Willy Aybar

Pos3B

B/TS/R

Born1983-03-09

Age (2027)44

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2015

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2011	28	INTLTigres del Li…	49	.244/.367/.317	0	1	104	—
2012	29	AAA/INTL2 orgs	95	.221/.295/.233	0	0	45	—	.154/.241/.154
2015	32	AAAVaqueros de l…	222	.294/.374/.459	7	0	77	—	.239/.288/.356

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)
2005	22	MLB	Los Angeles Dodgers	—	105	86	28	8	0	1	18	11	1	3	1	326	448	453	901	128	365	10	17	408	162	+8	+0	-1	+2	+2	1.2
2005	22	AAA	Las Vegas 51s	—	450	401	119	26	4	5	40	56	1	1	6	297	362	419	781	122	329	12	9	344	87	—	—	—	—	—	—
2006	23	MLB	Atlanta Braves	—	278	243	68	18	0	4	28	36	4	1	2	280	364	403	767	123	315	13	10	344	119	+6	-1	+1	+2	+6	1.5
2006	23	AAA	Richmond Braves	—	234	207	65	13	1	10	24	27	1	1	3	314	388	531	919	217	320	12	10	400	127	—	—	—	—	—	—
2008	25	MLB	Tampa Bay Rays	—	362	324	82	17	2	10	32	44	4	2	2	253	328	410	738	157	266	12	9	329	105	+2	-0	+8	+1	+8	1.9
2008	25	AAA	Durham Bulls	—	24	20	6	3	0	0	4	1	0	0	0	300	417	450	867	150	316	4	17	390	112	—	—	—	—	—	—
2009	26	MLB	Tampa Bay Rays	—	336	296	75	12	0	12	34	54	2	1	0	253	334	416	750	162	270	16	10	333	108	+3	+0	-7	-6	+7	-0.2
2010	27	MLB	Tampa Bay Rays	—	309	270	62	13	0	6	30	61	3	0	0	230	314	344	658	115	271	20	10	295	84	-6	+0	-1	+1	+7	0.1
2010	27	INTL	Tigres del Licey	—	54	49	20	4	0	1	5	5	0	1	0	408	463	551	1.014	143	442	9	9	450	190	—	—	—	—	—	—
2011	28	INTL	Tigres del Licey	—	49	41	10	3	0	0	7	5	1	1	1	244	367	317	684	73	278	10	14	323	104	—	—	—	—	—	—
2012	29	AAA	Delfines de Ciudad del Carmen	—	29	24	4	0	0	0	5	6	0	0	1	167	310	167	477		222	21	17	245	17	—	—	—	—	—	—
2012	29	INTL	Leones del Escogido	—	66	62	15	1	0	0	4	11	0	0	0	242	288	258	546	16	294	17	6	254	58	—	—	—	—	—	—
2015	32	AAA	Vaqueros de la Laguna	—	222	194	57	11	0	7	23	30	2	0	0	294	374	459	833	165	314	14	10	367	77	—	—	—	—	—	—
▸ Career Totals (raw MLB only — historical actual)
MLB Career	—			—	1390	1219	315	68	2	33	142	206	14	7	5	258	343	399	741	140	285	15	10	331	110	+17	-1	-0	+0	+30	4.8
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	22	MLB MLE	Los Angeles Dodgers	—	105	86	28	8	0	1	18	11	1	3	1	326	448	453	901	128	365	10	17	408	162	+8	+0	-1	+2	+2	1.2
2005	22	AAA MLE	Las Vegas 51s	—	450	411	108	22	3	4	30	72	1	1	6	263	314	360	675	97	298	16	7	297	87	—	—	—	—	—	—
2006	23	MLB MLE	Atlanta Braves	—	278	243	68	18	0	4	28	36	4	1	2	280	364	403	767	123	315	13	10	344	119	+6	-1	+1	+2	+6	1.5
2006	23	AAA MLE	Richmond Braves	—	234	214	63	12	1	9	17	32	1	1	3	294	349	486	835	192	302	14	7	356	127	—	—	—	—	—	—
2008	25	MLB MLE	Tampa Bay Rays	—	362	327	82	17	2	10	29	44	4	2	2	251	319	407	726	156	266	12	8	323	105	+2	-0	+8	+1	+8	1.9
2008	25	AAA MLE	Durham Bulls	—	24	21	6	3	0	0	3	1	0	0	0	286	375	429	804	143	287	4	12	333	112	—	—	—	—	—	—
2009	26	MLB MLE	Tampa Bay Rays	—	336	298	75	12	0	12	32	54	2	1	0	252	328	413	741	161	270	16	10	328	108	+3	+0	-7	-6	+7	-0.2
2010	27	MLB MLE	Tampa Bay Rays	—	309	271	61	13	0	6	29	61	3	0	0	225	307	339	646	114	271	20	9	293	84	-6	+0	-1	+1	+7	0.1
2012	29	AAA MLE	Delfines de Ciudad del Carmen	—	29	26	4	0	0	0	3	7	0	0	1	154	241	154	395		200	24	10	193	17	—	—	—	—	—	—
2015	32	AAA MLE	Vaqueros de la Laguna	—	222	205	49	9	0	5	12	38	2	0	0	239	288	356	644	117	262	17	5	282	77	—	—	—	—	—	—
2005	22	AAA MLE	2 teams	—	555	497	136	30	3	5	48	83	2	4	7	274	340	376	716	103	315	15	9	318	101	—	—	—	—	—	—
2005	22	AAA RAW	2 teams	—	555	487	147	34	4	6	58	67	2	4	7	302	378	425	803	123	335	12	10	356	101	—	—	—	—	—	—
2006	23	MLB MLE	2 teams	—	512	457	131	30	1	13	45	68	5	2	5	287	357	442	799	155	312	13	9	349	123	+14	-2	+1	+2	+11	2.7
2006	23	MLB RAW	2 teams	—	512	450	133	31	1	14	52	63	5	2	5	296	375	462	837	167	317	12	10	370	123	+14	-2	+1	+2	+11	2.7
2008	25	MLB MLE	2 teams	—	386	348	88	20	2	10	32	45	4	2	2	253	323	408	731	155	265	12	8	324	105	+2	-0	+8	+1	+8	2.0
2008	25	MLB RAW	2 teams	—	386	344	88	20	2	10	36	45	4	2	2	256	333	413	746	157	269	12	9	333	105	+2	-0	+8	+1	+8	2.0
2009	26	MLB MLE	Tampa Bay Rays	—	336	298	75	12	0	12	32	54	2	1	0	252	328	413	741	161	268	16	10	328	108	+3	+0	-7	-6	+7	-0.2
2009	26	MLB RAW	Tampa Bay Rays	—	336	296	75	12	0	12	34	54	2	1	0	253	334	416	750	162	270	16	10	333	108	+3	+0	-7	-6	+7	-0.2
2010	27	MLB MLE	2 teams	—	363	320	73	16	0	7	34	72	3	1	0	228	308	344	652	116	269	20	9	293	84	-7	+0	-1	+1	+8	0.1
2010	27	MLB RAW	2 teams	—	363	319	82	17	0	7	35	66	3	1	0	257	336	376	712	119	300	18	10	318	84	-7	+0	-1	+1	+8	0.1
2011	28	INTL MLE	Tigres del Licey	—	49	41	10	3	0	0	7	5	1	1	1	244	367	317	684	73	278	10	14	—	—	—	—	—	—	—	—
2011	28	INTL RAW	Tigres del Licey	—	49	41	10	3	0	0	7	5	1	1	1	244	367	317	684	73	278	10	14	323	104	—	—	—	—	—	—
2012	29	INTL MLE	2 teams	—	95	84	12	0	0	0	11	23	0	0	1	143	242	143	385		197	24	12	193	17	—	—	—	—	—	—
2012	29	INTL RAW	2 teams	—	95	86	19	1	0	0	9	17	0	0	1	221	295	233	527	12	275	18	9	251	17	—	—	—	—	—	—
2015	32	AAA MLE	Vaqueros de la Laguna	—	222	205	49	9	0	5	12	38	2	0	0	239	288	356	644	117	268	17	5	282	77	—	—	—	—	—	—
2015	32	AAA RAW	Vaqueros de la Laguna	—	222	194	57	11	0	7	23	30	2	0	0	294	374	459	833	165	314	14	10	367	77	—	—	—	—	—	—
2005	22	AAA MLE	2 teams	—	555	500	136	30	3	5	48	83	2	4	7	272	340	374	714	102	311	15	9	318	101	—	—	—	—	—	—
2006	23	MLB MLE	2 teams	—	512	457	131	30	1	13	45	68	5	2	5	287	357	442	799	155	309	13	9	349	123	—	—	—	—	—	—
2008	25	MLB MLE	2 teams	—	386	347	88	20	2	10	32	45	4	2	2	254	323	409	732	156	267	12	8	324	105	—	—	—	—	—	—
2009	26	MLB MLE	Tampa Bay Rays	—	336	299	75	12	0	12	32	54	2	1	0	251	328	411	740	161	270	16	10	328	108	—	—	—	—	—	—
2010	27	MLB MLE	2 teams	—	363	323	73	16	0	7	34	72	3	1	0	226	308	341	649	115	271	20	9	293	84	—	—	—	—	—	—
2012	29	INTL MLE	2 teams	—	95	84	12	0	0	0	11	23	0	0	1	143	242	143	385		200	24	12	193	17	—	—	—	—	—	—
2015	32	AAA MLE	Vaqueros de la Laguna	—	222	206	49	9	0	5	12	38	2	0	0	238	288	354	642	117	262	17	5	282	77	—	—	—	—	—	—
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	1390	1219	315	68	2	33	142	206	14	7	5	258	343	399	741	140	285	15	10	331	95	+17	-1	-0	+0	+30	4.8
/ 162G	—	A+C		—	650	570	147	32	1	15	66	96	7	3	2	258	342	396	739	139	285	15	10	331	95	+8	-0	-0	+0	+14	2.2
Career	—	MLE		—	2518	2250	574	120	6	52	221	388	19	11	16	255	327	383	710	128	285	15	9	309	95	+17	-1	-0	+0	+30	4.8
/ 162G	—	MLE		—	650	581	148	31	2	13	57	100	5	3	4	255	327	382	709	127	285	15	9	309	95	+8	-0	-0	+0	+14	2.2

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.

2015 AAAVaqueros de la Laguna · 222 PAwOBA .356 → .282 (−75)K% 13.5% → 17.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	13.51%	÷0.955	×1.200	—	—	16.99%
BB% (unintentional) /PA	9.01%	÷1.084	×0.690	—	×0.952	5.46%
HBP% /PA	0.90%	—	×0.940	—	×0.952	0.81%
Singles /BIP	23.78%	÷1.049	×0.930	×1.023	×0.952	20.54%
Doubles /BIP	6.71%	÷1.046	×0.830	×1.023	×0.952	5.18%
Triples /BIP	0.00%	÷1.080	×0.920	×1.023	×0.952	0.00%
Home runs /BIP	4.27%	÷1.006	×0.700	—	×0.952	2.83%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 101, 1B 110, 2B 109, 3B 116, K 91, BB 117 — 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 ×1.023.

Result: wOBA .356 → .282; ISO .165 → .120; BABIP .314 → .262. 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 AAADelfines de Ciudad del Carmen · 29 PAwOBA .240 → .193 (−47)K% 20.7% → 23.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.69%	÷1.040	×1.200	—	—	23.88%
BB% (unintentional) /PA	17.24%	÷1.015	×0.690	—	×0.982	11.51%
HBP% /PA	0.00%	—	×0.940	—	×0.982	0.00%
Singles /BIP	22.22%	÷1.017	×0.930	—	×0.982	19.95%
Doubles /BIP	0.00%	÷1.073	×0.830	—	×0.982	0.00%
Triples /BIP	0.00%	÷1.000	×0.920	—	×0.982	0.00%
Home runs /BIP	0.00%	÷0.889	×0.700	—	×0.982	0.00%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 78, 1B 103, 2B 114, 3B 100, K 108, BB 103 — 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).

Result: wOBA .240 → .193; ISO .000 → .000; BABIP .222 → .200. 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).

2008 AAADurham Bulls · 24 PAwOBA .381 → .333 (−48)K% 4.2% → 5.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	4.17%	÷1.000	×1.200	—	—	5.00%
BB% (unintentional) /PA	16.67%	÷1.000	×0.690	—	×1.033	11.88%
HBP% /PA	0.00%	—	×0.940	—	×1.033	0.00%
Singles /BIP	15.79%	÷1.000	×0.930	—	×1.033	15.17%
Doubles /BIP	15.79%	÷1.000	×0.830	—	×1.033	13.54%
Triples /BIP	0.00%	÷1.000	×0.970	—	×1.033	0.00%
Home runs /BIP	0.00%	÷1.000	×0.840	—	×1.033	0.00%

Factors used: league row IL. Park (home-season share, regressed): no park row on file (treated as neutral) — 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).

Result: wOBA .381 → .333; ISO .150 → .135; BABIP .316 → .287. 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).

2006 AAARichmond Braves · 234 PAwOBA .392 → .356 (−36)K% 11.5% → 13.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	11.54%	÷1.000	×1.200	—	—	13.85%
BB% (unintentional) /PA	9.83%	÷1.000	×0.690	—	×1.050	7.12%
HBP% /PA	0.43%	—	×0.940	—	×1.050	0.42%
Singles /BIP	22.78%	÷1.000	×0.930	×0.997	×1.050	22.18%
Doubles /BIP	7.22%	÷1.000	×0.830	×0.997	×1.050	6.28%
Triples /BIP	0.56%	÷1.000	×0.970	×0.997	×1.050	0.56%
Home runs /BIP	5.56%	÷1.000	×0.840	—	×1.050	4.90%

Factors used: league row IL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 23 vs a level average of 27.2 → +5.0% on BB/HBP/hit rates (4.2 yr younger than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.997.

Result: wOBA .392 → .356; ISO .217 → .196; BABIP .320 → .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).

2005 AAALas Vegas 51s · 450 PAwOBA .341 → .297 (−44)K% 12.4% → 16.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	12.44%	÷1.000	×1.290	—	—	16.05%
BB% (unintentional) /PA	8.89%	÷1.000	×0.710	—	×1.050	6.63%
HBP% /PA	0.22%	—	×0.980	—	×1.050	0.23%
Singles /BIP	24.35%	÷1.000	×0.900	×0.988	×1.050	22.73%
Doubles /BIP	7.54%	÷1.000	×0.810	×0.988	×1.050	6.33%
Triples /BIP	1.16%	÷1.000	×0.810	×0.988	×1.050	0.97%
Home runs /BIP	1.45%	÷1.000	×0.780	—	×1.050	1.19%

Factors used: league row PCL. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×0.988.

Result: wOBA .341 → .297; ISO .122 → .102; BABIP .329 → .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).

Not traceable per stint: some stints lack the counting stats the component translation needs. Level-wide factors that apply instead — .