Shawn Zarraga

PosC

B/TS/R

Born1989-01-21

Age (2027)38

No MLB projection yet. Career stats below are historical.

Overview

AALAST SEASON 2017

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	wRC+	WAR	MLE AVG/OBP/SLG
2015	26	AAA/AA2 orgs	205	.286/.350/.362	1	75	—	.262/.305/.324
2016	27	AAA/AA2 orgs	152	.256/.336/.323	0	58	—	.226/.282/.285
2017	28	AALAD	20	.278/.350/.611	1	88	—	.211/.250/.474

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. 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)
2008	19	ROK	AZL Brewers	—	139	110	33	9	0	2	23	24	4	3	0	300	438	436	874	136	360	17	17	393	88	—	—	—	—	—	—
2009	20	A	Wisconsin Timber Rattlers	—	59	46	7	1	0	0	10	14	0	0	0	152	304	174	477	22	200	24	17	232	21	—	—	—	—	—	—
2009	20	ROK	Helena Brewers	—	111	94	25	1	1	0	11	20	4	1	1	266	367	298	665	32	333	18	10	309	45	—	—	—	—	—	—
2010	21	A+	Brevard County Manatees	—	292	249	70	13	0	3	31	61	10	4	0	281	383	369	752	88	358	21	11	345	88	—	—	—	—	—	—
2011	22	A+	Brevard County Manatees	—	262	235	64	9	1	4	16	31	3	9	2	272	327	370	697	98	299	12	6	306	79	—	—	—	—	—	—
2012	23	A+	Brevard County Manatees	—	112	96	28	6	1	2	9	6	6	2	1	292	387	438	825	146	292	5	8	369	113	—	—	—	—	—	—
2013	24	AA	Huntsville Stars	—	190	168	49	9	0	1	14	30	3	0	1	292	357	363	720	71	348	16	7	321	77	—	—	—	—	—	—
2014	25	AAA	Nashville Sounds	—	57	47	10	2	0	0	5	7	2	0	0	213	315	255	570	43	238	12	9	259	47	—	—	—	—	—	—
2014	25	AA	Huntsville Stars	—	267	215	71	16	0	1	42	23	4	1	4	330	448	419	867	88	357	9	16	389	130	—	—	—	—	—	—
2014	25	INTL	Glendale Desert Dogs	—	36	31	11	0	0	0	5	5	0	0	0	355	444	355	799		423	14	14	373	139	—	—	—	—	—	—
2015	26	AAA	Oklahoma City Dodgers	—	72	66	20	5	0	1	4	11	0	0	0	303	343	424	767	121	345	15	6	333	81	—	—	—	—	—	—
2015	26	AA	Tulsa Drillers	—	133	119	33	6	0	0	14	19	0	0	1	277	353	328	681	50	330	14	11	315	72	—	—	—	—	—	—
2016	27	AAA	Oklahoma City Dodgers	—	53	48	8	2	0	0	4	10	0	0	0	167	231	208	439	42	205	19	8	204	-8	—	—	—	—	—	—
2016	27	AA	Tulsa Drillers	—	99	85	26	7	0	0	12	13	0	0	1	306	392	388	780	82	351	13	12	349	94	—	—	—	—	—	—
2017	28	AA	Tulsa Drillers	—	20	18	5	3	0	1	2	2	0	0	0	278	350	611	961	333	267	10	10	412	88	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2008	19	ROK MLE	AZL Brewers	—	139	119	28	7	0	2	14	35	4	3	0	235	336	345	680	109	300	25	10	298	88	—	—	—	—	—	—
2009	20	A MLE	Wisconsin Timber Rattlers	—	59	49	7	1	0	0	7	19	0	0	0	143	250	163	413	20	187	32	12	199	21	—	—	—	—	—	—
2009	20	ROK MLE	Helena Brewers	—	111	98	21	1	1	0	7	29	4	1	1	214	294	245	538	31	282	26	6	234	45	—	—	—	—	—	—
2010	21	A+ MLE	Brevard County Manatees	—	292	257	63	13	0	3	23	86	10	4	0	245	331	331	662	86	351	29	8	299	88	—	—	—	—	—	—
2011	22	A+ MLE	Brevard County Manatees	—	262	239	63	10	1	4	12	43	3	9	2	264	307	364	671	100	294	16	5	285	79	—	—	—	—	—	—
2012	23	A+ MLE	Brevard County Manatees	—	112	101	27	6	1	2	4	9	6	2	1	267	333	406	739	139	271	8	4	335	113	—	—	—	—	—	—
2013	24	AA MLE	Huntsville Stars	—	190	172	47	9	0	1	10	37	3	0	1	273	324	343	667	70	324	19	5	282	77	—	—	—	—	—	—
2014	25	AAA MLE	Nashville Sounds	—	57	48	10	2	0	0	4	9	2	0	0	208	296	250	546	42	221	16	7	238	47	—	—	—	—	—	—
2014	25	AA MLE	Huntsville Stars	—	267	229	74	17	0	1	28	28	4	1	4	323	406	410	817	87	343	10	10	361	130	—	—	—	—	—	—
2015	26	AAA MLE	Oklahoma City Dodgers	—	72	68	18	4	0	1	2	14	0	0	0	265	286	368	653	103	313	19	3	288	81	—	—	—	—	—	—
2015	26	AA MLE	Tulsa Drillers	—	133	123	32	5	0	0	10	23	0	0	1	260	316	301	617	41	317	17	8	274	72	—	—	—	—	—	—
2016	27	AAA MLE	Oklahoma City Dodgers	—	53	50	7	2	0	0	2	13	0	0	0	140	173	180	353	40	175	25	4	156	-8	—	—	—	—	—	—
2016	27	AA MLE	Tulsa Drillers	—	99	88	24	6	0	0	9	16	0	0	1	273	340	341	681	68	318	16	9	307	94	—	—	—	—	—	—
2017	28	AA MLE	Tulsa Drillers	—	20	19	4	2	0	1	1	3	0	0	0	211	250	474	724	263	216	15	5	298	88	—	—	—	—	—	—
2008	19	ROK MLE	AZL Brewers	—	139	119	28	7	0	2	14	35	4	3	0	235	336	345	680	109	310	25	10	298	88	—	—	—	—	—	—
2008	19	ROK RAW	AZL Brewers	—	139	110	33	9	0	2	23	24	4	3	0	300	438	436	874	136	360	17	17	393	88	—	—	—	—	—	—
2009	20	ROK MLE	2 teams	—	170	147	28	2	1	0	14	48	4	1	1	190	279	218	496	27	272	28	8	222	36	—	—	—	—	—	—
2009	20	ROK RAW	2 teams	—	170	140	32	2	1	0	21	34	4	1	1	229	345	257	603	29	291	20	12	282	36	—	—	—	—	—	—
2010	21	A+ MLE	Brevard County Manatees	—	292	257	63	13	0	3	23	86	10	4	0	245	331	331	662	86	353	29	8	299	88	—	—	—	—	—	—
2010	21	A+ RAW	Brevard County Manatees	—	292	249	70	13	0	3	31	61	10	4	0	281	383	369	752	88	358	21	11	345	88	—	—	—	—	—	—
2011	22	A+ MLE	Brevard County Manatees	—	262	239	63	10	1	4	12	43	3	9	2	264	307	364	671	100	306	16	5	285	79	—	—	—	—	—	—
2011	22	A+ RAW	Brevard County Manatees	—	262	235	64	9	1	4	16	31	3	9	2	272	327	370	697	98	299	12	6	306	79	—	—	—	—	—	—
2012	23	A+ MLE	Brevard County Manatees	—	112	101	27	6	1	2	4	9	6	2	1	267	333	406	739	139	275	8	4	335	113	—	—	—	—	—	—
2012	23	A+ RAW	Brevard County Manatees	—	112	96	28	6	1	2	9	6	6	2	1	292	387	438	825	146	292	5	8	369	113	—	—	—	—	—	—
2013	24	AA MLE	Huntsville Stars	—	190	172	47	9	0	1	10	37	3	0	1	273	324	343	667	70	341	19	5	282	77	—	—	—	—	—	—
2013	24	AA RAW	Huntsville Stars	—	190	168	49	9	0	1	14	30	3	0	1	292	357	363	720	71	348	16	7	321	77	—	—	—	—	—	—
2014	25	AA MLE	3 teams	—	360	310	93	21	0	1	35	41	6	1	4	300	382	377	759	77	335	11	10	339	116	—	—	—	—	—	—
2014	25	AA RAW	3 teams	—	360	293	92	18	0	1	52	35	6	1	4	314	427	386	813	72	345	10	14	367	116	—	—	—	—	—	—
2015	26	AA MLE	2 teams	—	205	191	50	9	0	1	12	38	0	0	1	262	305	325	630	63	320	19	6	279	75	—	—	—	—	—	—
2015	26	AA RAW	2 teams	—	205	185	53	11	0	1	18	30	0	0	1	286	350	362	712	76	335	15	9	321	75	—	—	—	—	—	—
2016	27	AA MLE	2 teams	—	152	138	31	8	0	0	11	29	0	0	1	225	282	283	564	58	277	19	7	254	58	—	—	—	—	—	—
2016	27	AA RAW	2 teams	—	152	133	34	9	0	0	16	23	0	0	1	256	336	323	659	68	301	15	11	298	58	—	—	—	—	—	—
2017	28	AA MLE	Tulsa Drillers	—	20	19	4	2	0	1	1	3	0	0	0	211	250	474	724	263	200	15	5	298	88	—	—	—	—	—	—
2017	28	AA RAW	Tulsa Drillers	—	20	18	5	3	0	1	2	2	0	0	0	278	350	611	961	333	267	10	10	412	88	—	—	—	—	—	—
2008	19	ROK MLE	AZL Brewers	—	139	120	28	7	0	2	14	35	4	3	0	233	336	342	677	108	300	25	10	298	88	—	—	—	—	—	—
2009	20	ROK MLE	2 teams	—	170	150	28	2	1	0	14	48	4	1	1	187	279	213	492	27	249	28	8	222	36	—	—	—	—	—	—
2010	21	A+ MLE	Brevard County Manatees	—	292	257	63	13	0	3	23	86	10	4	0	245	331	331	662	86	351	29	8	299	88	—	—	—	—	—	—
2011	22	A+ MLE	Brevard County Manatees	—	262	245	63	10	1	4	12	43	3	9	2	257	307	355	662	98	294	16	5	285	79	—	—	—	—	—	—
2012	23	A+ MLE	Brevard County Manatees	—	112	101	27	6	1	2	4	9	6	2	1	267	333	406	739	139	271	8	4	335	113	—	—	—	—	—	—
2013	24	AA MLE	Huntsville Stars	—	190	175	47	9	0	1	10	37	3	0	1	269	324	337	661	69	324	19	5	282	77	—	—	—	—	—	—
2014	25	AA MLE	3 teams	—	360	316	93	21	0	1	35	41	6	1	4	294	382	370	752	76	322	11	10	339	116	—	—	—	—	—	—
2015	26	AA MLE	2 teams	—	205	191	50	9	0	1	12	38	0	0	1	262	305	325	630	63	316	19	6	279	75	—	—	—	—	—	—
2016	27	AA MLE	2 teams	—	152	140	31	8	0	0	11	29	0	0	1	221	282	279	560	57	268	19	7	254	58	—	—	—	—	—	—
2017	28	AA MLE	Tulsa Drillers	—	20	19	4	2	0	1	1	3	0	0	0	211	250	474	724	263	216	15	5	298	88	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	1902	1693	434	87	3	15	136	369	36	20	11	256	325	338	663	82	315	19	7	292	84	-36	-0	+0	+34	+41	3.9
/ 162G	—	MLE		—	650	579	148	30	1	5	46	126	12	7	4	256	323	337	660	81	314	19	7	292	84	-12	-0	+0	+12	+14	1.3

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 AATulsa Drillers · 20 PAwOBA .400 → .298 (−102)K% 10.0% → 12.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	10.00%	÷0.955	×1.220	—	—	12.77%
BB% (unintentional) /PA	10.00%	÷1.058	×0.700	—	×0.968	6.41%
HBP% /PA	0.00%	—	×0.870	—	×0.968	0.00%
Singles /BIP	6.25%	÷1.005	×0.920	—	×0.968	5.54%
Doubles /BIP	18.75%	÷1.000	×0.840	—	×0.968	15.25%
Triples /BIP	0.00%	÷1.150	×0.940	—	×0.968	0.00%
Home runs /BIP	6.25%	÷1.295	×0.800	—	×0.968	3.74%

Factors used: league row TL. Park (home-season share, regressed): HR 159, 1B 101, 2B 100, 3B 130, K 91, BB 112 — 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 .400 → .298; ISO .333 → .238; BABIP .267 → .216. 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 AATulsa Drillers · 99 PAwOBA .348 → .307 (−41)K% 13.1% → 16.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.13%	÷0.996	×1.220	—	—	16.08%
BB% (unintentional) /PA	12.12%	÷0.935	×0.700	—	×0.978	8.87%
HBP% /PA	0.00%	—	×0.870	—	×0.978	0.00%
Singles /BIP	26.39%	÷0.990	×0.920	×1.002	×0.978	24.03%
Doubles /BIP	9.72%	÷0.926	×0.840	×1.002	×0.978	8.64%
Triples /BIP	0.00%	÷0.900	×0.940	×1.002	×0.978	0.00%
Home runs /BIP	0.00%	÷1.020	×0.800	—	×0.978	0.00%

Factors used: league row TL. Park (home-season share, regressed): HR 104, 1B 98, 2B 85, 3B 80, K 99, BB 87 — applied at half strength. Age: age 27 vs a level average of 24.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.002.

Result: wOBA .348 → .307; ISO .082 → .075; BABIP .351 → .318. 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 AAAOklahoma City Dodgers · 53 PAwOBA .193 → .156 (−37)K% 18.9% → 25.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.87%	÷0.972	×1.290	—	—	25.03%
BB% (unintentional) /PA	5.66%	÷1.059	×0.710	—	×1.003	3.81%
HBP% /PA	0.00%	—	×0.980	—	×1.003	0.00%
Singles /BIP	15.79%	÷1.017	×0.900	×0.978	×1.003	13.71%
Doubles /BIP	5.26%	÷0.975	×0.810	×0.978	×1.003	4.29%
Triples /BIP	0.00%	÷1.104	×0.810	×0.978	×1.003	0.00%
Home runs /BIP	0.00%	÷0.947	×0.780	—	×1.003	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 89, 1B 103, 2B 95, 3B 121, K 94, BB 112 — applied at half strength. Age: age 27 vs a level average of 27.2 → +0.3% on BB/HBP/hit rates (0.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.978.

Result: wOBA .193 → .156; ISO .042 → .034; BABIP .205 → .175. 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 AATulsa Drillers · 133 PAwOBA .307 → .274 (−33)K% 14.3% → 17.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.29%	÷0.989	×1.220	—	—	17.63%
BB% (unintentional) /PA	10.53%	÷0.976	×0.700	—	×0.988	7.46%
HBP% /PA	0.00%	—	×0.870	—	×0.988	0.00%
Singles /BIP	27.00%	÷0.938	×0.920	×1.018	×0.988	26.63%
Doubles /BIP	6.00%	÷1.006	×0.840	×1.018	×0.988	5.04%
Triples /BIP	0.00%	÷0.900	×0.940	×1.018	×0.988	0.00%
Home runs /BIP	0.00%	÷1.039	×0.800	—	×0.988	0.00%

Factors used: league row TL. Park (home-season share, regressed): HR 108, 1B 88, 2B 101, 3B 80, K 98, BB 95 — applied at half strength. Age: age 26 vs a level average of 24.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.018.

Result: wOBA .307 → .274; ISO .050 → .042; BABIP .330 → .317. 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 AAAOklahoma City Dodgers · 72 PAwOBA .323 → .288 (−35)K% 15.3% → 20.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.28%	÷0.984	×1.290	—	—	20.02%
BB% (unintentional) /PA	4.17%	÷1.095	×0.710	—	×1.018	2.75%
HBP% /PA	0.00%	—	×0.980	—	×1.018	0.00%
Singles /BIP	25.45%	÷1.028	×0.900	×1.029	×1.018	23.34%
Doubles /BIP	9.09%	÷0.965	×0.810	×1.029	×1.018	7.99%
Triples /BIP	0.00%	÷0.941	×0.810	×1.029	×1.018	0.00%
Home runs /BIP	1.82%	÷0.866	×0.780	—	×1.018	1.67%

Factors used: league row PCL. Park (home-season share, regressed): HR 73, 1B 106, 2B 93, 3B 88, K 97, BB 119 — 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 ×1.029.

Result: wOBA .323 → .288; ISO .121 → .109; BABIP .345 → .313. 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 AAHuntsville Stars · 267 PAwOBA .383 → .361 (−22)K% 8.6% → 10.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	8.61%	÷1.015	×1.220	—	—	10.35%
BB% (unintentional) /PA	14.61%	÷0.945	×0.680	—	×0.998	10.49%
HBP% /PA	1.50%	—	×0.840	—	×0.998	1.26%
Singles /BIP	28.12%	÷0.974	×0.920	×1.014	×0.998	26.88%
Doubles /BIP	8.33%	÷0.950	×0.910	×1.014	×0.998	8.08%
Triples /BIP	0.00%	÷0.900	×0.880	×1.014	×0.998	0.00%
Home runs /BIP	0.52%	÷1.047	×0.800	—	×0.998	0.40%

Factors used: league row SL. Park (home-season share, regressed): HR 109, 1B 95, 2B 90, 3B 80, K 103, BB 89 — applied at half strength. Age: age 25 vs a level average of 24.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.014.

Result: wOBA .383 → .361; ISO .088 → .090; BABIP .357 → .343. 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 AAANashville Sounds · 57 PAwOBA .262 → .238 (−24)K% 12.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.28%	÷0.964	×1.290	—	—	16.43%
BB% (unintentional) /PA	8.77%	÷1.040	×0.710	—	×1.033	6.18%
HBP% /PA	3.51%	—	×0.980	—	×1.033	3.55%
Singles /BIP	20.00%	÷0.975	×0.900	×1.006	×1.033	19.17%
Doubles /BIP	5.00%	÷1.051	×0.810	×1.006	×1.033	4.00%
Triples /BIP	0.00%	÷1.018	×0.810	×1.006	×1.033	0.00%
Home runs /BIP	0.00%	÷0.875	×0.780	—	×1.033	0.00%

Factors used: league row PCL. Park (home-season share, regressed): HR 75, 1B 95, 2B 110, 3B 104, K 93, BB 108 — 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 ×1.006.

Result: wOBA .262 → .238; ISO .043 → .036; BABIP .238 → .221. 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 AAHuntsville Stars · 190 PAwOBA .314 → .282 (−32)K% 15.8% → 19.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.79%	÷0.977	×1.220	—	—	19.72%
BB% (unintentional) /PA	7.37%	÷1.001	×0.680	—	×1.012	5.06%
HBP% /PA	1.58%	—	×0.840	—	×1.012	1.34%
Singles /BIP	28.26%	÷1.029	×0.920	×1.030	×1.012	26.33%
Doubles /BIP	6.52%	÷1.007	×0.910	×1.030	×1.012	6.14%
Triples /BIP	0.00%	÷0.900	×0.880	×1.030	×1.012	0.00%
Home runs /BIP	0.72%	÷1.040	×0.800	—	×1.012	0.56%

Factors used: league row SL. Park (home-season share, regressed): HR 108, 1B 106, 2B 101, 3B 80, K 95, BB 100 — applied at half strength. Age: age 24 vs a level average of 24.8 → +1.2% on BB/HBP/hit rates (0.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.030.

Result: wOBA .314 → .282; ISO .071 → .065; BABIP .348 → .324. 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 — .