Daniel Carbonell

PosLF

B/TR/R

Born1991-03-29

Age (2027)36

No MLB projection yet. Career stats below are historical.

Overview

AAALAST SEASON 2019

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2017	26	AA/A+SF	364	.268/.311/.422	8	8	65	—	.227/.261/.352
2018	27	AA/INTL2 orgs	66	.153/.219/.220	0	1	18	—	.067/.125/.067
2019	28	AAA/INTL2 orgs	571	.308/.389/.515	19	33	108	—	.267/.320/.433

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)
2014	23	A+	San Jose Giants	—	100	93	32	3	3	3	6	19	1	7	2	344	390	538	928	194	408	19	6	407	114	—	—	—	—	—	—
2014	23	ROK	AZL Giants	—	38	35	11	3	0	1	2	4	1	4	0	314	368	486	854	171	333	11	5	379	66	—	—	—	—	—	—
2014	23	INTL	Scottsdale Scorpions	—	60	58	11	0	1	1	2	16	0	0	1	190	217	276	493	86	244	27	3	221	35	—	—	—	—	—	—
2015	24	AA	Richmond Flying Squirrels	—	214	206	30	3	2	1	4	53	3	9	1	146	174	194	368	49	190	25	2	168	-18	—	—	—	—	—	—
2015	24	A+	San Jose Giants	—	282	258	72	14	2	6	13	51	7	9	7	279	331	419	750	140	324	18	5	330	67	—	—	—	—	—	—
2016	25	A+	San Jose Giants	—	235	211	60	12	0	3	17	51	4	11	5	284	349	384	733	100	361	22	7	328	60	—	—	—	—	—	—
2016	25	INTL	Tomateros de Culiacan	—	97	92	24	4	2	2	3	20	0	1	1	261	284	413	697	152	310	21	3	300	89	—	—	—	—	—	—
2017	26	AA	Richmond Flying Squirrels	—	207	191	46	11	1	4	11	40	2	5	2	241	289	372	661	131	282	19	5	292	53	—	—	—	—	—	—
2017	26	A+	San Jose Giants	—	157	148	45	13	1	4	5	31	3	3	2	304	340	486	826	182	360	20	3	362	80	—	—	—	—	—	—
2018	27	AA	Richmond Flying Squirrels	—	17	14	1	0	0	0	2	6	0	0	0	71	188	71	259		111	35	12	135	-37	—	—	—	—	—	—
2018	27	INTL	Charros de Jalisco	—	49	45	8	4	0	0	2	12	1	1	1	178	229	267	496	89	242	24	4	222	37	—	—	—	—	—	—
2019	28	AAA	Olmecas de Tabasco	—	468	411	134	25	6	16	43	85	6	28	5	326	398	533	931	207	372	18	9	402	105	—	—	—	—	—	—
2019	28	INTL	Tigres de Aragua	—	103	86	19	5	2	3	17	16	0	5	1	221	350	430	780	209	239	16	17	349	122	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2014	23	A+ MLE	San Jose Giants	—	100	95	27	2	2	3	4	25	1	7	2	284	320	442	762	158	371	25	4	336	114	—	—	—	—	—	—
2014	23	ROK MLE	AZL Giants	—	38	36	8	2	0	1	1	6	1	4	0	222	263	361	624	139	252	16	3	266	66	—	—	—	—	—	—
2015	24	AA MLE	Richmond Flying Squirrels	—	214	207	27	2	2	1	3	64	3	9	1	130	155	174	329	43	178	30	1	142	-18	—	—	—	—	—	—
2015	24	A+ MLE	San Jose Giants	—	282	262	61	10	1	5	9	70	7	9	7	233	277	336	613	103	288	25	3	267	67	—	—	—	—	—	—
2016	25	A+ MLE	San Jose Giants	—	235	216	49	10	0	2	12	68	4	11	5	227	280	301	581	74	312	29	5	257	60	—	—	—	—	—	—
2017	26	AA MLE	Richmond Flying Squirrels	—	207	195	41	8	1	4	7	52	2	5	2	210	245	323	568	113	261	25	3	247	53	—	—	—	—	—	—
2017	26	A+ MLE	San Jose Giants	—	157	149	37	10	1	3	4	41	3	3	2	248	282	389	671	141	312	26	3	286	80	—	—	—	—	—	—
2018	27	AA MLE	Richmond Flying Squirrels	—	17	15	1	0	0	0	1	7	0	0	0	67	125	67	192		106	41	6	113	-37	—	—	—	—	—	—
2019	28	AAA MLE	Olmecas de Tabasco	—	468	427	114	22	5	13	27	102	6	28	5	267	320	433	753	166	309	22	6	324	105	—	—	—	—	—	—
2014	23	A+ MLE	3 teams	—	198	188	52	7	3	5	8	44	2	11	3	277	313	426	739	149	338	22	4	317	100	—	—	—	—	—	—
2014	23	A+ RAW	3 teams	—	198	186	54	6	4	5	10	39	2	11	3	290	333	446	780	156	345	20	5	345	100	—	—	—	—	—	—
2015	24	A+ MLE	2 teams	—	496	469	88	13	3	6	12	134	10	18	8	188	224	267	491	79	246	27	2	213	30	—	—	—	—	—	—
2015	24	A+ RAW	2 teams	—	496	464	102	17	4	7	17	104	10	18	8	220	263	319	582	99	266	21	3	260	30	—	—	—	—	—	—
2016	25	A+ MLE	2 teams	—	332	306	69	13	0	3	17	97	4	12	6	225	275	297	573	72	317	29	5	257	60	—	—	—	—	—	—
2016	25	A+ RAW	2 teams	—	332	303	84	16	2	5	20	71	4	12	6	277	330	393	723	116	345	21	6	320	60	—	—	—	—	—	—
2017	26	AA MLE	2 teams	—	364	344	79	18	2	7	11	92	5	8	4	230	264	355	619	125	290	25	3	264	65	—	—	—	—	—	—
2017	26	AA RAW	2 teams	—	364	339	91	24	2	8	16	71	5	8	4	268	311	422	733	153	316	20	4	322	65	—	—	—	—	—	—
2018	27	INTL MLE	2 teams	—	66	58	4	0	0	0	5	29	1	1	1	69	156	69	225		133	44	8	113	-37	—	—	—	—	—	—
2018	27	INTL RAW	2 teams	—	66	59	9	4	0	0	4	18	1	1	1	153	219	220	439	68	214	27	6	200	-37	—	—	—	—	—	—
2019	28	AAA MLE	2 teams	—	571	524	139	27	6	16	33	125	6	33	6	265	316	431	747	166	315	22	6	324	105	—	—	—	—	—	—
2019	28	AAA RAW	2 teams	—	571	497	153	30	8	19	60	101	6	33	6	308	389	515	904	207	349	18	11	393	105	—	—	—	—	—	—
2014	23	A+ MLE	3 teams	—	198	186	52	7	3	5	8	44	2	11	3	280	313	430	743	151	338	22	4	317	100	—	—	—	—	—	—
2015	24	A+ MLE	2 teams	—	496	471	88	13	3	6	12	134	10	18	8	187	224	265	489	79	241	27	2	213	30	—	—	—	—	—	—
2016	25	A+ MLE	2 teams	—	332	308	69	13	0	3	17	97	4	12	6	224	275	295	571	71	312	29	5	257	60	—	—	—	—	—	—
2017	26	AA MLE	2 teams	—	364	345	79	18	2	7	11	92	5	8	4	229	264	354	618	125	283	25	3	264	65	—	—	—	—	—	—
2018	27	INTL MLE	2 teams	—	66	60	4	0	0	0	5	29	1	1	1	67	156	67	223		106	44	8	113	-37	—	—	—	—	—	—
2019	28	AAA MLE	2 teams	—	571	527	139	27	6	16	33	125	6	33	6	264	316	429	745	165	309	22	6	324	105	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	2027	1889	431	78	14	37	86	521	28	83	28	228	272	343	615	115	292	26	4	267	67	-79	+5	+0	-22	+44	-5.3
/ 162G	—	MLE		—	650	606	138	25	4	12	28	167	9	27	9	228	272	342	614	114	292	26	4	267	67	-25	+2	+0	-7	+14	-1.7

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 AAAOlmecas de Tabasco · 468 PAwOBA .397 → .324 (−73)K% 18.2% → 21.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.16%	÷0.994	×1.200	—	—	21.92%
BB% (unintentional) /PA	9.19%	÷1.078	×0.690	—	×0.992	5.83%
HBP% /PA	1.28%	—	×0.940	—	×0.992	1.20%
Singles /BIP	26.69%	÷1.056	×0.930	×0.950	×0.992	22.15%
Doubles /BIP	7.67%	÷0.900	×0.830	×0.950	×0.992	6.67%
Triples /BIP	1.84%	÷1.057	×0.920	×0.950	×0.992	1.51%
Home runs /BIP	4.91%	÷0.865	×0.700	—	×0.992	3.94%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 73, 1B 111, 2B 80, 3B 111, K 99, BB 116 — 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 .397 → .324; ISO .207 → .174; BABIP .372 → .309. 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 AARichmond Flying Squirrels · 17 PAwOBA .141 → .113 (−28)K% 35.3% → 44.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	35.29%	÷0.975	×1.220	—	—	44.14%
BB% (unintentional) /PA	11.76%	÷0.983	×0.700	—	×0.978	8.19%
HBP% /PA	0.00%	—	×0.850	—	×0.978	0.00%
Singles /BIP	12.50%	÷0.995	×0.970	—	×0.978	11.92%
Doubles /BIP	0.00%	÷0.949	×0.860	—	×0.978	0.00%
Triples /BIP	0.00%	÷1.150	×0.950	—	×0.978	0.00%
Home runs /BIP	0.00%	÷0.869	×0.780	—	×0.978	0.00%

Factors used: league row EL. Park (home-season share, regressed): HR 74, 1B 99, 2B 90, 3B 130, K 95, BB 97 — 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).

Result: wOBA .141 → .113; ISO .000 → .000; BABIP .111 → .106. 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 AARichmond Flying Squirrels · 207 PAwOBA .284 → .247 (−37)K% 19.3% → 24.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.32%	÷0.948	×1.220	—	—	24.87%
BB% (unintentional) /PA	4.83%	÷0.974	×0.700	—	×0.988	3.43%
HBP% /PA	0.97%	—	×0.850	—	×0.988	0.81%
Singles /BIP	19.87%	÷1.004	×0.970	×1.022	×0.988	19.38%
Doubles /BIP	7.28%	÷1.096	×0.860	×1.022	×0.988	5.77%
Triples /BIP	0.66%	÷0.900	×0.950	×1.022	×0.988	0.71%
Home runs /BIP	2.65%	÷0.848	×0.780	—	×0.988	2.41%

Factors used: league row EL. Park (home-season share, regressed): HR 70, 1B 101, 2B 119, 3B 80, K 90, 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 ×1.022.

Result: wOBA .284 → .247; ISO .131 → .111; BABIP .282 → .261. 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+San Jose Giants · 157 PAwOBA .353 → .286 (−68)K% 19.7% → 26.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.75%	÷1.018	×1.340	—	—	25.98%
BB% (unintentional) /PA	3.18%	÷0.968	×0.710	—	×0.968	2.26%
HBP% /PA	1.91%	—	×0.790	—	×0.968	1.46%
Singles /BIP	23.08%	÷0.990	×0.910	×1.020	×0.968	20.94%
Doubles /BIP	11.11%	÷1.008	×0.820	×1.020	×0.968	8.92%
Triples /BIP	0.85%	÷0.900	×0.760	×1.020	×0.968	0.71%
Home runs /BIP	3.42%	÷1.010	×0.920	—	×0.968	3.01%

Factors used: league row CAL. Park (home-season share, regressed): HR 102, 1B 98, 2B 102, 3B 80, K 104, BB 94 — applied at half strength. Age: age 26 vs a level average of 22.8 → −3.2% on BB/HBP/hit rates (3.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.020.

Result: wOBA .353 → .286; ISO .182 → .145; BABIP .360 → .312. 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+San Jose Giants · 235 PAwOBA .321 → .257 (−65)K% 21.7% → 29.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.70%	÷0.998	×1.340	—	—	29.15%
BB% (unintentional) /PA	7.23%	÷0.992	×0.710	—	×0.978	5.06%
HBP% /PA	1.70%	—	×0.790	—	×0.978	1.32%
Singles /BIP	28.12%	÷1.008	×0.910	×0.992	×0.978	24.64%
Doubles /BIP	7.50%	÷0.951	×0.820	×0.992	×0.978	6.27%
Triples /BIP	0.00%	÷0.900	×0.760	×0.992	×0.978	0.00%
Home runs /BIP	1.88%	÷1.045	×0.920	—	×0.978	1.61%

Factors used: league row CAL. Park (home-season share, regressed): HR 109, 1B 102, 2B 90, 3B 80, K 100, BB 98 — applied at half strength. Age: age 25 vs a level average of 22.8 → −2.2% on BB/HBP/hit rates (2.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×0.992.

Result: wOBA .321 → .257; ISO .100 → .080; BABIP .361 → .312. 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+San Jose Giants · 282 PAwOBA .325 → .267 (−58)K% 18.1% → 24.7%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	18.09%	÷0.983	×1.340	—	—	24.65%
BB% (unintentional) /PA	4.61%	÷0.996	×0.710	—	×0.988	3.25%
HBP% /PA	2.48%	—	×0.790	—	×0.988	1.94%
Singles /BIP	24.15%	÷0.971	×0.910	×1.013	×0.988	22.65%
Doubles /BIP	6.76%	÷1.071	×0.820	×1.013	×0.988	5.18%
Triples /BIP	0.97%	÷1.150	×0.760	×1.013	×0.988	0.64%
Home runs /BIP	2.90%	÷1.031	×0.920	—	×0.988	2.56%

Factors used: league row CAL. Park (home-season share, regressed): HR 106, 1B 94, 2B 114, 3B 130, K 97, 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 ×1.013.

Result: wOBA .325 → .267; ISO .140 → .108; BABIP .324 → .288. 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 AARichmond Flying Squirrels · 214 PAwOBA .164 → .142 (−22)K% 24.8% → 30.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	24.77%	÷1.003	×1.220	—	—	30.14%
BB% (unintentional) /PA	1.87%	÷0.992	×0.700	—	×1.012	1.33%
HBP% /PA	1.40%	—	×0.850	—	×1.012	1.21%
Singles /BIP	15.69%	÷1.013	×0.970	×0.984	×1.012	14.96%
Doubles /BIP	1.96%	÷0.998	×0.860	×0.984	×1.012	1.68%
Triples /BIP	1.31%	÷1.025	×0.950	×0.984	×1.012	1.21%
Home runs /BIP	0.65%	÷0.860	×0.780	—	×1.012	0.60%

Factors used: league row EL. Park (home-season share, regressed): HR 72, 1B 103, 2B 100, 3B 105, K 101, BB 98 — 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 ×0.984.

Result: wOBA .164 → .142; ISO .049 → .041; BABIP .190 → .178. 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 A+San Jose Giants · 100 PAwOBA .396 → .336 (−60)K% 19.0% → 24.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.00%	÷1.026	×1.340	—	—	24.83%
BB% (unintentional) /PA	6.00%	÷1.009	×0.710	—	×0.998	4.21%
HBP% /PA	1.00%	—	×0.790	—	×0.998	0.79%
Singles /BIP	31.08%	÷0.996	×0.910	×1.020	×0.998	28.89%
Doubles /BIP	4.05%	÷0.953	×0.820	×1.020	×0.998	3.55%
Triples /BIP	4.05%	÷0.979	×0.760	×1.020	×0.998	3.20%
Home runs /BIP	4.05%	÷0.931	×0.920	—	×0.998	4.00%

Factors used: league row CAL. Park (home-season share, regressed): HR 86, 1B 99, 2B 91, 3B 96, K 105, 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 ×1.020.

Result: wOBA .396 → .336; ISO .194 → .166; BABIP .408 → .371. 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 — .