Francisco Cervelli

PosC

B/TR/R

Born1986-03-06

Age (2027)41

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2020

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2018	32	MLBPIT	404	.259/.382/.431	12	2	133	2.9
2019	33	MLBATL	160	.213/.302/.348	3	1	86	0.5
2020	34	MLBMIA	62	.245/.355/.453	3	1	138	0.6
2021	35	No MLB games played
2022	36	No MLB games played
2023	37	No MLB games played
2024	38	No MLB games played
2025	39	No MLB games played
2026	40	No MLB games played

Last 3 seasons WAR 4.0

Contract

No contract data on file.

Skills · percentileStatcast 2018-2020

xwOBA70

Barrel%46

Avg EV40

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. 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)
2005	19	ROK	GCL Yankees	—	70	58	11	2	0	1	8	13	2	1	0	190	309	276	585	86	217	19	11	271	24	—	—	—	—	—	—
2007	21	A+	Tampa Yankees	—	348	290	81	24	2	2	36	59	16	4	3	279	389	397	785	117	342	17	10	354	97	—	—	—	—	—	—
2008	22	AA	Trenton Thunder	—	88	73	23	5	0	0	11	14	4	0	0	315	432	384	815	68	390	16	12	379	124	—	—	—	—	—	—
2009	23	MLB	New York Yankees	—	101	94	28	4	0	1	2	11	0	0	3	298	312	372	685	74	325	11	2	291	83	-2	-1	+4	+4	+2	0.8
2009	23	AAA	Scranton/Wilkes-Barre Yankees	—	75	69	19	5	0	1	3	13	1	0	2	275	315	391	706	116	321	17	4	308	78	—	—	—	—	—	—
2009	23	AA	Trenton Thunder	—	64	58	11	1	0	2	6	13	0	0	0	190	266	310	576	121	209	20	9	264	38	—	—	—	—	—	—
2010	24	MLB	New York Yankees	—	317	266	72	11	3	0	33	42	6	1	1	271	364	335	699	64	316	13	10	312	96	-1	-0	+8	+6	+7	1.9
2011	25	MLB	New York Yankees	—	137	124	33	4	0	4	9	29	2	4	1	266	326	395	721	129	315	21	7	320	100	+0	+0	+6	+3	+3	1.2
2011	25	AAA	Scranton/Wilkes-Barre Yankees	—	15	13	2	0	0	0	1	5	1	0	0	154	267	154	421		250	33	7	216	11	—	—	—	—	—	—
2012	26	AAA	Scranton/Wilkes-Barre Yankees	—	417	354	87	15	2	2	39	82	15	6	0	246	346	316	662	71	308	20	9	303	70	—	—	—	—	—	—
2012	26	INTL	Navegantes del Magallanes	—	75	59	18	5	1	2	10	19	4	1	0	305	438	525	964	220	410	25	13	416	167	—	—	—	—	—	—
2013	27	MLB	New York Yankees	—	61	52	14	3	0	3	8	9	1	0	0	269	377	500	877	231	275	15	13	388	145	+3	+0	+4	+1	+1	1.0
2014	28	MLB	New York Yankees	—	162	146	44	11	1	2	11	41	5	1	0	301	370	432	802	130	408	25	7	360	130	+6	+0	+8	+3	+4	2.1
2014	28	AA	Trenton Thunder	—	20	15	2	0	0	0	4	4	1	0	0	133	350	133	483		182	20	20	267	30	—	—	—	—	—	—
2015	29	MLB	Pittsburgh Pirates	—	510	451	133	17	5	7	46	94	8	1	1	295	370	401	772	106	359	18	9	346	121	+12	-0	+31	+9	+11	6.4
2016	30	MLB	Pittsburgh Pirates	—	393	326	86	14	1	1	56	72	6	6	2	264	381	322	704	58	329	18	14	327	106	+3	+0	+16	+7	+9	3.5
2017	31	MLB	Pittsburgh Pirates	—	304	265	66	13	2	5	32	65	6	0	2	249	343	370	713	121	311	21	11	325	107	+2	-1	-3	+5	+7	1.1
2018	32	MLB	Pittsburgh Pirates	—	404	332	86	15	3	12	51	84	15	2	3	259	382	431	813	172	308	21	13	362	133	+16	-1	-2	+7	+9	2.9
2019	33	MLB	Atlanta Braves	—	160	141	30	8	1	3	13	41	5	1	0	213	302	348	649	135	278	26	8	295	86	-3	+0	+1	+3	+3	0.5
2019	33	AAA	Indianapolis Indians	—	20	16	7	1	0	1	2	5	2	0	0	438	550	688	1.238	250	600	25	10	538	180	—	—	—	—	—	—
2020	34	MLB	Miami Marlins	—	62	53	13	2	0	3	8	14	1	1	0	245	355	453	808	208	278	23	13	361	138	+3	+0	+0	+1	+1	0.6
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	2611	2250	605	102	16	41	269	502	55	17	13	269	361	383	744	114	327	19	10	335	113	+39	-2	+73	+50	+57	22.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	19	ROK MLE	GCL Yankees	—	70	61	9	1	0	1	5	19	2	1	0	148	235	213	448	66	177	27	7	203	24	—	—	—	—	—	—
2007	21	A+ MLE	Tampa Yankees	—	348	298	76	23	2	2	28	84	16	4	3	255	351	366	717	111	331	24	8	311	97	—	—	—	—	—	—
2008	22	AA MLE	Trenton Thunder	—	88	76	24	5	0	0	8	17	4	0	0	316	409	382	791	66	404	19	9	351	124	—	—	—	—	—	—
2009	23	MLB MLE	New York Yankees	—	101	94	28	4	0	1	2	11	0	0	3	298	312	372	685	74	325	11	2	291	83	-2	-1	+4	+4	+2	0.8
2009	23	AAA MLE	Scranton/Wilkes-Barre Yankees	—	75	70	18	4	0	1	2	16	1	0	2	257	288	357	645	100	309	21	3	283	78	—	—	—	—	—	—
2009	23	AA MLE	Trenton Thunder	—	64	60	11	1	0	2	4	16	0	0	0	183	234	300	534	117	214	25	6	225	38	—	—	—	—	—	—
2010	24	MLB MLE	New York Yankees	—	317	267	72	11	3	0	32	42	6	1	1	270	361	333	694	64	316	13	10	310	96	-1	-0	+8	+6	+7	1.9
2011	25	MLB MLE	New York Yankees	—	137	124	33	4	0	4	9	29	2	4	1	266	326	395	721	129	315	21	7	317	100	+0	+0	+6	+3	+3	1.2
2011	25	AAA MLE	Scranton/Wilkes-Barre Yankees	—	15	13	2	0	0	0	1	6	1	0	0	154	267	154	421		246	40	7	184	11	—	—	—	—	—	—
2012	26	AAA MLE	Scranton/Wilkes-Barre Yankees	—	417	367	85	13	2	2	26	100	15	6	0	232	309	294	603	63	295	24	6	271	70	—	—	—	—	—	—
2013	27	MLB MLE	New York Yankees	—	61	52	14	3	0	3	8	9	1	0	0	269	377	500	877	231	275	15	13	382	145	+3	+0	+4	+1	+1	1.0
2014	28	MLB MLE	New York Yankees	—	162	146	44	11	1	2	11	41	5	1	0	301	370	432	802	130	408	25	7	360	130	+6	+0	+8	+3	+4	2.1
2014	28	AA MLE	Trenton Thunder	—	20	16	2	0	0	0	3	5	1	0	0	125	300	125	425		171	25	15	212	30	—	—	—	—	—	—
2015	29	MLB MLE	Pittsburgh Pirates	—	510	452	134	16	5	8	45	94	8	1	1	296	370	407	777	111	359	18	9	346	121	+12	-0	+31	+9	+11	6.4
2016	30	MLB MLE	Pittsburgh Pirates	—	393	327	85	13	1	1	55	72	6	6	2	260	376	315	691	55	329	18	14	325	106	+3	+0	+16	+7	+9	3.5
2017	31	MLB MLE	Pittsburgh Pirates	—	304	265	65	12	2	5	32	65	6	0	2	245	340	362	702	117	311	21	11	326	107	+2	-1	-3	+5	+7	1.1
2018	32	MLB MLE	Pittsburgh Pirates	—	404	333	86	14	3	13	50	84	15	2	3	258	379	435	815	177	308	21	12	364	133	+16	-1	-2	+7	+9	2.9
2019	33	MLB MLE	Atlanta Braves	—	160	141	30	8	1	3	13	41	5	1	0	213	302	348	649	135	278	26	8	295	86	-3	+0	+1	+3	+3	0.5
2019	33	AAA MLE	Indianapolis Indians	—	20	17	6	1	0	1	1	6	2	0	0	353	450	588	1.038	235	505	30	5	434	180	—	—	—	—	—	—
2020	34	MLB MLE	Miami Marlins	—	62	53	13	2	0	3	8	14	1	1	0	245	355	453	808	208	278	23	13	372	138	+3	+0	+0	+1	+1	0.6
2005	19	ROK MLE	GCL Yankees	—	70	61	9	1	0	1	5	19	2	1	0	148	235	213	448	66	186	27	7	203	24	—	—	—	—	—	—
2005	19	ROK RAW	GCL Yankees	—	70	58	11	2	0	1	8	13	2	1	0	190	309	276	585	86	217	19	11	271	24	—	—	—	—	—	—
2007	21	A+ MLE	Tampa Yankees	—	348	298	76	23	2	2	28	84	16	4	3	255	351	366	717	111	346	24	8	311	97	—	—	—	—	—	—
2007	21	A+ RAW	Tampa Yankees	—	348	290	81	24	2	2	36	59	16	4	3	279	389	397	785	117	342	17	10	354	97	—	—	—	—	—	—
2008	22	AA MLE	Trenton Thunder	—	88	76	24	5	0	0	8	17	4	0	0	316	409	382	791	66	407	19	9	351	124	—	—	—	—	—	—
2008	22	AA RAW	Trenton Thunder	—	88	73	23	5	0	0	11	14	4	0	0	315	432	384	815	68	390	16	12	379	124	—	—	—	—	—	—
2009	23	MLB MLE	3 teams	—	240	224	56	9	0	3	8	42	1	0	5	250	279	330	609	80	293	18	3	271	70	-9	-2	+4	+4	+5	0.3
2009	23	MLB RAW	3 teams	—	240	221	58	10	0	4	11	37	1	0	5	262	300	362	662	100	297	15	5	289	70	-9	-2	+4	+4	+5	0.3
2010	24	MLB MLE	New York Yankees	—	317	267	72	11	3	0	32	42	6	1	1	270	361	333	694	64	314	13	10	310	96	-1	-0	+8	+6	+7	1.9
2010	24	MLB RAW	New York Yankees	—	317	266	72	11	3	0	33	42	6	1	1	271	364	335	699	64	316	13	10	312	96	-1	-0	+8	+6	+7	1.9
2011	25	MLB MLE	2 teams	—	152	137	35	4	0	4	10	35	3	4	1	255	320	372	692	117	313	23	7	303	92	-2	+0	+6	+3	+3	1.1
2011	25	MLB RAW	2 teams	—	152	137	35	4	0	4	10	34	3	4	1	255	320	372	692	117	310	22	7	310	92	-2	+0	+6	+3	+3	1.1
2012	26	AAA MLE	2 teams	—	492	431	100	15	3	2	31	118	19	7	0	232	312	295	607	63	308	24	6	271	70	—	—	—	—	—	—
2012	26	AAA RAW	2 teams	—	492	413	105	20	3	4	49	101	19	7	0	254	360	346	706	92	321	21	10	320	70	—	—	—	—	—	—
2013	27	MLB MLE	New York Yankees	—	61	52	14	3	0	3	8	9	1	0	0	269	377	500	877	231	275	15	13	382	145	+3	+0	+4	+1	+1	1.0
2013	27	MLB RAW	New York Yankees	—	61	52	14	3	0	3	8	9	1	0	0	269	377	500	877	231	275	15	13	388	145	+3	+0	+4	+1	+1	1.0
2014	28	MLB MLE	2 teams	—	182	162	46	11	1	2	14	46	6	1	0	284	363	401	764	117	386	25	8	344	119	+4	+0	+8	+3	+4	2.0
2014	28	MLB RAW	2 teams	—	182	161	46	11	1	2	15	45	6	1	0	286	368	404	772	118	386	25	8	350	119	+4	+0	+8	+3	+4	2.0
2015	29	MLB MLE	Pittsburgh Pirates	—	510	452	134	16	5	8	45	94	8	1	1	296	370	407	777	111	359	18	9	346	121	+12	-0	+31	+9	+11	6.4
2015	29	MLB RAW	Pittsburgh Pirates	—	510	451	133	17	5	7	46	94	8	1	1	295	370	401	772	106	359	18	9	346	121	+12	-0	+31	+9	+11	6.4
2016	30	MLB MLE	Pittsburgh Pirates	—	393	327	85	13	1	1	55	72	6	6	2	260	376	315	691	55	324	18	14	325	106	+3	+0	+16	+7	+9	3.5
2016	30	MLB RAW	Pittsburgh Pirates	—	393	326	86	14	1	1	56	72	6	6	2	264	381	322	704	58	329	18	14	327	106	+3	+0	+16	+7	+9	3.5
2017	31	MLB MLE	Pittsburgh Pirates	—	304	265	65	12	2	5	32	65	6	0	2	245	340	362	702	117	306	21	11	326	107	+2	-1	-3	+5	+7	1.1
2017	31	MLB RAW	Pittsburgh Pirates	—	304	265	66	13	2	5	32	65	6	0	2	249	343	370	713	121	311	21	11	325	107	+2	-1	-3	+5	+7	1.1
2018	32	MLB MLE	Pittsburgh Pirates	—	404	333	86	14	3	13	50	84	15	2	3	258	379	435	815	177	304	21	12	364	133	+16	-1	-2	+7	+9	2.9
2018	32	MLB RAW	Pittsburgh Pirates	—	404	332	86	15	3	12	51	84	15	2	3	259	382	431	813	172	308	21	13	362	133	+16	-1	-2	+7	+9	2.9
2019	33	MLB MLE	2 teams	—	180	158	36	9	1	4	14	47	7	1	0	228	318	373	692	146	299	26	8	310	96	-1	+0	+1	+3	+4	0.7
2019	33	MLB RAW	2 teams	—	180	157	37	9	1	4	15	46	7	1	0	236	330	382	712	146	308	26	8	322	96	-1	+0	+1	+3	+4	0.7
2020	34	MLB MLE	Miami Marlins	—	62	53	13	2	0	3	8	14	1	1	0	245	355	453	808	208	278	23	13	372	138	+3	+0	+0	+1	+1	0.6
2020	34	MLB RAW	Miami Marlins	—	62	53	13	2	0	3	8	14	1	1	0	245	355	453	808	208	278	23	13	361	138	+3	+0	+0	+1	+1	0.6
2005	19	ROK MLE	GCL Yankees	—	70	63	9	1	0	1	5	19	2	1	0	143	235	206	442	63	177	27	7	203	24	—	—	—	—	—	—
2007	21	A+ MLE	Tampa Yankees	—	348	301	76	23	2	2	28	84	16	4	3	252	351	362	713	110	331	24	8	311	97	—	—	—	—	—	—
2008	22	AA MLE	Trenton Thunder	—	88	76	24	5	0	0	8	17	4	0	0	316	409	382	791	66	404	19	9	351	124	—	—	—	—	—	—
2009	23	MLB MLE	3 teams	—	240	229	56	9	0	3	8	42	1	0	5	245	279	323	602	79	291	18	3	271	70	—	—	—	—	—	—
2010	24	MLB MLE	New York Yankees	—	317	276	72	11	3	0	32	42	6	1	1	261	361	322	683	62	316	13	10	310	96	—	—	—	—	—	—
2011	25	MLB MLE	2 teams	—	152	138	35	4	0	4	10	35	3	4	1	254	320	370	690	116	308	23	7	303	92	—	—	—	—	—	—
2012	26	AAA MLE	2 teams	—	492	439	100	15	3	2	31	118	19	7	0	228	312	289	601	62	295	24	6	271	70	—	—	—	—	—	—
2013	27	MLB MLE	New York Yankees	—	61	52	14	3	0	3	8	9	1	0	0	269	377	500	877	231	275	15	13	382	145	—	—	—	—	—	—
2014	28	MLB MLE	2 teams	—	182	160	46	11	1	2	14	46	6	1	0	287	363	406	769	119	382	25	8	344	119	—	—	—	—	—	—
2015	29	MLB MLE	Pittsburgh Pirates	—	510	452	134	16	5	8	45	94	8	1	1	296	370	407	777	111	359	18	9	346	121	—	—	—	—	—	—
2016	30	MLB MLE	Pittsburgh Pirates	—	393	329	85	13	1	1	55	72	6	6	2	258	376	313	689	55	329	18	14	325	106	—	—	—	—	—	—
2017	31	MLB MLE	Pittsburgh Pirates	—	304	263	65	12	2	5	32	65	6	0	2	247	340	365	705	118	311	21	11	326	107	—	—	—	—	—	—
2018	32	MLB MLE	Pittsburgh Pirates	—	404	336	86	14	3	13	50	84	15	2	3	256	379	432	811	176	308	21	12	364	133	—	—	—	—	—	—
2019	33	MLB MLE	2 teams	—	180	157	36	9	1	4	14	47	7	1	0	229	318	376	694	146	304	26	8	310	96	—	—	—	—	—	—
2020	34	MLB MLE	Miami Marlins	—	62	53	13	2	0	3	8	14	1	1	0	245	355	453	808	208	278	23	13	372	138	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2611	2250	605	102	16	41	269	502	55	17	13	269	361	383	744	114	327	19	10	335	102	+39	-2	+73	+50	+57	22.1
/ 162G	—	A+C		—	650	560	150	25	4	10	67	125	14	4	3	268	360	380	741	112	326	19	10	335	102	+10	-0	+18	+12	+14	5.5
Career	—	MLE		—	3803	3296	851	148	21	51	348	788	101	29	18	258	347	362	709	104	322	21	9	319	102	+39	-2	+73	+50	+57	22.1
/ 162G	—	MLE		—	650	563	146	25	4	9	59	135	17	5	3	259	347	366	713	107	323	21	9	319	102	+10	-0	+18	+12	+14	5.5

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.

2019 AAAIndianapolis Indians · 20 PAwOBA .524 → .434 (−90)K% 25.0% → 29.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷1.013	×1.200	—	—	29.62%
BB% (unintentional) /PA	10.00%	÷1.010	×0.690	—	×0.942	6.43%
HBP% /PA	10.00%	—	×0.940	—	×0.942	8.85%
Singles /BIP	45.45%	÷1.026	×0.930	—	×0.942	38.83%
Doubles /BIP	9.09%	÷0.901	×0.830	—	×0.942	7.89%
Triples /BIP	0.00%	÷1.150	×0.970	—	×0.942	0.00%
Home runs /BIP	9.09%	÷0.953	×0.840	—	×0.942	7.55%

Factors used: league row IL. Park (home-season share, regressed): HR 91, 1B 105, 2B 80, 3B 130, K 103, BB 102 — 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).

Result: wOBA .524 → .434; ISO .250 → .210; BABIP .600 → .505. 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 AATrenton Thunder · 20 PAwOBA .262 → .212 (−50)K% 20.0% → 24.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷0.994	×1.220	—	—	24.54%
BB% (unintentional) /PA	20.00%	÷0.977	×0.700	—	×0.968	13.87%
HBP% /PA	5.00%	—	×0.850	—	×0.968	4.11%
Singles /BIP	18.18%	÷1.000	×0.970	—	×0.968	17.08%
Doubles /BIP	0.00%	÷0.972	×0.860	—	×0.968	0.00%
Triples /BIP	0.00%	÷1.150	×0.950	—	×0.968	0.00%
Home runs /BIP	0.00%	÷0.910	×0.780	—	×0.968	0.00%

Factors used: league row EL. Park (home-season share, regressed): HR 82, 1B 100, 2B 94, 3B 130, K 99, BB 95 — applied at half strength. Age: age 28 vs a level average of 24.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average).

Result: wOBA .262 → .212; ISO .000 → .000; BABIP .182 → .171. 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 AAAScranton/Wilkes-Barre Yankees · 417 PAwOBA .299 → .271 (−28)K% 19.7% → 23.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.66%	÷0.988	×1.200	—	—	23.87%
BB% (unintentional) /PA	9.11%	÷1.012	×0.690	—	×1.018	6.32%
HBP% /PA	3.60%	—	×0.940	—	×1.018	3.44%
Singles /BIP	25.00%	÷1.006	×0.930	×1.044	×1.018	24.57%
Doubles /BIP	5.51%	÷1.076	×0.830	×1.044	×1.018	4.52%
Triples /BIP	0.74%	÷0.926	×0.970	×1.044	×1.018	0.82%
Home runs /BIP	0.74%	÷0.945	×0.840	—	×1.018	0.67%

Factors used: league row IL. Park (home-season share, regressed): HR 89, 1B 101, 2B 115, 3B 85, K 98, 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 ×1.044.

Result: wOBA .299 → .271; ISO .071 → .064; BABIP .308 → .295. 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).

2011 AAAScranton/Wilkes-Barre Yankees · 15 PAwOBA .211 → .184 (−27)K% 33.3% → 40.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	33.33%	÷0.990	×1.200	—	—	40.40%
BB% (unintentional) /PA	6.67%	÷1.005	×0.690	—	×1.033	4.73%
HBP% /PA	6.67%	—	×0.940	—	×1.033	6.47%
Singles /BIP	25.00%	÷0.976	×0.930	—	×1.033	24.61%
Doubles /BIP	0.00%	÷0.931	×0.830	—	×1.033	0.00%
Triples /BIP	0.00%	÷1.113	×0.970	—	×1.033	0.00%
Home runs /BIP	0.00%	÷0.965	×0.840	—	×1.033	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 93, 1B 95, 2B 86, 3B 123, K 98, BB 101 — 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).

Result: wOBA .211 → .184; ISO .000 → .000; BABIP .250 → .246. 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).

2009 AAAScranton/Wilkes-Barre Yankees · 75 PAwOBA .304 → .283 (−21)K% 17.3% → 20.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.33%	÷1.000	×1.200	—	—	20.80%
BB% (unintentional) /PA	4.00%	÷1.000	×0.690	—	×1.050	2.90%
HBP% /PA	1.33%	—	×0.940	—	×1.050	1.32%
Singles /BIP	23.21%	÷1.000	×0.930	×1.016	×1.050	23.03%
Doubles /BIP	8.93%	÷1.000	×0.830	×1.016	×1.050	7.91%
Triples /BIP	0.00%	÷1.000	×0.970	×1.016	×1.050	0.00%
Home runs /BIP	1.79%	÷1.000	×0.840	—	×1.050	1.57%

Factors used: league row IL. 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 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 ×1.016.

Result: wOBA .304 → .283; ISO .116 → .103; BABIP .321 → .309. 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).

2009 AATrenton Thunder · 64 PAwOBA .257 → .225 (−32)K% 20.3% → 24.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.31%	÷1.000	×1.220	—	—	24.78%
BB% (unintentional) /PA	9.38%	÷1.000	×0.700	—	×1.027	6.74%
HBP% /PA	0.00%	—	×0.850	—	×1.027	0.00%
Singles /BIP	17.78%	÷1.000	×0.970	×1.050	×1.027	18.60%
Doubles /BIP	2.22%	÷1.000	×0.860	×1.050	×1.027	2.06%
Triples /BIP	0.00%	÷1.000	×0.950	×1.050	×1.027	0.00%
Home runs /BIP	4.44%	÷1.000	×0.780	—	×1.027	3.56%

Factors used: league row EL. 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 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 .257 → .225; ISO .121 → .096; BABIP .209 → .214. 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).

2008 AATrenton Thunder · 88 PAwOBA .370 → .351 (−19)K% 15.9% → 19.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.91%	÷1.000	×1.220	—	—	19.41%
BB% (unintentional) /PA	12.50%	÷1.000	×0.700	—	×1.042	9.12%
HBP% /PA	4.55%	—	×0.850	—	×1.042	4.03%
Singles /BIP	30.51%	÷1.000	×0.970	×1.050	×1.042	32.38%
Doubles /BIP	8.47%	÷1.000	×0.860	×1.050	×1.042	7.97%
Triples /BIP	0.00%	÷1.000	×0.950	×1.050	×1.042	0.00%
Home runs /BIP	0.00%	÷1.000	×0.780	—	×1.042	0.00%

Factors used: league row EL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 22 vs a level average of 24.8 → +4.2% on BB/HBP/hit rates (2.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .370 → .351; ISO .068 → .065; BABIP .390 → .404. 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).

2007 A+Tampa Yankees · 348 PAwOBA .347 → .311 (−36)K% 17.0% → 24.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.95%	÷1.000	×1.420	—	—	24.07%
BB% (unintentional) /PA	10.34%	÷1.000	×0.750	—	×1.027	7.97%
HBP% /PA	4.60%	—	×0.930	—	×1.027	4.39%
Singles /BIP	22.94%	÷1.000	×0.920	×1.016	×1.027	22.02%
Doubles /BIP	10.39%	÷1.000	×0.960	×1.016	×1.027	10.40%
Triples /BIP	0.87%	÷1.000	×0.810	×1.016	×1.027	0.73%
Home runs /BIP	0.87%	÷1.000	×0.880	—	×1.027	0.78%

Factors used: league row FSL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 21 vs a level average of 22.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.016.

Result: wOBA .347 → .311; ISO .117 → .108; BABIP .342 → .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).

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