Mike Zunino

PosC

B/TR/R

Born1991-03-25

Age (2027)36

No MLB projection yet. Career stats below are historical.

Overview

MLBLAST SEASON 2023

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2021	30	MLBTB	375	.216/.302/.559	33	0	139	4.6
2022	31	MLBTB	123	.148/.197/.304	5	0	38	-0.3
2023	32	MLBCLE	140	.177/.271/.306	3	0	66	-0.0
2024	33	No MLB games played
2025	34	No MLB games played
2026	35	No MLB games played

Last 3 seasons WAR 4.3

Contract

No contract data on file.

Skills · percentileStatcast 2021-2023

Barrel%90

Avg EV61

xwOBA52

Speed20

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)
2012	21	AA	Jackson Generals	—	57	51	17	4	0	3	5	7	0	0	0	333	393	588	981	255	333	12	9	420	141	—	—	—	—	—	—
2012	21	INTL	Peoria Javelinas	—	86	80	23	4	2	2	5	20	1	1	1	287	337	463	800	175	362	23	6	353	125	—	—	—	—	—	—
2013	22	MLB	Seattle Mariners	—	193	173	37	5	0	5	16	49	3	1	0	214	292	329	621	116	267	25	8	283	79	-5	+0	+7	+8	+4	1.5
2013	22	AAA	Tacoma Rainiers	—	229	203	46	12	3	11	17	66	5	0	0	227	302	478	780	251	269	29	7	335	72	—	—	—	—	—	—
2014	23	MLB	Seattle Mariners	—	476	438	87	20	2	22	17	158	17	0	3	199	256	404	660	205	248	33	4	290	84	-9	-1	+30	+8	+10	3.9
2015	24	MLB	Seattle Mariners	—	386	350	61	11	0	11	21	132	5	0	1	174	231	300	531	126	239	34	5	235	47	-24	-0	+18	+8	+8	1.0
2015	24	AAA	Tacoma Rainiers	—	43	41	13	2	0	3	0	8	2	0	0	317	349	585	934	268	333	19	0	407	107	—	—	—	—	—	—
2016	25	MLB	Seattle Mariners	—	192	164	34	7	0	12	21	65	6	0	0	207	319	470	789	262	250	34	11	347	124	+5	+0	+5	+9	+4	2.5
2016	25	AAA	Tacoma Rainiers	—	327	280	80	15	0	17	35	69	8	0	1	286	381	521	902	236	318	21	11	393	109	—	—	—	—	—	—
2017	26	MLB	Seattle Mariners	—	435	387	97	25	0	25	39	160	8	1	0	251	332	509	841	258	355	37	9	367	138	+20	+0	+18	+9	+9	5.7
2017	26	AAA	Tacoma Rainiers	—	45	41	12	2	0	5	4	5	0	0	0	293	356	707	1.063	415	226	11	9	451	133	—	—	—	—	—	—
2018	27	MLB	Seattle Mariners	—	405	373	75	18	0	20	24	150	6	0	0	201	261	410	671	209	268	37	6	295	88	-6	+0	+15	+7	+9	2.6
2019	28	MLB	Tampa Bay Rays	—	289	266	44	10	1	9	20	98	3	0	0	165	232	312	544	147	220	34	7	246	53	-16	+0	+15	+5	+6	1.1
2020	29	MLB	Tampa Bay Rays	—	84	75	11	4	0	4	6	37	3	0	0	147	238	360	598	213	206	44	7	269	70	-3	+0	-0	+1	+2	0.0
2021	30	MLB	Tampa Bay Rays	—	375	333	72	11	2	33	34	132	7	0	0	216	302	559	861	342	231	35	9	369	139	+17	+0	+13	+7	+8	4.6
2022	31	MLB	Tampa Bay Rays	—	123	115	17	3	0	5	6	46	1	0	0	148	197	304	501	157	185	37	5	222	38	-9	+0	+1	+2	+3	-0.3
2023	32	MLB	Cleveland Guardians	—	140	124	22	7	0	3	15	61	1	0	0	177	271	306	578	129	317	44	11	266	66	-6	+0	-0	+3	+3	-0.0
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	3098	2798	557	121	5	149	219	1088	60	2	4	199	272	406	677	207	259	35	7	299	88	-43	-1	+123	+67	+67	21.7
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2012	21	AA MLE	Jackson Generals	—	57	53	17	3	0	3	3	9	0	0	0	321	357	547	904	226	315	16	5	377	141	—	—	—	—	—	—
2013	22	MLB MLE	Seattle Mariners	—	193	173	37	5	0	5	16	49	3	1	0	214	292	329	621	116	267	25	8	286	79	-5	+0	+7	+8	+4	1.5
2013	22	AAA MLE	Tacoma Rainiers	—	229	209	40	10	3	9	11	83	5	0	0	191	249	397	646	206	241	36	5	275	72	—	—	—	—	—	—
2014	23	MLB MLE	Seattle Mariners	—	476	439	88	20	2	23	16	158	17	0	3	200	256	412	669	212	248	33	3	292	84	-9	-1	+30	+8	+10	3.9
2015	24	MLB MLE	Seattle Mariners	—	386	350	61	11	0	11	21	132	5	0	1	174	231	300	531	126	239	34	5	237	47	-24	-0	+18	+8	+8	1.0
2015	24	AAA MLE	Tacoma Rainiers	—	43	41	11	2	0	2	0	10	2	0	0	268	302	463	766	195	306	23	0	327	107	—	—	—	—	—	—
2016	25	MLB MLE	Seattle Mariners	—	192	164	34	7	0	12	21	65	6	0	0	207	319	470	789	262	250	34	11	351	124	+5	+0	+5	+9	+4	2.5
2016	25	AAA MLE	Tacoma Rainiers	—	327	292	71	13	0	15	23	86	8	0	1	243	316	442	758	199	281	26	7	329	109	—	—	—	—	—	—
2017	26	MLB MLE	Seattle Mariners	—	435	387	98	25	0	26	39	160	8	1	0	253	334	519	853	266	355	37	9	372	138	+20	+0	+18	+9	+9	5.7
2017	26	AAA MLE	Tacoma Rainiers	—	45	42	11	2	0	4	3	6	0	0	0	262	311	595	906	333	199	13	7	365	133	—	—	—	—	—	—
2018	27	MLB MLE	Seattle Mariners	—	405	373	76	18	0	21	24	150	6	0	0	204	263	421	684	217	268	37	6	299	88	-6	+0	+15	+7	+9	2.6
2019	28	MLB MLE	Tampa Bay Rays	—	289	266	44	10	1	9	20	98	3	0	0	165	232	312	544	147	220	34	7	247	53	-16	+0	+15	+5	+6	1.1
2020	29	MLB MLE	Tampa Bay Rays	—	84	75	11	4	0	4	6	37	3	0	0	147	238	360	598	213	206	44	7	272	70	-3	+0	-0	+1	+2	0.0
2021	30	MLB MLE	Tampa Bay Rays	—	375	333	72	11	2	34	34	132	7	0	0	216	302	568	870	351	231	35	9	373	139	+17	+0	+13	+7	+8	4.6
2022	31	MLB MLE	Tampa Bay Rays	—	123	115	17	3	0	5	6	46	1	0	0	148	197	304	501	157	185	37	5	224	38	-9	+0	+1	+2	+3	-0.3
2023	32	MLB MLE	Cleveland Guardians	—	140	124	22	7	0	3	15	61	1	0	0	177	271	306	578	129	317	44	11	265	66	-6	+0	-0	+3	+3	-0.0
2012	21	INTL MLE	2 teams	—	143	134	41	8	0	7	7	22	1	1	1	306	345	522	867	216	321	15	5	377	141	—	—	—	—	—	—
2012	21	INTL RAW	2 teams	—	143	131	40	8	2	5	10	27	1	1	1	305	359	511	871	206	350	19	7	379	141	—	—	—	—	—	—
2013	22	AAA MLE	2 teams	—	422	382	77	15	3	14	27	132	8	1	0	202	269	366	635	165	261	31	6	280	76	—	—	—	—	—	—
2013	22	AAA RAW	2 teams	—	422	376	83	17	3	16	33	115	8	1	0	221	297	410	707	189	268	27	8	311	76	—	—	—	—	—	—
2014	23	MLB MLE	Seattle Mariners	—	476	439	88	20	2	23	16	158	17	0	3	200	256	412	669	212	248	33	3	292	84	-9	-1	+30	+8	+10	3.9
2014	23	MLB RAW	Seattle Mariners	—	476	438	87	20	2	22	17	158	17	0	3	199	256	404	660	205	248	33	4	290	84	-9	-1	+30	+8	+10	3.9
2015	24	MLB MLE	2 teams	—	429	391	72	13	0	13	21	142	7	0	1	184	239	317	556	133	248	33	5	246	53	-24	-0	+18	+8	+9	1.1
2015	24	MLB RAW	2 teams	—	429	391	74	13	0	14	21	140	7	0	1	189	243	330	573	141	251	33	5	252	53	-24	-0	+18	+8	+9	1.1
2016	25	AAA MLE	2 teams	—	519	456	106	20	0	28	44	151	14	0	1	232	319	461	780	228	277	29	8	337	114	—	—	—	—	—	—
2016	25	AAA RAW	2 teams	—	519	444	114	22	0	29	56	134	14	0	1	257	358	502	860	245	297	26	11	376	114	—	—	—	—	—	—
2017	26	MLB MLE	2 teams	—	480	429	109	27	0	30	42	166	8	1	0	254	332	527	859	273	338	35	9	371	137	+21	+0	+18	+9	+10	6.0
2017	26	MLB RAW	2 teams	—	480	428	109	27	0	30	43	165	8	1	0	255	334	528	862	273	338	34	9	375	137	+21	+0	+18	+9	+10	6.0
2018	27	MLB MLE	Seattle Mariners	—	405	373	76	18	0	21	24	150	6	0	0	204	263	421	684	217	270	37	6	299	88	-6	+0	+15	+7	+9	2.6
2018	27	MLB RAW	Seattle Mariners	—	405	373	75	18	0	20	24	150	6	0	0	201	261	410	671	209	268	37	6	295	88	-6	+0	+15	+7	+9	2.6
2019	28	MLB MLE	Tampa Bay Rays	—	289	266	44	10	1	9	20	98	3	0	0	165	232	312	544	147	220	34	7	247	53	-16	+0	+15	+5	+6	1.1
2019	28	MLB RAW	Tampa Bay Rays	—	289	266	44	10	1	9	20	98	3	0	0	165	232	312	544	147	220	34	7	246	53	-16	+0	+15	+5	+6	1.1
2020	29	MLB MLE	Tampa Bay Rays	—	84	75	11	4	0	4	6	37	3	0	0	147	238	360	598	213	206	44	7	272	70	-3	+0	-0	+1	+2	0.0
2020	29	MLB RAW	Tampa Bay Rays	—	84	75	11	4	0	4	6	37	3	0	0	147	238	360	598	213	206	44	7	269	70	-3	+0	-0	+1	+2	0.0
2021	30	MLB MLE	Tampa Bay Rays	—	375	333	72	11	2	34	34	132	7	0	0	216	302	568	870	351	226	35	9	373	139	+17	+0	+13	+7	+8	4.6
2021	30	MLB RAW	Tampa Bay Rays	—	375	333	72	11	2	33	34	132	7	0	0	216	302	559	861	342	231	35	9	369	139	+17	+0	+13	+7	+8	4.6
2022	31	MLB MLE	Tampa Bay Rays	—	123	115	17	3	0	5	6	46	1	0	0	148	197	304	501	157	185	37	5	224	38	-9	+0	+1	+2	+3	-0.3
2022	31	MLB RAW	Tampa Bay Rays	—	123	115	17	3	0	5	6	46	1	0	0	148	197	304	501	157	185	37	5	222	38	-9	+0	+1	+2	+3	-0.3
2023	32	MLB MLE	Cleveland Guardians	—	140	124	22	7	0	3	15	61	1	0	0	177	271	306	578	129	317	44	11	265	66	-6	+0	-0	+3	+3	-0.0
2023	32	MLB RAW	Cleveland Guardians	—	140	124	22	7	0	3	15	61	1	0	0	177	271	306	578	129	317	44	11	266	66	-6	+0	-0	+3	+3	-0.0
2012	21	INTL MLE	2 teams	—	143	134	41	8	0	7	7	22	1	1	1	306	345	522	867	216	315	15	5	377	141	—	—	—	—	—	—
2013	22	AAA MLE	2 teams	—	422	384	77	15	3	14	27	132	8	1	0	201	269	365	633	164	253	31	6	280	76	—	—	—	—	—	—
2014	23	MLB MLE	Seattle Mariners	—	476	440	88	20	2	23	16	158	17	0	3	200	256	411	668	211	248	33	3	292	84	—	—	—	—	—	—
2015	24	MLB MLE	2 teams	—	429	398	72	13	0	13	21	142	7	0	1	181	239	312	550	131	246	33	5	246	53	—	—	—	—	—	—
2016	25	AAA MLE	2 teams	—	519	456	106	20	0	28	44	151	14	0	1	232	319	461	780	228	270	29	8	337	114	—	—	—	—	—	—
2017	26	MLB MLE	2 teams	—	480	427	109	27	0	30	42	166	8	1	0	255	332	529	861	274	340	35	9	371	137	—	—	—	—	—	—
2018	27	MLB MLE	Seattle Mariners	—	405	372	76	18	0	21	24	150	6	0	0	204	263	422	685	218	268	37	6	299	88	—	—	—	—	—	—
2019	28	MLB MLE	Tampa Bay Rays	—	289	264	44	10	1	9	20	98	3	0	0	167	232	314	546	148	220	34	7	247	53	—	—	—	—	—	—
2020	29	MLB MLE	Tampa Bay Rays	—	84	75	11	4	0	4	6	37	3	0	0	147	238	360	598	213	206	44	7	272	70	—	—	—	—	—	—
2021	30	MLB MLE	Tampa Bay Rays	—	375	331	72	11	2	34	34	132	7	0	0	218	302	571	873	353	231	35	9	373	139	—	—	—	—	—	—
2022	31	MLB MLE	Tampa Bay Rays	—	123	115	17	3	0	5	6	46	1	0	0	148	197	304	501	157	185	37	5	224	38	—	—	—	—	—	—
2023	32	MLB MLE	Cleveland Guardians	—	140	123	22	7	0	3	15	61	1	0	0	179	271	309	580	130	317	44	11	265	66	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	3098	2798	557	121	5	149	219	1088	60	2	4	199	272	406	677	207	259	35	7	299	93	-43	-1	+123	+67	+67	21.7
/ 162G	—	A+C		—	650	587	116	25	1	31	46	228	13	0	1	198	271	402	673	204	257	35	7	299	93	-9	-0	+26	+14	+14	4.6
Career	—	MLE		—	3885	3517	735	156	8	191	262	1295	76	3	6	209	278	421	699	212	265	33	7	306	93	-43	-1	+123	+67	+67	21.7
/ 162G	—	MLE		—	650	588	123	26	1	32	44	217	13	1	1	209	279	420	699	211	265	33	7	306	93	-9	-0	+26	+14	+14	4.6

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.

2017 AAATacoma Rainiers · 45 PAwOBA .437 → .365 (−72)K% 11.1% → 13.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.11%	÷1.028	×1.290	—	—	13.94%
BB% (unintentional) /PA	8.89%	÷0.979	×0.710	—	×1.018	6.56%
HBP% /PA	0.00%	—	×0.980	—	×1.018	0.00%
Singles /BIP	13.89%	÷0.978	×0.900	—	×1.018	13.01%
Doubles /BIP	5.56%	÷0.988	×0.810	—	×1.018	4.64%
Triples /BIP	0.00%	÷0.900	×0.810	—	×1.018	0.00%
Home runs /BIP	13.89%	÷0.963	×0.780	—	×1.018	11.45%

Factors used: league row PCL. Park (home-season share, regressed): HR 93, 1B 96, 2B 98, 3B 80, K 106, BB 96 — 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).

Result: wOBA .437 → .365; ISO .415 → .340; BABIP .226 → .199. 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 AAATacoma Rainiers · 327 PAwOBA .387 → .329 (−57)K% 21.1% → 26.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.10%	÷1.041	×1.290	—	—	26.16%
BB% (unintentional) /PA	10.70%	÷1.115	×0.710	—	×1.033	7.04%
HBP% /PA	2.45%	—	×0.980	—	×1.033	2.48%
Singles /BIP	22.75%	÷0.987	×0.900	×0.950	×1.033	20.36%
Doubles /BIP	7.11%	÷0.901	×0.810	×0.950	×1.033	6.27%
Triples /BIP	0.00%	÷1.063	×0.810	×0.950	×1.033	0.00%
Home runs /BIP	8.06%	÷0.896	×0.780	—	×1.033	7.24%

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 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 .387 → .329; ISO .236 → .210; BABIP .318 → .281. 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 AAATacoma Rainiers · 43 PAwOBA .395 → .327 (−68)K% 18.6% → 22.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.60%	÷1.049	×1.290	—	—	22.87%
BB% (unintentional) /PA	0.00%	÷1.046	×0.710	—	×1.048	0.00%
HBP% /PA	4.65%	—	×0.980	—	×1.048	4.78%
Singles /BIP	24.24%	÷0.995	×0.900	—	×1.048	22.98%
Doubles /BIP	6.06%	÷0.910	×0.810	—	×1.048	5.65%
Triples /BIP	0.00%	÷0.900	×0.810	—	×1.048	0.00%
Home runs /BIP	9.09%	÷1.127	×0.780	—	×1.048	6.59%

Factors used: league row PCL. Park (home-season share, regressed): HR 125, 1B 99, 2B 82, 3B 80, K 110, BB 109 — 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).

Result: wOBA .395 → .327; ISO .268 → .193; BABIP .333 → .306. 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 AAATacoma Rainiers · 229 PAwOBA .330 → .275 (−55)K% 28.8% → 36.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	28.82%	÷1.030	×1.290	—	—	36.11%
BB% (unintentional) /PA	6.99%	÷1.049	×0.710	—	×1.050	4.96%
HBP% /PA	2.18%	—	×0.980	—	×1.050	2.25%
Singles /BIP	14.60%	÷0.983	×0.900	×0.969	×1.050	13.59%
Doubles /BIP	8.76%	÷0.957	×0.810	×0.969	×1.050	7.54%
Triples /BIP	2.19%	÷0.900	×0.810	×0.969	×1.050	2.01%
Home runs /BIP	8.03%	÷0.938	×0.780	—	×1.050	7.01%

Factors used: league row PCL. Park (home-season share, regressed): HR 88, 1B 97, 2B 91, 3B 80, K 106, BB 110 — 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 ×0.969.

Result: wOBA .330 → .275; ISO .251 → .208; BABIP .269 → .241. 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 AAJackson Generals · 57 PAwOBA .410 → .377 (−34)K% 12.3% → 15.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.28%	÷0.974	×1.220	—	—	15.38%
BB% (unintentional) /PA	7.02%	÷0.997	×0.680	—	×1.050	5.03%
HBP% /PA	0.00%	—	×0.840	—	×1.050	0.00%
Singles /BIP	22.73%	÷0.943	×0.920	—	×1.050	23.28%
Doubles /BIP	9.09%	÷1.228	×0.910	—	×1.050	7.07%
Triples /BIP	0.00%	÷1.150	×0.880	—	×1.050	0.00%
Home runs /BIP	6.82%	÷0.957	×0.800	—	×1.050	5.99%

Factors used: league row SL. Park (home-season share, regressed): HR 91, 1B 89, 2B 146, 3B 130, K 95, BB 99 — applied at half strength. Age: age 21 vs a level average of 24.8 → +5.0% on BB/HBP/hit rates (3.8 yr younger than average).

Result: wOBA .410 → .377; ISO .255 → .223; BABIP .333 → .315. 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 — .