Munenori Kawasaki

Pos2B

B/TL/R

Born1981-06-03

Age (2027)46

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2016

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2014	33	AAATOR	129	.276/.323/.388	0	1	65	—	.252/.282/.345
2014	33	MLBTOR	274	.258/.328/.296	0	1	76	-0.0
2015	34	AAATOR	227	.245/.333/.286	0	8	51	—	.224/.284/.259
2015	34	MLBTOR	34	.214/.312/.286	0	0	65	0.1
2016	35	AAACHC	378	.255/.357/.312	1	20	57	—	.228/.291/.278
2016	35	MLBCHC	26	.333/.462/.429	0	2	160	0.5
2017	36	No MLB games played
2018	37	No MLB games played
2019	38	No MLB games played
2020	39	No MLB games played
2021	40	No MLB games played
2022	41	No MLB games played
2023	42	No MLB games played
2024	43	No MLB games played
2025	44	No MLB games played
2026	45	No MLB games played

Last 3 seasons WAR 0.5

Contract

No contract data on file.

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	31	MLB	Seattle Mariners	—	115	104	20	1	0	0	8	18	1	2	2	192	257	202	459	10	233	16	7	216	33	-9	-0	+3	+1	+2	-0.3
2013	32	MLB	Toronto Blue Jays	—	289	240	55	6	5	1	32	41	4	7	1	229	330	308	638	79	269	14	11	284	77	-8	+1	+3	+4	+6	0.7
2013	32	AAA	Buffalo Bisons	—	81	60	15	0	0	0	14	12	1	3	0	250	400	250	650		312	15	17	297	68	—	—	—	—	—	—
2014	33	MLB	Toronto Blue Jays	—	274	240	62	7	1	0	22	49	3	1	0	258	328	296	624	37	323	18	8	281	76	-8	+0	-0	+1	+6	-0.0
2014	33	AAA	Buffalo Bisons	—	129	116	32	11	1	0	8	17	0	1	1	276	323	388	711	112	320	13	6	306	65	—	—	—	—	—	—
2015	34	MLB	Toronto Blue Jays	—	34	28	6	2	0	0	4	6	0	0	1	214	312	286	598	71	273	18	12	264	65	-1	-0	+1	+1	+1	0.1
2015	34	AAA	Buffalo Bisons	—	227	196	48	8	0	0	24	32	2	8	4	245	333	286	619	41	291	14	11	285	51	—	—	—	—	—	—
2016	35	MLB	Chicago Cubs	—	26	21	7	2	0	0	4	5	1	2	0	333	462	429	890	95	438	19	15	408	160	+2	+0	+0	+1	+1	0.5
2016	35	AAA	Iowa Cubs	—	378	314	80	11	2	1	49	61	1	20	8	255	357	312	669	57	307	16	13	302	57	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	738	633	150	18	6	1	70	119	9	12	4	237	322	289	611	52	288	16	9	276	73	-24	+1	+8	+9	+16	1.0
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	31	MLB MLE	Seattle Mariners	—	115	104	20	1	0	0	8	18	1	2	2	192	257	202	459	10	233	16	7	217	33	-9	-0	+3	+1	+2	-0.3
2013	32	MLB MLE	Toronto Blue Jays	—	289	240	55	6	5	1	32	41	4	7	1	229	330	308	638	79	269	14	11	282	77	-8	+1	+3	+4	+6	0.7
2013	32	AAA MLE	Buffalo Bisons	—	81	65	17	0	0	0	9	15	1	3	0	262	360	262	622		298	19	11	268	68	—	—	—	—	—	—
2014	33	MLB MLE	Toronto Blue Jays	—	274	240	62	7	1	0	22	49	3	1	0	258	328	296	624	37	323	18	8	280	76	-8	+0	-0	+1	+6	-0.0
2014	33	AAA MLE	Buffalo Bisons	—	129	119	30	9	1	0	5	22	0	1	1	252	282	345	627	92	290	17	4	265	65	—	—	—	—	—	—
2015	34	MLB MLE	Toronto Blue Jays	—	34	28	6	2	0	0	4	6	0	0	1	214	312	286	598	71	273	18	12	264	65	-1	-0	+1	+1	+1	0.1
2015	34	AAA MLE	Buffalo Bisons	—	227	205	46	7	0	0	15	38	2	8	4	224	284	259	542	34	269	17	7	244	51	—	—	—	—	—	—
2016	35	MLB MLE	Chicago Cubs	—	26	21	7	2	0	0	4	5	1	2	0	333	462	429	890	95	438	19	15	405	160	+2	+0	+0	+1	+1	0.5
2016	35	AAA MLE	Iowa Cubs	—	378	334	76	10	2	1	29	76	1	20	8	228	291	278	570	51	270	20	8	253	57	—	—	—	—	—	—
2012	31	MLB MLE	Seattle Mariners	—	115	104	20	1	0	0	8	18	1	2	2	192	257	202	459	10	233	16	7	217	33	-9	-0	+3	+1	+2	-0.3
2012	31	MLB RAW	Seattle Mariners	—	115	104	20	1	0	0	8	18	1	2	2	192	257	202	459	10	233	16	7	216	33	-9	-0	+3	+1	+2	-0.3
2013	32	MLB MLE	2 teams	—	370	305	72	6	5	1	41	56	5	10	1	236	336	298	635	62	283	15	11	279	75	-11	+2	+3	+4	+8	0.6
2013	32	MLB RAW	2 teams	—	370	300	70	6	5	1	46	53	5	10	1	233	345	297	641	63	277	14	12	287	75	-11	+2	+3	+4	+8	0.6
2014	33	MLB MLE	2 teams	—	403	359	92	17	2	0	27	71	3	2	1	256	314	315	628	58	317	18	7	275	72	-13	+0	-0	+1	+9	-0.3
2014	33	MLB RAW	2 teams	—	403	356	94	18	2	0	30	66	3	2	1	264	326	326	652	62	322	16	7	289	72	-13	+0	-0	+1	+9	-0.3
2015	34	AAA MLE	2 teams	—	261	233	52	9	0	0	19	44	2	8	5	223	287	262	549	39	274	17	7	247	53	—	—	—	—	—	—
2015	34	AAA RAW	2 teams	—	261	224	54	10	0	0	28	38	2	8	5	241	331	286	616	45	289	15	11	282	53	—	—	—	—	—	—
2016	35	AAA MLE	2 teams	—	404	355	83	12	2	1	33	81	2	22	8	234	303	287	590	54	295	20	8	263	64	—	—	—	—	—	—
2016	35	AAA RAW	2 teams	—	404	335	87	13	2	1	53	66	2	22	8	260	364	319	684	60	315	16	13	309	64	—	—	—	—	—	—
2012	31	MLB MLE	Seattle Mariners	—	115	105	20	1	0	0	8	18	1	2	2	190	257	200	457	10	233	16	7	217	33	—	—	—	—	—	—
2013	32	MLB MLE	2 teams	—	370	321	72	6	5	1	41	56	5	10	1	224	336	283	620	59	275	15	11	279	75	—	—	—	—	—	—
2014	33	MLB MLE	2 teams	—	403	370	92	17	2	0	27	71	3	2	1	249	314	305	619	57	312	18	7	275	72	—	—	—	—	—	—
2015	34	AAA MLE	2 teams	—	261	238	52	9	0	0	19	44	2	8	5	218	287	256	544	38	269	17	7	247	53	—	—	—	—	—	—
2016	35	AAA MLE	2 teams	—	404	366	83	12	2	1	33	81	2	22	8	227	303	279	581	52	281	20	8	263	64	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	738	633	150	18	6	1	70	119	9	12	4	237	322	289	611	52	288	16	9	276	65	-24	+1	+8	+9	+16	1.0
/ 162G	—	A+C		—	650	558	132	16	5	1	62	105	8	11	4	237	322	289	611	52	287	16	10	276	65	-21	+1	+7	+8	+14	0.9
Career	—	MLE		—	1553	1356	319	45	9	2	128	270	13	44	17	235	307	286	593	51	289	17	8	264	65	-24	+1	+8	+9	+16	1.0
/ 162G	—	MLE		—	650	568	134	19	4	1	54	113	5	18	7	236	308	289	597	53	290	17	8	264	65	-21	+1	+7	+8	+14	0.9

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 AAAIowa Cubs · 378 PAwOBA .295 → .253 (−42)K% 16.1% → 20.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.14%	÷1.037	×1.290	—	—	20.07%
BB% (unintentional) /PA	11.90%	÷1.034	×0.710	—	×0.940	7.68%
HBP% /PA	0.26%	—	×0.980	—	×0.940	0.24%
Singles /BIP	26.09%	÷1.006	×0.900	×1.050	×0.940	23.03%
Doubles /BIP	4.35%	÷0.927	×0.810	×1.050	×0.940	3.75%
Triples /BIP	0.79%	÷0.945	×0.810	×1.050	×0.940	0.67%
Home runs /BIP	0.40%	÷0.890	×0.780	—	×0.940	0.33%

Factors used: league row PCL. Park (home-season share, regressed): HR 78, 1B 101, 2B 85, 3B 89, K 107, BB 107 — applied at half strength. Age: age 35 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (7.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .295 → .253; ISO .057 → .053; BABIP .307 → .270. 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 AAABuffalo Bisons · 227 PAwOBA .279 → .244 (−35)K% 14.1% → 16.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.10%	÷1.008	×1.200	—	—	16.79%
BB% (unintentional) /PA	10.57%	÷1.040	×0.690	—	×0.940	6.59%
HBP% /PA	0.88%	—	×0.940	—	×0.940	0.78%
Singles /BIP	24.39%	÷0.981	×0.930	×1.050	×0.940	22.82%
Doubles /BIP	4.88%	÷0.944	×0.830	×1.050	×0.940	4.24%
Triples /BIP	0.00%	÷0.900	×0.970	×1.050	×0.940	0.00%
Home runs /BIP	0.00%	÷0.966	×0.840	—	×0.940	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 93, 1B 96, 2B 89, 3B 80, K 102, BB 108 — 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 .279 → .244; ISO .041 → .037; BABIP .291 → .269. 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 AAABuffalo Bisons · 129 PAwOBA .300 → .265 (−35)K% 13.2% → 16.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.18%	÷0.942	×1.200	—	—	16.79%
BB% (unintentional) /PA	6.20%	÷1.041	×0.690	—	×0.942	3.87%
HBP% /PA	0.00%	—	×0.940	—	×0.942	0.00%
Singles /BIP	20.20%	÷0.968	×0.930	×1.050	×0.942	19.20%
Doubles /BIP	11.11%	÷0.985	×0.830	×1.050	×0.942	9.26%
Triples /BIP	1.01%	÷1.150	×0.970	×1.050	×0.942	0.84%
Home runs /BIP	0.00%	÷1.006	×0.840	—	×0.942	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 101, 1B 94, 2B 97, 3B 130, K 88, BB 108 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .300 → .265; ISO .112 → .097; BABIP .320 → .290. 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 AAABuffalo Bisons · 81 PAwOBA .291 → .268 (−23)K% 14.8% → 18.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.81%	÷0.987	×1.200	—	—	18.01%
BB% (unintentional) /PA	17.28%	÷1.015	×0.690	—	×0.952	11.19%
HBP% /PA	1.23%	—	×0.940	—	×0.952	1.10%
Singles /BIP	31.25%	÷0.976	×0.930	×1.050	×0.952	29.77%
Doubles /BIP	0.00%	÷1.094	×0.830	×1.050	×0.952	0.00%
Triples /BIP	0.00%	÷0.900	×0.970	×1.050	×0.952	0.00%
Home runs /BIP	0.00%	÷0.853	×0.840	—	×0.952	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 71, 1B 95, 2B 119, 3B 80, K 97, BB 103 — applied at half strength. Age: age 32 vs a level average of 27.2 → −4.8% on BB/HBP/hit rates (4.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.050.

Result: wOBA .291 → .268; ISO .000 → .000; BABIP .312 → .298. 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).