Andrew Knapp

PosC

B/TS/R

Born1991-11-09

Age (2027)35

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2024

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2022	30	AAASF	230	.245/.314/.486	12	1	59	—	.187/.245/.350
2022	30	MLBSF	46	.128/.244/.154	0	0	21	0.0
2023	31	AAAHOU	358	.233/.328/.377	9	3	59	—	.202/.269/.318
2024	32	AAASF	400	.285/.387/.448	10	1	81	—	.235/.305/.350
2025	33	No MLB games played
2026	34	No MLB games played

Last 3 seasons WAR 0.0

Contract

No contract data on file.

Skills · percentileStatcast 2021-2024

Speed30

Bat Spd20

Barrel%10

xwOBA10

Avg EV10

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. Catcher framing: only 2027 Statcast framing is modeled (Baseball Savant server-caches the leaderboard to the current season); prior-year framing is unmodeled — projections for established framers may run 1-3 WAR low.

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)
2014	22	A+	Clearwater Threshers	—	90	83	13	1	0	1	5	26	2	1	0	157	222	205	427	48	214	29	6	203	-3	—	—	—	—	—	—
2014	22	A	Lakewood BlueClaws	—	314	283	82	19	4	5	27	71	2	3	3	290	356	438	794	148	368	23	9	352	79	—	—	—	—	—	—
2015	23	AA	Reading Fightin Phils	—	241	214	77	21	2	11	22	43	2	1	0	360	424	631	1.055	271	405	18	9	452	149	—	—	—	—	—	—
2015	23	A+	Clearwater Threshers	—	281	244	64	14	3	2	29	63	7	0	1	262	357	369	726	107	344	22	10	331	68	—	—	—	—	—	—
2015	23	INTL	Glendale Desert Dogs	—	64	51	12	3	0	0	11	16	1	1	0	235	381	294	675	59	333	25	17	319	102	—	—	—	—	—	—
2016	24	AAA	Lehigh Valley IronPigs	—	443	403	107	24	1	8	37	107	2	2	2	266	330	390	720	124	343	24	8	324	74	—	—	—	—	—	—
2016	24	INTL	Aguilas Cibaenas	—	49	45	11	2	0	1	3	10	1	0	0	244	306	356	662	111	294	20	6	300	89	—	—	—	—	—	—
2017	25	MLB	Philadelphia Phillies	—	204	171	44	8	1	3	31	56	0	1	0	257	371	368	740	111	360	27	15	337	104	+1	+0	-5	+4	+4	0.5
2018	26	MLB	Philadelphia Phillies	—	215	187	37	6	2	4	24	75	2	1	0	198	296	316	611	118	303	35	11	280	72	-7	+0	-5	+4	+5	-0.3
2018	26	AAA	Lehigh Valley IronPigs	—	25	20	5	1	0	0	5	6	0	0	0	250	400	300	700	50	357	24	20	336	72	—	—	—	—	—	—
2019	27	MLB	Philadelphia Phillies	—	160	136	29	9	0	2	18	51	3	0	0	213	318	324	642	110	325	32	11	292	78	-4	+0	+3	+3	+3	0.5
2020	28	MLB	Philadelphia Phillies	—	89	72	20	4	1	2	15	19	1	0	0	278	409	444	854	167	346	21	17	381	142	+4	+0	-1	+2	+2	0.7
2021	29	MLB	Philadelphia Phillies	—	159	145	22	3	0	2	10	61	2	0	0	152	217	214	430	62	241	38	6	200	21	-15	+0	-2	+3	+3	-1.1
2022	30	MLB	San Francisco Giants	—	46	39	5	1	0	0	5	12	1	0	0	128	244	154	398	26	179	26	11	198	21	-4	+0	-1	+5	+1	0.0
2022	30	AAA	Sacramento River Cats	—	230	208	51	14	0	12	17	57	4	1	1	245	314	486	800	240	279	25	7	349	59	—	—	—	—	—	—
2023	31	AAA	Sugar Land Space Cowboys	—	358	313	73	14	2	9	38	94	6	3	1	233	328	377	705	144	305	26	11	319	59	—	—	—	—	—	—
2024	32	AAA	Sacramento River Cats	—	400	337	96	21	2	10	52	95	4	1	4	285	387	448	835	163	361	24	13	368	81	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	873	750	157	31	4	13	103	274	9	2	0	209	312	313	625	104	307	31	12	287	80	-20	+0	-11	+20	+19	0.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	22	A+ MLE	Clearwater Threshers	—	90	84	11	1	0	1	4	36	2	1	0	131	189	179	367	48	213	40	4	164	-3	—	—	—	—	—	—
2014	22	A MLE	Lakewood BlueClaws	—	314	291	71	16	3	4	19	93	2	3	3	244	295	361	656	117	336	30	6	285	79	—	—	—	—	—	—
2015	23	AA MLE	Reading Fightin Phils	—	241	221	72	19	2	9	15	49	2	1	0	326	374	552	926	226	371	20	6	388	149	—	—	—	—	—	—
2015	23	A+ MLE	Clearwater Threshers	—	281	251	53	12	2	1	22	95	7	0	1	211	293	287	580	76	334	34	8	268	68	—	—	—	—	—	—
2016	24	AAA MLE	Lehigh Valley IronPigs	—	443	415	100	21	1	7	25	126	2	2	2	241	287	347	634	106	324	28	6	277	74	—	—	—	—	—	—
2017	25	MLB MLE	Philadelphia Phillies	—	204	175	44	8	1	3	27	56	0	1	0	251	351	360	711	109	360	27	13	322	104	+1	+0	-5	+4	+4	0.5
2018	26	MLB MLE	Philadelphia Phillies	—	215	188	37	6	2	4	23	75	2	1	0	197	291	314	605	117	303	35	11	274	72	-7	+0	-5	+4	+5	-0.3
2018	26	AAA MLE	Lehigh Valley IronPigs	—	25	21	5	1	0	0	4	7	0	0	0	238	360	286	646	48	328	28	16	274	72	—	—	—	—	—	—
2019	27	MLB MLE	Philadelphia Phillies	—	160	138	29	9	0	2	16	51	3	0	0	210	306	319	625	109	325	32	10	283	78	-4	+0	+3	+3	+3	0.5
2020	28	MLB MLE	Philadelphia Phillies	—	89	72	20	4	1	2	15	19	1	0	0	278	409	444	854	167	346	21	17	378	142	+4	+0	-1	+2	+2	0.7
2021	29	MLB MLE	Philadelphia Phillies	—	159	145	22	3	0	2	10	61	2	0	0	152	217	214	430	62	241	38	6	199	21	-15	+0	-2	+3	+3	-1.1
2022	30	MLB MLE	San Francisco Giants	—	46	39	5	1	0	0	5	12	1	0	0	128	244	154	398	26	179	26	11	199	21	-4	+0	-1	+5	+1	0.0
2022	30	AAA MLE	Sacramento River Cats	—	230	214	40	11	0	8	12	69	4	1	1	187	245	350	595	164	232	30	5	256	59	—	—	—	—	—	—
2023	31	AAA MLE	Sugar Land Space Cowboys	—	358	327	66	13	2	7	24	113	6	3	1	202	269	318	587	116	281	32	7	255	59	—	—	—	—	—	—
2024	32	AAA MLE	Sacramento River Cats	—	400	357	84	16	2	7	32	106	4	1	4	235	305	350	655	115	297	26	8	288	81	—	—	—	—	—	—
2014	22	A MLE	2 teams	—	404	376	81	16	3	5	22	129	4	4	3	215	266	314	580	98	311	32	5	258	61	—	—	—	—	—	—
2014	22	A RAW	2 teams	—	404	366	95	20	4	6	32	97	4	4	3	260	326	385	711	126	336	24	8	319	61	—	—	—	—	—	—
2015	23	A+ MLE	3 teams	—	586	529	139	35	4	11	42	162	10	2	1	263	329	406	735	144	355	28	7	323	105	—	—	—	—	—	—
2015	23	A+ RAW	3 teams	—	586	509	153	38	5	13	62	122	10	2	1	301	387	472	859	171	369	21	11	379	105	—	—	—	—	—	—
2016	24	AAA MLE	2 teams	—	492	460	110	23	1	8	28	140	3	2	2	239	287	346	633	107	326	28	6	277	74	—	—	—	—	—	—
2016	24	AAA RAW	2 teams	—	492	448	118	26	1	9	40	117	3	2	2	263	328	386	714	123	337	24	8	321	74	—	—	—	—	—	—
2017	25	MLB MLE	Philadelphia Phillies	—	204	175	44	8	1	3	27	56	0	1	0	251	351	360	711	109	347	27	13	322	104	+1	+0	-5	+4	+4	0.5
2017	25	MLB RAW	Philadelphia Phillies	—	204	171	44	8	1	3	31	56	0	1	0	257	371	368	740	111	360	27	15	337	104	+1	+0	-5	+4	+4	0.5
2018	26	MLB MLE	2 teams	—	240	209	42	7	2	4	27	82	2	1	0	201	298	311	609	110	306	34	11	274	72	-8	+0	-5	+4	+5	-0.4
2018	26	MLB RAW	2 teams	—	240	207	42	7	2	4	29	81	2	1	0	203	307	314	621	111	309	34	12	285	72	-8	+0	-5	+4	+5	-0.4
2019	27	MLB MLE	Philadelphia Phillies	—	160	138	29	9	0	2	16	51	3	0	0	210	306	319	625	109	318	32	10	283	78	-4	+0	+3	+3	+3	0.5
2019	27	MLB RAW	Philadelphia Phillies	—	160	136	29	9	0	2	18	51	3	0	0	213	318	324	642	110	325	32	11	292	78	-4	+0	+3	+3	+3	0.5
2020	28	MLB MLE	Philadelphia Phillies	—	89	72	20	4	1	2	15	19	1	0	0	278	409	444	854	167	346	21	17	378	142	+4	+0	-1	+2	+2	0.7
2020	28	MLB RAW	Philadelphia Phillies	—	89	72	20	4	1	2	15	19	1	0	0	278	409	444	854	167	346	21	17	381	142	+4	+0	-1	+2	+2	0.7
2021	29	MLB MLE	Philadelphia Phillies	—	159	145	22	3	0	2	10	61	2	0	0	152	217	214	430	62	241	38	6	199	21	-15	+0	-2	+3	+3	-1.1
2021	29	MLB RAW	Philadelphia Phillies	—	159	145	22	3	0	2	10	61	2	0	0	152	217	214	430	62	241	38	6	200	21	-15	+0	-2	+3	+3	-1.1
2022	30	AAA MLE	2 teams	—	276	253	45	12	0	8	16	81	5	1	1	178	241	320	561	142	223	29	6	247	53	—	—	—	—	—	—
2022	30	AAA RAW	2 teams	—	276	247	56	15	0	12	22	69	5	1	1	227	303	433	736	206	262	25	8	324	53	—	—	—	—	—	—
2023	31	AAA MLE	Sugar Land Space Cowboys	—	358	327	66	13	2	7	24	113	6	3	1	202	269	318	587	116	285	32	7	255	59	—	—	—	—	—	—
2023	31	AAA RAW	Sugar Land Space Cowboys	—	358	313	73	14	2	9	38	94	6	3	1	233	328	377	705	144	305	26	11	319	59	—	—	—	—	—	—
2024	32	AAA MLE	Sacramento River Cats	—	400	357	84	16	2	7	32	106	4	1	4	235	305	350	655	115	308	26	8	288	81	—	—	—	—	—	—
2024	32	AAA RAW	Sacramento River Cats	—	400	337	96	21	2	10	52	95	4	1	4	285	387	448	835	163	361	24	13	368	81	—	—	—	—	—	—
2014	22	A MLE	2 teams	—	404	375	81	16	3	5	22	129	4	4	3	216	266	315	581	99	309	32	5	258	61	—	—	—	—	—	—
2015	23	A+ MLE	3 teams	—	586	529	139	35	4	11	42	162	10	2	1	263	329	406	735	144	351	28	7	323	105	—	—	—	—	—	—
2016	24	AAA MLE	2 teams	—	492	458	110	23	1	8	28	140	3	2	2	240	287	347	634	107	324	28	6	277	74	—	—	—	—	—	—
2017	25	MLB MLE	Philadelphia Phillies	—	204	175	44	8	1	3	27	56	0	1	0	251	351	360	711	109	360	27	13	322	104	—	—	—	—	—	—
2018	26	MLB MLE	2 teams	—	240	209	42	7	2	4	27	82	2	1	0	201	298	311	609	110	305	34	11	274	72	—	—	—	—	—	—
2019	27	MLB MLE	Philadelphia Phillies	—	160	140	29	9	0	2	16	51	3	0	0	207	306	314	620	107	325	32	10	283	78	—	—	—	—	—	—
2020	28	MLB MLE	Philadelphia Phillies	—	89	73	20	4	1	2	15	19	1	0	0	274	409	438	847	164	346	21	17	378	142	—	—	—	—	—	—
2021	29	MLB MLE	Philadelphia Phillies	—	159	146	22	3	0	2	10	61	2	0	0	151	217	212	429	62	241	38	6	199	21	—	—	—	—	—	—
2022	30	AAA MLE	2 teams	—	276	253	45	12	0	8	16	81	5	1	1	178	241	320	561	142	223	29	6	247	53	—	—	—	—	—	—
2023	31	AAA MLE	Sugar Land Space Cowboys	—	358	325	66	13	2	7	24	113	6	3	1	203	269	320	589	117	281	32	7	255	59	—	—	—	—	—	—
2024	32	AAA MLE	Sacramento River Cats	—	400	361	84	16	2	7	32	106	4	1	4	233	305	346	652	114	297	26	8	288	81	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons)
2024	32	AAA MLE	Sacramento River Cats	—	400	361	84	16	2	7	32	106	4	1	4	233	305	346	652	114	297	26	8	288	81	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	873	750	157	31	4	13	103	274	9	2	0	209	312	313	625	104	307	31	12	287	76	-20	+0	-11	+20	+19	0.8
/ 162G	—	A+C		—	650	558	117	23	3	10	77	204	7	1	0	210	313	315	628	106	307	31	12	287	76	-15	+0	-8	+15	+14	0.6
Career	—	MLE		—	3368	3041	682	146	16	59	259	1000	40	15	12	224	294	341	635	117	311	30	8	281	76	-20	+0	-11	+20	+19	0.8
/ 162G	—	MLE		—	650	587	131	28	3	11	50	193	8	3	2	223	293	337	630	114	310	30	8	281	76	-15	+0	-8	+15	+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 AAASacramento River Cats · 400 PAwOBA .363 → .288 (−76)K% 23.8% → 26.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.75%	÷1.081	×1.200	—	—	26.36%
BB% (unintentional) /PA	12.75%	÷1.032	×0.690	—	×0.942	8.03%
HBP% /PA	1.00%	—	×0.940	—	×0.942	0.89%
Singles /BIP	26.03%	÷0.976	×0.930	×0.969	×0.942	22.64%
Doubles /BIP	8.68%	÷1.052	×0.830	×0.969	×0.942	6.25%
Triples /BIP	0.83%	÷1.091	×0.970	×0.969	×0.942	0.67%
Home runs /BIP	4.13%	÷1.010	×0.700	—	×0.942	2.70%

Factors used: league row International League. Park (home-season share, regressed): HR 102, 1B 95, 2B 110, 3B 118, K 116, 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 ×0.969.

Result: wOBA .363 → .288; ISO .163 → .120; BABIP .361 → .297. 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 AAASugar Land Space Cowboys · 358 PAwOBA .310 → .255 (−55)K% 26.3% → 31.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	26.26%	÷1.000	×1.200	—	—	31.50%
BB% (unintentional) /PA	10.34%	÷1.028	×0.690	—	×0.952	6.60%
HBP% /PA	1.68%	—	×0.940	—	×0.952	1.50%
Singles /BIP	21.92%	÷0.981	×0.930	×1.034	×0.952	20.45%
Doubles /BIP	6.39%	÷0.882	×0.830	×1.034	×0.952	5.92%
Triples /BIP	0.91%	÷1.056	×0.970	×1.034	×0.952	0.83%
Home runs /BIP	4.11%	÷0.896	×0.700	—	×0.952	3.06%

Factors used: league row International League. Park (home-season share, regressed): HR 79, 1B 96, 2B 76, 3B 111, K 100, BB 106 — 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 ×1.034.

Result: wOBA .310 → .255; ISO .144 → .116; BABIP .305 → .281. 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 AAASacramento River Cats · 230 PAwOBA .341 → .256 (−86)K% 24.8% → 30.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.78%	÷0.986	×1.200	—	—	30.15%
BB% (unintentional) /PA	7.39%	÷0.984	×0.690	—	×0.962	4.99%
HBP% /PA	1.74%	—	×0.940	—	×0.962	1.57%
Singles /BIP	16.56%	÷0.968	×0.930	×0.962	×0.962	14.72%
Doubles /BIP	9.27%	÷0.967	×0.830	×0.962	×0.962	7.37%
Triples /BIP	0.00%	÷0.900	×0.970	×0.962	×0.962	0.00%
Home runs /BIP	7.95%	÷0.989	×0.700	—	×0.962	5.41%

Factors used: league row International League. Park (home-season share, regressed): HR 98, 1B 94, 2B 93, 3B 80, K 97, BB 97 — 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 ×0.962.

Result: wOBA .341 → .256; ISO .240 → .165; BABIP .279 → .232. 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 AAALehigh Valley IronPigs · 25 PAwOBA .329 → .274 (−55)K% 24.0% → 29.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.00%	÷0.962	×1.200	—	—	29.93%
BB% (unintentional) /PA	20.00%	÷0.932	×0.690	—	×1.003	14.85%
HBP% /PA	0.00%	—	×0.940	—	×1.003	0.00%
Singles /BIP	28.57%	÷1.000	×0.930	—	×1.003	26.65%
Doubles /BIP	7.14%	÷0.971	×0.830	—	×1.003	6.12%
Triples /BIP	0.00%	÷0.900	×0.970	—	×1.003	0.00%
Home runs /BIP	0.00%	÷0.954	×0.840	—	×1.003	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 100, 2B 94, 3B 80, K 92, BB 86 — 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 .329 → .274; ISO .050 → .042; BABIP .357 → .328. 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 AAALehigh Valley IronPigs · 443 PAwOBA .315 → .277 (−38)K% 24.2% → 28.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.15%	÷1.018	×1.200	—	—	28.48%
BB% (unintentional) /PA	8.13%	÷1.035	×0.690	—	×1.033	5.60%
HBP% /PA	0.45%	—	×0.940	—	×1.033	0.44%
Singles /BIP	25.00%	÷1.028	×0.930	×1.041	×1.033	24.32%
Doubles /BIP	8.11%	÷1.018	×0.830	×1.041	×1.033	7.11%
Triples /BIP	0.34%	÷1.107	×0.970	×1.041	×1.033	0.32%
Home runs /BIP	2.70%	÷0.942	×0.840	—	×1.033	2.49%

Factors used: league row IL. Park (home-season share, regressed): HR 88, 1B 106, 2B 104, 3B 121, K 104, BB 107 — 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 ×1.041.

Result: wOBA .315 → .277; ISO .124 → .110; BABIP .343 → .324. 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+Clearwater Threshers · 281 PAwOBA .323 → .268 (−55)K% 22.4% → 33.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.42%	÷0.940	×1.420	—	—	33.87%
BB% (unintentional) /PA	9.96%	÷0.918	×0.750	—	×0.988	8.04%
HBP% /PA	2.49%	—	×0.930	—	×0.988	2.29%
Singles /BIP	24.86%	÷0.965	×0.920	×1.025	×0.988	24.00%
Doubles /BIP	7.73%	÷0.950	×0.960	×1.025	×0.988	7.91%
Triples /BIP	1.66%	÷0.984	×0.810	×1.025	×0.988	1.38%
Home runs /BIP	1.10%	÷1.117	×0.880	—	×0.988	0.86%

Factors used: league row FSL. Park (home-season share, regressed): HR 123, 1B 93, 2B 90, 3B 97, K 88, BB 84 — 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 ×1.025.

Result: wOBA .323 → .268; ISO .107 → .085; BABIP .344 → .334. 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 AAReading Fightin Phils · 241 PAwOBA .445 → .388 (−57)K% 17.8% → 20.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.84%	÷1.060	×1.220	—	—	20.53%
BB% (unintentional) /PA	9.13%	÷1.029	×0.700	—	×1.012	6.29%
HBP% /PA	0.83%	—	×0.850	—	×1.012	0.71%
Singles /BIP	25.15%	÷0.995	×0.970	×0.968	×1.012	24.00%
Doubles /BIP	12.28%	÷0.949	×0.860	×0.968	×1.012	10.90%
Triples /BIP	1.17%	÷1.150	×0.950	×0.968	×1.012	0.95%
Home runs /BIP	6.43%	÷1.021	×0.780	—	×1.012	4.97%

Factors used: league row EL. Park (home-season share, regressed): HR 104, 1B 99, 2B 90, 3B 130, K 112, BB 106 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.968.

Result: wOBA .445 → .388; ISO .271 → .226; BABIP .405 → .371. 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 ALakewood BlueClaws · 314 PAwOBA .345 → .285 (−60)K% 22.6% → 29.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.61%	÷1.020	×1.340	—	—	29.70%
BB% (unintentional) /PA	8.60%	÷0.950	×0.660	—	×0.990	5.91%
HBP% /PA	0.64%	—	×0.770	—	×0.990	0.49%
Singles /BIP	25.47%	÷0.993	×0.920	×1.026	×0.990	23.97%
Doubles /BIP	8.96%	÷0.965	×0.820	×1.026	×0.990	7.73%
Triples /BIP	1.89%	÷1.150	×0.940	×1.026	×0.990	1.57%
Home runs /BIP	2.36%	÷0.911	×0.820	—	×0.990	2.10%

Factors used: league row SAL. Park (home-season share, regressed): HR 82, 1B 99, 2B 93, 3B 130, K 104, BB 90 — applied at half strength. Age: age 23 vs a level average of 22.0 → −1.0% on BB/HBP/hit rates (1.0 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.026.

Result: wOBA .345 → .285; ISO .148 → .122; BABIP .368 → .336. 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 — .