Norichika Aoki

PosRF

B/TL/R

Born1982-01-05

Age (2027)45

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2017

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2015	33	MLBSF	392	.287/.353/.380	5	14	114	1.1
2016	34	AAASEA	108	.323/.381/.406	1	4	91	—	.293/.333/.374
2016	34	MLBSEA	467	.283/.349/.388	4	7	111	0.3
2017	35	MLBNYM	374	.277/.340/.393	5	10	111	0.8
2018	36	No MLB games played
2019	37	No MLB games played
2020	38	No MLB games played
2021	39	No MLB games played
2022	40	No MLB games played
2023	41	No MLB games played
2024	42	No MLB games played
2025	43	No MLB games played
2026	44	No MLB games played

Last 3 seasons WAR 2.2

Contract

No contract data on file.

Skills · percentileStatcast 2015-2017

Speed43

xwOBA32

Avg EV13

Barrel%10

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)
2012	30	MLB	Milwaukee Brewers	—	588	520	150	37	4	10	43	55	13	30	8	288	358	433	790	144	304	9	7	347	123	+16	+3	-4	-6	+13	2.2
2013	31	MLB	Milwaukee Brewers	—	674	597	171	20	3	8	55	40	11	20	12	286	357	370	728	84	295	6	8	327	108	+7	-1	+2	-7	+15	1.6
2014	32	MLB	Kansas City Royals	—	549	491	140	22	6	1	43	49	6	17	8	285	350	360	710	75	314	9	8	319	102	+1	+0	-3	-6	+12	0.5
2015	33	MLB	San Francisco Giants	—	392	355	102	12	3	5	30	25	6	14	5	287	353	380	733	93	298	6	8	332	114	+7	+1	-1	-4	+8	1.1
2016	34	MLB	Seattle Mariners	—	467	417	118	24	4	4	34	45	9	7	9	283	349	388	738	106	309	10	7	329	111	+6	-2	-5	-6	+10	0.3
2016	34	AAA	Tacoma Rainiers	—	108	96	31	5	0	1	8	13	1	4	0	323	381	406	787	83	357	12	7	347	91	—	—	—	—	—	—
2017	35	MLB	New York Mets	—	374	336	93	20	2	5	29	44	3	10	2	277	340	393	733	116	301	12	8	325	111	+5	+1	-3	-4	+8	0.8
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3044	2716	774	135	22	33	234	258	48	98	44	285	352	387	739	102	304	8	8	330	109	+34	+2	-13	-34	+66	5.7
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	30	MLB MLE	Milwaukee Brewers	—	588	521	153	40	4	10	42	55	13	30	8	294	361	443	804	150	304	9	7	351	123	+16	+3	-4	-6	+13	2.2
2013	31	MLB MLE	Milwaukee Brewers	—	674	598	173	21	3	8	54	40	11	20	12	289	359	375	734	85	295	6	8	328	108	+7	-1	+2	-7	+15	1.6
2014	32	MLB MLE	Kansas City Royals	—	549	491	141	22	6	1	43	49	6	17	8	287	352	363	714	75	314	9	8	319	102	+1	+0	-3	-6	+12	0.5
2015	33	MLB MLE	San Francisco Giants	—	392	355	103	12	3	5	30	25	6	14	5	290	355	383	739	93	298	6	8	337	114	+7	+1	-1	-4	+8	1.1
2016	34	MLB MLE	Seattle Mariners	—	467	418	118	24	4	4	34	45	9	7	9	282	349	388	737	105	309	10	7	332	111	+6	-2	-5	-6	+10	0.3
2016	34	AAA MLE	Tacoma Rainiers	—	108	99	29	5	0	1	5	16	1	4	0	293	333	374	707	81	320	15	5	302	91	—	—	—	—	—	—
2017	35	MLB MLE	New York Mets	—	374	337	96	21	2	5	28	44	3	10	2	285	345	404	749	119	301	12	7	332	111	+5	+1	-3	-4	+8	0.8
2012	30	MLB MLE	Milwaukee Brewers	—	588	521	153	40	4	10	42	55	13	30	8	294	361	443	804	150	310	9	7	351	123	+16	+3	-4	-6	+13	2.2
2012	30	MLB RAW	Milwaukee Brewers	—	588	520	150	37	4	10	43	55	13	30	8	288	358	433	790	144	304	9	7	347	123	+16	+3	-4	-6	+13	2.2
2013	31	MLB MLE	Milwaukee Brewers	—	674	598	173	21	3	8	54	40	11	20	12	289	359	375	734	85	298	6	8	328	108	+7	-1	+2	-7	+15	1.6
2013	31	MLB RAW	Milwaukee Brewers	—	674	597	171	20	3	8	55	40	11	20	12	286	357	370	728	84	295	6	8	327	108	+7	-1	+2	-7	+15	1.6
2014	32	MLB MLE	Kansas City Royals	—	549	491	141	22	6	1	43	49	6	17	8	287	352	363	714	75	317	9	8	319	102	+1	+0	-3	-6	+12	0.5
2014	32	MLB RAW	Kansas City Royals	—	549	491	140	22	6	1	43	49	6	17	8	285	350	360	710	75	314	9	8	319	102	+1	+0	-3	-6	+12	0.5
2015	33	MLB MLE	San Francisco Giants	—	392	355	103	12	3	5	30	25	6	14	5	290	355	383	739	93	302	6	8	337	114	+7	+1	-1	-4	+8	1.1
2015	33	MLB RAW	San Francisco Giants	—	392	355	102	12	3	5	30	25	6	14	5	287	353	380	733	93	298	6	8	332	114	+7	+1	-1	-4	+8	1.1
2016	34	MLB MLE	2 teams	—	575	517	148	29	4	5	39	61	10	11	9	286	348	387	735	101	315	11	7	326	107	+5	-1	-5	-6	+12	0.5
2016	34	MLB RAW	2 teams	—	575	513	149	29	4	5	42	58	10	11	9	290	355	392	747	101	318	10	7	333	107	+5	-1	-5	-6	+12	0.5
2017	35	MLB MLE	New York Mets	—	374	337	96	21	2	5	28	44	3	10	2	285	345	404	749	119	311	12	7	332	111	+5	+1	-3	-4	+8	0.8
2017	35	MLB RAW	New York Mets	—	374	336	93	20	2	5	29	44	3	10	2	277	340	393	733	116	301	12	8	325	111	+5	+1	-3	-4	+8	0.8
2012	30	MLB MLE	Milwaukee Brewers	—	588	528	153	40	4	10	42	55	13	30	8	290	361	438	799	148	304	9	7	351	123	—	—	—	—	—	—
2013	31	MLB MLE	Milwaukee Brewers	—	674	604	173	21	3	8	54	40	11	20	12	286	359	371	730	84	295	6	8	328	108	—	—	—	—	—	—
2014	32	MLB MLE	Kansas City Royals	—	549	495	141	22	6	1	43	49	6	17	8	285	352	360	711	75	314	9	8	319	102	—	—	—	—	—	—
2015	33	MLB MLE	San Francisco Giants	—	392	353	103	12	3	5	30	25	6	14	5	292	355	385	741	93	298	6	8	337	114	—	—	—	—	—	—
2016	34	MLB MLE	2 teams	—	575	521	148	29	4	5	39	61	10	11	9	284	348	384	732	100	311	11	7	326	107	—	—	—	—	—	—
2017	35	MLB MLE	New York Mets	—	374	340	96	21	2	5	28	44	3	10	2	282	345	400	745	118	301	12	7	332	111	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3044	2716	774	135	22	33	234	258	48	98	44	285	352	387	739	102	304	8	8	330	111	+34	+2	-13	-34	+66	5.7
/ 162G	—	A+C		—	650	580	166	29	5	7	50	55	10	21	9	286	353	390	742	103	305	8	8	330	111	+7	+0	-3	-7	+14	1.2
Career	—	MLE		—	3152	2819	814	145	22	34	236	274	49	102	44	289	354	392	746	103	309	9	7	332	111	+34	+2	-13	-34	+66	5.7
/ 162G	—	MLE		—	650	581	168	30	5	7	49	57	10	21	9	289	355	394	749	105	309	9	8	332	111	+7	+0	-3	-7	+14	1.2

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.

2016 AAATacoma Rainiers · 108 PAwOBA .344 → .302 (−43)K% 12.0% → 14.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.04%	÷1.041	×1.290	—	—	14.92%
BB% (unintentional) /PA	7.41%	÷1.115	×0.710	—	×0.940	4.43%
HBP% /PA	0.93%	—	×0.980	—	×0.940	0.85%
Singles /BIP	30.12%	÷0.987	×0.900	×1.050	×0.940	27.11%
Doubles /BIP	6.02%	÷0.901	×0.810	×1.050	×0.940	5.34%
Triples /BIP	0.00%	÷1.063	×0.810	×1.050	×0.940	0.00%
Home runs /BIP	1.20%	÷0.896	×0.780	—	×0.940	0.99%

Factors used: league row PCL. Park (home-season share, regressed): HR 79, 1B 97, 2B 80, 3B 113, K 108, BB 123 — applied at half strength. Age: age 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .344 → .302; ISO .083 → .075; BABIP .357 → .320. 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).