Brian Burgamy

PosLF

B/TS/R

Born1981-06-27

Age (2027)46

No MLB projection yet. Career stats below are historical.

Overview

INTLLAST SEASON 2017

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2015	34	AAA/AA/INTL3 orgs	508	.270/.374/.440	17	0	103	—	.208/.278/.323
2016	35	AAA/INTL2 orgs	569	.292/.415/.491	18	9	97	—	.229/.303/.337
2017	36	INTLGigantes del …	33	.143/.250/.250	0	0	41	—

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	24	AA	Mobile BayBears	—	205	176	35	6	2	2	27	45	0	2	0	199	305	290	595	91	256	22	13	276	38	—	—	—	—	—	—
2005	24	A+	Lake Elsinore Storm	—	265	234	69	12	4	7	25	47	1	4	3	295	365	470	835	175	341	18	9	363	92	—	—	—	—	—	—
2006	25	AA	Reading Phillies	—	39	31	6	0	1	0	7	6	0	0	0	194	342	258	600	65	231	15	18	283	56	—	—	—	—	—	—
2006	25	A+	Clearwater Threshers	—	535	441	121	21	5	13	88	96	2	24	8	274	397	433	830	159	324	18	16	372	85	—	—	—	—	—	—
2007	26	AA	Reading Phillies	—	213	183	35	7	0	3	26	47	2	4	2	191	299	279	577	87	239	22	12	270	36	—	—	—	—	—	—
2007	26	A+	Clearwater Threshers	—	308	260	68	14	3	10	44	52	0	7	5	262	368	454	822	192	289	17	14	362	84	—	—	—	—	—	—
2008	27	A+	St. Lucie Mets	—	38	30	9	2	0	0	6	9	1	0	0	300	432	367	799	67	409	24	16	364	87	—	—	—	—	—	—
2011	30	INTL	Canberra Cavalry	—	200	164	67	8	0	12	34	20	1	2	2	409	513	677	1.189	268	414	10	17	511	232	—	—	—	—	—	—
2012	31	INTL	Venados de Mazatlan	—	63	57	12	2	0	0	5	8	0	0	0	211	274	246	520	35	245	13	8	240	48	—	—	—	—	—	—
2013	32	AAA	Piratas de Campeche	—	201	167	56	5	0	15	30	35	2	2	1	335	442	635	1.077	299	347	17	15	461	128	—	—	—	—	—	—
2013	32	INTL	Caneros de los Mochis	—	284	231	67	13	0	15	50	56	2	2	2	290	420	541	962	251	323	20	18	421	171	—	—	—	—	—	—
2014	33	AA	Binghamton Mets	—	527	450	124	32	1	23	71	101	3	6	2	276	378	504	882	229	307	19	13	387	89	—	—	—	—	—	—
2014	33	INTL	Toros del Este	—	219	178	42	6	1	2	37	55	1	0	2	236	370	315	685	79	331	25	17	319	102	—	—	—	—	—	—
2015	34	AAA	Oklahoma City Dodgers	—	52	46	7	3	0	0	6	13	0	0	1	152	250	217	467	65	212	25	12	224	-9	—	—	—	—	—	—
2015	34	AA	Tulsa Drillers	—	256	220	59	11	0	9	32	52	2	0	2	268	366	441	807	173	311	20	12	359	80	—	—	—	—	—	—
2015	34	INTL	Tiburones de La Guaira	—	200	168	51	7	1	8	30	40	2	0	1	304	415	500	915	196	358	20	15	407	161	—	—	—	—	—	—
2016	35	AAA	Rieleros de Aguascalientes	—	464	379	112	24	3	12	77	99	3	9	4	296	418	470	888	174	370	21	17	394	80	—	—	—	—	—	—
2016	35	INTL	Tiburones de La Guaira	—	105	87	24	7	1	6	18	23	0	0	0	276	400	586	986	310	310	22	17	426	174	—	—	—	—	—	—
2017	36	INTL	Gigantes del Cibao	—	33	28	4	3	0	0	4	9	0	0	0	143	250	250	500	107	200	27	12	229	41	—	—	—	—	—	—
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2005	24	AA MLE	Mobile BayBears	—	205	185	33	6	2	2	18	55	0	2	0	178	251	265	516	86	236	27	9	225	38	—	—	—	—	—	—
2005	24	A+ MLE	Lake Elsinore Storm	—	265	242	62	10	3	6	17	63	1	4	3	256	308	397	704	140	310	24	6	304	92	—	—	—	—	—	—
2006	25	AA MLE	Reading Phillies	—	39	33	6	0	1	0	5	7	0	0	0	182	289	242	532	61	223	18	13	251	56	—	—	—	—	—	—
2006	25	A+ MLE	Clearwater Threshers	—	535	467	104	19	4	11	62	136	2	24	8	223	316	351	668	128	283	25	12	294	85	—	—	—	—	—	—
2007	26	AA MLE	Reading Phillies	—	213	191	32	6	0	2	18	57	2	4	2	168	246	230	477	63	223	27	8	221	36	—	—	—	—	—	—
2007	26	A+ MLE	Clearwater Threshers	—	308	273	59	13	2	8	31	74	0	7	5	216	296	366	662	150	256	24	10	292	84	—	—	—	—	—	—
2008	27	A+ MLE	St. Lucie Mets	—	38	32	8	2	0	0	4	13	1	0	0	250	351	312	664	62	363	34	11	297	87	—	—	—	—	—	—
2013	32	AAA MLE	Piratas de Campeche	—	201	177	49	4	0	11	20	42	2	2	1	277	357	486	843	209	299	21	10	358	128	—	—	—	—	—	—
2014	33	AA MLE	Binghamton Mets	—	527	476	108	25	1	17	45	122	3	6	2	227	298	391	688	164	264	23	9	300	89	—	—	—	—	—	—
2015	34	AAA MLE	Oklahoma City Dodgers	—	52	48	5	2	0	0	4	17	0	0	1	104	173	146	319	42	172	33	8	155	-9	—	—	—	—	—	—
2015	34	AA MLE	Tulsa Drillers	—	256	231	53	9	0	7	21	64	2	0	2	229	299	359	659	130	279	25	8	286	80	—	—	—	—	—	—
2016	35	AAA MLE	Rieleros de Aguascalientes	—	464	415	95	20	2	7	41	126	3	9	4	229	303	337	640	108	303	27	9	287	80	—	—	—	—	—	—
2005	24	A+ MLE	2 teams	—	470	427	95	16	5	8	35	118	1	6	3	222	283	340	623	117	287	25	7	270	69	—	—	—	—	—	—
2005	24	A+ RAW	2 teams	—	470	410	104	18	6	9	52	92	1	6	3	254	339	393	732	139	305	20	11	325	69	—	—	—	—	—	—
2006	25	A+ MLE	2 teams	—	574	501	110	19	5	11	66	144	2	24	8	220	313	343	656	124	284	25	11	291	83	—	—	—	—	—	—
2006	25	A+ RAW	2 teams	—	574	472	127	21	6	13	95	102	2	24	8	269	394	422	815	153	318	18	17	366	83	—	—	—	—	—	—
2007	26	A+ MLE	2 teams	—	521	464	92	19	2	11	49	131	2	11	7	198	278	319	597	121	248	25	9	263	64	—	—	—	—	—	—
2007	26	A+ RAW	2 teams	—	521	443	103	21	3	13	70	99	2	11	7	233	340	381	721	149	269	19	13	324	64	—	—	—	—	—	—
2008	27	A+ MLE	St. Lucie Mets	—	38	32	8	2	0	0	4	13	1	0	0	250	351	312	664	62	400	34	11	297	87	—	—	—	—	—	—
2008	27	A+ RAW	St. Lucie Mets	—	38	30	9	2	0	0	6	9	1	0	0	300	432	367	799	67	409	24	16	364	87	—	—	—	—	—	—
2011	30	INTL MLE	Canberra Cavalry	—	200	164	67	8	0	12	34	20	1	2	2	409	513	677	1.189	268	414	10	17	—	—	—	—	—	—	—	—
2011	30	INTL RAW	Canberra Cavalry	—	200	164	67	8	0	12	34	20	1	2	2	409	513	677	1.189	268	414	10	17	511	232	—	—	—	—	—	—
2012	31	INTL MLE	Venados de Mazatlan	—	63	57	12	2	0	0	5	8	0	0	0	211	274	246	520	35	245	13	8	—	—	—	—	—	—	—	—
2012	31	INTL RAW	Venados de Mazatlan	—	63	57	12	2	0	0	5	8	0	0	0	211	274	246	520	35	245	13	8	240	48	—	—	—	—	—	—
2013	32	INTL MLE	2 teams	—	485	430	117	10	0	25	48	102	4	4	3	272	351	470	820	198	302	21	10	358	128	—	—	—	—	—	—
2013	32	INTL RAW	2 teams	—	485	398	123	18	0	30	80	91	4	4	3	309	429	580	1.010	271	333	19	16	437	128	—	—	—	—	—	—
2014	33	AA MLE	2 teams	—	746	673	152	36	1	24	63	172	4	6	4	226	296	389	685	163	267	23	8	300	89	—	—	—	—	—	—
2014	33	AA RAW	2 teams	—	746	628	166	38	2	25	108	156	4	6	4	264	376	451	826	186	313	21	14	367	89	—	—	—	—	—	—
2015	34	AA MLE	3 teams	—	508	461	95	18	0	11	41	134	4	0	4	206	277	317	593	111	264	26	8	264	65	—	—	—	—	—	—
2015	34	AA RAW	3 teams	—	508	434	117	21	1	17	68	105	4	0	4	270	374	440	814	171	318	21	13	364	65	—	—	—	—	—	—
2016	35	AAA MLE	2 teams	—	569	510	115	24	3	8	51	155	3	9	4	225	300	331	631	106	307	27	9	287	80	—	—	—	—	—	—
2016	35	AAA RAW	2 teams	—	569	466	136	31	4	18	95	122	3	9	4	292	415	491	906	200	360	21	17	400	80	—	—	—	—	—	—
2017	36	INTL MLE	Gigantes del Cibao	—	33	28	4	3	0	0	4	9	0	0	0	143	250	250	500	107	200	27	12	—	—	—	—	—	—	—	—
2017	36	INTL RAW	Gigantes del Cibao	—	33	28	4	3	0	0	4	9	0	0	0	143	250	250	500	107	200	27	12	229	41	—	—	—	—	—	—
2005	24	A+ MLE	2 teams	—	470	431	95	16	5	8	35	118	1	6	3	220	283	336	619	116	278	25	7	270	69	—	—	—	—	—	—
2006	25	A+ MLE	2 teams	—	574	501	110	19	5	11	66	144	2	24	8	220	313	343	656	124	279	25	11	291	83	—	—	—	—	—	—
2007	26	A+ MLE	2 teams	—	521	465	92	19	2	11	49	131	2	11	7	198	278	318	596	120	243	25	9	263	64	—	—	—	—	—	—
2008	27	A+ MLE	St. Lucie Mets	—	38	33	8	2	0	0	4	13	1	0	0	242	351	303	654	61	363	34	11	297	87	—	—	—	—	—	—
2013	32	INTL MLE	2 teams	—	485	430	117	10	0	25	48	102	4	4	3	272	351	470	820	198	299	21	10	358	128	—	—	—	—	—	—
2014	33	AA MLE	2 teams	—	746	673	152	36	1	24	63	172	4	6	4	226	296	389	685	163	264	23	8	300	89	—	—	—	—	—	—
2015	34	AA MLE	3 teams	—	508	458	95	18	0	11	41	134	4	0	4	207	277	319	595	111	261	26	8	264	65	—	—	—	—	—	—
2016	35	AAA MLE	2 teams	—	569	510	115	24	3	8	51	155	3	9	4	225	300	331	631	106	303	27	9	287	80	—	—	—	—	—	—
▸ Career Totals
Career	—	MLE		—	4207	3747	867	157	16	110	400	1006	22	62	35	231	309	370	679	139	286	24	10	270	69	-155	-2	+0	-45	+91	-11.3
/ 162G	—	MLE		—	650	579	133	24	2	17	62	155	3	10	5	230	307	366	674	136	283	24	10	270	69	-24	+0	+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.

2016 AAARieleros de Aguascalientes · 464 PAwOBA .379 → .287 (−92)K% 21.3% → 27.2%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	21.34%	÷0.941	×1.200	—	—	27.20%
BB% (unintentional) /PA	14.44%	÷1.053	×0.690	—	×0.940	8.89%
HBP% /PA	0.65%	—	×0.940	—	×0.940	0.57%
Singles /BIP	26.07%	÷1.053	×0.930	×1.031	×0.940	22.31%
Doubles /BIP	8.57%	÷1.035	×0.830	×1.031	×0.940	6.66%
Triples /BIP	1.07%	÷1.150	×0.920	×1.031	×0.940	0.83%
Home runs /BIP	4.29%	÷1.236	×0.700	—	×0.940	2.28%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 147, 1B 111, 2B 107, 3B 130, K 88, BB 111 — applied at half strength. Age: age 35 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (7.8 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.031.

Result: wOBA .379 → .287; ISO .174 → .118; BABIP .370 → .303. 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 · 256 PAwOBA .351 → .286 (−65)K% 20.3% → 25.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	20.31%	÷0.989	×1.220	—	—	25.06%
BB% (unintentional) /PA	12.11%	÷0.976	×0.700	—	×0.940	8.17%
HBP% /PA	0.78%	—	×0.870	—	×0.940	0.64%
Singles /BIP	23.21%	÷0.938	×0.920	×1.024	×0.940	21.90%
Doubles /BIP	6.55%	÷1.006	×0.840	×1.024	×0.940	5.26%
Triples /BIP	0.00%	÷0.900	×0.940	×1.024	×0.940	0.00%
Home runs /BIP	5.36%	÷1.039	×0.800	—	×0.940	3.88%

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 34 vs a level average of 24.8 → −6.0% on BB/HBP/hit rates (9.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.024.

Result: wOBA .351 → .286; ISO .173 → .130; BABIP .311 → .279. 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 · 52 PAwOBA .219 → .155 (−64)K% 25.0% → 32.8%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	25.00%	÷0.984	×1.290	—	—	32.77%
BB% (unintentional) /PA	11.54%	÷1.095	×0.710	—	×0.940	7.03%
HBP% /PA	0.00%	—	×0.980	—	×0.940	0.00%
Singles /BIP	12.12%	÷1.028	×0.900	—	×0.940	9.98%
Doubles /BIP	9.09%	÷0.965	×0.810	—	×0.940	7.17%
Triples /BIP	0.00%	÷0.941	×0.810	—	×0.940	0.00%
Home runs /BIP	0.00%	÷0.866	×0.780	—	×0.940	0.00%

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 34 vs a level average of 27.2 → −6.0% on BB/HBP/hit rates (6.8 yr older than average).

Result: wOBA .219 → .155; ISO .065 → .049; BABIP .212 → .172. 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 AABinghamton Mets · 527 PAwOBA .378 → .300 (−78)K% 19.2% → 23.1%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	19.17%	÷1.011	×1.220	—	—	23.13%
BB% (unintentional) /PA	13.28%	÷1.032	×0.700	—	×0.940	8.47%
HBP% /PA	0.57%	—	×0.850	—	×0.940	0.45%
Singles /BIP	19.48%	÷0.990	×0.970	×1.006	×0.940	18.04%
Doubles /BIP	9.17%	÷1.050	×0.860	×1.006	×0.940	7.10%
Triples /BIP	0.29%	÷1.036	×0.950	×1.006	×0.940	0.25%
Home runs /BIP	6.59%	÷1.009	×0.780	—	×0.940	4.79%

Factors used: league row EL. Park (home-season share, regressed): HR 102, 1B 98, 2B 110, 3B 107, K 102, BB 106 — applied at half strength. Age: age 33 vs a level average of 24.8 → −6.0% on BB/HBP/hit rates (8.2 yr older than average). Ground-ball/fly-ball mix moves 1B/2B/3B by ×1.006.

Result: wOBA .378 → .300; ISO .229 → .175; BABIP .307 → .264. 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 AAAPiratas de Campeche · 201 PAwOBA .449 → .358 (−91)K% 17.4% → 21.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	17.41%	÷0.996	×1.200	—	—	20.97%
BB% (unintentional) /PA	14.43%	÷0.959	×0.690	—	×0.952	9.88%
HBP% /PA	1.00%	—	×0.940	—	×0.952	0.89%
Singles /BIP	27.27%	÷0.990	×0.930	×1.016	×0.952	24.78%
Doubles /BIP	3.79%	÷0.994	×0.830	×1.016	×0.952	3.06%
Triples /BIP	0.00%	÷1.150	×0.920	×1.016	×0.952	0.00%
Home runs /BIP	11.36%	÷0.988	×0.700	—	×0.952	7.67%

Factors used: level-wide AAA factors (no league-specific row for this league/era). Park (home-season share, regressed): HR 98, 1B 98, 2B 99, 3B 130, K 99, BB 92 — 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 ×1.016.

Result: wOBA .449 → .358; ISO .299 → .214; BABIP .347 → .299. 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 A+St. Lucie Mets · 38 PAwOBA .365 → .297 (−69)K% 23.7% → 33.6%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	23.68%	÷1.000	×1.420	—	—	33.63%
BB% (unintentional) /PA	15.79%	÷1.000	×0.750	—	×0.958	11.34%
HBP% /PA	2.63%	—	×0.930	—	×0.958	2.34%
Singles /BIP	33.33%	÷1.000	×0.920	—	×0.958	29.38%
Doubles /BIP	9.52%	÷1.000	×0.960	—	×0.958	8.76%
Triples /BIP	0.00%	÷1.000	×0.810	—	×0.958	0.00%
Home runs /BIP	0.00%	÷1.000	×0.880	—	×0.958	0.00%

Factors used: league row FSL. Park (home-season share, regressed): no park row on file (treated as neutral) — applied at half strength. Age: age 27 vs a level average of 22.8 → −4.2% on BB/HBP/hit rates (4.2 yr older than average).

Result: wOBA .365 → .297; ISO .067 → .058; BABIP .409 → .363. 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).

2007 A+Clearwater Threshers · 308 PAwOBA .355 → .292 (−63)K% 16.9% → 24.0%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	16.88%	÷1.000	×1.420	—	—	23.97%
BB% (unintentional) /PA	13.96%	÷1.000	×0.750	—	×0.968	10.14%
HBP% /PA	0.00%	—	×0.930	—	×0.968	0.00%
Singles /BIP	19.71%	÷1.000	×0.920	×0.999	×0.968	17.53%
Doubles /BIP	6.73%	÷1.000	×0.960	×0.999	×0.968	6.25%
Triples /BIP	1.44%	÷1.000	×0.810	×0.999	×0.968	1.13%
Home runs /BIP	4.81%	÷1.000	×0.880	—	×0.968	4.10%

Factors used: league row FSL. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×0.999.

Result: wOBA .355 → .292; ISO .192 → .162; BABIP .289 → .256. 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).

2007 AAReading Phillies · 213 PAwOBA .265 → .221 (−44)K% 22.1% → 26.9%

Component	Raw	Park ÷	Level factor ×	GB/FB ×	Age ×	= MLE
K% /PA	22.07%	÷1.000	×1.220	—	—	26.92%
BB% (unintentional) /PA	12.21%	÷1.000	×0.700	—	×0.988	8.44%
HBP% /PA	0.94%	—	×0.850	—	×0.988	0.79%
Singles /BIP	18.38%	÷1.000	×0.970	×1.004	×0.988	17.69%
Doubles /BIP	5.15%	÷1.000	×0.860	×1.004	×0.988	4.39%
Triples /BIP	0.00%	÷1.000	×0.950	×1.004	×0.988	0.00%
Home runs /BIP	2.21%	÷1.000	×0.780	—	×0.988	1.70%

Factors used: league row EL. Park (home-season share, regressed): no park row on file (treated as neutral) — 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 ×1.004.

Result: wOBA .265 → .221; ISO .087 → .071; BABIP .239 → .223. 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 — .