Taylor Gushue

PosC

B/TS/R

Born1993-12-19

Age (2027)33

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2022

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	wRC+	WAR	MLE AVG/OBP/SLG
2019	25	AAACOL	288	.312/.363/.517	11	88	—	.249/.289/.409
2021	27	AAACHC	277	.223/.297/.377	8	38	—	.180/.231/.285
2022	28	AAA/AAWSH	285	.217/.350/.391	10	61	—	.180/.275/.317

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)
2015	21	A	West Virginia Power	—	395	360	83	17	4	5	25	79	5	1	2	231	290	342	631	111	280	20	6	282	35	—	—	—	—	—	—
2016	22	A+	Bradenton Marauders	—	359	328	74	17	1	8	23	69	4	0	0	226	285	357	641	131	260	19	6	286	40	—	—	—	—	—	—
2017	23	A+	Potomac Nationals	—	376	323	78	9	0	18	41	88	4	0	0	241	334	437	771	195	267	23	11	337	42	—	—	—	—	—	—
2017	23	INTL	Mesa Solar Sox	—	51	49	7	0	0	2	2	15	0	0	0	143	176	265	442	122	156	29	4	198	20	—	—	—	—	—	—
2018	24	AA	Harrisburg Senators	—	386	339	72	19	1	10	37	93	4	0	1	212	297	363	660	150	256	24	10	294	45	—	—	—	—	—	—
2018	24	INTL	Gigantes del Cibao	—	68	64	13	4	0	1	3	18	1	0	0	203	250	312	562	109	267	26	4	254	58	—	—	—	—	—	—
2019	25	AAA	Fresno Grizzlies	—	288	263	82	19	1	11	20	63	1	0	0	312	363	517	880	205	368	22	7	381	88	—	—	—	—	—	—
2021	27	AAA	Iowa Cubs	—	277	247	55	14	0	8	25	83	1	0	0	223	297	377	673	154	297	30	9	298	38	—	—	—	—	—	—
2022	28	AAA	Rochester Red Wings	—	208	174	35	8	0	4	32	65	0	0	0	201	325	316	641	115	292	31	15	297	41	—	—	—	—	—	—
2022	28	AA	Harrisburg Senators	—	77	61	16	3	0	6	15	14	1	0	0	262	416	607	1.022	344	244	18	19	440	114	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2015	21	A MLE	West Virginia Power	—	395	369	69	13	4	3	16	105	5	1	2	187	231	268	499	81	244	27	4	220	35	—	—	—	—	—	—
2016	22	A+ MLE	Bradenton Marauders	—	359	335	62	14	1	6	16	98	4	0	0	185	231	287	518	101	235	27	4	227	40	—	—	—	—	—	—
2017	23	A+ MLE	Potomac Nationals	—	376	341	58	7	0	11	23	130	4	0	0	170	231	287	518	117	216	35	6	231	42	—	—	—	—	—	—
2018	24	AA MLE	Harrisburg Senators	—	386	351	61	15	1	8	25	115	4	0	1	174	237	291	527	117	222	30	6	235	45	—	—	—	—	—	—
2019	25	AAA MLE	Fresno Grizzlies	—	288	269	67	14	1	9	14	85	1	0	0	249	289	409	698	160	319	30	5	298	88	—	—	—	—	—	—
2021	27	AAA MLE	Iowa Cubs	—	277	256	46	12	0	5	16	96	1	0	0	180	231	285	516	105	251	35	6	225	38	—	—	—	—	—	—
2022	28	AAA MLE	Rochester Red Wings	—	208	184	31	7	0	3	22	74	0	0	0	168	257	255	513	87	252	36	11	229	41	—	—	—	—	—	—
2022	28	AA MLE	Harrisburg Senators	—	77	66	14	3	0	5	10	17	1	0	0	212	325	485	810	273	202	22	13	337	114	—	—	—	—	—	—
2015	21	A MLE	West Virginia Power	—	395	369	69	13	4	3	16	105	5	1	2	187	231	268	499	81	250	27	4	220	35	—	—	—	—	—	—
2015	21	A RAW	West Virginia Power	—	395	360	83	17	4	5	25	79	5	1	2	231	290	342	631	111	280	20	6	282	35	—	—	—	—	—	—
2016	22	A+ MLE	Bradenton Marauders	—	359	335	62	14	1	6	16	98	4	0	0	185	231	287	518	101	239	27	4	227	40	—	—	—	—	—	—
2016	22	A+ RAW	Bradenton Marauders	—	359	328	74	17	1	8	23	69	4	0	0	226	285	357	641	131	260	19	6	286	40	—	—	—	—	—	—
2017	23	A+ MLE	2 teams	—	427	389	65	7	0	12	26	147	4	0	0	167	227	278	504	111	223	34	6	231	42	—	—	—	—	—	—
2017	23	A+ RAW	2 teams	—	427	372	85	9	0	20	43	103	4	0	0	228	315	414	729	185	253	24	10	320	42	—	—	—	—	—	—
2018	24	AA MLE	2 teams	—	454	413	73	18	1	10	30	135	5	0	1	177	241	298	539	121	230	30	7	235	45	—	—	—	—	—	—
2018	24	AA RAW	2 teams	—	454	403	85	23	1	11	40	111	5	0	1	211	290	355	645	144	258	24	9	288	45	—	—	—	—	—	—
2019	25	AAA MLE	Fresno Grizzlies	—	288	269	67	14	1	9	14	85	1	0	0	249	289	409	698	160	324	30	5	298	88	—	—	—	—	—	—
2019	25	AAA RAW	Fresno Grizzlies	—	288	263	82	19	1	11	20	63	1	0	0	312	363	517	880	205	368	22	7	381	88	—	—	—	—	—	—
2021	27	AAA MLE	Iowa Cubs	—	277	256	46	12	0	5	16	96	1	0	0	180	231	285	516	105	261	35	6	225	38	—	—	—	—	—	—
2021	27	AAA RAW	Iowa Cubs	—	277	247	55	14	0	8	25	83	1	0	0	223	297	377	673	154	297	30	9	298	38	—	—	—	—	—	—
2022	28	AAA MLE	2 teams	—	285	250	44	10	0	7	32	92	1	0	0	176	272	300	572	124	243	32	11	258	61	—	—	—	—	—	—
2022	28	AAA RAW	2 teams	—	285	235	51	11	0	10	47	79	1	0	0	217	350	391	741	174	279	28	16	335	61	—	—	—	—	—	—
2015	21	A MLE	West Virginia Power	—	395	371	69	13	4	3	16	105	5	1	2	186	231	267	498	81	244	27	4	220	35	—	—	—	—	—	—
2016	22	A+ MLE	Bradenton Marauders	—	359	336	62	14	1	6	16	98	4	0	0	185	231	286	517	101	235	27	4	227	40	—	—	—	—	—	—
2017	23	A+ MLE	2 teams	—	427	394	65	7	0	12	26	147	4	0	0	165	227	274	501	109	216	34	6	231	42	—	—	—	—	—	—
2018	24	AA MLE	2 teams	—	454	416	73	18	1	10	30	135	5	0	1	175	241	296	537	120	222	30	7	235	45	—	—	—	—	—	—
2019	25	AAA MLE	Fresno Grizzlies	—	288	271	67	14	1	9	14	85	1	0	0	247	289	406	695	159	319	30	5	298	88	—	—	—	—	—	—
2021	27	AAA MLE	Iowa Cubs	—	277	258	46	12	0	5	16	96	1	0	0	178	231	283	514	105	251	35	6	225	38	—	—	—	—	—	—
2022	28	AAA MLE	2 teams	—	285	250	44	10	0	7	32	92	1	0	0	176	272	300	572	124	238	32	11	258	61	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	2485	2281	426	88	7	52	150	758	21	1	3	187	243	300	543	113	250	31	6	240	48	-153	-1	-0	+34	+54	-6.7
/ 162G	—	MLE		—	650	597	112	23	2	14	39	198	5	0	1	188	243	303	547	116	250	30	6	240	48	-40	-0	-0	+9	+14	-1.8

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 AAARochester Red Wings · 208 PAwOBA .289 → .229 (−60)K% 31.2% → 35.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	31.25%	÷1.049	×1.200	—	—	35.76%
BB% (unintentional) /PA	14.90%	÷0.973	×0.690	—	×0.982	10.38%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	21.10%	÷1.011	×0.930	×0.976	×0.982	18.61%
Doubles /BIP	7.34%	÷0.930	×0.830	×0.976	×0.982	6.28%
Triples /BIP	0.00%	÷0.913	×0.970	×0.976	×0.982	0.00%
Home runs /BIP	3.67%	÷1.084	×0.700	—	×0.982	2.33%

Factors used: league row International League. Park (home-season share, regressed): HR 117, 1B 102, 2B 86, 3B 83, K 110, BB 95 — applied at half strength. Age: age 29 vs a level average of 27.2 → −1.8% on BB/HBP/hit rates (1.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.976.

Result: wOBA .289 → .229; ISO .115 → .085; BABIP .292 → .252. 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).

2022 AAHarrisburg Senators · 77 PAwOBA .428 → .337 (−91)K% 18.2% → 22.3%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.18%	÷0.996	×1.220	—	—	22.27%
BB% (unintentional) /PA	19.48%	÷0.980	×0.700	—	×0.958	13.34%
HBP% /PA	1.30%	—	×0.850	—	×0.958	1.06%
Singles /BIP	14.89%	÷1.016	×0.970	×0.950	×0.958	12.93%
Doubles /BIP	6.38%	÷0.936	×0.860	×0.950	×0.958	5.34%
Triples /BIP	0.00%	÷1.150	×0.950	×0.950	×0.958	0.00%
Home runs /BIP	12.77%	÷0.979	×0.780	—	×0.958	9.74%

Factors used: league row EL. Park (home-season share, regressed): HR 96, 1B 103, 2B 87, 3B 130, K 99, BB 96 — applied at half strength. Age: age 29 vs a level average of 24.8 → −4.2% on BB/HBP/hit rates (4.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.950.

Result: wOBA .428 → .337; ISO .344 → .276; BABIP .244 → .202. 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).

2021 AAAIowa Cubs · 277 PAwOBA .291 → .225 (−66)K% 30.0% → 34.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	29.96%	÷1.032	×1.200	—	—	34.84%
BB% (unintentional) /PA	8.66%	÷1.023	×0.690	—	×0.992	5.80%
HBP% /PA	0.36%	—	×0.940	—	×0.992	0.34%
Singles /BIP	20.12%	÷1.039	×0.930	×0.978	×0.992	17.46%
Doubles /BIP	8.54%	÷0.963	×0.830	×0.978	×0.992	7.14%
Triples /BIP	0.00%	÷0.988	×0.920	×0.978	×0.992	0.00%
Home runs /BIP	4.88%	÷1.081	×0.700	—	×0.992	3.13%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 116, 1B 108, 2B 93, 3B 98, K 106, BB 105 — applied at half strength. Age: age 28 vs a level average of 27.2 → −0.8% on BB/HBP/hit rates (0.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.978.

Result: wOBA .291 → .225; ISO .154 → .109; BABIP .297 → .251. 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).

2019 AAAFresno Grizzlies · 288 PAwOBA .374 → .298 (−76)K% 21.9% → 29.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.88%	÷0.953	×1.290	—	—	29.61%
BB% (unintentional) /PA	6.60%	÷0.990	×0.710	—	×1.018	4.81%
HBP% /PA	0.35%	—	×0.980	—	×1.018	0.35%
Singles /BIP	25.50%	÷0.959	×0.900	×0.950	×1.018	23.14%
Doubles /BIP	9.50%	÷0.976	×0.810	×0.950	×1.018	7.63%
Triples /BIP	0.50%	÷1.140	×0.810	×0.950	×1.018	0.34%
Home runs /BIP	5.50%	÷0.962	×0.780	—	×1.018	4.54%

Factors used: league row PCL. Park (home-season share, regressed): HR 92, 1B 92, 2B 95, 3B 128, K 91, BB 98 — 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 ×0.950.

Result: wOBA .374 → .298; ISO .205 → .157; BABIP .368 → .319. 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).

2018 AAHarrisburg Senators · 386 PAwOBA .291 → .235 (−56)K% 24.1% → 29.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.09%	÷0.987	×1.220	—	—	29.78%
BB% (unintentional) /PA	9.59%	÷1.037	×0.700	—	×0.998	6.46%
HBP% /PA	1.04%	—	×0.850	—	×0.998	0.88%
Singles /BIP	17.07%	÷1.017	×0.970	×0.950	×0.998	15.45%
Doubles /BIP	7.72%	÷1.012	×0.860	×0.950	×0.998	6.22%
Triples /BIP	0.41%	÷1.070	×0.950	×0.950	×0.998	0.34%
Home runs /BIP	4.07%	÷0.925	×0.780	—	×0.998	3.42%

Factors used: league row EL. Park (home-season share, regressed): HR 85, 1B 103, 2B 102, 3B 114, K 97, BB 107 — 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 ×0.950.

Result: wOBA .291 → .235; ISO .150 → .123; BABIP .256 → .222. 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).

2017 A+Potomac Nationals · 376 PAwOBA .330 → .231 (−99)K% 23.4% → 34.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.40%	÷0.963	×1.420	—	—	34.50%
BB% (unintentional) /PA	9.57%	÷0.982	×0.630	—	×0.988	6.07%
HBP% /PA	1.06%	—	×0.860	—	×0.988	0.90%
Singles /BIP	21.70%	÷1.050	×0.940	×0.955	×0.988	18.33%
Doubles /BIP	3.83%	÷1.012	×0.830	×0.955	×0.988	2.96%
Triples /BIP	0.00%	÷1.150	×0.800	×0.955	×0.988	0.00%
Home runs /BIP	7.66%	÷1.368	×0.900	—	×0.988	4.98%

Factors used: league row CAR. Park (home-season share, regressed): HR 174, 1B 110, 2B 102, 3B 130, K 93, BB 96 — applied at half strength. Age: age 24 vs a level average of 22.8 → −1.2% on BB/HBP/hit rates (1.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.955.

Result: wOBA .330 → .231; ISO .195 → .122; 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 A+Bradenton Marauders · 359 PAwOBA .279 → .227 (−52)K% 19.2% → 27.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.22%	÷0.996	×1.420	—	—	27.40%
BB% (unintentional) /PA	6.13%	÷1.009	×0.750	—	×0.998	4.55%
HBP% /PA	1.11%	—	×0.930	—	×0.998	1.03%
Singles /BIP	18.53%	÷0.999	×0.920	×0.995	×0.998	16.95%
Doubles /BIP	6.56%	÷1.059	×0.960	×0.995	×0.998	5.91%
Triples /BIP	0.39%	÷0.900	×0.810	×0.995	×0.998	0.35%
Home runs /BIP	3.09%	÷1.098	×0.880	—	×0.998	2.47%

Factors used: league row FSL. Park (home-season share, regressed): HR 120, 1B 100, 2B 112, 3B 80, K 99, BB 102 — applied at half strength. Age: age 23 vs a level average of 22.8 → −0.2% on BB/HBP/hit rates (0.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.995.

Result: wOBA .279 → .227; ISO .131 → .103; BABIP .260 → .235. 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 AWest Virginia Power · 395 PAwOBA .276 → .220 (−56)K% 20.0% → 26.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.00%	÷1.009	×1.340	—	—	26.55%
BB% (unintentional) /PA	6.08%	÷1.012	×0.660	—	—	3.96%
HBP% /PA	1.27%	—	×0.770	—	—	0.97%
Singles /BIP	20.28%	÷1.024	×0.920	×0.994	—	18.10%
Doubles /BIP	6.05%	÷0.998	×0.820	×0.994	—	4.94%
Triples /BIP	1.42%	÷0.987	×0.940	×0.994	—	1.35%
Home runs /BIP	1.78%	÷1.137	×0.820	—	—	1.28%

Factors used: league row SAL. Park (home-season share, regressed): HR 127, 1B 105, 2B 100, 3B 97, K 102, BB 102 — applied at half strength. Age: age 22 vs a level average of 22.0 → +0.0% on BB/HBP/hit rates (0.0 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.994.

Result: wOBA .276 → .220; ISO .111 → .086; BABIP .280 → .244. 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 — .