Joey Rickard

PosRF

B/TR/L

Born1991-05-21

Age (2027)36

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2021

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2018	27	AAABAL	185	.275/.390/.412	2	3	86	—	.233/.313/.344
2018	27	MLBBAL	230	.244/.300/.413	8	4	96	0.2
2019	28	AAASF	272	.326/.409/.555	10	1	105	—	.250/.320/.406
2019	28	MLBSF	189	.226/.312/.357	3	4	93	-0.4
2021	30	INTLLeones del Es…	65	.241/.323/.310	0	1	85	—
2022	31	No MLB games played
2023	32	No MLB games played
2024	33	No MLB games played
2025	34	No MLB games played
2026	35	No MLB games played

Last 3 seasons WAR -0.3

Contract

No contract data on file.

Skills · percentileStatcast 2018-2020

Speed73

Barrel%14

xwOBA14

Avg EV10

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)
2013	22	A	Bowling Green Hot Rods	—	559	452	122	29	5	8	78	98	16	30	10	270	396	409	805	139	322	18	14	359	76	—	—	—	—	—	—
2013	22	INTL	Brisbane Bandits	—	203	178	51	10	1	4	16	32	3	14	2	287	355	421	777	135	329	16	8	339	115	—	—	—	—	—	—
2014	23	AA	Montgomery Biscuits	—	247	206	50	8	0	1	28	40	4	9	4	243	345	296	641	53	288	16	11	291	62	—	—	—	—	—	—
2015	24	AAA	Durham Bulls	—	104	89	32	6	2	0	10	20	3	1	0	360	441	472	913	112	457	19	10	402	137	—	—	—	—	—	—
2015	24	AA	Montgomery Biscuits	—	282	236	76	19	6	2	39	42	3	19	4	322	424	479	903	157	379	15	14	397	116	—	—	—	—	—	—
2015	24	A+	Charlotte Stone Crabs	—	94	71	19	3	0	0	20	13	2	3	2	268	441	310	751	42	322	14	21	359	93	—	—	—	—	—	—
2015	24	INTL	Leones del Escogido	—	217	191	53	13	1	6	16	36	5	3	1	277	349	450	799	173	309	17	7	348	122	—	—	—	—	—	—
2016	25	MLB	Baltimore Orioles	—	282	257	69	13	0	5	18	54	2	4	1	268	321	377	699	109	320	19	6	310	93	-2	+0	+0	-3	+6	0.1
2017	26	MLB	Baltimore Orioles	—	277	261	63	15	0	4	9	63	4	8	1	241	277	345	622	103	303	23	3	277	71	-9	+1	+4	-4	+6	-0.2
2017	26	AAA	Norfolk Tides	—	58	47	9	1	0	1	11	9	0	0	0	191	345	277	621	85	216	16	19	300	59	—	—	—	—	—	—
2018	27	MLB	Baltimore Orioles	—	230	213	52	10	1	8	15	55	2	4	2	244	300	413	713	169	293	24	7	317	96	-1	+0	+2	-4	+5	0.2
2018	27	AAA	Norfolk Tides	—	185	153	42	13	1	2	26	28	3	3	0	275	390	412	802	137	317	15	14	359	86	—	—	—	—	—	—
2019	28	MLB	San Francisco Giants	—	189	168	38	9	2	3	18	50	3	4	2	226	312	357	669	131	304	26	10	304	93	-2	+0	-2	-5	+4	-0.4
2019	28	AAA	Sacramento River Cats	—	272	236	77	20	2	10	29	43	4	1	2	326	409	555	964	229	360	16	11	418	105	—	—	—	—	—	—
2021	30	INTL	Leones del Escogido	—	65	58	14	4	0	0	7	11	0	1	0	241	323	310	633	69	298	17	11	293	85	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	978	899	222	47	3	20	60	222	11	20	6	247	302	373	675	126	306	23	6	301	90	-12	+2	+4	-16	+21	-0.1
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2013	22	A MLE	Bowling Green Hot Rods	—	559	481	106	23	5	6	49	139	16	30	10	220	313	326	640	106	277	25	9	281	76	—	—	—	—	—	—
2014	23	AA MLE	Montgomery Biscuits	—	247	213	48	7	0	1	21	47	4	9	4	225	307	272	579	47	265	19	9	260	62	—	—	—	—	—	—
2015	24	AAA MLE	Durham Bulls	—	104	93	31	5	2	0	6	23	3	1	0	333	392	430	822	97	441	22	6	370	137	—	—	—	—	—	—
2015	24	AA MLE	Montgomery Biscuits	—	282	248	71	18	5	2	27	52	3	19	4	286	363	423	787	137	341	18	10	339	116	—	—	—	—	—	—
2015	24	A+ MLE	Charlotte Stone Crabs	—	94	76	18	3	0	0	15	19	2	3	2	237	376	276	653	39	302	20	16	306	93	—	—	—	—	—	—
2016	25	MLB MLE	Baltimore Orioles	—	282	257	68	13	0	5	18	54	2	4	1	265	318	374	691	109	320	19	6	305	93	-2	+0	+0	-3	+6	0.1
2017	26	MLB MLE	Baltimore Orioles	—	277	261	63	15	0	4	9	63	4	8	1	241	277	345	622	103	303	23	3	274	71	-9	+1	+4	-4	+6	-0.2
2017	26	AAA MLE	Norfolk Tides	—	58	50	9	1	0	1	8	11	0	0	0	180	293	260	553	80	204	19	14	255	59	—	—	—	—	—	—
2018	27	MLB MLE	Baltimore Orioles	—	230	213	51	10	1	7	15	55	2	4	2	239	296	394	690	155	293	24	7	310	96	-1	+0	+2	-4	+5	0.2
2018	27	AAA MLE	Norfolk Tides	—	185	163	38	10	1	2	16	33	3	3	0	233	313	344	657	110	269	18	9	295	86	—	—	—	—	—	—
2019	28	MLB MLE	San Francisco Giants	—	189	169	38	9	2	3	17	50	3	4	2	225	307	355	662	130	304	26	9	305	93	-2	+0	-2	-5	+4	-0.4
2019	28	AAA MLE	Sacramento River Cats	—	272	244	61	15	1	7	21	57	4	1	2	250	320	406	725	156	297	21	8	324	105	—	—	—	—	—	—
2013	22	A MLE	2 teams	—	762	657	144	31	6	8	67	190	19	44	12	219	310	321	631	102	291	25	9	281	76	—	—	—	—	—	—
2013	22	A RAW	2 teams	—	762	630	173	39	6	12	94	130	19	44	12	275	385	413	798	138	324	17	12	353	76	—	—	—	—	—	—
2014	23	AA MLE	Montgomery Biscuits	—	247	213	48	7	0	1	21	47	4	9	4	225	307	272	579	47	276	19	9	260	62	—	—	—	—	—	—
2014	23	AA RAW	Montgomery Biscuits	—	247	206	50	8	0	1	28	40	4	9	4	243	345	296	641	53	288	16	11	291	62	—	—	—	—	—	—
2015	24	AA MLE	4 teams	—	697	602	174	39	10	2	70	137	13	26	7	289	375	397	772	108	365	20	10	339	116	—	—	—	—	—	—
2015	24	AA RAW	4 teams	—	697	587	180	41	9	8	85	111	13	26	7	307	406	448	854	141	361	16	12	377	116	—	—	—	—	—	—
2016	25	MLB MLE	Baltimore Orioles	—	282	257	68	13	0	5	18	54	2	4	1	265	318	374	691	109	315	19	6	305	93	-2	+0	+0	-3	+6	0.1
2016	25	MLB RAW	Baltimore Orioles	—	282	257	69	13	0	5	18	54	2	4	1	268	321	377	699	109	320	19	6	310	93	-2	+0	+0	-3	+6	0.1
2017	26	MLB MLE	2 teams	—	335	311	71	16	0	5	17	74	4	8	1	228	277	328	605	100	283	22	5	270	69	-12	+1	+4	-4	+7	-0.4
2017	26	MLB RAW	2 teams	—	335	308	72	16	0	5	20	72	4	8	1	234	289	334	624	101	289	21	6	281	69	-12	+1	+4	-4	+7	-0.4
2018	27	MLB MLE	2 teams	—	415	376	89	20	2	9	31	88	5	7	2	237	303	372	676	136	284	21	7	303	91	-4	+1	+2	-4	+9	0.3
2018	27	MLB RAW	2 teams	—	415	366	94	23	2	10	41	83	5	7	2	257	340	413	752	156	304	20	10	336	91	-4	+1	+2	-4	+9	0.3
2019	28	AAA MLE	2 teams	—	461	413	102	24	4	11	38	107	7	5	4	247	321	404	725	157	305	23	8	316	100	—	—	—	—	—	—
2019	28	AAA RAW	2 teams	—	461	404	115	29	4	13	47	93	7	5	4	285	369	473	842	188	339	20	10	371	100	—	—	—	—	—	—
2021	30	INTL MLE	Leones del Escogido	—	65	58	14	4	0	0	7	11	0	1	0	241	323	310	633	69	298	17	11	—	—	—	—	—	—	—	—
2021	30	INTL RAW	Leones del Escogido	—	65	58	14	4	0	0	7	11	0	1	0	241	323	310	633	69	298	17	11	293	85	—	—	—	—	—	—
2013	22	A MLE	2 teams	—	762	670	144	31	6	8	67	190	19	44	12	215	310	315	624	100	277	25	9	281	76	—	—	—	—	—	—
2014	23	AA MLE	Montgomery Biscuits	—	247	220	48	7	0	1	21	47	4	9	4	218	307	264	570	45	265	19	9	260	62	—	—	—	—	—	—
2015	24	AA MLE	4 teams	—	697	609	174	39	10	2	70	137	13	26	7	286	375	392	768	107	355	20	10	339	116	—	—	—	—	—	—
2016	25	MLB MLE	Baltimore Orioles	—	282	260	68	13	0	5	18	54	2	4	1	262	318	369	687	108	320	19	6	305	93	—	—	—	—	—	—
2017	26	MLB MLE	2 teams	—	335	311	71	16	0	5	17	74	4	8	1	228	277	328	605	100	285	22	5	270	69	—	—	—	—	—	—
2018	27	MLB MLE	2 teams	—	415	376	89	20	2	9	31	88	5	7	2	237	303	372	676	136	282	21	7	303	91	—	—	—	—	—	—
2019	28	AAA MLE	2 teams	—	461	413	102	24	4	11	38	107	7	5	4	247	321	404	725	157	300	23	8	316	100	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	978	899	222	47	3	20	60	222	11	20	6	247	302	373	675	126	306	23	6	301	86	-12	+2	+4	-16	+21	-0.1
/ 162G	—	A+C		—	650	597	147	31	2	13	40	148	7	13	4	246	301	370	671	124	306	23	6	301	86	-8	+1	+3	-11	+14	-0.0
Career	—	MLE		—	3264	2887	710	154	22	41	269	708	54	104	31	246	322	357	679	111	308	22	8	295	86	-12	+2	+4	-16	+21	-0.1
/ 162G	—	MLE		—	650	575	141	31	4	8	54	141	11	21	6	245	322	355	677	110	308	22	8	295	86	-8	+1	+3	-11	+14	-0.0

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.

2019 AAASacramento River Cats · 272 PAwOBA .411 → .324 (−87)K% 15.8% → 21.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.81%	÷0.971	×1.290	—	—	20.99%
BB% (unintentional) /PA	10.66%	÷0.980	×0.710	—	×0.992	7.66%
HBP% /PA	1.47%	—	×0.980	—	×0.992	1.43%
Singles /BIP	23.32%	÷0.982	×0.900	×0.950	×0.992	20.13%
Doubles /BIP	10.36%	÷0.981	×0.810	×0.950	×0.992	8.07%
Triples /BIP	1.04%	÷1.008	×0.810	×0.950	×0.992	0.78%
Home runs /BIP	5.18%	÷1.027	×0.780	—	×0.992	3.90%

Factors used: league row PCL. Park (home-season share, regressed): HR 105, 1B 96, 2B 96, 3B 102, K 94, BB 96 — 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 ×0.950.

Result: wOBA .411 → .324; ISO .229 → .172; BABIP .360 → .297. 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 AAANorfolk Tides · 185 PAwOBA .350 → .295 (−55)K% 15.1% → 18.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.14%	÷1.009	×1.200	—	—	18.00%
BB% (unintentional) /PA	12.43%	÷0.997	×0.690	—	×1.003	8.63%
HBP% /PA	1.62%	—	×0.940	—	×1.003	1.53%
Singles /BIP	20.80%	÷0.984	×0.930	×0.950	×1.003	18.74%
Doubles /BIP	10.40%	÷1.063	×0.830	×0.950	×1.003	7.74%
Triples /BIP	0.80%	÷1.150	×0.970	×0.950	×1.003	0.64%
Home runs /BIP	1.60%	÷0.964	×0.840	—	×1.003	1.40%

Factors used: league row IL. Park (home-season share, regressed): HR 93, 1B 97, 2B 113, 3B 130, K 102, BB 99 — 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 ×0.950.

Result: wOBA .350 → .295; ISO .137 → .115; BABIP .317 → .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).

2017 AAANorfolk Tides · 58 PAwOBA .293 → .255 (−38)K% 15.5% → 18.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	15.52%	÷0.995	×1.200	—	—	18.72%
BB% (unintentional) /PA	18.97%	÷0.948	×0.690	—	×1.018	14.05%
HBP% /PA	0.00%	—	×0.940	—	×1.018	0.00%
Singles /BIP	18.42%	÷0.989	×0.930	—	×1.018	17.63%
Doubles /BIP	2.63%	÷1.001	×0.830	—	×1.018	2.22%
Triples /BIP	0.00%	÷1.150	×0.970	—	×1.018	0.00%
Home runs /BIP	2.63%	÷0.866	×0.840	—	×1.018	2.60%

Factors used: league row IL. Park (home-season share, regressed): HR 73, 1B 98, 2B 100, 3B 130, K 99, BB 90 — 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 .293 → .255; ISO .085 → .083; BABIP .216 → .204. 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 AAMontgomery Biscuits · 282 PAwOBA .392 → .339 (−53)K% 14.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	14.89%	÷0.990	×1.220	—	—	18.35%
BB% (unintentional) /PA	13.83%	÷0.987	×0.680	—	×1.012	9.64%
HBP% /PA	1.06%	—	×0.840	—	×1.012	0.90%
Singles /BIP	25.26%	÷1.005	×0.920	×0.973	×1.012	22.77%
Doubles /BIP	9.79%	÷0.953	×0.910	×0.973	×1.012	9.20%
Triples /BIP	3.09%	÷1.150	×0.880	×0.973	×1.012	2.33%
Home runs /BIP	1.03%	÷0.983	×0.800	—	×1.012	0.85%

Factors used: league row SL. Park (home-season share, regressed): HR 97, 1B 101, 2B 91, 3B 130, K 98, BB 97 — 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 ×0.973.

Result: wOBA .392 → .339; ISO .157 → .139; BABIP .379 → .341. 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 AAADurham Bulls · 104 PAwOBA .396 → .370 (−26)K% 19.2% → 22.5%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.23%	÷1.025	×1.200	—	—	22.51%
BB% (unintentional) /PA	9.62%	÷1.148	×0.690	—	×1.048	6.05%
HBP% /PA	2.88%	—	×0.940	—	×1.048	2.84%
Singles /BIP	34.78%	÷1.025	×0.930	×1.027	×1.048	33.99%
Doubles /BIP	8.70%	÷1.062	×0.830	×1.027	×1.048	7.32%
Triples /BIP	2.90%	÷0.900	×0.970	×1.027	×1.048	3.36%
Home runs /BIP	0.00%	÷1.039	×0.840	—	×1.048	0.00%

Factors used: league row IL. Park (home-season share, regressed): HR 108, 1B 105, 2B 112, 3B 80, K 105, BB 130 — 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). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.027.

Result: wOBA .396 → .370; ISO .112 → .113; BABIP .457 → .441. 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 A+Charlotte Stone Crabs · 94 PAwOBA .355 → .306 (−50)K% 13.8% → 20.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.83%	÷0.979	×1.420	—	—	20.06%
BB% (unintentional) /PA	21.28%	÷0.994	×0.750	—	×0.988	15.85%
HBP% /PA	2.13%	—	×0.930	—	×0.988	1.95%
Singles /BIP	27.59%	÷0.976	×0.920	×0.999	×0.988	25.67%
Doubles /BIP	5.17%	÷0.978	×0.960	×0.999	×0.988	5.01%
Triples /BIP	0.00%	÷1.150	×0.810	×0.999	×0.988	0.00%
Home runs /BIP	0.00%	÷0.822	×0.880	—	×0.988	0.00%

Factors used: league row FSL. Park (home-season share, regressed): HR 64, 1B 95, 2B 96, 3B 130, K 96, BB 99 — 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 ×0.999.

Result: wOBA .355 → .306; ISO .042 → .041; BABIP .322 → .302. 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 AAMontgomery Biscuits · 247 PAwOBA .290 → .260 (−30)K% 16.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.19%	÷1.036	×1.220	—	—	19.07%
BB% (unintentional) /PA	11.34%	÷0.945	×0.680	—	×1.027	8.38%
HBP% /PA	1.62%	—	×0.840	—	×1.027	1.40%
Singles /BIP	24.70%	÷0.967	×0.920	×0.954	×1.027	23.02%
Doubles /BIP	4.82%	÷1.057	×0.910	×0.954	×1.027	4.07%
Triples /BIP	0.00%	÷1.150	×0.880	×0.954	×1.027	0.00%
Home runs /BIP	0.60%	÷1.037	×0.800	—	×1.027	0.48%

Factors used: league row SL. Park (home-season share, regressed): HR 107, 1B 93, 2B 111, 3B 130, K 107, BB 89 — applied at half strength. Age: age 23 vs a level average of 24.8 → +2.7% on BB/HBP/hit rates (1.8 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.954.

Result: wOBA .290 → .260; ISO .053 → .047; BABIP .288 → .265. 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 ABowling Green Hot Rods · 559 PAwOBA .355 → .281 (−74)K% 17.5% → 24.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.53%	÷0.958	×1.360	—	—	24.88%
BB% (unintentional) /PA	13.95%	÷1.098	×0.690	—	—	8.77%
HBP% /PA	2.86%	—	×0.780	—	—	2.23%
Singles /BIP	22.60%	÷1.004	×0.920	×0.975	—	20.21%
Doubles /BIP	8.19%	÷1.038	×0.830	×0.975	—	6.39%
Triples /BIP	1.41%	÷0.974	×0.910	×0.975	—	1.29%
Home runs /BIP	2.26%	÷1.044	×0.800	—	—	1.73%

Factors used: level-wide A factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 109, 1B 101, 2B 108, 3B 95, K 92, BB 120 — 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 ×0.975.

Result: wOBA .355 → .281; ISO .139 → .112; BABIP .322 → .277. 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 — .