Daniel Vogelbach

Pos1B

B/TL/R

Born1992-12-17

Age (2027)34

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
2022	29	MLBNYM	461	.238/.361/.433	18	0	129	1.7
2023	30	MLBNYM	319	.233/.339/.404	13	0	115	0.7
2024	31	MLBTOR	79	.186/.278/.300	1	0	67	-0.3
2025	32	No MLB games played
2026	33	No MLB games played

Last 3 seasons WAR 2.2

Contract

No contract data on file.

Skills · percentileStatcast 2022-2024

xwOBA81

Avg EV69

Barrel%62

Bat Spd61

Speed10

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)
2011	18	ROK	AZL Cubs	—	27	24	7	3	0	1	2	2	1	1	0	292	370	542	912	250	286	7	7	399	84	—	—	—	—	—	—
2012	19	ROK	AZL Cubs	—	115	102	33	12	2	7	12	14	0	1	0	324	395	686	1.081	363	317	12	10	456	113	—	—	—	—	—	—
2013	20	A+	Daytona Cubs	—	66	50	14	2	0	2	16	13	0	1	0	280	455	440	895	160	343	20	24	408	108	—	—	—	—	—	—
2013	20	A	Kane County Cougars	—	502	433	123	21	0	17	57	77	2	4	4	284	368	450	819	166	305	15	11	360	85	—	—	—	—	—	—
2014	21	A+	Daytona Cubs	—	560	482	129	28	1	16	66	91	5	4	4	268	362	429	791	162	296	16	12	351	87	—	—	—	—	—	—
2014	21	INTL	Mesa Solar Sox	—	88	69	18	4	0	0	17	11	0	1	0	261	407	319	726	58	300	12	19	337	114	—	—	—	—	—	—
2015	22	AA	Tennessee Smokies	—	313	254	69	16	1	7	57	61	0	1	1	272	405	425	830	154	330	19	18	374	103	—	—	—	—	—	—
2015	22	ROK	AZL Cubs	—	17	11	5	2	0	0	6	1	0	0	0	455	647	636	1.283	182	500	6	35	557	167	—	—	—	—	—	—
2016	23	AAA	Tacoma Rainiers	—	563	459	134	25	2	23	97	101	4	0	0	292	420	505	925	214	328	18	17	408	126	—	—	—	—	—	—
2017	24	MLB	Seattle Mariners	—	31	28	6	1	0	0	3	9	0	0	0	214	290	250	540	36	316	29	10	255	60	-1	+0	-2	-10	+1	-1.3
2017	24	AAA	Tacoma Rainiers	—	541	459	133	25	0	17	76	98	1	3	1	290	392	455	847	166	332	18	14	376	105	—	—	—	—	—	—
2018	25	MLB	Seattle Mariners	—	102	87	18	2	0	4	13	26	2	0	0	207	324	368	691	161	246	25	13	317	102	+0	+0	-0	-9	+2	-0.7
2018	25	AAA	Tacoma Rainiers	—	378	297	86	16	0	20	77	59	1	0	1	290	437	545	983	256	299	16	20	428	127	—	—	—	—	—	—
2019	26	MLB	Seattle Mariners	—	558	462	96	17	0	30	92	149	2	0	0	208	342	439	781	232	232	27	16	348	123	+15	+0	-6	-10	+12	1.2
2020	27	MLB	Milwaukee Brewers	—	136	115	24	3	0	6	20	33	1	0	0	209	331	391	722	183	237	24	15	328	103	+1	+0	+0	-2	+3	0.1
2021	28	MLB	Milwaukee Brewers	—	258	215	47	8	0	9	43	57	0	0	0	219	349	381	730	163	255	22	17	334	110	+3	+0	-4	-6	+6	-0.1
2021	28	AAA	Nashville Sounds	—	65	48	15	0	0	3	16	13	0	0	0	312	484	500	984	188	364	20	25	435	137	—	—	—	—	—	—
2022	29	MLB	New York Mets	—	461	386	92	19	1	18	73	114	1	0	0	238	361	433	794	194	290	25	16	356	129	+16	+0	-1	-8	+10	1.7
2023	30	MLB	New York Mets	—	319	275	64	8	0	13	42	81	2	0	0	233	339	404	742	171	282	25	13	335	115	+6	+0	+0	-6	+7	0.7
2024	31	MLB	Toronto Blue Jays	—	79	70	13	5	0	1	9	17	0	0	0	186	278	300	578	114	231	22	11	267	67	-3	+0	+0	-1	+2	-0.3
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1944	1638	360	63	1	81	295	486	8	0	0	220	342	408	749	188	260	25	15	338	115	+35	+0	-12	-52	+42	1.2
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2011	18	ROK MLE	AZL Cubs	—	27	25	5	2	0	1	1	3	1	1	0	200	259	400	659	200	219	11	4	292	84	—	—	—	—	—	—
2012	19	ROK MLE	AZL Cubs	—	115	107	25	9	1	5	7	20	0	1	0	234	281	477	757	243	246	17	6	335	113	—	—	—	—	—	—
2013	20	A+ MLE	Daytona Cubs	—	66	54	13	2	0	2	12	17	0	1	0	241	379	389	768	148	312	26	18	328	108	—	—	—	—	—	—
2013	20	A MLE	Kane County Cougars	—	502	456	107	18	0	15	36	107	2	4	4	235	294	373	666	138	264	21	7	294	85	—	—	—	—	—	—
2014	21	A+ MLE	Daytona Cubs	—	560	501	116	26	1	15	47	135	5	4	4	232	304	377	681	146	275	24	8	297	87	—	—	—	—	—	—
2015	22	AA MLE	Tennessee Smokies	—	313	270	67	16	1	6	41	77	0	1	1	248	347	381	729	133	317	25	13	320	103	—	—	—	—	—	—
2015	22	ROK MLE	AZL Cubs	—	17	13	5	2	0	0	4	1	0	0	0	385	529	538	1.068	154	376	6	24	415	167	—	—	—	—	—	—
2016	23	AAA MLE	Tacoma Rainiers	—	563	496	133	25	2	22	60	125	4	0	0	268	352	460	811	192	313	22	11	355	126	—	—	—	—	—	—
2017	24	MLB MLE	Seattle Mariners	—	31	28	6	1	0	0	3	9	0	0	0	214	290	250	540	36	316	29	10	256	60	-1	+0	-2	-10	+1	-1.3
2017	24	AAA MLE	Tacoma Rainiers	—	541	479	124	22	0	14	56	123	1	3	1	259	338	392	730	134	313	23	10	323	105	—	—	—	—	—	—
2018	25	MLB MLE	Seattle Mariners	—	102	87	18	2	0	4	13	26	2	0	0	207	324	368	691	161	246	25	13	320	102	+0	+0	-0	-9	+2	-0.7
2018	25	AAA MLE	Tacoma Rainiers	—	378	326	83	16	0	19	48	74	1	0	1	255	352	479	831	224	264	20	13	356	127	—	—	—	—	—	—
2019	26	MLB MLE	Seattle Mariners	—	558	464	97	17	0	31	90	149	2	0	0	209	340	446	786	237	232	27	16	350	123	+15	+0	-6	-10	+12	1.2
2020	27	MLB MLE	Milwaukee Brewers	—	136	116	24	3	0	6	19	33	1	0	0	207	324	388	711	181	237	24	14	321	103	+1	+0	+0	-2	+3	0.1
2021	28	MLB MLE	Milwaukee Brewers	—	258	216	48	9	0	9	42	57	0	0	0	222	349	389	738	167	255	22	16	331	110	+3	+0	-4	-6	+6	-0.1
2021	28	AAA MLE	Nashville Sounds	—	65	53	14	0	0	2	11	15	0	0	0	264	391	377	768	113	337	23	17	371	137	—	—	—	—	—	—
2022	29	MLB MLE	New York Mets	—	461	388	94	20	1	18	71	114	1	0	0	242	361	438	799	196	290	25	15	359	129	+16	+0	-1	-8	+10	1.7
2023	30	MLB MLE	New York Mets	—	319	276	65	8	0	13	41	81	2	0	0	236	339	406	744	170	282	25	13	339	115	+6	+0	+0	-6	+7	0.7
2024	31	MLB MLE	Toronto Blue Jays	—	79	70	13	5	0	1	9	17	0	0	0	186	278	300	578	114	231	22	11	267	67	-3	+0	+0	-1	+2	-0.3
2011	18	ROK MLE	AZL Cubs	—	27	25	5	2	0	1	1	3	1	1	0	200	259	400	659	200	190	11	4	292	84	—	—	—	—	—	—
2011	18	ROK RAW	AZL Cubs	—	27	24	7	3	0	1	2	2	1	1	0	292	370	542	912	250	286	7	7	399	84	—	—	—	—	—	—
2012	19	ROK MLE	AZL Cubs	—	115	107	25	9	1	5	7	20	0	1	0	234	281	477	757	243	241	17	6	335	113	—	—	—	—	—	—
2012	19	ROK RAW	AZL Cubs	—	115	102	33	12	2	7	12	14	0	1	0	324	395	686	1.081	363	317	12	10	456	113	—	—	—	—	—	—
2013	20	A MLE	2 teams	—	568	510	121	20	0	17	48	124	2	5	4	237	305	376	682	139	276	22	8	298	88	—	—	—	—	—	—
2013	20	A RAW	2 teams	—	568	483	137	23	0	19	73	90	2	5	4	284	379	449	828	166	309	16	13	365	88	—	—	—	—	—	—
2014	21	A+ MLE	2 teams	—	648	580	134	30	1	17	54	156	5	5	4	231	302	374	676	143	281	24	8	297	87	—	—	—	—	—	—
2014	21	A+ RAW	2 teams	—	648	551	147	32	1	16	83	102	5	5	4	267	368	416	783	149	296	16	13	349	87	—	—	—	—	—	—
2015	22	AA MLE	2 teams	—	330	284	72	18	1	6	44	78	0	1	1	254	354	387	741	134	327	24	13	325	106	—	—	—	—	—	—
2015	22	AA RAW	2 teams	—	330	265	74	18	1	7	63	62	0	1	1	279	418	434	852	155	338	19	19	384	106	—	—	—	—	—	—
2016	23	AAA MLE	Tacoma Rainiers	—	563	496	133	25	2	22	60	125	4	0	0	268	352	460	811	192	315	22	11	355	126	—	—	—	—	—	—
2016	23	AAA RAW	Tacoma Rainiers	—	563	459	134	25	2	23	97	101	4	0	0	292	420	505	925	214	328	18	17	408	126	—	—	—	—	—	—
2017	24	AAA MLE	2 teams	—	572	507	130	23	0	14	59	132	1	3	1	256	335	385	720	128	317	23	10	319	102	—	—	—	—	—	—
2017	24	AAA RAW	2 teams	—	572	487	139	26	0	17	79	107	1	3	1	285	386	444	830	158	332	19	14	370	102	—	—	—	—	—	—
2018	25	AAA MLE	2 teams	—	480	413	101	18	0	23	61	100	3	0	1	245	346	455	801	211	266	21	13	348	122	—	—	—	—	—	—
2018	25	AAA RAW	2 teams	—	480	384	104	18	0	24	90	85	3	0	1	271	413	505	918	234	288	18	19	404	122	—	—	—	—	—	—
2019	26	MLB MLE	Seattle Mariners	—	558	464	97	17	0	31	90	149	2	0	0	209	340	446	786	237	231	27	16	350	123	+15	+0	-6	-10	+12	1.2
2019	26	MLB RAW	Seattle Mariners	—	558	462	96	17	0	30	92	149	2	0	0	208	342	439	781	232	232	27	16	348	123	+15	+0	-6	-10	+12	1.2
2020	27	MLB MLE	Milwaukee Brewers	—	136	116	24	3	0	6	19	33	1	0	0	207	324	388	711	181	234	24	14	321	103	+1	+0	+0	-2	+3	0.1
2020	27	MLB RAW	Milwaukee Brewers	—	136	115	24	3	0	6	20	33	1	0	0	209	331	391	722	183	237	24	15	328	103	+1	+0	+0	-2	+3	0.1
2021	28	MLB MLE	2 teams	—	323	269	63	9	0	11	53	72	0	0	0	234	360	390	751	156	278	22	16	339	116	+6	+0	-4	-6	+7	0.3
2021	28	MLB RAW	2 teams	—	323	263	62	8	0	12	59	70	0	0	0	236	376	403	779	167	275	22	18	354	116	+6	+0	-4	-6	+7	0.3
2022	29	MLB MLE	New York Mets	—	461	388	94	20	1	18	71	114	1	0	0	242	361	438	799	196	296	25	15	359	129	+16	+0	-1	-8	+10	1.7
2022	29	MLB RAW	New York Mets	—	461	386	92	19	1	18	73	114	1	0	0	238	361	433	794	194	290	25	16	356	129	+16	+0	-1	-8	+10	1.7
2023	30	MLB MLE	New York Mets	—	319	276	65	8	0	13	41	81	2	0	0	236	339	406	744	170	286	25	13	339	115	+6	+0	+0	-6	+7	0.7
2023	30	MLB RAW	New York Mets	—	319	275	64	8	0	13	42	81	2	0	0	233	339	404	742	171	282	25	13	335	115	+6	+0	+0	-6	+7	0.7
2024	31	MLB MLE	Toronto Blue Jays	—	79	70	13	5	0	1	9	17	0	0	0	186	278	300	578	114	231	22	11	267	67	-3	+0	+0	-1	+2	-0.3
2024	31	MLB RAW	Toronto Blue Jays	—	79	70	13	5	0	1	9	17	0	0	0	186	278	300	578	114	231	22	11	267	67	-3	+0	+0	-1	+2	-0.3
2011	18	ROK MLE	AZL Cubs	—	27	25	5	2	0	1	1	3	1	1	0	200	259	400	659	200	219	11	4	292	84	—	—	—	—	—	—
2012	19	ROK MLE	AZL Cubs	—	115	107	25	9	1	5	7	20	0	1	0	234	281	477	757	243	246	17	6	335	113	—	—	—	—	—	—
2013	20	A MLE	2 teams	—	568	513	121	20	0	17	48	124	2	5	4	236	305	374	680	138	270	22	8	298	88	—	—	—	—	—	—
2014	21	A+ MLE	2 teams	—	648	584	134	30	1	17	54	156	5	5	4	229	302	372	674	142	275	24	8	297	87	—	—	—	—	—	—
2015	22	AA MLE	2 teams	—	330	283	72	18	1	6	44	78	0	1	1	254	354	389	742	134	320	24	13	325	106	—	—	—	—	—	—
2016	23	AAA MLE	Tacoma Rainiers	—	563	494	133	25	2	22	60	125	4	0	0	269	352	462	813	192	313	22	11	355	126	—	—	—	—	—	—
2017	24	AAA MLE	2 teams	—	572	507	130	23	0	14	59	132	1	3	1	256	335	385	720	128	313	23	10	319	102	—	—	—	—	—	—
2018	25	AAA MLE	2 teams	—	480	413	101	18	0	23	61	100	3	0	1	245	346	455	801	211	260	21	13	348	122	—	—	—	—	—	—
2019	26	MLB MLE	Seattle Mariners	—	558	461	97	17	0	31	90	149	2	0	0	210	340	449	789	239	232	27	16	350	123	—	—	—	—	—	—
2020	27	MLB MLE	Milwaukee Brewers	—	136	115	24	3	0	6	19	33	1	0	0	209	324	391	715	183	237	24	14	321	103	—	—	—	—	—	—
2021	28	MLB MLE	2 teams	—	323	267	63	9	0	11	53	72	0	0	0	236	360	393	754	157	272	22	16	339	116	—	—	—	—	—	—
2022	29	MLB MLE	New York Mets	—	461	386	94	20	1	18	71	114	1	0	0	244	361	440	801	197	290	25	15	359	129	—	—	—	—	—	—
2023	30	MLB MLE	New York Mets	—	319	273	65	8	0	13	41	81	2	0	0	238	339	410	749	172	282	25	13	339	115	—	—	—	—	—	—
2024	31	MLB MLE	Toronto Blue Jays	—	79	70	13	5	0	1	9	17	0	0	0	186	278	300	578	114	231	22	11	267	67	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	31	MLB MLE	Toronto Blue Jays	—	79	70	13	5	0	1	9	17	0	0	0	186	278	300	578	114	231	22	11	267	67	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1944	1638	360	63	1	81	295	486	8	0	0	220	342	408	749	188	260	25	15	338	109	+35	+0	-12	-52	+42	1.2
/ 162G	—	A+C		—	650	548	120	21	0	27	99	162	3	0	0	219	342	405	747	186	258	25	15	338	109	+12	+0	-4	-17	+14	0.4
Career	—	MLE		—	5179	4505	1077	207	6	185	617	1204	22	16	11	239	334	411	744	172	283	23	12	330	109	+35	+0	-12	-52	+42	1.2
/ 162G	—	MLE		—	650	565	135	26	1	23	77	151	3	2	1	239	333	411	743	172	284	23	12	330	109	+12	+0	-4	-17	+14	0.4

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 AAANashville Sounds · 65 PAwOBA .431 → .371 (−60)K% 20.0% → 23.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷1.024	×1.200	—	—	23.44%
BB% (unintentional) /PA	24.62%	÷0.946	×0.690	—	×0.982	17.63%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	34.29%	÷0.966	×0.930	—	×0.982	32.40%
Doubles /BIP	0.00%	÷1.030	×0.830	—	×0.982	0.00%
Triples /BIP	0.00%	÷1.150	×0.920	—	×0.982	0.00%
Home runs /BIP	8.57%	÷0.915	×0.700	—	×0.982	6.44%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 83, 1B 93, 2B 106, 3B 130, K 105, BB 89 — 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).

Result: wOBA .431 → .371; ISO .188 → .154; BABIP .364 → .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).

2018 AAATacoma Rainiers · 378 PAwOBA .419 → .356 (−63)K% 15.6% → 19.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.61%	÷1.031	×1.290	—	—	19.52%
BB% (unintentional) /PA	19.58%	÷1.103	×0.710	—	×1.018	12.82%
HBP% /PA	0.26%	—	×0.980	—	×1.018	0.26%
Singles /BIP	21.01%	÷1.006	×0.900	×0.975	×1.018	18.66%
Doubles /BIP	6.72%	÷0.885	×0.810	×0.975	×1.018	6.11%
Triples /BIP	0.00%	÷0.900	×0.810	×0.975	×1.018	0.00%
Home runs /BIP	8.40%	÷0.918	×0.780	—	×1.018	7.27%

Factors used: league row PCL. Park (home-season share, regressed): HR 84, 1B 101, 2B 77, 3B 80, K 106, BB 121 — 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 ×0.975.

Result: wOBA .419 → .356; ISO .256 → .239; BABIP .299 → .264. 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 AAATacoma Rainiers · 541 PAwOBA .370 → .323 (−47)K% 18.1% → 22.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.11%	÷1.028	×1.290	—	—	22.72%
BB% (unintentional) /PA	13.86%	÷0.979	×0.710	—	×1.033	10.39%
HBP% /PA	0.18%	—	×0.980	—	×1.033	0.19%
Singles /BIP	25.21%	÷0.978	×0.900	×1.023	×1.033	24.51%
Doubles /BIP	6.93%	÷0.988	×0.810	×1.023	×1.033	6.00%
Triples /BIP	0.00%	÷0.900	×0.810	×1.023	×1.033	0.00%
Home runs /BIP	4.71%	÷0.963	×0.780	—	×1.033	3.94%

Factors used: league row PCL. Park (home-season share, regressed): HR 93, 1B 96, 2B 98, 3B 80, K 106, BB 96 — applied at half strength. Age: age 25 vs a level average of 27.2 → +3.3% on BB/HBP/hit rates (2.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.023.

Result: wOBA .370 → .323; ISO .166 → .140; BABIP .332 → .313. 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 AAATacoma Rainiers · 563 PAwOBA .396 → .355 (−42)K% 17.9% → 22.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.94%	÷1.041	×1.290	—	—	22.24%
BB% (unintentional) /PA	15.99%	÷1.115	×0.710	—	×1.048	10.67%
HBP% /PA	0.71%	—	×0.980	—	×1.048	0.73%
Singles /BIP	23.46%	÷0.987	×0.900	×1.008	×1.048	22.60%
Doubles /BIP	6.98%	÷0.901	×0.810	×1.008	×1.048	6.63%
Triples /BIP	0.56%	÷1.063	×0.810	×1.008	×1.048	0.45%
Home runs /BIP	6.42%	÷0.896	×0.780	—	×1.048	5.86%

Factors used: league row PCL. Park (home-season share, regressed): HR 79, 1B 97, 2B 80, 3B 113, K 108, BB 123 — applied at half strength. Age: age 24 vs a level average of 27.2 → +4.8% on BB/HBP/hit rates (3.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.008.

Result: wOBA .396 → .355; ISO .214 → .204; BABIP .328 → .313. 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 AATennessee Smokies · 313 PAwOBA .367 → .320 (−47)K% 19.5% → 24.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.49%	÷0.967	×1.220	—	—	24.59%
BB% (unintentional) /PA	17.89%	÷0.959	×0.680	—	×1.027	13.03%
HBP% /PA	0.00%	—	×0.840	—	×1.027	0.00%
Singles /BIP	23.32%	÷1.026	×0.920	×1.050	×1.027	22.55%
Doubles /BIP	8.29%	÷0.998	×0.910	×1.050	×1.027	8.15%
Triples /BIP	0.52%	÷1.058	×0.880	×1.050	×1.027	0.46%
Home runs /BIP	3.63%	÷1.048	×0.800	—	×1.027	2.84%

Factors used: league row SL. Park (home-season share, regressed): HR 110, 1B 105, 2B 100, 3B 112, K 93, BB 92 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .367 → .320; ISO .154 → .135; BABIP .330 → .317. 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 ROKAZL Cubs · 17 PAwOBA .545 → .415 (−131)K% 5.9% → 8.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	5.88%	÷1.000	×1.440	—	—	8.47%
BB% (unintentional) /PA	35.29%	÷1.000	×0.620	—	×0.965	21.12%
HBP% /PA	0.00%	—	×0.720	—	×0.965	0.00%
Singles /BIP	30.00%	÷1.000	×0.820	—	×0.965	23.74%
Doubles /BIP	20.00%	÷1.000	×0.720	—	×0.965	13.90%
Triples /BIP	0.00%	÷1.000	×0.720	—	×0.965	0.00%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×0.965	0.00%

Factors used: level-wide ROK factors (no league-specific row for this league/era). Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 23 vs a level average of 19.5 → −3.5% on BB/HBP/hit rates (3.5 yr older than average).

Result: wOBA .545 → .415; ISO .182 → .151; BABIP .500 → .376. 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 A+Daytona Cubs · 560 PAwOBA .346 → .297 (−49)K% 16.2% → 24.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.25%	÷0.959	×1.420	—	—	24.07%
BB% (unintentional) /PA	11.61%	÷1.044	×0.750	—	×1.012	8.44%
HBP% /PA	0.89%	—	×0.930	—	×1.012	0.84%
Singles /BIP	21.48%	÷0.995	×0.920	×0.990	×1.012	19.89%
Doubles /BIP	7.16%	÷1.006	×0.960	×0.990	×1.012	6.84%
Triples /BIP	0.26%	÷0.986	×0.810	×0.990	×1.012	0.21%
Home runs /BIP	4.09%	÷0.930	×0.880	—	×1.012	3.92%

Factors used: league row FSL. Park (home-season share, regressed): HR 86, 1B 99, 2B 101, 3B 97, K 92, 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.990.

Result: wOBA .346 → .297; ISO .162 → .147; BABIP .296 → .275. 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 AKane County Cougars · 502 PAwOBA .354 → .294 (−59)K% 15.3% → 21.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.34%	÷0.980	×1.360	—	—	21.29%
BB% (unintentional) /PA	10.76%	÷1.047	×0.690	—	×1.015	7.19%
HBP% /PA	0.40%	—	×0.780	—	×1.015	0.32%
Singles /BIP	23.88%	÷1.091	×0.920	×1.017	×1.015	20.78%
Doubles /BIP	5.90%	÷0.990	×0.830	×1.017	×1.015	5.11%
Triples /BIP	0.00%	÷1.105	×0.910	×1.017	×1.015	0.00%
Home runs /BIP	4.78%	÷0.913	×0.800	—	×1.015	4.25%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 83, 1B 118, 2B 98, 3B 121, K 96, BB 109 — applied at half strength. Age: age 21 vs a level average of 22.0 → +1.5% on BB/HBP/hit rates (1.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.017.

Result: wOBA .354 → .294; ISO .166 → .147; BABIP .305 → .264. 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 — .