Nick Franklin

Pos2B

B/TS/R

Born1991-03-02

Age (2027)36

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2022

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2018	27	AAMIL	71	.288/.400/.441	2	4	107	—	.270/.343/.413
2019	28	AAA/A+2 orgs	323	.228/.328/.373	6	5	49	—	.175/.253/.277
2022	31	INTLLeones del Es…	45	.147/.341/.324	1	0	93	—

Contract

No contract data on file.

Skills · percentileStatcast 2016-2018

xwOBA33

Speed27

Barrel%18

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.

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)
2009	18	ROK	AZL Mariners	—	44	43	13	2	0	1	1	6	0	0	0	302	318	419	737	116	333	14	2	327	49	—	—	—	—	—	—
2010	19	A	Clinton LumberKings	—	574	513	144	22	7	23	50	123	7	25	10	281	353	485	838	205	328	21	9	367	81	—	—	—	—	—	—
2011	20	AA	Jackson Generals	—	92	83	27	3	2	2	6	18	0	5	3	325	371	482	853	157	397	20	7	364	112	—	—	—	—	—	—
2011	20	A+	High Desert Mavericks	—	297	258	71	10	5	5	31	56	2	13	1	275	357	411	768	136	333	19	10	339	68	—	—	—	—	—	—
2011	20	INTL	Peoria Javelinas	—	102	89	23	4	1	2	11	26	0	1	0	258	340	393	733	135	333	25	11	324	106	—	—	—	—	—	—
2012	21	AAA	Tacoma Rainiers	—	296	267	65	15	5	7	24	68	2	3	2	243	311	416	726	172	301	23	8	319	63	—	—	—	—	—	—
2012	21	AA	Jackson Generals	—	239	205	66	17	4	4	24	38	1	9	2	322	396	502	898	180	378	16	10	382	120	—	—	—	—	—	—
2012	21	INTL	Peoria Javelinas	—	90	77	26	6	1	2	12	15	0	3	0	338	427	519	946	182	393	17	13	414	166	—	—	—	—	—	—
2013	22	MLB	Seattle Mariners	—	412	369	83	20	1	12	42	113	0	6	1	225	304	382	686	157	290	27	10	308	95	-2	+1	+2	+2	+9	1.2
2013	22	AAA	Tacoma Rainiers	—	177	142	46	9	0	4	30	20	1	7	0	324	445	472	917	148	350	11	17	403	123	—	—	—	—	—	—
2014	23	MLB	Tampa Bay Rays	—	90	81	13	2	1	1	6	32	1	2	0	160	227	247	474	86	240	36	7	215	31	-7	+0	+4	+2	+2	0.0
2014	23	AAA	Durham Bulls	—	446	379	103	18	1	11	57	94	2	11	5	272	370	412	781	140	330	21	13	347	94	—	—	—	—	—	—
2015	24	MLB	Tampa Bay Rays	—	109	101	16	4	1	3	7	37	0	1	0	158	213	307	520	149	213	34	6	230	43	-7	+0	-3	+1	+2	-0.7
2015	24	AAA	Durham Bulls	—	221	192	51	10	1	11	27	48	0	4	3	266	356	500	856	234	296	22	12	373	91	—	—	—	—	—	—
2016	25	MLB	Tampa Bay Rays	—	191	174	47	10	1	6	12	42	3	6	1	270	328	443	771	172	325	22	6	339	113	+3	+1	-5	-5	+4	-0.2
2016	25	AAA	Durham Bulls	—	270	240	61	16	1	5	26	56	0	10	1	254	327	392	719	138	306	21	10	319	62	—	—	—	—	—	—
2017	26	MLB	Los Angeles Angels	—	119	106	19	3	1	2	10	22	3	2	0	179	269	283	552	104	207	18	8	257	61	-6	+0	+1	-1	+3	-0.3
2018	27	AA	Biloxi Shuckers	—	71	59	17	3	0	2	11	7	0	4	1	288	400	441	841	153	294	10	15	374	107	—	—	—	—	—	—
2019	28	AAA	Salt Lake Bees	—	307	260	63	18	2	6	38	59	3	5	3	242	346	396	742	154	285	19	12	329	57	—	—	—	—	—	—
2019	28	A+	Bradenton Marauders	—	16	16	0	0	0	0	0	8	0	0	0							50	0		-114	—	—	—	—	—	—
2022	31	INTL	Leones del Escogido	—	45	34	5	1	1	1	10	12	0	0	0	147	341	324	664	176	182	27	22	306	93	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	921	831	178	39	5	24	77	246	7	17	2	214	286	360	646	146	273	27	8	289	82	-20	+3	-1	-1	+20	0.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2009	18	ROK MLE	AZL Mariners	—	44	43	10	1	0	1	1	9	0	0	0	233	250	326	576	93	272	20	2	241	49	—	—	—	—	—	—
2010	19	A MLE	Clinton LumberKings	—	574	531	121	17	5	20	32	169	7	25	10	228	281	392	672	164	288	29	6	288	81	—	—	—	—	—	—
2011	20	AA MLE	Jackson Generals	—	92	85	28	3	2	2	4	21	0	5	3	329	360	482	842	153	392	23	4	333	112	—	—	—	—	—	—
2011	20	A+ MLE	High Desert Mavericks	—	297	267	60	8	4	4	22	75	2	13	1	225	289	330	618	105	286	25	7	269	68	—	—	—	—	—	—
2012	21	AAA MLE	Tacoma Rainiers	—	296	274	57	13	4	6	17	84	2	3	2	208	259	350	610	142	271	28	6	262	63	—	—	—	—	—	—
2012	21	AA MLE	Jackson Generals	—	239	213	66	14	3	4	16	48	1	9	2	310	361	460	821	150	364	20	7	345	120	—	—	—	—	—	—
2013	22	MLB MLE	Seattle Mariners	—	412	370	83	20	1	12	41	113	0	6	1	224	302	381	683	157	290	27	10	309	95	-2	+1	+2	+2	+9	1.2
2013	22	AAA MLE	Tacoma Rainiers	—	177	152	44	8	0	4	20	25	1	7	0	289	376	421	797	132	313	14	11	350	123	—	—	—	—	—	—
2014	23	MLB MLE	Tampa Bay Rays	—	90	81	13	2	1	1	6	32	1	2	0	160	227	247	474	86	240	36	7	213	31	-7	+0	+4	+2	+2	0.0
2014	23	AAA MLE	Durham Bulls	—	446	395	100	16	1	10	41	105	2	11	5	253	326	375	701	122	306	24	9	307	94	—	—	—	—	—	—
2015	24	MLB MLE	Tampa Bay Rays	—	109	101	16	4	1	3	7	37	0	1	0	158	213	307	520	149	213	34	6	231	43	-7	+0	-3	+1	+2	-0.7
2015	24	AAA MLE	Durham Bulls	—	221	202	46	8	1	10	17	56	0	4	3	228	288	426	713	198	258	25	8	303	91	—	—	—	—	—	—
2016	25	MLB MLE	Tampa Bay Rays	—	191	175	46	10	1	6	11	42	3	6	1	263	317	434	752	171	325	22	6	335	113	+3	+1	-5	-5	+4	-0.2
2016	25	AAA MLE	Durham Bulls	—	270	250	55	13	1	4	16	68	0	10	1	220	267	328	595	108	273	25	6	260	62	—	—	—	—	—	—
2017	26	MLB MLE	Los Angeles Angels	—	119	106	19	3	1	2	10	22	3	2	0	179	269	283	552	104	207	18	8	258	61	-6	+0	+1	-1	+3	-0.3
2018	27	AA MLE	Biloxi Shuckers	—	71	63	17	3	0	2	7	9	0	4	1	270	343	413	756	143	284	13	10	327	107	—	—	—	—	—	—
2019	28	AAA MLE	Salt Lake Bees	—	307	271	50	13	2	4	27	76	3	5	3	185	266	292	557	107	227	25	9	252	57	—	—	—	—	—	—
2019	28	A+ MLE	Bradenton Marauders	—	16	16	0	0	0	0	0	11	0	0	0							69	0		-114	—	—	—	—	—	—
2009	18	ROK MLE	AZL Mariners	—	44	43	10	1	0	1	1	9	0	0	0	233	250	326	576	93	273	20	2	241	49	—	—	—	—	—	—
2009	18	ROK RAW	AZL Mariners	—	44	43	13	2	0	1	1	6	0	0	0	302	318	419	737	116	333	14	2	327	49	—	—	—	—	—	—
2010	19	A MLE	Clinton LumberKings	—	574	531	121	17	5	20	32	169	7	25	10	228	281	392	672	164	294	29	6	288	81	—	—	—	—	—	—
2010	19	A RAW	Clinton LumberKings	—	574	513	144	22	7	23	50	123	7	25	10	281	353	485	838	205	328	21	9	367	81	—	—	—	—	—	—
2011	20	A+ MLE	3 teams	—	491	445	110	13	7	8	33	122	2	19	4	247	302	362	664	115	321	25	7	284	78	—	—	—	—	—	—
2011	20	A+ RAW	3 teams	—	491	430	121	17	8	9	48	100	2	19	4	281	356	421	777	140	346	20	10	340	78	—	—	—	—	—	—
2012	21	AAA MLE	3 teams	—	625	570	143	31	9	11	39	154	3	15	4	251	302	395	697	144	324	25	6	299	89	—	—	—	—	—	—
2012	21	AAA RAW	3 teams	—	625	549	157	38	10	13	60	121	3	15	4	286	359	463	822	177	344	19	10	357	89	—	—	—	—	—	—
2013	22	MLB MLE	2 teams	—	589	522	128	28	1	16	61	138	1	13	1	245	325	395	720	149	302	23	10	322	104	+3	+2	+2	+2	+13	2.2
2013	22	MLB RAW	2 teams	—	589	511	129	29	1	16	72	133	1	13	1	252	346	407	753	155	310	23	12	337	104	+3	+2	+2	+2	+13	2.2
2014	23	AAA MLE	2 teams	—	536	476	112	18	2	11	47	137	3	13	5	235	308	351	659	116	301	26	9	291	83	—	—	—	—	—	—
2014	23	AAA RAW	2 teams	—	536	460	116	20	2	12	63	126	3	13	5	252	346	383	729	130	316	24	12	325	83	—	—	—	—	—	—
2015	24	AAA MLE	2 teams	—	330	303	62	12	2	13	24	93	0	5	3	205	263	386	649	182	246	28	7	279	75	—	—	—	—	—	—
2015	24	AAA RAW	2 teams	—	330	293	67	14	2	14	34	85	0	5	3	229	309	433	742	205	270	26	10	326	75	—	—	—	—	—	—
2016	25	AAA MLE	2 teams	—	461	425	102	23	2	10	27	110	3	16	2	240	290	374	664	134	298	24	6	291	83	—	—	—	—	—	—
2016	25	AAA RAW	2 teams	—	461	414	108	26	2	11	38	98	3	16	2	261	327	413	741	152	314	21	8	327	83	—	—	—	—	—	—
2017	26	MLB MLE	Los Angeles Angels	—	119	106	19	3	1	2	10	22	3	2	0	179	269	283	552	104	207	18	8	258	61	-6	+0	+1	-1	+3	-0.3
2017	26	MLB RAW	Los Angeles Angels	—	119	106	19	3	1	2	10	22	3	2	0	179	269	283	552	104	207	18	8	257	61	-6	+0	+1	-1	+3	-0.3
2018	27	AA MLE	Biloxi Shuckers	—	71	63	17	3	0	2	7	9	0	4	1	270	343	413	756	143	283	13	10	327	107	—	—	—	—	—	—
2018	27	AA RAW	Biloxi Shuckers	—	71	59	17	3	0	2	11	7	0	4	1	288	400	441	841	153	294	10	15	374	107	—	—	—	—	—	—
2019	28	AAA MLE	2 teams	—	323	287	50	13	2	4	27	87	3	5	3	174	252	275	528	101	229	27	8	240	48	—	—	—	—	—	—
2019	28	AAA RAW	2 teams	—	323	276	63	18	2	6	38	67	3	5	3	228	328	373	701	145	274	21	12	313	48	—	—	—	—	—	—
2022	31	INTL MLE	Leones del Escogido	—	45	34	5	1	1	1	10	12	0	0	0	147	341	324	664	176	182	27	22	—	—	—	—	—	—	—	—
2022	31	INTL RAW	Leones del Escogido	—	45	34	5	1	1	1	10	12	0	0	0	147	341	324	664	176	182	27	22	306	93	—	—	—	—	—	—
2009	18	ROK MLE	AZL Mariners	—	44	43	10	1	0	1	1	9	0	0	0	233	250	326	576	93	272	20	2	241	49	—	—	—	—	—	—
2010	19	A MLE	Clinton LumberKings	—	574	530	121	17	5	20	32	169	7	25	10	228	281	392	673	164	288	29	6	288	81	—	—	—	—	—	—
2011	20	A+ MLE	3 teams	—	491	453	110	13	7	8	33	122	2	19	4	243	302	355	657	113	311	25	7	284	78	—	—	—	—	—	—
2012	21	AAA MLE	3 teams	—	625	578	143	31	9	11	39	154	3	15	4	247	302	389	692	142	313	25	6	299	89	—	—	—	—	—	—
2013	22	MLB MLE	2 teams	—	589	522	128	28	1	16	61	138	1	13	1	245	325	395	720	149	297	23	10	322	104	—	—	—	—	—	—
2014	23	AAA MLE	2 teams	—	536	481	112	18	2	11	47	137	3	13	5	233	308	347	655	114	295	26	9	291	83	—	—	—	—	—	—
2015	24	AAA MLE	2 teams	—	330	303	62	12	2	13	24	93	0	5	3	205	263	386	649	182	243	28	7	279	75	—	—	—	—	—	—
2016	25	AAA MLE	2 teams	—	461	428	102	23	2	10	27	110	3	16	2	238	290	371	662	133	295	24	6	291	83	—	—	—	—	—	—
2017	26	MLB MLE	Los Angeles Angels	—	119	105	19	3	1	2	10	22	3	2	0	181	269	286	555	105	207	18	8	258	61	—	—	—	—	—	—
2018	27	AA MLE	Biloxi Shuckers	—	71	64	17	3	0	2	7	9	0	4	1	266	343	406	749	141	284	13	10	327	107	—	—	—	—	—	—
2019	28	AAA MLE	2 teams	—	323	290	50	13	2	4	27	87	3	5	3	172	252	272	525	100	216	27	8	240	48	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	921	831	178	39	5	24	77	246	7	17	2	214	286	360	646	146	273	27	8	289	80	-20	+3	-1	-1	+20	0.1
/ 162G	—	A+C		—	650	586	127	28	4	17	54	174	5	12	1	217	288	365	653	148	277	27	8	289	80	-14	+2	-1	-1	+14	0.0
Career	—	MLE		—	4208	3805	879	163	32	99	318	1062	25	117	33	231	295	369	663	138	292	25	8	286	80	-20	+3	-1	-1	+20	0.1
/ 162G	—	MLE		—	650	588	135	25	5	15	49	164	4	18	5	230	293	366	659	136	290	25	8	286	80	-14	+2	-1	-1	+14	0.0

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.

2019 AAASalt Lake Bees · 307 PAwOBA .326 → .252 (−74)K% 19.2% → 24.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.22%	÷1.009	×1.290	—	—	24.57%
BB% (unintentional) /PA	12.38%	÷0.980	×0.710	—	×0.992	8.90%
HBP% /PA	0.98%	—	×0.980	—	×0.992	0.95%
Singles /BIP	18.41%	÷1.007	×0.900	×0.950	×0.992	15.51%
Doubles /BIP	8.96%	÷1.062	×0.810	×0.950	×0.992	6.44%
Triples /BIP	1.00%	÷0.900	×0.810	×0.950	×0.992	0.84%
Home runs /BIP	2.99%	÷1.059	×0.780	—	×0.992	2.18%

Factors used: league row PCL. Park (home-season share, regressed): HR 112, 1B 101, 2B 112, 3B 80, K 102, BB 96 — 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 .326 → .252; ISO .154 → .114; BABIP .285 → .227. 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 A+Bradenton Marauders · 16 PAwOBA .000 → .000 (0)K% 50.0% → 70.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	50.00%	÷1.005	×1.420	—	—	70.66%
BB% (unintentional) /PA	0.00%	÷0.999	×0.750	—	×0.948	0.00%
HBP% /PA	0.00%	—	×0.930	—	×0.948	0.00%
Singles /BIP	0.00%	÷0.993	×0.920	—	×0.948	0.00%
Doubles /BIP	0.00%	÷1.005	×0.960	—	×0.948	0.00%
Triples /BIP	0.00%	÷0.915	×0.810	—	×0.948	0.00%
Home runs /BIP	0.00%	÷1.069	×0.880	—	×0.948	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 114, 1B 99, 2B 101, 3B 83, K 101, BB 100 — applied at half strength. Age: age 28 vs a level average of 22.8 → −5.2% on BB/HBP/hit rates (5.2 yr older than average).

Result: wOBA .000 → .000; ISO .000 → .000; BABIP .000 → .000. 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 AABiloxi Shuckers · 71 PAwOBA .365 → .327 (−38)K% 9.9% → 12.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	9.86%	÷0.933	×1.220	—	—	12.89%
BB% (unintentional) /PA	14.08%	÷0.964	×0.680	—	×0.978	9.71%
HBP% /PA	0.00%	—	×0.840	—	×0.978	0.00%
Singles /BIP	23.08%	÷0.967	×0.920	×1.038	×0.978	22.29%
Doubles /BIP	5.77%	÷0.918	×0.910	×1.038	×0.978	5.81%
Triples /BIP	0.00%	÷0.900	×0.880	×1.038	×0.978	0.00%
Home runs /BIP	3.85%	÷1.078	×0.800	—	×0.978	2.79%

Factors used: league row SL. Park (home-season share, regressed): HR 116, 1B 93, 2B 84, 3B 80, K 87, BB 93 — applied at half strength. Age: age 27 vs a level average of 24.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.038.

Result: wOBA .365 → .327; ISO .153 → .132; BABIP .294 → .284. 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 AAADurham Bulls · 270 PAwOBA .314 → .260 (−53)K% 20.7% → 25.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.74%	÷0.994	×1.200	—	—	25.05%
BB% (unintentional) /PA	9.26%	÷1.082	×0.690	—	×1.033	6.10%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	21.20%	÷1.010	×0.930	×0.990	×1.033	19.96%
Doubles /BIP	8.70%	÷1.093	×0.830	×0.990	×1.033	6.75%
Triples /BIP	0.54%	÷0.900	×0.970	×0.990	×1.033	0.60%
Home runs /BIP	2.72%	÷1.167	×0.840	—	×1.033	2.02%

Factors used: league row IL. Park (home-season share, regressed): HR 133, 1B 102, 2B 119, 3B 80, K 99, BB 116 — 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 ×0.990.

Result: wOBA .314 → .260; ISO .138 → .109; BABIP .306 → .273. 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 AAADurham Bulls · 221 PAwOBA .366 → .303 (−63)K% 21.7% → 25.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.72%	÷1.025	×1.200	—	—	25.43%
BB% (unintentional) /PA	12.22%	÷1.148	×0.690	—	×1.048	7.69%
HBP% /PA	0.00%	—	×0.940	—	×1.048	0.00%
Singles /BIP	20.14%	÷1.025	×0.930	×0.955	×1.048	18.30%
Doubles /BIP	6.94%	÷1.062	×0.830	×0.955	×1.048	5.43%
Triples /BIP	0.69%	÷0.900	×0.970	×0.955	×1.048	0.75%
Home runs /BIP	7.64%	÷1.039	×0.840	—	×1.048	6.47%

Factors used: league row IL. Park (home-season share, regressed): HR 108, 1B 105, 2B 112, 3B 80, K 105, BB 130 — 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 ×0.955.

Result: wOBA .366 → .303; ISO .234 → .203; BABIP .296 → .258. 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 AAADurham Bulls · 446 PAwOBA .340 → .307 (−33)K% 21.1% → 23.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.08%	÷1.070	×1.200	—	—	23.65%
BB% (unintentional) /PA	12.11%	÷0.950	×0.690	—	×1.050	9.23%
HBP% /PA	0.45%	—	×0.940	—	×1.050	0.44%
Singles /BIP	25.61%	÷1.005	×0.930	×0.981	×1.050	24.42%
Doubles /BIP	6.32%	÷1.023	×0.830	×0.981	×1.050	5.28%
Triples /BIP	0.35%	÷0.900	×0.970	×0.981	×1.050	0.39%
Home runs /BIP	3.86%	÷1.046	×0.840	—	×1.050	3.26%

Factors used: league row IL. Park (home-season share, regressed): HR 109, 1B 101, 2B 105, 3B 80, K 114, BB 90 — 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 ×0.981.

Result: wOBA .340 → .307; ISO .140 → .124; BABIP .330 → .306. 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 AAATacoma Rainiers · 177 PAwOBA .395 → .350 (−44)K% 11.3% → 14.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.30%	÷1.030	×1.290	—	—	14.16%
BB% (unintentional) /PA	15.82%	÷1.049	×0.710	—	×1.050	11.24%
HBP% /PA	0.56%	—	×0.980	—	×1.050	0.58%
Singles /BIP	27.05%	÷0.983	×0.900	×0.950	×1.050	24.69%
Doubles /BIP	7.38%	÷0.957	×0.810	×0.950	×1.050	6.23%
Triples /BIP	0.00%	÷0.900	×0.810	×0.950	×1.050	0.00%
Home runs /BIP	3.28%	÷0.938	×0.780	—	×1.050	2.86%

Factors used: league row PCL. Park (home-season share, regressed): HR 88, 1B 97, 2B 91, 3B 80, K 106, BB 110 — 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 ×0.950.

Result: wOBA .395 → .350; ISO .148 → .137; BABIP .350 → .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).

2012 AAATacoma Rainiers · 296 PAwOBA .312 → .262 (−50)K% 23.0% → 28.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.97%	÷1.042	×1.290	—	—	28.44%
BB% (unintentional) /PA	8.11%	÷1.061	×0.710	—	×1.050	5.70%
HBP% /PA	0.68%	—	×0.980	—	×1.050	0.70%
Singles /BIP	19.10%	÷0.979	×0.900	×0.956	×1.050	17.62%
Doubles /BIP	7.54%	÷0.936	×0.810	×0.956	×1.050	6.55%
Triples /BIP	2.51%	÷0.900	×0.810	×0.956	×1.050	2.27%
Home runs /BIP	3.52%	÷0.963	×0.780	—	×1.050	2.99%

Factors used: league row PCL. Park (home-season share, regressed): HR 93, 1B 96, 2B 87, 3B 80, K 108, BB 112 — applied at half strength. Age: age 21 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (6.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.956.

Result: wOBA .312 → .262; ISO .172 → .145; BABIP .301 → .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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .