Dilson Herrera

Pos2B

B/TR/R

Born1994-03-03

Age (2027)33

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2024

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2021	27	AAA/INTL2 orgs	369	.216/.284/.404	16	2	58	—	.156/.216/.289
2022	28	INTLColombia	36	.194/.286/.258	0	1	55	—
2024	30	INTLVenados de Ma…	82	.261/.370/.348	1	0	109	—

Contract

No contract data on file.

Skills · percentileStatcast 2015-2020

Speed52

Barrel%44

xwOBA18

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)
2011	17	ROK	VSL Pirates	—	260	214	66	19	5	2	32	40	9	16	8	308	420	472	892	164	364	15	12	391	61	—	—	—	—	—	—
2012	18	ROK	GCL Pirates	—	227	199	56	11	4	7	18	41	0	11	4	281	341	482	823	201	325	18	8	346	61	—	—	—	—	—	—
2013	19	A	Savannah Sand Gnats	—	503	442	118	27	3	11	40	116	8	14	6	267	339	416	755	149	332	23	8	330	76	—	—	—	—	—	—
2014	20	MLB	New York Mets	—	66	59	13	0	1	3	7	17	0	0	0	220	303	407	710	186	256	26	11	316	103	+0	+0	-0	+2	+1	0.4
2014	20	AA	Binghamton Mets	—	278	241	82	17	3	10	29	52	2	9	4	340	415	560	976	220	389	19	10	418	147	—	—	—	—	—	—
2014	20	A+	St. Lucie Mets	—	309	283	87	16	2	3	18	44	4	14	3	307	357	410	767	102	353	14	6	341	88	—	—	—	—	—	—
2014	20	INTL	Tigres del Licey	—	29	25	6	2	0	0	3	4	0	0	0	240	321	320	641	80	273	14	10	286	79	—	—	—	—	—	—
2015	21	MLB	New York Mets	—	103	90	19	3	1	3	11	23	2	2	0	211	311	367	677	156	250	22	11	308	94	-1	+0	+2	+2	+2	0.5
2015	21	AAA	Las Vegas 51s	—	364	327	107	23	2	11	28	59	3	13	9	327	385	511	896	183	369	16	8	389	101	—	—	—	—	—	—
2016	22	AAA	Louisville Bats	—	469	423	116	24	4	15	38	87	2	7	9	274	337	456	793	182	312	19	8	347	92	—	—	—	—	—	—
2017	23	AAA	Louisville Bats	—	265	239	63	9	1	7	15	61	3	2	4	264	314	397	711	134	322	23	6	310	62	—	—	—	—	—	—
2018	24	MLB	Cincinnati Reds	—	97	87	16	5	0	5	8	39	2	0	0	184	268	414	682	230	256	40	8	302	85	-2	+0	-1	+2	+2	0.1
2018	24	AAA	Louisville Bats	—	208	185	55	10	0	7	19	50	2	0	1	297	369	465	834	168	372	24	9	368	90	—	—	—	—	—	—
2018	24	A+	Daytona Tortugas	—	92	84	25	3	1	2	7	19	1	1	1	298	359	429	787	131	365	21	8	353	65	—	—	—	—	—	—
2018	24	INTL	Tigres del Licey	—	53	46	9	1	0	1	5	9	2	0	1	196	302	283	584	87	222	17	9	277	73	—	—	—	—	—	—
2019	25	AAA	Syracuse Mets	—	460	407	101	29	1	24	43	127	8	12	5	248	332	501	833	253	298	28	9	363	83	—	—	—	—	—	—
2020	26	INTL	Colombia	—	20	15	2	1	0	0	4	7	1	1	0	133	350	200	550	67	250	35	20	286	80	—	—	—	—	—	—
2021	27	AAA	Buffalo Bisons	—	196	174	37	5	1	10	18	62	2	0	1	213	294	425	719	213	260	32	9	316	36	—	—	—	—	—	—
2021	27	INTL	Colombia	—	173	160	35	8	0	6	10	43	2	2	0	219	273	381	655	162	259	25	6	290	83	—	—	—	—	—	—
2022	28	INTL	Colombia	—	36	31	6	2	0	0	4	7	0	1	0	194	286	258	544	65	250	19	11	249	55	—	—	—	—	—	—
2024	30	INTL	Venados de Mazatlan	—	82	69	18	3	0	1	12	12	0	0	1	261	370	348	718	87	304	15	15	329	109	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	266	236	48	8	2	11	26	79	4	2	0	203	293	394	687	191	253	30	10	308	95	-2	+0	+0	+6	+6	1.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2011	17	ROK MLE	VSL Pirates	—	260	224	44	12	3	1	22	49	9	16	8	196	294	290	584	94	230	19	8	259	61	—	—	—	—	—	—
2012	18	ROK MLE	GCL Pirates	—	227	206	46	8	3	6	11	59	0	11	4	223	263	379	641	155	262	26	5	259	61	—	—	—	—	—	—
2013	19	A MLE	Savannah Sand Gnats	—	503	454	104	22	3	11	28	157	8	14	6	229	286	363	649	134	303	31	6	280	76	—	—	—	—	—	—
2014	20	MLB MLE	New York Mets	—	66	59	13	0	1	3	7	17	0	0	0	220	303	407	710	186	256	26	11	321	103	+0	+0	-0	+2	+1	0.4
2014	20	AA MLE	Binghamton Mets	—	278	249	82	15	3	8	21	63	2	9	4	329	386	510	896	181	387	23	8	385	147	—	—	—	—	—	—
2014	20	A+ MLE	St. Lucie Mets	—	309	288	79	17	1	2	13	64	4	14	3	274	315	361	676	87	338	21	4	299	88	—	—	—	—	—	—
2015	21	MLB MLE	New York Mets	—	103	91	19	3	1	3	10	23	2	2	0	209	301	363	664	154	250	22	10	307	94	-1	+0	+2	+2	+2	0.5
2015	21	AAA MLE	Las Vegas 51s	—	364	334	93	18	2	8	21	78	3	13	9	278	327	416	743	138	328	21	6	317	101	—	—	—	—	—	—
2016	22	AAA MLE	Louisville Bats	—	469	433	108	19	3	15	28	106	2	7	9	249	298	411	709	162	289	23	6	304	92	—	—	—	—	—	—
2017	23	AAA MLE	Louisville Bats	—	265	244	55	7	1	6	11	74	3	2	4	225	267	336	604	111	284	28	4	260	62	—	—	—	—	—	—
2018	24	MLB MLE	Cincinnati Reds	—	97	87	16	5	0	5	8	39	2	0	0	184	268	414	682	230	256	40	8	293	85	-2	+0	-1	+2	+2	0.1
2018	24	AAA MLE	Louisville Bats	—	208	190	48	8	0	6	14	62	2	0	1	253	311	389	700	137	331	30	7	301	90	—	—	—	—	—	—
2018	24	A+ MLE	Daytona Tortugas	—	92	86	20	2	1	2	5	26	1	1	1	233	283	349	631	116	308	28	5	265	65	—	—	—	—	—	—
2019	25	AAA MLE	Syracuse Mets	—	460	420	84	22	1	21	30	150	8	12	5	200	266	407	674	207	248	33	7	291	83	—	—	—	—	—	—
2021	27	AAA MLE	Buffalo Bisons	—	196	180	28	4	1	6	12	77	2	0	1	156	216	289	505	133	213	39	6	221	36	—	—	—	—	—	—
2011	17	ROK MLE	VSL Pirates	—	260	224	44	12	3	1	22	49	9	16	8	196	294	290	584	94	242	19	8	259	61	—	—	—	—	—	—
2011	17	ROK RAW	VSL Pirates	—	260	214	66	19	5	2	32	40	9	16	8	308	420	472	892	164	364	15	12	391	61	—	—	—	—	—	—
2012	18	ROK MLE	GCL Pirates	—	227	206	46	8	3	6	11	59	0	11	4	223	263	379	641	155	284	26	5	259	61	—	—	—	—	—	—
2012	18	ROK RAW	GCL Pirates	—	227	199	56	11	4	7	18	41	0	11	4	281	341	482	823	201	325	18	8	346	61	—	—	—	—	—	—
2013	19	A MLE	Savannah Sand Gnats	—	503	454	104	22	3	11	28	157	8	14	6	229	286	363	649	134	317	31	6	280	76	—	—	—	—	—	—
2013	19	A RAW	Savannah Sand Gnats	—	503	442	118	27	3	11	40	116	8	14	6	267	339	416	755	149	332	23	8	330	76	—	—	—	—	—	—
2014	20	A+ MLE	4 teams	—	682	623	183	34	6	14	42	150	6	23	7	294	344	435	779	141	361	22	6	338	115	—	—	—	—	—	—
2014	20	A+ RAW	4 teams	—	682	608	188	35	6	16	57	117	6	23	7	309	374	465	840	156	355	17	8	368	115	—	—	—	—	—	—
2015	21	AAA MLE	2 teams	—	467	425	112	21	3	11	31	101	5	15	9	264	321	405	726	141	320	22	7	315	99	—	—	—	—	—	—
2015	21	AAA RAW	2 teams	—	467	417	126	26	3	14	39	82	5	15	9	302	369	480	848	177	346	18	8	371	99	—	—	—	—	—	—
2016	22	AAA MLE	Louisville Bats	—	469	433	108	19	3	15	28	106	2	7	9	249	298	411	709	162	295	23	6	304	92	—	—	—	—	—	—
2016	22	AAA RAW	Louisville Bats	—	469	423	116	24	4	15	38	87	2	7	9	274	337	456	793	182	312	19	8	347	92	—	—	—	—	—	—
2017	23	AAA MLE	Louisville Bats	—	265	244	55	7	1	6	11	74	3	2	4	225	267	336	604	111	293	28	4	260	62	—	—	—	—	—	—
2017	23	AAA RAW	Louisville Bats	—	265	239	63	9	1	7	15	61	3	2	4	264	314	397	711	134	322	23	6	310	62	—	—	—	—	—	—
2018	24	AAA MLE	4 teams	—	450	411	94	17	1	14	30	144	7	1	3	229	292	377	670	148	315	32	7	291	83	—	—	—	—	—	—
2018	24	AAA RAW	4 teams	—	450	402	105	19	1	15	39	117	7	1	3	261	337	425	762	164	332	26	9	340	83	—	—	—	—	—	—
2019	25	AAA MLE	Syracuse Mets	—	460	420	84	22	1	21	30	150	8	12	5	200	266	407	674	207	251	33	7	291	83	—	—	—	—	—	—
2019	25	AAA RAW	Syracuse Mets	—	460	407	101	29	1	24	43	127	8	12	5	248	332	501	833	253	298	28	9	363	83	—	—	—	—	—	—
2020	26	INTL MLE	Colombia	—	20	15	2	1	0	0	4	7	1	1	0	133	350	200	550	67	250	35	20	—	—	—	—	—	—	—	—
2020	26	INTL RAW	Colombia	—	20	15	2	1	0	0	4	7	1	1	0	133	350	200	550	67	250	35	20	286	80	—	—	—	—	—	—
2021	27	AAA MLE	2 teams	—	369	339	51	7	1	11	23	145	4	2	1	150	213	274	487	124	215	39	6	221	36	—	—	—	—	—	—
2021	27	AAA RAW	2 teams	—	369	334	72	13	1	16	28	105	4	2	1	216	284	404	688	189	259	28	8	304	36	—	—	—	—	—	—
2022	28	INTL MLE	Colombia	—	36	31	6	2	0	0	4	7	0	1	0	194	286	258	544	65	250	19	11	—	—	—	—	—	—	—	—
2022	28	INTL RAW	Colombia	—	36	31	6	2	0	0	4	7	0	1	0	194	286	258	544	65	250	19	11	249	55	—	—	—	—	—	—
2024	30	INTL MLE	Venados de Mazatlan	—	82	69	18	3	0	1	12	12	0	0	1	261	370	348	718	87	304	15	15	—	—	—	—	—	—	—	—
2024	30	INTL RAW	Venados de Mazatlan	—	82	69	18	3	0	1	12	12	0	0	1	261	370	348	718	87	304	15	15	329	109	—	—	—	—	—	—
2011	17	ROK MLE	VSL Pirates	—	260	227	44	12	3	1	22	49	9	16	8	194	294	286	580	93	230	19	8	259	61	—	—	—	—	—	—
2012	18	ROK MLE	GCL Pirates	—	227	214	46	8	3	6	11	59	0	11	4	215	263	364	627	150	262	26	5	259	61	—	—	—	—	—	—
2013	19	A MLE	Savannah Sand Gnats	—	503	462	104	22	3	11	28	157	8	14	6	225	286	357	643	132	303	31	6	280	76	—	—	—	—	—	—
2014	20	A+ MLE	4 teams	—	682	629	183	34	6	14	42	150	6	23	7	291	344	431	775	140	351	22	6	338	115	—	—	—	—	—	—
2015	21	AAA MLE	2 teams	—	467	428	112	21	3	11	31	101	5	15	9	262	321	402	723	140	311	22	7	315	99	—	—	—	—	—	—
2016	22	AAA MLE	Louisville Bats	—	469	436	108	19	3	15	28	106	2	7	9	248	298	408	706	161	289	23	6	304	92	—	—	—	—	—	—
2017	23	AAA MLE	Louisville Bats	—	265	249	55	7	1	6	11	74	3	2	4	221	267	329	597	108	284	28	4	260	62	—	—	—	—	—	—
2018	24	AAA MLE	4 teams	—	450	410	94	17	1	14	30	144	7	1	3	229	292	378	670	149	307	32	7	291	83	—	—	—	—	—	—
2019	25	AAA MLE	Syracuse Mets	—	460	419	84	22	1	21	30	150	8	12	5	200	266	408	674	208	248	33	7	291	83	—	—	—	—	—	—
2021	27	AAA MLE	2 teams	—	369	339	51	7	1	11	23	145	4	2	1	150	213	274	487	124	213	39	6	221	36	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	266	236	48	8	2	11	26	79	4	2	0	203	293	394	687	191	253	30	10	308	76	-2	+0	+0	+6	+6	1.1
/ 162G	—	A+C		—	650	577	118	20	5	27	64	193	10	5	0	205	295	397	692	192	255	30	10	308	76	-4	+1	+1	+14	+14	2.7
Career	—	MLE		—	4290	3894	907	175	25	111	276	1161	53	105	57	233	293	376	669	143	300	27	6	280	76	-2	+0	+0	+6	+6	1.1
/ 162G	—	MLE		—	650	590	138	27	4	17	42	176	8	16	9	234	294	380	673	146	301	27	6	280	76	-4	+1	+1	+14	+14	2.7

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 AAABuffalo Bisons · 196 PAwOBA .310 → .221 (−90)K% 31.6% → 39.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.63%	÷0.965	×1.200	—	—	39.32%
BB% (unintentional) /PA	9.18%	÷1.024	×0.690	—	×1.003	6.21%
HBP% /PA	1.02%	—	×0.940	—	×1.003	0.96%
Singles /BIP	18.75%	÷1.071	×0.930	×0.979	×1.003	15.99%
Doubles /BIP	4.46%	÷0.962	×0.830	×0.979	×1.003	3.78%
Triples /BIP	0.89%	÷1.150	×0.920	×0.979	×1.003	0.70%
Home runs /BIP	8.93%	÷1.081	×0.700	—	×1.003	5.80%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 116, 1B 114, 2B 92, 3B 130, K 93, BB 105 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.979.

Result: wOBA .310 → .221; ISO .213 → .136; BABIP .260 → .213. 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 AAASyracuse Mets · 460 PAwOBA .354 → .291 (−63)K% 27.6% → 32.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	27.61%	÷1.020	×1.200	—	—	32.49%
BB% (unintentional) /PA	8.91%	÷0.966	×0.690	—	×1.033	6.58%
HBP% /PA	1.74%	—	×0.940	—	×1.033	1.69%
Singles /BIP	16.79%	÷1.042	×0.930	×0.950	×1.033	14.71%
Doubles /BIP	10.36%	÷1.060	×0.830	×0.950	×1.033	7.96%
Triples /BIP	0.36%	÷0.900	×0.970	×0.950	×1.033	0.38%
Home runs /BIP	8.57%	÷0.960	×0.840	—	×1.033	7.75%

Factors used: league row IL. Park (home-season share, regressed): HR 92, 1B 108, 2B 112, 3B 80, K 104, BB 93 — 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 .354 → .291; ISO .253 → .214; BABIP .298 → .248. 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 AAALouisville Bats · 208 PAwOBA .358 → .301 (−57)K% 24.0% → 30.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.04%	÷0.962	×1.200	—	—	29.97%
BB% (unintentional) /PA	8.65%	÷0.967	×0.690	—	×1.048	6.47%
HBP% /PA	0.96%	—	×0.940	—	×1.048	0.95%
Singles /BIP	28.15%	÷1.011	×0.930	×0.950	×1.048	25.77%
Doubles /BIP	7.41%	÷1.018	×0.830	×0.950	×1.048	6.01%
Triples /BIP	0.00%	÷1.001	×0.970	×0.950	×1.048	0.00%
Home runs /BIP	5.19%	÷0.988	×0.840	—	×1.048	4.62%

Factors used: league row IL. Park (home-season share, regressed): HR 98, 1B 102, 2B 104, 3B 100, K 92, BB 93 — 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 ×0.950.

Result: wOBA .358 → .301; ISO .168 → .140; BABIP .372 → .331. 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 A+Daytona Tortugas · 92 PAwOBA .339 → .265 (−74)K% 20.7% → 28.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.65%	÷1.035	×1.420	—	—	28.34%
BB% (unintentional) /PA	6.52%	÷0.994	×0.750	—	×0.988	4.86%
HBP% /PA	1.09%	—	×0.930	—	×0.988	1.00%
Singles /BIP	29.23%	÷1.006	×0.920	×0.950	×0.988	25.09%
Doubles /BIP	4.62%	÷1.088	×0.960	×0.950	×0.988	3.82%
Triples /BIP	1.54%	÷1.047	×0.810	×0.950	×0.988	1.12%
Home runs /BIP	3.08%	÷1.058	×0.880	—	×0.988	2.53%

Factors used: league row FSL. Park (home-season share, regressed): HR 112, 1B 101, 2B 118, 3B 109, K 107, BB 99 — 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 ×0.950.

Result: wOBA .339 → .265; ISO .131 → .098; BABIP .365 → .308. 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 AAALouisville Bats · 265 PAwOBA .305 → .260 (−45)K% 23.0% → 28.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.02%	÷0.985	×1.200	—	—	28.06%
BB% (unintentional) /PA	5.66%	÷1.015	×0.690	—	×1.050	4.04%
HBP% /PA	1.13%	—	×0.940	—	×1.050	1.12%
Singles /BIP	25.84%	÷1.038	×0.930	×0.963	×1.050	23.41%
Doubles /BIP	5.06%	÷1.051	×0.830	×0.963	×1.050	4.04%
Triples /BIP	0.56%	÷1.113	×0.970	×0.963	×1.050	0.50%
Home runs /BIP	3.93%	÷1.042	×0.840	—	×1.050	3.33%

Factors used: league row IL. Park (home-season share, regressed): HR 108, 1B 108, 2B 110, 3B 123, K 97, BB 103 — 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 ×0.963.

Result: wOBA .305 → .260; ISO .134 → .111; BABIP .322 → .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 AAALouisville Bats · 469 PAwOBA .339 → .304 (−36)K% 18.6% → 22.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.55%	÷0.984	×1.200	—	—	22.61%
BB% (unintentional) /PA	8.10%	÷0.978	×0.690	—	×1.050	6.00%
HBP% /PA	0.43%	—	×0.940	—	×1.050	0.42%
Singles /BIP	21.73%	÷0.952	×0.930	×0.954	×1.050	21.27%
Doubles /BIP	7.14%	÷1.053	×0.830	×0.954	×1.050	5.64%
Triples /BIP	1.19%	÷1.150	×0.970	×0.954	×1.050	1.01%
Home runs /BIP	4.46%	÷0.882	×0.840	—	×1.050	4.47%

Factors used: league row IL. Park (home-season share, regressed): HR 76, 1B 90, 2B 111, 3B 130, K 97, 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.954.

Result: wOBA .339 → .304; ISO .182 → .166; BABIP .312 → .289. 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 AAALas Vegas 51s · 364 PAwOBA .382 → .317 (−64)K% 16.2% → 21.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.21%	÷0.977	×1.290	—	—	21.40%
BB% (unintentional) /PA	7.69%	÷1.010	×0.710	—	×1.050	5.68%
HBP% /PA	0.82%	—	×0.980	—	×1.050	0.85%
Singles /BIP	26.49%	÷0.983	×0.900	×0.974	×1.050	24.81%
Doubles /BIP	8.58%	÷1.042	×0.810	×0.974	×1.050	6.82%
Triples /BIP	0.75%	÷1.061	×0.810	×0.974	×1.050	0.58%
Home runs /BIP	4.10%	÷1.099	×0.780	—	×1.050	3.06%

Factors used: league row PCL. Park (home-season share, regressed): HR 120, 1B 97, 2B 108, 3B 112, K 95, BB 102 — 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 ×0.974.

Result: wOBA .382 → .317; ISO .183 → .138; BABIP .369 → .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).

2014 A+St. Lucie Mets · 309 PAwOBA .334 → .299 (−35)K% 14.2% → 20.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.24%	÷0.984	×1.420	—	—	20.55%
BB% (unintentional) /PA	5.83%	÷1.106	×0.750	—	×1.042	4.12%
HBP% /PA	1.29%	—	×0.930	—	×1.042	1.25%
Singles /BIP	27.62%	÷1.018	×0.920	×0.987	×1.042	25.68%
Doubles /BIP	6.69%	÷0.883	×0.960	×0.987	×1.042	7.49%
Triples /BIP	0.84%	÷1.150	×0.810	×0.987	×1.042	0.61%
Home runs /BIP	1.26%	÷1.054	×0.880	—	×1.042	1.09%

Factors used: league row FSL. Park (home-season share, regressed): HR 111, 1B 104, 2B 77, 3B 130, K 97, BB 121 — applied at half strength. Age: age 20 vs a level average of 22.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.987.

Result: wOBA .334 → .299; ISO .102 → .097; BABIP .353 → .338. 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 — .