Adam Engel

PosCF

B/TR/R

Born1991-12-09

Age (2027)35

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2023

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2021	29	AAACWS	60	.222/.288/.370	2	5	35	—	.164/.220/.236
2021	29	MLBCWS	140	.252/.338/.496	7	7	131	1.3
2022	30	MLBCWS	260	.224/.269/.310	2	12	62	-0.3
2023	31	AAASEA	376	.237/.355/.435	14	22	59	—	.182/.267/.307
2024	32	No MLB games played
2025	33	No MLB games played
2026	34	No MLB games played

Last 3 seasons WAR 0.9

Contract

No contract data on file.

Skills · percentileStatcast 2021-2023

Speed90

xwOBA25

Barrel%18

Avg EV12

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)
2013	21	ROK	Great Falls Voyagers	—	274	239	72	12	3	3	21	34	10	31	8	301	381	414	796	113	338	12	8	355	61	—	—	—	—	—	—
2014	22	A+	Winston-Salem Dash	—	100	88	21	0	0	0	6	21	2	9	1	239	302	239	541		304	21	6	247	31	—	—	—	—	—	—
2014	22	A	Kannapolis Intimidators	—	341	307	80	14	7	6	29	86	5	28	11	261	334	410	745	150	344	25	9	333	58	—	—	—	—	—	—
2014	22	ROK	ACL White Sox	—	38	33	12	3	3	1	3	6	2	2	0	364	447	727	1.175	364	423	16	8	496	114	—	—	—	—	—	—
2014	22	INTL	Melbourne Aces	—	212	192	48	9	2	4	14	41	4	18	4	250	314	380	694	130	299	19	7	310	96	—	—	—	—	—	—
2015	23	A+	Winston-Salem Dash	—	608	529	133	23	9	7	62	132	6	65	11	251	337	369	705	117	321	22	10	315	41	—	—	—	—	—	—
2015	23	INTL	Glendale Desert Dogs	—	86	67	27	9	2	1	16	11	2	10	4	403	529	642	1.171	239	464	13	19	501	225	—	—	—	—	—	—
2016	24	AAA	Charlotte Knights	—	161	149	36	6	2	3	10	50	2	8	5	242	298	369	667	128	344	31	6	300	51	—	—	—	—	—	—
2016	24	AA	Birmingham Barons	—	357	306	78	18	9	4	39	70	7	31	9	255	352	412	764	157	319	20	11	339	78	—	—	—	—	—	—
2016	24	A+	Winston-Salem Dash	—	64	55	18	6	1	0	7	11	1	6	0	327	413	473	885	145	409	17	11	389	91	—	—	—	—	—	—
2017	25	MLB	Chicago White Sox	—	336	301	50	11	3	6	19	117	8	8	1	166	235	282	517	116	247	35	6	231	42	-23	+1	+14	+2	+7	0.1
2017	25	AAA	Charlotte Knights	—	192	165	36	12	2	8	19	51	4	4	3	218	314	461	774	242	262	27	10	334	61	—	—	—	—	—	—
2018	26	MLB	Chicago White Sox	—	463	429	101	17	4	6	18	129	8	16	8	235	279	336	615	100	322	28	4	273	70	-17	+0	+11	+2	+10	0.6
2019	27	MLB	Chicago White Sox	—	248	227	55	10	2	6	14	78	6	3	3	242	304	383	687	141	343	31	6	307	93	-2	-1	+5	+2	+5	0.9
2019	27	AAA	Charlotte Knights	—	277	248	67	13	4	9	22	62	7	13	3	270	347	464	810	194	328	22	8	359	68	—	—	—	—	—	—
2020	28	MLB	Chicago White Sox	—	93	88	26	5	1	3	3	19	2	1	0	295	333	477	811	182	348	20	3	357	127	+3	+0	+2	-1	+2	0.6
2021	29	MLB	Chicago White Sox	—	140	123	31	9	0	7	11	31	5	7	1	252	338	496	834	244	279	22	8	365	131	+5	+1	+2	+1	+3	1.3
2021	29	AAA	Charlotte Knights	—	60	54	12	2	0	2	3	16	2	5	0	222	288	370	659	148	270	27	5	292	35	—	—	—	—	—	—
2022	30	MLB	Chicago White Sox	—	260	245	55	13	1	2	11	76	4	12	4	224	269	310	579	86	317	29	4	263	62	-12	+1	+1	+1	+6	-0.3
2023	31	AAA	Tacoma Rainiers	—	376	317	75	17	2	14	53	116	5	22	2	237	355	435	790	199	324	31	14	353	59	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1540	1413	318	65	11	30	76	450	33	47	17	225	281	350	631	125	308	29	5	281	76	-43	+3	+36	+6	+33	3.5
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	21	ROK MLE	Great Falls Voyagers	—	274	247	55	8	2	2	13	49	10	31	8	223	289	296	584	73	263	18	5	258	61	—	—	—	—	—	—
2014	22	A+ MLE	Winston-Salem Dash	—	100	90	19	0	0	0	4	31	2	9	1	211	260	211	472		297	31	4	214	31	—	—	—	—	—	—
2014	22	A MLE	Kannapolis Intimidators	—	341	318	65	10	5	5	18	113	5	28	11	204	258	314	573	110	302	33	5	254	58	—	—	—	—	—	—
2014	22	ROK MLE	ACL White Sox	—	38	34	9	2	2	1	2	9	2	2	0	265	342	529	872	265	310	24	5	336	114	—	—	—	—	—	—
2015	23	A+ MLE	Winston-Salem Dash	—	608	555	108	15	6	5	36	201	6	65	11	195	251	270	522	76	282	33	6	229	41	—	—	—	—	—	—
2016	24	AAA MLE	Charlotte Knights	—	161	152	31	5	2	3	7	57	2	8	5	204	248	322	571	118	303	35	4	244	51	—	—	—	—	—	—
2016	24	AA MLE	Birmingham Barons	—	357	318	72	18	7	4	27	86	7	31	9	226	301	365	666	138	291	24	8	284	78	—	—	—	—	—	—
2016	24	A+ MLE	Winston-Salem Dash	—	64	58	16	5	1	0	4	17	1	6	0	276	333	397	730	121	363	27	6	302	91	—	—	—	—	—	—
2017	25	MLB MLE	Chicago White Sox	—	336	301	50	11	3	6	19	117	8	8	1	166	235	282	517	116	247	35	6	230	42	-23	+1	+14	+2	+7	0.1
2017	25	AAA MLE	Charlotte Knights	—	192	172	30	10	2	6	12	64	4	4	3	174	245	360	605	186	226	33	6	258	61	—	—	—	—	—	—
2018	26	MLB MLE	Chicago White Sox	—	463	429	101	17	4	6	18	129	8	16	8	235	279	336	615	100	322	28	4	272	70	-17	+0	+11	+2	+10	0.6
2019	27	MLB MLE	Chicago White Sox	—	248	227	55	10	2	6	14	78	6	3	3	242	304	383	687	141	343	31	6	306	93	-2	-1	+5	+2	+5	0.9
2019	27	AAA MLE	Charlotte Knights	—	277	256	54	11	4	6	14	77	7	13	3	211	271	355	626	145	272	28	5	268	68	—	—	—	—	—	—
2020	28	MLB MLE	Chicago White Sox	—	93	88	26	5	1	3	3	19	2	1	0	295	333	477	811	182	348	20	3	355	127	+3	+0	+2	-1	+2	0.6
2021	29	MLB MLE	Chicago White Sox	—	140	123	31	9	0	7	11	31	5	7	1	252	338	496	834	244	279	22	8	362	131	+5	+1	+2	+1	+3	1.3
2021	29	AAA MLE	Charlotte Knights	—	60	55	9	1	0	1	2	19	2	5	0	164	220	236	457	73	231	32	3	220	35	—	—	—	—	—	—
2022	30	MLB MLE	Chicago White Sox	—	260	246	55	13	1	2	10	76	4	12	4	224	265	309	574	85	317	29	4	259	62	-12	+1	+1	+1	+6	-0.3
2023	31	AAA MLE	Tacoma Rainiers	—	376	336	61	14	2	8	34	136	5	22	2	182	267	307	573	125	271	36	9	256	59	—	—	—	—	—	—
2013	21	ROK MLE	Great Falls Voyagers	—	274	247	55	8	2	2	13	49	10	31	8	223	289	296	584	73	268	18	5	258	61	—	—	—	—	—	—
2013	21	ROK RAW	Great Falls Voyagers	—	274	239	72	12	3	3	21	34	10	31	8	301	381	414	796	113	338	12	8	355	61	—	—	—	—	—	—
2014	22	A MLE	4 teams	—	691	638	135	18	11	8	34	220	13	57	16	212	266	312	578	100	308	32	5	252	57	—	—	—	—	—	—
2014	22	A RAW	4 teams	—	691	620	161	26	12	11	52	154	13	57	16	260	330	394	723	134	328	22	8	322	57	—	—	—	—	—	—
2015	23	A+ MLE	2 teams	—	694	632	123	17	6	6	42	230	8	75	15	195	254	269	523	74	292	33	6	229	41	—	—	—	—	—	—
2015	23	A+ RAW	2 teams	—	694	596	160	32	11	8	78	143	8	75	15	268	361	399	760	131	339	21	11	338	41	—	—	—	—	—	—
2016	24	AA MLE	3 teams	—	582	528	118	28	10	6	38	160	10	45	14	223	288	348	637	125	309	27	7	275	72	—	—	—	—	—	—
2016	24	AA RAW	3 teams	—	582	510	132	30	12	7	56	131	10	45	14	259	344	406	750	147	336	23	10	333	72	—	—	—	—	—	—
2017	25	MLB MLE	2 teams	—	528	473	80	21	5	12	31	181	12	12	4	169	238	311	549	142	242	34	6	240	49	-32	+1	+14	+2	+11	-0.4
2017	25	MLB RAW	2 teams	—	528	466	86	23	5	14	38	168	12	12	4	185	264	345	609	161	253	32	7	269	49	-32	+1	+14	+2	+11	-0.4
2018	26	MLB MLE	Chicago White Sox	—	463	429	101	17	4	6	18	129	8	16	8	235	279	336	615	100	322	28	4	272	70	-17	+0	+11	+2	+10	0.6
2018	26	MLB RAW	Chicago White Sox	—	463	429	101	17	4	6	18	129	8	16	8	235	279	336	615	100	322	28	4	273	70	-17	+0	+11	+2	+10	0.6
2019	27	AAA MLE	2 teams	—	525	483	109	21	6	12	28	155	13	16	6	226	286	369	655	143	307	30	5	286	80	—	—	—	—	—	—
2019	27	AAA RAW	2 teams	—	525	475	122	23	6	15	36	140	13	16	6	257	326	425	752	168	334	27	7	335	80	—	—	—	—	—	—
2020	28	MLB MLE	Chicago White Sox	—	93	88	26	5	1	3	3	19	2	1	0	295	333	477	811	182	348	20	3	355	127	+3	+0	+2	-1	+2	0.6
2020	28	MLB RAW	Chicago White Sox	—	93	88	26	5	1	3	3	19	2	1	0	295	333	477	811	182	348	20	3	357	127	+3	+0	+2	-1	+2	0.6
2021	29	MLB MLE	2 teams	—	200	178	40	10	0	8	13	50	7	12	1	225	303	416	719	191	262	25	6	319	102	+1	+2	+2	+1	+4	1.0
2021	29	MLB RAW	2 teams	—	200	177	43	11	0	9	14	47	7	12	1	243	323	458	781	215	276	24	7	343	102	+1	+2	+2	+1	+4	1.0
2022	30	MLB MLE	Chicago White Sox	—	260	246	55	13	1	2	10	76	4	12	4	224	265	309	574	85	315	29	4	259	62	-12	+1	+1	+1	+6	-0.3
2022	30	MLB RAW	Chicago White Sox	—	260	245	55	13	1	2	11	76	4	12	4	224	269	310	579	86	317	29	4	263	62	-12	+1	+1	+1	+6	-0.3
2023	31	AAA MLE	Tacoma Rainiers	—	376	336	61	14	2	8	34	136	5	22	2	182	267	307	573	125	275	36	9	256	59	—	—	—	—	—	—
2023	31	AAA RAW	Tacoma Rainiers	—	376	317	75	17	2	14	53	116	5	22	2	237	355	435	790	199	324	31	14	353	59	—	—	—	—	—	—
2013	21	ROK MLE	Great Falls Voyagers	—	274	249	55	8	2	2	13	49	10	31	8	221	289	293	582	72	263	18	5	258	61	—	—	—	—	—	—
2014	22	A MLE	4 teams	—	691	639	135	18	11	8	34	220	13	57	16	211	266	311	577	100	302	32	5	252	57	—	—	—	—	—	—
2015	23	A+ MLE	2 teams	—	694	639	123	17	6	6	42	230	8	75	15	192	254	266	520	74	282	33	6	229	41	—	—	—	—	—	—
2016	24	AA MLE	3 teams	—	582	529	118	28	10	6	38	160	10	45	14	223	288	348	636	125	302	27	7	275	72	—	—	—	—	—	—
2017	25	MLB MLE	2 teams	—	528	480	80	21	5	12	31	181	12	12	4	167	238	306	545	140	239	34	6	240	49	—	—	—	—	—	—
2018	26	MLB MLE	Chicago White Sox	—	463	434	101	17	4	6	18	129	8	16	8	233	279	332	611	99	322	28	4	272	70	—	—	—	—	—	—
2019	27	AAA MLE	2 teams	—	525	479	109	21	6	12	28	155	13	16	6	228	286	372	658	144	305	30	5	286	80	—	—	—	—	—	—
2020	28	MLB MLE	Chicago White Sox	—	93	88	26	5	1	3	3	19	2	1	0	295	333	477	811	182	348	20	3	355	127	—	—	—	—	—	—
2021	29	MLB MLE	2 teams	—	200	178	40	10	0	8	13	50	7	12	1	225	303	416	719	191	265	25	6	319	102	—	—	—	—	—	—
2022	30	MLB MLE	Chicago White Sox	—	260	244	55	13	1	2	10	76	4	12	4	225	265	311	577	86	317	29	4	259	62	—	—	—	—	—	—
2023	31	AAA MLE	Tacoma Rainiers	—	376	334	61	14	2	8	34	136	5	22	2	183	267	308	575	126	271	36	9	256	59	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1540	1413	318	65	11	30	76	450	33	47	17	225	281	350	631	125	308	29	5	281	63	-43	+3	+36	+6	+33	3.5
/ 162G	—	A+C		—	650	596	134	27	5	13	32	190	14	20	7	225	280	352	633	128	307	29	5	281	63	-18	+1	+15	+3	+14	1.5
Career	—	MLE		—	4686	4278	903	172	48	73	264	1405	92	299	78	211	272	325	597	114	295	30	6	262	63	-43	+3	+36	+6	+33	3.5
/ 162G	—	MLE		—	650	593	126	24	7	10	37	195	13	41	11	212	274	327	601	115	297	30	6	262	63	-18	+1	+15	+3	+14	1.5

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.

2023 AAATacoma Rainiers · 376 PAwOBA .345 → .256 (−90)K% 30.9% → 36.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	30.85%	÷1.024	×1.200	—	—	36.16%
BB% (unintentional) /PA	14.10%	÷1.013	×0.690	—	×0.952	9.14%
HBP% /PA	1.33%	—	×0.940	—	×0.952	1.19%
Singles /BIP	20.90%	÷0.989	×0.930	×0.973	×0.952	18.21%
Doubles /BIP	8.46%	÷0.940	×0.830	×0.973	×0.952	6.92%
Triples /BIP	1.00%	÷0.900	×0.970	×0.973	×0.952	0.99%
Home runs /BIP	6.97%	÷1.157	×0.700	—	×0.952	4.01%

Factors used: league row International League. Park (home-season share, regressed): HR 131, 1B 98, 2B 88, 3B 80, K 105, BB 103 — 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 ×0.973.

Result: wOBA .345 → .256; ISO .199 → .133; BABIP .324 → .271. 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).

2021 AAACharlotte Knights · 60 PAwOBA .289 → .220 (−69)K% 26.7% → 31.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.67%	÷1.011	×1.200	—	—	31.66%
BB% (unintentional) /PA	5.00%	÷1.053	×0.690	—	×0.972	3.18%
HBP% /PA	3.33%	—	×0.940	—	×0.972	3.05%
Singles /BIP	21.05%	÷0.986	×0.930	—	×0.972	19.29%
Doubles /BIP	5.26%	÷1.128	×0.830	—	×0.972	3.76%
Triples /BIP	0.00%	÷1.020	×0.920	—	×0.972	0.00%
Home runs /BIP	5.26%	÷1.190	×0.700	—	×0.972	3.01%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 138, 1B 97, 2B 126, 3B 104, K 102, BB 111 — 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).

Result: wOBA .289 → .220; ISO .148 → .088; BABIP .270 → .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).

2019 AAACharlotte Knights · 277 PAwOBA .349 → .268 (−81)K% 22.4% → 27.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.38%	÷0.962	×1.200	—	—	27.93%
BB% (unintentional) /PA	7.94%	÷1.077	×0.690	—	×0.992	5.05%
HBP% /PA	2.53%	—	×0.940	—	×0.992	2.36%
Singles /BIP	22.04%	÷1.061	×0.930	×0.950	×0.992	18.21%
Doubles /BIP	6.99%	÷0.921	×0.830	×0.950	×0.992	5.93%
Triples /BIP	2.15%	÷0.900	×0.970	×0.950	×0.992	2.18%
Home runs /BIP	4.84%	÷1.212	×0.840	—	×0.992	3.33%

Factors used: league row IL. Park (home-season share, regressed): HR 142, 1B 112, 2B 84, 3B 80, K 92, BB 115 — 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 ×0.950.

Result: wOBA .349 → .268; ISO .194 → .146; BABIP .328 → .272. 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 AAACharlotte Knights · 192 PAwOBA .325 → .258 (−66)K% 26.6% → 33.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.56%	÷0.952	×1.200	—	—	33.49%
BB% (unintentional) /PA	9.38%	÷1.008	×0.690	—	×1.018	6.53%
HBP% /PA	2.08%	—	×0.940	—	×1.018	1.99%
Singles /BIP	12.28%	÷1.012	×0.930	×0.967	×1.018	11.11%
Doubles /BIP	10.53%	÷0.958	×0.830	×0.967	×1.018	8.98%
Triples /BIP	1.75%	÷1.077	×0.970	×0.967	×1.018	1.56%
Home runs /BIP	7.02%	÷1.150	×0.840	—	×1.018	5.22%

Factors used: league row IL. Park (home-season share, regressed): HR 130, 1B 102, 2B 92, 3B 115, K 90, BB 102 — 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 ×0.967.

Result: wOBA .325 → .258; ISO .242 → .187; BABIP .262 → .226. 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 AABirmingham Barons · 357 PAwOBA .330 → .284 (−46)K% 19.6% → 24.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.61%	÷0.991	×1.220	—	—	24.13%
BB% (unintentional) /PA	10.92%	÷0.990	×0.680	—	×0.998	7.49%
HBP% /PA	1.96%	—	×0.840	—	×0.998	1.64%
Singles /BIP	19.92%	÷1.004	×0.920	×0.995	×0.998	18.12%
Doubles /BIP	7.63%	÷0.897	×0.910	×0.995	×0.998	7.68%
Triples /BIP	3.81%	÷1.150	×0.880	×0.995	×0.998	2.90%
Home runs /BIP	1.69%	÷0.918	×0.800	—	×0.998	1.47%

Factors used: league row SL. Park (home-season share, regressed): HR 84, 1B 101, 2B 79, 3B 130, K 98, BB 98 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.995.

Result: wOBA .330 → .284; ISO .157 → .139; BABIP .319 → .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).

2016 AAACharlotte Knights · 161 PAwOBA .292 → .244 (−47)K% 31.1% → 35.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.06%	÷1.053	×1.200	—	—	35.40%
BB% (unintentional) /PA	6.21%	÷0.990	×0.690	—	×1.033	4.47%
HBP% /PA	1.24%	—	×0.940	—	×1.033	1.21%
Singles /BIP	25.25%	÷1.031	×0.930	×0.950	×1.033	22.35%
Doubles /BIP	6.06%	÷0.974	×0.830	×0.950	×1.033	5.07%
Triples /BIP	2.02%	÷0.926	×0.970	×0.950	×1.033	2.08%
Home runs /BIP	3.03%	÷0.950	×0.840	—	×1.033	2.77%

Factors used: league row IL. Park (home-season share, regressed): HR 90, 1B 106, 2B 95, 3B 85, K 111, BB 98 — 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 ×0.950.

Result: wOBA .292 → .244; ISO .128 → .112; BABIP .344 → .303. 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 A+Winston-Salem Dash · 64 PAwOBA .379 → .302 (−77)K% 17.2% → 26.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.19%	÷0.938	×1.420	—	—	26.02%
BB% (unintentional) /PA	10.94%	÷0.996	×0.630	—	×0.978	6.76%
HBP% /PA	1.56%	—	×0.860	—	×0.978	1.31%
Singles /BIP	25.00%	÷0.994	×0.940	—	×0.978	23.13%
Doubles /BIP	13.64%	÷0.970	×0.830	—	×0.978	11.41%
Triples /BIP	2.27%	÷1.013	×0.800	—	×0.978	1.76%
Home runs /BIP	0.00%	÷1.098	×0.900	—	×0.978	0.00%

Factors used: league row CAR. Park (home-season share, regressed): HR 120, 1B 99, 2B 94, 3B 103, K 88, BB 99 — applied at half strength. Age: age 25 vs a level average of 22.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average).

Result: wOBA .379 → .302; ISO .145 → .114; BABIP .409 → .363. 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 A+Winston-Salem Dash · 608 PAwOBA .308 → .229 (−79)K% 21.7% → 33.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.71%	÷0.932	×1.420	—	—	33.07%
BB% (unintentional) /PA	10.20%	÷1.060	×0.630	—	×0.988	5.99%
HBP% /PA	0.99%	—	×0.860	—	×0.988	0.84%
Singles /BIP	23.68%	÷0.963	×0.940	×0.985	×0.988	22.49%
Doubles /BIP	5.79%	÷1.175	×0.830	×0.985	×0.988	3.98%
Triples /BIP	2.27%	÷1.150	×0.800	×0.985	×0.988	1.53%
Home runs /BIP	1.76%	÷1.090	×0.900	—	×0.988	1.44%

Factors used: league row CAR. Park (home-season share, regressed): HR 118, 1B 93, 2B 135, 3B 130, K 86, BB 112 — applied at half strength. Age: age 24 vs a level average of 22.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.985.

Result: wOBA .308 → .229; ISO .117 → .079; BABIP .321 → .282. 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).