Robinson Canó

Pos2B

B/TL/R

Born1982-10-22

Age (2027)44

No MLB projection yet. Career stats below are historical.

Overview

INTL

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2023	40	INTLDominican Rep…	135	.220/.250/.299	1	0	50	—
2024	41	INTLDominican Rep…	64	.241/.302/.345	1	0	82	—
2025	42	INTLEstrellas Ori…	126	.219/.288/.263	1	1	60	—

Contract

No contract data on file.

Skills · percentileStatcast 2019-2022

Avg EV68

xwOBA62

Barrel%40

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.

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	22	MLB	New York Yankees	—	551	522	155	34	4	14	16	68	3	1	3	297	322	458	779	161	318	12	3	337	114	+9	-1	-20	+2	+12	0.3
2005	22	AAA	Columbus Clippers	—	114	108	36	8	3	4	6	13	0	0	0	333	368	574	942	241	352	11	5	409	143	—	—	—	—	—	—
2006	23	MLB	New York Yankees	—	508	482	165	41	1	15	18	54	2	5	2	342	369	525	893	183	359	11	4	388	146	+28	+0	-7	+2	+11	3.5
2007	24	MLB	New York Yankees	—	669	617	189	41	7	19	39	85	8	4	5	306	355	488	843	182	329	13	6	369	132	+26	-1	+10	+2	+14	5.2
2008	25	MLB	New York Yankees	—	634	597	162	35	3	14	26	65	5	2	4	271	307	410	718	139	283	10	4	316	98	-2	-1	-9	+2	+14	0.4
2009	26	MLB	New York Yankees	—	674	637	204	48	2	25	30	63	3	5	7	320	354	520	873	199	324	9	4	381	143	+34	-2	-0	+2	+15	5.0
2010	27	MLB	New York Yankees	—	696	626	200	41	3	29	57	77	8	3	2	319	384	534	917	214	326	11	8	400	144	+37	-0	+2	+2	+15	5.7
2011	28	MLB	New York Yankees	—	681	623	188	46	7	28	38	96	12	8	2	302	354	533	887	231	316	14	6	383	135	+28	+1	-0	+2	+15	4.7
2012	29	MLB	New York Yankees	—	697	627	196	48	1	33	61	96	7	3	2	313	380	550	930	238	326	14	9	406	150	+42	-0	+11	+2	+15	7.2
2013	30	MLB	New York Yankees	—	681	605	190	41	0	27	65	85	6	7	1	314	386	516	902	202	327	12	10	395	139	+32	+1	+4	+2	+15	5.6
2014	31	MLB	Seattle Mariners	—	665	595	187	37	2	14	61	68	6	10	3	314	384	454	837	139	335	10	9	373	127	+21	+1	+3	+2	+14	4.2
2015	32	MLB	Seattle Mariners	—	674	624	179	34	1	21	43	107	3	2	6	287	336	446	781	159	316	16	6	345	119	+15	-2	+1	+2	+15	3.1
2016	33	MLB	Seattle Mariners	—	715	655	195	33	2	39	47	100	8	0	1	298	352	533	885	235	299	14	7	385	144	+38	-0	+9	+3	+15	6.6
2017	34	MLB	Seattle Mariners	—	648	592	166	33	0	23	49	85	4	1	0	280	340	453	792	172	294	13	8	350	120	+15	+0	-1	+2	+14	3.2
2018	35	MLB	Seattle Mariners	—	348	310	94	22	0	10	32	47	4	0	0	303	376	471	847	168	329	14	9	375	140	+16	+0	+1	+1	+8	2.7
2019	36	MLB	New York Mets	—	423	390	100	28	0	13	25	69	5	0	0	256	310	428	738	172	280	16	6	325	109	+4	+0	+2	+2	+9	1.7
2020	37	MLB	New York Mets	—	182	171	54	9	0	10	9	24	1	0	0	316	354	544	897	228	319	13	5	390	154	+12	+0	+2	+1	+4	1.8
2020	37	INTL	Dominican Republic	—	25	19	7	0	0	0	6	1	0	0	0	368	520	368	888		389	4	24	421	171	—	—	—	—	—	—
2021	38	INTL	Dominican Republic	—	74	64	22	2	1	0	9	7	0	0	0	344	425	406	831	62	379	9	12	374	139	—	—	—	—	—	—
2022	39	MLB	Atlanta Braves	—	104	100	15	1	0	1	4	25	0	0	0	150	183	190	373	40	189	24	4	172	3	-12	+0	-2	+1	+2	-1.1
2022	39	AAA	El Paso Chihuahuas	—	104	96	32	5	0	3	7	22	0	0	0	333	379	479	858	146	403	21	7	378	76	—	—	—	—	—	—
2022	39	INTL	Dominican Republic	—	36	35	10	3	0	0	1	0	0	0	0	286	306	371	677	86	286	0	3	302	91	—	—	—	—	—	—
2023	40	INTL	Dominican Republic	—	135	127	28	7	0	1	5	17	0	0	0	220	250	299	549	79	241	13	4	242	50	—	—	—	—	—	—
2024	41	INTL	Dominican Republic	—	64	58	14	3	0	1	4	8	1	0	0	241	302	345	646	103	260	12	6	289	82	—	—	—	—	—	—
2025	42	INTL	Estrellas Orientales	—	126	114	25	2	0	1	8	27	3	1	0	219	288	263	551	44	279	21	6	257	60	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	9550	8773	2639	572	33	335	620	1214	85	51	38	301	353	488	841	187	316	13	6	368	135	+402	-5	+5	+35	+207	65.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	22	MLB MLE	New York Yankees	—	551	523	155	34	4	14	15	68	3	1	3	296	320	457	777	161	318	12	3	336	114	+9	-1	-20	+2	+12	0.3
2005	22	AAA MLE	Columbus Clippers	—	114	112	36	7	3	4	2	16	0	0	0	321	333	545	878	223	350	14	2	380	143	—	—	—	—	—	—
2006	23	MLB MLE	New York Yankees	—	508	485	165	41	1	15	15	54	2	5	2	340	363	522	884	181	359	11	3	384	146	+28	+0	-7	+2	+11	3.5
2007	24	MLB MLE	New York Yankees	—	669	622	189	41	7	19	34	85	8	4	5	304	348	484	832	180	329	13	5	364	132	+26	-1	+10	+2	+14	5.2
2008	25	MLB MLE	New York Yankees	—	634	600	162	35	3	14	23	65	5	2	4	270	303	408	711	138	283	10	4	313	98	-2	-1	-9	+2	+14	0.4
2009	26	MLB MLE	New York Yankees	—	674	639	204	48	2	25	28	63	3	5	7	319	351	518	869	199	324	9	4	379	143	+34	-2	-0	+2	+15	5.0
2010	27	MLB MLE	New York Yankees	—	696	640	199	42	3	27	43	77	8	3	2	311	362	512	874	202	326	11	6	381	144	+37	-0	+2	+2	+15	5.7
2011	28	MLB MLE	New York Yankees	—	681	634	187	47	7	26	27	96	12	8	2	295	336	514	850	219	316	14	4	367	135	+28	+1	-0	+2	+15	4.7
2012	29	MLB MLE	New York Yankees	—	697	637	195	49	1	31	51	96	7	3	2	306	364	532	896	226	326	14	7	391	150	+42	-0	+11	+2	+15	7.2
2013	30	MLB MLE	New York Yankees	—	681	621	189	42	0	25	49	85	6	7	1	304	361	493	854	188	327	12	7	374	139	+32	+1	+4	+2	+15	5.6
2014	31	MLB MLE	Seattle Mariners	—	665	615	189	38	2	14	41	68	6	10	3	307	356	444	800	137	335	10	6	355	127	+21	+1	+3	+2	+14	4.2
2015	32	MLB MLE	Seattle Mariners	—	674	629	182	35	1	22	38	107	3	2	6	289	333	453	786	164	316	16	6	343	119	+15	-2	+1	+2	+15	3.1
2016	33	MLB MLE	Seattle Mariners	—	715	663	198	34	2	40	39	100	8	0	1	299	345	537	882	238	299	14	5	381	144	+38	-0	+9	+3	+15	6.6
2017	34	MLB MLE	Seattle Mariners	—	648	600	169	34	0	24	41	85	4	1	0	282	332	458	790	177	294	13	6	345	120	+15	+0	-1	+2	+14	3.2
2018	35	MLB MLE	Seattle Mariners	—	348	312	94	22	0	10	30	47	4	0	0	301	370	468	838	167	329	14	9	374	140	+16	+0	+1	+1	+8	2.7
2019	36	MLB MLE	New York Mets	—	423	393	104	30	0	13	22	69	5	0	0	265	312	440	752	176	280	16	5	329	109	+4	+0	+2	+2	+9	1.7
2020	37	MLB MLE	New York Mets	—	182	172	56	10	0	10	8	24	1	0	0	326	359	558	917	233	319	13	4	395	154	+12	+0	+2	+1	+4	1.8
2022	39	MLB MLE	Atlanta Braves	—	104	100	15	1	0	1	4	25	0	0	0	150	183	190	373	40	189	24	4	172	3	-12	+0	-2	+1	+2	-1.1
2022	39	AAA MLE	El Paso Chihuahuas	—	104	98	26	4	0	2	5	28	0	0	0	265	301	367	668	102	336	27	5	281	76	—	—	—	—	—	—
2005	22	MLB MLE	2 teams	—	665	635	191	41	7	18	17	84	3	1	3	301	322	472	795	172	323	13	3	344	119	+15	-1	-20	+2	+14	1.1
2005	22	MLB RAW	2 teams	—	665	630	191	42	7	18	22	81	3	1	3	303	330	478	808	175	324	12	3	350	119	+15	-1	-20	+2	+14	1.1
2006	23	MLB MLE	New York Yankees	—	508	485	165	41	1	15	15	54	2	5	2	340	363	522	884	181	356	11	3	384	146	+28	+0	-7	+2	+11	3.5
2006	23	MLB RAW	New York Yankees	—	508	482	165	41	1	15	18	54	2	5	2	342	369	525	893	183	359	11	4	388	146	+28	+0	-7	+2	+11	3.5
2007	24	MLB MLE	New York Yankees	—	669	622	189	41	7	19	34	85	8	4	5	304	348	484	832	180	326	13	5	364	132	+26	-1	+10	+2	+14	5.2
2007	24	MLB RAW	New York Yankees	—	669	617	189	41	7	19	39	85	8	4	5	306	355	488	843	182	329	13	6	369	132	+26	-1	+10	+2	+14	5.2
2008	25	MLB MLE	New York Yankees	—	634	600	162	35	3	14	23	65	5	2	4	270	303	408	711	138	281	10	4	313	98	-2	-1	-9	+2	+14	0.4
2008	25	MLB RAW	New York Yankees	—	634	597	162	35	3	14	26	65	5	2	4	271	307	410	718	139	283	10	4	316	98	-2	-1	-9	+2	+14	0.4
2009	26	MLB MLE	New York Yankees	—	674	639	204	48	2	25	28	63	3	5	7	319	351	518	869	199	323	9	4	379	143	+34	-2	-0	+2	+15	5.0
2009	26	MLB RAW	New York Yankees	—	674	637	204	48	2	25	30	63	3	5	7	320	354	520	873	199	324	9	4	381	143	+34	-2	-0	+2	+15	5.0
2010	27	MLB MLE	New York Yankees	—	696	640	199	42	3	27	43	77	8	3	2	311	362	512	874	202	318	11	6	381	144	+37	-0	+2	+2	+15	5.7
2010	27	MLB RAW	New York Yankees	—	696	626	200	41	3	29	57	77	8	3	2	319	384	534	917	214	326	11	8	400	144	+37	-0	+2	+2	+15	5.7
2011	28	MLB MLE	New York Yankees	—	681	634	187	47	7	26	27	96	12	8	2	295	336	514	850	219	310	14	4	367	135	+28	+1	-0	+2	+15	4.7
2011	28	MLB RAW	New York Yankees	—	681	623	188	46	7	28	38	96	12	8	2	302	354	533	887	231	316	14	6	383	135	+28	+1	-0	+2	+15	4.7
2012	29	MLB MLE	New York Yankees	—	697	637	195	49	1	31	51	96	7	3	2	306	364	532	896	226	320	14	7	391	150	+42	-0	+11	+2	+15	7.2
2012	29	MLB RAW	New York Yankees	—	697	627	196	48	1	33	61	96	7	3	2	313	380	550	930	238	326	14	9	406	150	+42	-0	+11	+2	+15	7.2
2013	30	MLB MLE	New York Yankees	—	681	621	189	42	0	25	49	85	6	7	1	304	361	493	854	188	318	12	7	374	139	+32	+1	+4	+2	+15	5.6
2013	30	MLB RAW	New York Yankees	—	681	605	190	41	0	27	65	85	6	7	1	314	386	516	902	202	327	12	10	395	139	+32	+1	+4	+2	+15	5.6
2014	31	MLB MLE	Seattle Mariners	—	665	615	189	38	2	14	41	68	6	10	3	307	356	444	800	137	326	10	6	355	127	+21	+1	+3	+2	+14	4.2
2014	31	MLB RAW	Seattle Mariners	—	665	595	187	37	2	14	61	68	6	10	3	314	384	454	837	139	335	10	9	373	127	+21	+1	+3	+2	+14	4.2
2015	32	MLB MLE	Seattle Mariners	—	674	629	182	35	1	22	38	107	3	2	6	289	333	453	786	164	317	16	6	343	119	+15	-2	+1	+2	+15	3.1
2015	32	MLB RAW	Seattle Mariners	—	674	624	179	34	1	21	43	107	3	2	6	287	336	446	781	159	316	16	6	345	119	+15	-2	+1	+2	+15	3.1
2016	33	MLB MLE	Seattle Mariners	—	715	663	198	34	2	40	39	100	8	0	1	299	345	537	882	238	299	14	5	381	144	+38	-0	+9	+3	+15	6.6
2016	33	MLB RAW	Seattle Mariners	—	715	655	195	33	2	39	47	100	8	0	1	298	352	533	885	235	299	14	7	385	144	+38	-0	+9	+3	+15	6.6
2017	34	MLB MLE	Seattle Mariners	—	648	600	169	34	0	24	41	85	4	1	0	282	332	458	790	177	294	13	6	345	120	+15	+0	-1	+2	+14	3.2
2017	34	MLB RAW	Seattle Mariners	—	648	592	166	33	0	23	49	85	4	1	0	280	340	453	792	172	294	13	8	350	120	+15	+0	-1	+2	+14	3.2
2018	35	MLB MLE	Seattle Mariners	—	348	312	94	22	0	10	30	47	4	0	0	301	370	468	838	167	327	14	9	374	140	+16	+0	+1	+1	+8	2.7
2018	35	MLB RAW	Seattle Mariners	—	348	310	94	22	0	10	32	47	4	0	0	303	376	471	847	168	329	14	9	375	140	+16	+0	+1	+1	+8	2.7
2019	36	MLB MLE	New York Mets	—	423	393	104	30	0	13	22	69	5	0	0	265	312	440	752	176	290	16	5	329	109	+4	+0	+2	+2	+9	1.7
2019	36	MLB RAW	New York Mets	—	423	390	100	28	0	13	25	69	5	0	0	256	310	428	738	172	280	16	6	325	109	+4	+0	+2	+2	+9	1.7
2020	37	MLB MLE	2 teams	—	207	196	63	11	0	11	9	27	1	0	0	321	354	546	900	224	327	13	4	395	154	+13	+0	+2	+1	+4	2.1
2020	37	MLB RAW	2 teams	—	207	190	61	9	0	10	15	25	1	0	0	321	374	526	900	205	327	12	7	394	154	+13	+0	+2	+1	+4	2.1
2021	38	INTL MLE	Dominican Republic	—	74	64	22	2	1	0	9	7	0	0	0	344	425	406	831	62	379	9	12	—	—	—	—	—	—	—	—
2021	38	INTL RAW	Dominican Republic	—	74	64	22	2	1	0	9	7	0	0	0	344	425	406	831	62	379	9	12	374	139	—	—	—	—	—	—
2022	39	MLB MLE	3 teams	—	244	233	47	5	0	3	10	62	0	0	0	202	235	262	496	60	260	25	4	227	40	-18	+0	-2	+1	+5	-1.4
2022	39	MLB RAW	3 teams	—	244	231	57	9	0	4	12	47	0	0	0	247	284	338	622	91	293	19	5	279	40	-18	+0	-2	+1	+5	-1.4
2023	40	INTL MLE	Dominican Republic	—	135	127	28	7	0	1	5	17	0	0	0	220	250	299	549	79	241	13	4	—	—	—	—	—	—	—	—
2023	40	INTL RAW	Dominican Republic	—	135	127	28	7	0	1	5	17	0	0	0	220	250	299	549	79	241	13	4	242	50	—	—	—	—	—	—
2024	41	INTL MLE	Dominican Republic	—	64	58	14	3	0	1	4	8	1	0	0	241	302	345	646	103	260	12	6	—	—	—	—	—	—	—	—
2024	41	INTL RAW	Dominican Republic	—	64	58	14	3	0	1	4	8	1	0	0	241	302	345	646	103	260	12	6	289	82	—	—	—	—	—	—
2025	42	INTL MLE	Estrellas Orientales	—	126	114	25	2	0	1	8	27	3	1	0	219	288	263	551	44	279	21	6	—	—	—	—	—	—	—	—
2025	42	INTL RAW	Estrellas Orientales	—	126	114	25	2	0	1	8	27	3	1	0	219	288	263	551	44	279	21	6	257	60	—	—	—	—	—	—
2005	22	MLB MLE	2 teams	—	665	640	191	41	7	18	17	84	3	1	3	298	322	469	791	170	324	13	3	344	119	—	—	—	—	—	—
2006	23	MLB MLE	New York Yankees	—	508	486	165	41	1	15	15	54	2	5	2	340	363	521	883	181	359	11	3	384	146	—	—	—	—	—	—
2007	24	MLB MLE	New York Yankees	—	669	622	189	41	7	19	34	85	8	4	5	304	348	484	832	180	329	13	5	364	132	—	—	—	—	—	—
2008	25	MLB MLE	New York Yankees	—	634	601	162	35	3	14	23	65	5	2	4	270	303	408	710	138	283	10	4	313	98	—	—	—	—	—	—
2009	26	MLB MLE	New York Yankees	—	674	638	204	48	2	25	28	63	3	5	7	320	351	519	870	199	324	9	4	379	143	—	—	—	—	—	—
2010	27	MLB MLE	New York Yankees	—	696	640	199	42	3	27	43	77	8	3	2	311	362	512	874	202	326	11	6	381	144	—	—	—	—	—	—
2011	28	MLB MLE	New York Yankees	—	681	637	187	47	7	26	27	96	12	8	2	294	336	512	848	218	316	14	4	367	135	—	—	—	—	—	—
2012	29	MLB MLE	New York Yankees	—	697	634	195	49	1	31	51	96	7	3	2	308	364	535	899	227	326	14	7	391	150	—	—	—	—	—	—
2013	30	MLB MLE	New York Yankees	—	681	621	189	42	0	25	49	85	6	7	1	304	361	493	854	188	327	12	7	374	139	—	—	—	—	—	—
2014	31	MLB MLE	Seattle Mariners	—	665	613	189	38	2	14	41	68	6	10	3	308	356	445	802	137	335	10	6	355	127	—	—	—	—	—	—
2015	32	MLB MLE	Seattle Mariners	—	674	628	182	35	1	22	38	107	3	2	6	290	333	454	787	164	316	16	6	343	119	—	—	—	—	—	—
2016	33	MLB MLE	Seattle Mariners	—	715	662	198	34	2	40	39	100	8	0	1	299	345	538	883	239	299	14	5	381	144	—	—	—	—	—	—
2017	34	MLB MLE	Seattle Mariners	—	648	598	169	34	0	24	41	85	4	1	0	283	332	460	792	177	294	13	6	345	120	—	—	—	—	—	—
2018	35	MLB MLE	Seattle Mariners	—	348	311	94	22	0	10	30	47	4	0	0	302	370	469	839	167	329	14	9	374	140	—	—	—	—	—	—
2019	36	MLB MLE	New York Mets	—	423	393	104	30	0	13	22	69	5	0	0	265	312	440	752	176	280	16	5	329	109	—	—	—	—	—	—
2020	37	MLB MLE	2 teams	—	207	195	63	11	0	11	9	27	1	0	0	323	354	549	903	226	319	13	4	395	154	—	—	—	—	—	—
2022	39	MLB MLE	3 teams	—	244	232	47	5	0	3	10	62	0	0	0	203	235	263	497	60	263	25	4	227	40	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	9550	8773	2639	572	33	335	620	1214	85	51	38	301	353	488	841	187	316	13	6	368	120	+402	-5	+5	+35	+207	65.8
/ 162G	—	A+C		—	650	597	180	39	2	23	42	83	6	3	3	302	353	489	843	188	317	13	6	368	120	+27	-0	+0	+2	+14	4.5
Career	—	MLE		—	10228	9517	2816	609	37	340	543	1329	89	52	38	296	340	475	815	179	313	13	5	346	120	+402	-5	+5	+35	+207	65.8
/ 162G	—	MLE		—	650	605	179	39	2	22	35	84	6	3	2	296	341	476	817	180	312	13	5	346	120	+27	-0	+0	+2	+14	4.5

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.

2022 AAAEl Paso Chihuahuas · 104 PAwOBA .371 → .281 (−90)K% 21.2% → 26.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.15%	÷0.959	×1.200	—	—	26.48%
BB% (unintentional) /PA	6.73%	÷0.990	×0.690	—	×0.940	4.41%
HBP% /PA	0.00%	—	×0.940	—	×0.940	0.00%
Singles /BIP	32.43%	÷1.047	×0.930	×1.050	×0.940	28.44%
Doubles /BIP	6.76%	÷1.133	×0.830	×1.050	×0.940	4.89%
Triples /BIP	0.00%	÷1.002	×0.970	×1.050	×0.940	0.00%
Home runs /BIP	4.05%	÷1.138	×0.700	—	×0.940	2.34%

Factors used: league row International League. Park (home-season share, regressed): HR 128, 1B 109, 2B 127, 3B 100, K 92, BB 98 — applied at half strength. Age: age 40 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (12.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .371 → .281; ISO .146 → .089; BABIP .403 → .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).

2005 AAAColumbus Clippers · 114 PAwOBA .389 → .380 (−9)K% 11.4% → 13.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.40%	÷1.000	×1.200	—	—	13.68%
BB% (unintentional) /PA	2.63%	÷1.000	×0.690	—	×1.050	1.91%
HBP% /PA	0.00%	—	×0.940	—	×1.050	0.00%
Singles /BIP	22.11%	÷1.000	×0.930	×1.050	×1.050	22.67%
Doubles /BIP	8.42%	÷1.000	×0.830	×1.050	×1.050	7.71%
Triples /BIP	3.16%	÷1.000	×0.970	×1.050	×1.050	3.38%
Home runs /BIP	4.21%	÷1.000	×0.840	—	×1.050	3.71%

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 ×1.050.

Result: wOBA .389 → .380; ISO .241 → .228; BABIP .352 → .350. 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 — .