE	Fresno Grizzlies	—	20	20	7	2	0	1	0	6	0	0	1	350	350	600	950	250	562	30	0	513	233	—	—	—	—	—	—
2015	27	MLB MLE	San Francisco Giants	—	556	494	140	33	5	19	54	147	4	9	3	283	359	486	845	202	363	26	10	372	138	+25	+1	-3	-10	+12	2.6
2016	28	MLB MLE	San Francisco Giants	—	655	546	151	41	8	18	100	148	5	0	4	277	393	480	873	203	346	23	15	387	148	+37	-2	-7	-12	+14	3.2
2017	29	MLB MLE	San Francisco Giants	—	451	384	94	27	3	19	64	104	2	3	2	245	356	479	835	234	284	23	14	369	136	+19	-0	+3	-8	+10	2.4
2018	30	MLB MLE	San Francisco Giants	—	456	405	103	18	2	15	43	107	6	4	0	254	335	420	755	165	311	23	9	337	114	+8	+1	-2	-8	+10	0.9
2019	31	MLB MLE	San Francisco Giants	—	616	529	125	32	3	18	80	127	3	4	3	236	340	410	750	174	275	21	13	337	114	+10	-0	-6	-11	+13	0.7
2020	32	MLB MLE	San Francisco Giants	—	179	150	47	13	1	10	29	36	0	0	0	313	425	613	1.038	300	356	20	16	446	188	+19	+0	-1	-3	+4	1.8
2021	33	MLB MLE	San Francisco Giants	—	381	328	92	14	2	31	45	103	7	3	2	280	379	619	998	338	309	27	12	429	176	+35	-0	-2	-7	+8	3.4
2021	33	AAA MLE	Sacramento River Cats	—	15	13	3	0	0	0	1	3	0	0	0	231	286	231	516		253	20	7	245	52	—	—	—	—	—	—
2022	34	MLB MLE	San Francisco Giants	—	298	256	56	9	1	9	35	81	6	1	0	219	327	367	694	148	277	27	12	312	97	-1	+0	-5	-5	+6	-0.5
2023	35	MLB MLE	Toronto Blue Jays	—	404	340	86	23	0	19	60	141	2	0	0	253	368	488	856	235	370	35	15	377	141	+20	+0	-0	-7	+9	2.1
2010	22	A+ MLE	4 teams	—	691	605	183	43	10	25	75	152	5	23	10	302	384	531	915	228	364	22	11	393	152	—	—	—	—	—	—
2010	22	A+ RAW	4 teams	—	691	578	205	51	15	24	102	123	5	23	10	355	455	619	1.075	265	414	18	15	461	152	—	—	—	—	—	—
2011	23	AAA MLE	4 teams	—	558	483	123	22	1	20	65	149	5	12	7	255	349	429	778	174	323	27	12	346	120	—	—	—	—	—	—
2011	23	AAA RAW	4 teams	—	558	465	129	27	1	20	83	124	5	12	7	277	392	469	861	191	334	22	15	381	120	—	—	—	—	—	—
2012	24	MLB MLE	San Francisco Giants	—	472	416	115	27	6	8	49	106	3	12	2	276	357	428	785	151	350	22	10	346	121	+12	+2	-8	-8	+10	0.7
2012	24	MLB RAW	San Francisco Giants	—	472	411	113	27	6	7	54	106	3	12	2	275	363	421	784	146	351	22	11	349	121	+12	+2	-8	-8	+10	0.7
2013	25	MLB MLE	San Francisco Giants	—	571	513	149	39	4	18	48	125	6	5	2	290	358	487	845	197	351	22	8	372	138	+26	+0	-7	-10	+12	2.2
2013	25	MLB RAW	San Francisco Giants	—	571	509	147	39	4	17	52	125	6	5	2	289	362	481	843	193	351	22	9	370	138	+26	+0	-7	-10	+12	2.2
2014	26	MLB MLE	2 teams	—	255	236	61	10	0	14	16	70	2	3	2	258	311	479	790	220	307	27	6	351	124	+7	-0	-2	-5	+6	0.6
2014	26	MLB RAW	2 teams	—	255	233	62	11	0	14	19	69	2	3	2	266	327	494	820	227	318	27	7	359	124	+7	-0	-2	-5	+6	0.6
2015	27	MLB MLE	San Francisco Giants	—	556	494	140	33	5	19	54	147	4	9	3	283	359	486	845	202	364	26	10	372	138	+25	+1	-3	-10	+12	2.6
2015	27	MLB RAW	San Francisco Giants	—	556	492	138	33	5	18	56	147	4	9	3	280	359	478	836	197	363	26	10	367	138	+25	+1	-3	-10	+12	2.6
2016	28	MLB MLE	San Francisco Giants	—	655	546	151	41	8	18	100	148	5	0	4	277	393	480	873	203	346	23	15	387	148	+37	-2	-7	-12	+14	3.2
2016	28	MLB RAW	San Francisco Giants	—	655	542	149	41	8	17	104	148	5	0	4	275	396	474	870	199	346	23	16	385	148	+37	-2	-7	-12	+14	3.2
2017	29	MLB MLE	San Francisco Giants	—	451	384	94	27	3	19	64	104	2	3	2	245	356	479	835	234	286	23	14	369	136	+19	-0	+3	-8	+10	2.4
2017	29	MLB RAW	San Francisco Giants	—	451	382	92	27	3	18	66	104	2	3	2	241	356	469	824	228	284	23	15	364	136	+19	-0	+3	-8	+10	2.4
2018	30	MLB MLE	San Francisco Giants	—	456	405	103	18	2	15	43	107	6	4	0	254	335	420	755	165	309	23	9	337	114	+8	+1	-2	-8	+10	0.9
2018	30	MLB RAW	San Francisco Giants	—	456	399	101	18	2	14	49	107	6	4	0	253	344	414	757	160	311	23	11	339	114	+8	+1	-2	-8	+10	0.9
2019	31	MLB MLE	San Francisco Giants	—	616	529	125	32	3	18	80	127	3	4	3	236	340	410	750	174	276	21	13	337	114	+10	-0	-6	-11	+13	0.7
2019	31	MLB RAW	San Francisco Giants	—	616	526	123	32	3	17	83	127	3	4	3	234	342	403	745	169	275	21	13	334	114	+10	-0	-6	-11	+13	0.7
2020	32	MLB MLE	San Francisco Giants	—	179	150	47	13	1	10	29	36	0	0	0	313	425	613	1.038	300	356	20	16	446	188	+19	+0	-1	-3	+4	1.8
2020	32	MLB RAW	San Francisco Giants	—	179	149	46	13	1	9	30	36	0	0	0	309	425	591	1.015	282	356	20	17	440	188	+19	+0	-1	-3	+4	1.8
2021	33	MLB MLE	2 teams	—	396	341	94	14	2	31	46	106	7	3	2	276	373	601	974	326	306	27	12	422	172	+34	-0	-2	-7	+9	3.3
2021	33	MLB RAW	2 teams	—	396	337	92	14	2	29	50	106	7	3	2	273	378	585	963	312	309	27	13	414	172	+34	-0	-2	-7	+9	3.3
2022	34	MLB MLE	San Francisco Giants	—	298	256	56	9	1	9	35	81	6	1	0	219	327	367	694	148	281	27	12	312	97	-1	+0	-5	-5	+6	-0.5
2022	34	MLB RAW	San Francisco Giants	—	298	254	54	9	1	8	37	81	6	1	0	213	327	350	677	138	277	27	12	311	97	-1	+0	-5	-5	+6	-0.5
2023	35	MLB MLE	Toronto Blue Jays	—	404	340	86	23	0	19	60	141	2	0	0	253	368	488	856	235	368	35	15	377	141	+20	+0	-0	-7	+9	2.1
2023	35	MLB RAW	Toronto Blue Jays	—	404	339	86	23	0	19	61	141	2	0	0	254	371	490	860	236	370	35	15	379	141	+20	+0	-0	-7	+9	2.1
2010	22	A+ MLE	4 teams	—	691	606	183	43	10	25	75	152	5	23	10	302	384	530	914	228	356	22	11	393	152	—	—	—	—	—	—
2011	23	AAA MLE	4 teams	—	558	483	123	22	1	20	65	149	5	12	7	255	349	429	778	174	317	27	12	346	120	—	—	—	—	—	—
2012	24	MLB MLE	San Francisco Giants	—	472	417	115	27	6	8	49	106	3	12	2	276	357	427	784	151	351	22	10	346	121	—	—	—	—	—	—
2013	25	MLB MLE	San Francisco Giants	—	571	512	149	39	4	18	48	125	6	5	2	291	358	488	846	197	351	22	8	372	138	—	—	—	—	—	—
2014	26	MLB MLE	2 teams	—	255	235	61	10	0	14	16	70	2	3	2	260	311	481	792	221	309	27	6	351	124	—	—	—	—	—	—
2015	27	MLB MLE	San Francisco Giants	—	556	493	140	33	5	19	54	147	4	9	3	284	359	487	846	203	363	26	10	372	138	—	—	—	—	—	—
2016	28	MLB MLE	San Francisco Giants	—	655	545	151	41	8	18	100	148	5	0	4	277	393	481	874	204	346	23	15	387	148	—	—	—	—	—	—
2017	29	MLB MLE	San Francisco Giants	—	451	382	94	27	3	19	64	104	2	3	2	246	356	482	837	236	284	23	14	369	136	—	—	—	—	—	—
2018	30	MLB MLE	San Francisco Giants	—	456	404	103	18	2	15	43	107	6	4	0	255	335	421	756	166	311	23	9	337	114	—	—	—	—	—	—
2019	31	MLB MLE	San Francisco Giants	—	616	528	125	32	3	18	80	127	3	4	3	237	340	411	751	174	275	21	13	337	114	—	—	—	—	—	—
2020	32	MLB MLE	San Francisco Giants	—	179	148	47	13	1	10	29	36	0	0	0	318	425	622	1.046	304	356	20	16	446	188	—	—	—	—	—	—
2021	33	MLB MLE	2 teams	—	396	340	94	14	2	31	46	106	7	3	2	276	373	603	976	326	307	27	12	422	172	—	—	—	—	—	—
2022	34	MLB MLE	San Francisco Giants	—	298	255	56	9	1	9	35	81	6	1	0	220	327	369	695	149	277	27	12	312	97	—	—	—	—	—	—
2023	35	MLB MLE	Toronto Blue Jays	—	404	339	86	23	0	19	60	141	2	0	0	254	368	490	858	236	370	35	15	377	141	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	5483	4729	1232	290	36	194	678	1346	48	47	21	261	359	460	819	200	323	25	12	362	135	+205	+1	-43	-101	+119	18.5
/ 162G	—	A+C		—	650	561	145	34	4	23	80	160	6	6	2	258	357	456	813	198	320	25	12	362	135	+24	+0	-5	-12	+14	2.2
Career	—	MLE		—	6558	5698	1527	351	46	243	764	1599	56	79	37	268	360	474	834	206	330	24	12	367	135	+205	+1	-43	-101	+119	18.5
/ 162G	—	MLE		—	650	565	152	35	5	24	76	158	6	8	4	269	362	476	838	207	331	24	12	367	135	+24	+0	-5	-12	+14	2.2

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.

2021 AAASacramento River Cats · 15 PAwOBA .287 → .245 (−42)K% 20.0% → 23.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷1.034	×1.200	—	—	23.21%
BB% (unintentional) /PA	13.33%	÷0.956	×0.690	—	×0.942	9.07%
HBP% /PA	0.00%	—	×0.940	—	×0.942	0.00%
Singles /BIP	33.33%	÷1.049	×0.930	—	×0.942	27.83%
Doubles /BIP	0.00%	÷0.916	×0.830	—	×0.942	0.00%
Triples /BIP	0.00%	÷0.900	×0.920	—	×0.942	0.00%
Home runs /BIP	0.00%	÷0.995	×0.700	—	×0.942	0.00%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 99, 1B 110, 2B 83, 3B 80, K 107, BB 91 — 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 .287 → .245; ISO .000 → .000; BABIP .300 → .253. 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 AAAFresno Grizzlies · 20 PAwOBA .639 → .513 (−126)K% 25.0% → 32.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷0.994	×1.290	—	—	32.44%
BB% (unintentional) /PA	0.00%	÷1.005	×0.710	—	×1.018	0.00%
HBP% /PA	0.00%	—	×0.980	—	×1.018	0.00%
Singles /BIP	35.71%	÷1.002	×0.900	—	×1.018	32.67%
Doubles /BIP	21.43%	÷1.014	×0.810	—	×1.018	17.42%
Triples /BIP	0.00%	÷0.900	×0.810	—	×1.018	0.00%
Home runs /BIP	14.29%	÷1.045	×0.780	—	×1.018	10.86%

Factors used: league row PCL. Park (home-season share, regressed): HR 109, 1B 100, 2B 103, 3B 80, K 99, BB 101 — 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).

Result: wOBA .639 → .513; ISO .474 → .356; BABIP .667 → .562. 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).

2011 AAAFresno Grizzlies · 212 PAwOBA .422 → .357 (−64)K% 22.2% → 27.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.17%	÷1.027	×1.290	—	—	27.86%
BB% (unintentional) /PA	18.87%	÷1.043	×0.710	—	×1.050	13.49%
HBP% /PA	0.94%	—	×0.980	—	×1.050	0.97%
Singles /BIP	26.27%	÷0.960	×0.900	×0.993	×1.050	25.66%
Doubles /BIP	10.17%	÷1.013	×0.810	×0.993	×1.050	8.48%
Triples /BIP	0.00%	÷1.150	×0.810	×0.993	×1.050	0.00%
Home runs /BIP	6.78%	÷1.112	×0.780	—	×1.050	4.99%

Factors used: league row PCL. Park (home-season share, regressed): HR 122, 1B 92, 2B 103, 3B 130, K 105, BB 109 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.993.

Result: wOBA .422 → .357; ISO .218 → .174; BABIP .381 → .350. 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).

2011 A+San Jose Giants · 18 PAwOBA .505 → .449 (−56)K% 5.6% → 7.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.56%	÷0.981	×1.340	—	—	7.59%
BB% (unintentional) /PA	27.78%	÷0.926	×0.710	—	×0.998	21.26%
HBP% /PA	0.00%	—	×0.790	—	×0.998	0.00%
Singles /BIP	41.67%	÷0.991	×0.910	—	×0.998	38.17%
Doubles /BIP	8.33%	÷0.951	×0.820	—	×0.998	7.17%
Triples /BIP	0.00%	÷0.900	×0.760	—	×0.998	0.00%
Home runs /BIP	0.00%	÷0.972	×0.920	—	×0.998	0.00%

Factors used: league row CAL. Park (home-season share, regressed): HR 94, 1B 98, 2B 90, 3B 80, K 96, BB 85 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average).

Result: wOBA .505 → .449; ISO .077 → .071; BABIP .500 → .453. 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 A+San Jose Giants · 333 PAwOBA .474 → .402 (−72)K% 15.0% → 20.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.02%	÷0.972	×1.340	—	—	20.69%
BB% (unintentional) /PA	16.52%	÷0.990	×0.710	—	×1.012	11.99%
HBP% /PA	0.90%	—	×0.790	—	×1.012	0.72%
Singles /BIP	27.85%	÷0.980	×0.910	×0.964	×1.012	25.22%
Doubles /BIP	12.79%	÷0.939	×0.820	×0.964	×1.012	10.89%
Triples /BIP	1.83%	÷1.085	×0.760	×0.964	×1.012	1.25%
Home runs /BIP	4.57%	÷1.016	×0.920	—	×1.012	4.18%

Factors used: league row CAL. Park (home-season share, regressed): HR 103, 1B 96, 2B 88, 3B 117, K 94, BB 98 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.964.

Result: wOBA .474 → .402; ISO .245 → .214; BABIP .439 → .384. 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 AARichmond Flying Squirrels · 201 PAwOBA .435 → .399 (−36)K% 16.9% → 21.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.92%	÷0.983	×1.220	—	—	21.00%
BB% (unintentional) /PA	10.45%	÷1.018	×0.700	—	×1.042	7.49%
HBP% /PA	1.00%	—	×0.850	—	×1.042	0.88%
Singles /BIP	23.40%	÷1.035	×0.970	×0.976	×1.042	22.30%
Doubles /BIP	7.80%	÷0.992	×0.860	×0.976	×1.042	6.88%
Triples /BIP	4.26%	÷1.008	×0.950	×0.976	×1.042	4.08%
Home runs /BIP	6.38%	÷0.813	×0.780	—	×1.042	6.38%

Factors used: league row EL. Park (home-season share, regressed): HR 63, 1B 107, 2B 98, 3B 102, K 97, BB 104 — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.976.

Result: wOBA .435 → .399; ISO .286 → .277; BABIP .373 → .350. 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 AAAFresno Grizzlies · 61 PAwOBA .403 → .321 (−82)K% 24.6% → 32.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.59%	÷0.969	×1.290	—	—	32.73%
BB% (unintentional) /PA	21.31%	÷0.981	×0.710	—	×1.050	16.20%
HBP% /PA	0.00%	—	×0.980	—	×1.050	0.00%
Singles /BIP	9.09%	÷0.951	×0.900	—	×1.050	9.03%
Doubles /BIP	12.12%	÷0.910	×0.810	—	×1.050	11.32%
Triples /BIP	0.00%	÷1.022	×0.810	—	×1.050	0.00%
Home runs /BIP	12.12%	÷1.047	×0.780	—	×1.050	9.48%

Factors used: league row PCL. Park (home-season share, regressed): HR 109, 1B 90, 2B 82, 3B 104, K 94, BB 96 — 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).

Result: wOBA .403 → .321; ISO .333 → .258; BABIP .241 → .225. 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 — .