Matthew Wood — OGILVIE

Matthew WoodC Biloxi Shuckers

Age 25 L/R 5'10" / 191 lbs AA HR +10%K +6% Svc 0.0 · Ctrl thru 2032

2026 ROS PROJECTION386 act + 9 ros · stats below = ROS only

showingROS

wRC+†94

AVG/OBP/SLG.125 / .222 / .125

PA9

HR0

K%22

BB%11

BABIP242

ISO106

MLB%2%

Value2026 · WAR

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$19M ctrl surplus

Tools · ContractCON 40 / POW 35

Toolsscout grade

CONTACT40

scouting grade only

POWER35

scouting grade only

EYE55

scouting grade only

SPEED30

scouting grade only

DEFENSE45

scouting grade only

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status MiLB

MLB Debut 2027

Service 0 yrs (est)

Team Control Through 2032

First FA Year 2033

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2027
2027	Pre-Arb	$0.8M	+0.5	$2M	+$1M
2028	Pre-Arb	$0.8M	+0.8	$3M	+$2M
2029	Pre-Arb	$0.8M	+0.9	$3M	+$2M
2030	Arb-1	$3M	+0.8	$2M	+$0.5M
2031	Arb-2	$4M	+0.7	$2M	+$0.0M (cut)
2032	Arb-3	$5M	+0.5	$1M	+$0.0M (cut)
Totals		$5M		$13M	+$6M

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. 2026 = actual YTD + projected ROS + total. 2027+ via Advanced Marcel + aging curve. Catcher framing: only 2026 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 below FG-DC by 1-3 WAR.

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)
2023	22	A+	Wisconsin Timber Rattlers	—	361	306	74	8	1	1	47	53	5	2	1	242	352	284	636	42	286	15	13	300	89	-5	+0	—	—	+8	0.3
2023	22	A	Carolina Mudcats	—	109	82	24	7	0	3	26	15	1	1	0	293	468	488	956	195	328	14	24	429	177	+10	+0	—	—	+2	1.3
2024	23	A+	Wisconsin Timber Rattlers	—	379	319	75	15	2	4	47	52	9	2	1	235	349	332	682	97	266	14	12	314	99	-1	+0	—	—	+8	0.8
2025	24	AA	Biloxi Shuckers	—	245	207	56	12	0	6	30	33	5	8	1	271	376	415	791	145	292	13	12	355	126	+8	+1	—	—	+5	1.4
2025	24	A+	Wisconsin Timber Rattlers	—	116	90	20	4	0	1	20	18	3	2	1	222	377	300	677	78	260	16	17	319	102	+0	+0	—	—	+3	0.3
▸ Career — adjusted (every ACTUAL line translated to park/league-neutral MLB equivalents)
2023	22	A+ MLE	Wisconsin Timber Rattlers	—	361	321	65	7	1	1	32	75	5	2	1	202	285	240	525	37	250	21	9	238	47	-23	+0	—	—	+8	-1.5
2023	22	A MLE	Carolina Mudcats	—	109	92	21	5	0	3	16	21	1	1	0	228	349	380	729	152	263	19	15	318	101	+0	+0	—	—	+2	0.3
2024	23	A+ MLE	Wisconsin Timber Rattlers	—	379	333	63	12	1	3	33	71	9	2	1	189	280	258	538	69	224	19	9	249	55	-20	+0	—	—	+8	-1.2
2025	24	AA MLE	Biloxi Shuckers	—	245	217	49	9	0	4	20	43	5	8	1	226	306	323	628	97	256	18	8	283	78	-7	+1	—	—	+5	-0.0
2025	24	A+ MLE	Wisconsin Timber Rattlers	—	116	96	17	3	0	1	15	26	3	2	1	177	307	240	547	62	221	22	13	254	58	-6	+0	—	—	+3	-0.3
2023	22	A+ MLE	2 teams	—	470	413	84	12	1	3	48	97	6	3	1	203	296	259	555	56	256	21	10	257	60	—	—	—	—	—	—
2023	22	A+ RAW	2 teams	—	470	388	98	15	1	4	73	68	6	3	1	253	379	327	706	75	295	14	16	330	60	—	—	—	—	—	—
2024	23	A+ MLE	Wisconsin Timber Rattlers	—	379	333	63	12	1	3	33	71	9	2	1	189	280	258	538	69	228	19	9	249	55	—	—	—	—	—	—
2024	23	A+ RAW	Wisconsin Timber Rattlers	—	379	319	75	15	2	4	47	52	9	2	1	235	349	332	682	97	266	14	12	314	55	—	—	—	—	—	—
2025	24	AA MLE	2 teams	—	361	313	67	13	0	5	35	69	8	10	2	214	309	304	613	89	254	19	10	274	71	—	—	—	—	—	—
2025	24	AA RAW	2 teams	—	361	297	76	16	0	7	50	51	8	10	2	256	376	380	757	125	283	14	14	343	71	—	—	—	—	—	—
2023	22	A+ MLE	2 teams	—	470	413	84	12	1	3	48	97	6	3	1	203	296	259	555	56	253	21	10	257	60	—	—	—	—	—	—
2024	23	A+ MLE	Wisconsin Timber Rattlers	—	379	334	63	12	1	3	33	71	9	2	1	189	280	257	537	69	224	19	9	249	55	—	—	—	—	—	—
2025	24	AA MLE	2 teams	—	361	315	67	13	0	5	35	69	8	10	2	213	309	302	611	89	245	19	10	274	71	—	—	—	—	—	—
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2023	22	A+ MLE	2 teams	—	470	413	84	12	1	3	48	97	6	3	1	203	296	259	555	56	253	21	10	257	60	—	—	—	—	—	—
2024	23	A+ MLE	Wisconsin Timber Rattlers	—	379	334	63	12	1	3	33	71	9	2	1	189	280	257	537	69	224	19	9	249	55	—	—	—	—	—	—
2025	24	AA MLE	2 teams	—	361	315	67	13	0	5	35	69	8	10	2	213	309	302	611	89	245	19	10	274	71	—	—	—	—	—	—
YTD	25	AA MLE	MIL	—	386	326	73	12	2	15	49	63	4	3	2	224	332	411	743	187	228	16	13	323	105	+2	-0	+0	+7	+8	1.8
▸ 2026 season
YTD	25	AA RAW	MIL	—	386	303	78	13	2	18	71	52	4	3	2	257	404	492	895	234	251	13	18	390	105	—	—	—	—	—	—
ROS	25	AA MLE	MIL	2%	9	8	1	0	0	0	1	2	0	0	0	125	222	125	347		243	22	11	307	94	-0	+0	-0	+0	+0	0.0
TOT	25	AA MLE	MIL	—	395	334	74	12	2	15	50	65	4	3	2	222	330	404	734	183	227	16	13	323	104	+2	-0	-0	+7	+9	1.8
▸ Career projection (2027+) — MLB context, MLB playing time (PA × MLB%)
2027	26	MLB MLE	MIL	43%	360	313	69	12	1	10	40	65	4	3	1	220	317	361	678	141	247	18	11	309	95	-2	+0	-0	+6	+8	1.3
2028	27	MLB MLE	MIL	59%	385	334	74	13	1	11	43	71	5	3	1	222	319	365	685	144	250	18	11	311	96	-2	+0	-0	+7	+8	1.4
2029	28	MLB MLE	MIL	67%	398	346	78	14	2	11	44	75	5	3	1	225	322	373	694	147	252	19	11	310	96	-2	+0	-1	+7	+9	1.3
2030	29	MLB MLE	MIL	69%	399	347	77	14	1	11	44	76	5	3	1	222	318	363	681	141	252	19	11	309	95	-2	+0	-2	+7	+9	1.2
2031	30	MLB MLE	MIL	70%	397	345	76	13	1	11	44	77	5	3	1	220	317	359	677	139	250	19	11	306	93	-3	+0	-2	+7	+9	1.1
2032	31	MLB MLE	MIL	71%	374	326	70	12	1	10	41	73	4	2	1	215	310	350	660	135	248	20	11	302	90	-4	+0	-3	+7	+8	0.8
2033	32	MLB MLE	MIL	78%	347	302	64	11	1	9	38	70	4	2	1	212	308	344	653	132	245	20	11	296	87	-6	+0	-4	+6	+8	0.5
2034	33	MLB MLE	MIL	82%	310	270	55	9	1	7	34	64	3	1	1	204	300	322	622	119	241	21	11	289	82	-7	-0	-4	+6	+7	0.1
2035	34	MLB MLE	MIL	78%	262	228	46	7	1	6	29	56	3	1	0	202	300	320	620	118	235	21	11	281	76	-7	+0	-5	+5	+6	-0.2
2027	26	MLB CTX	MIL	43%	155	135	31	5	1	5	17	28	2	1	1	230	325	393	717	163	246	18	11	302	95	-1	-0	-0	+3	+3	0.5
2028	27	MLB CTX	MIL	59%	226	196	45	8	1	7	25	42	3	2	1	230	326	388	714	158	249	19	11	303	96	-1	+0	-0	+4	+5	0.8
2029	28	MLB CTX	MIL	67%	267	232	52	9	1	8	30	50	3	2	1	224	321	375	696	151	250	19	11	303	96	-1	+0	-1	+5	+6	0.9
2030	29	MLB CTX	MIL	69%	275	240	53	9	1	8	30	52	3	2	1	221	315	367	682	146	250	19	11	302	95	-2	+0	-1	+5	+6	0.8
2031	30	MLB CTX	MIL	70%	279	243	53	9	1	8	31	54	3	2	1	218	314	362	676	144	249	19	11	299	93	-2	+0	-2	+5	+6	0.7
2032	31	MLB CTX	MIL	71%	265	231	50	9	1	7	29	52	3	2	1	216	312	355	667	139	247	20	11	295	90	-3	+0	-2	+5	+6	0.5
2033	32	MLB CTX	MIL	78%	269	234	49	8	1	7	30	54	3	1	1	209	307	342	649	132	243	20	11	289	87	-4	-0	-3	+5	+6	0.3
2034	33	MLB CTX	MIL	82%	254	221	46	8	1	6	28	52	3	1	0	208	306	335	640	127	240	20	11	283	82	-5	+0	-4	+5	+6	0.1
2035	34	MLB CTX	MIL	78%	203	177	36	6	1	5	22	43	2	1	0	203	299	333	632	130	234	21	11	274	76	-6	+0	-4	+4	+4	-0.1
▸ Career Totals
▸ Career totals — MLB only (actual + projected)
Career	—	A+C		—	2193	1909	415	71	9	61	242	427	25	14	7	217	313	360	673	142	248	19	11	295	83	-25	+0	-16	+39	+48	4.6
/ 162G	—	A+C		—	650	566	123	21	3	18	72	127	7	4	2	217	313	360	674	143	248	20	11	295	83	-8	+0	-5	+12	+14	1.4
Career	—	MLE		—	4451	3878	824	142	12	97	474	866	61	36	12	212	308	330	638	118	247	19	11	291	83	-35	+1	-22	+58	+70	7.4
/ 162G	—	MLE		—	650	566	121	21	2	14	69	126	9	5	2	214	309	332	641	118	249	19	11	291	83	-7	+0	-4	+12	+14	1.5

PLAYER · career totals + /162 games	162s	PA	HR	SB	AVG	OBP	SLG	POS	FLD	WAR	JAWS
#1John Bucklast yr '14 career totals — 11 seasons, 4,009 PA	6.0	4,009	134	6	234	301	398	+72	+7	16.9	15.7
/162	664	22	1	+11.9	+1.2	2.8	pk7: 14
#2Jarrod Saltalamacchialast yr '16 career totals — 9 seasons, 3,127 PA	4.7	3,127	110	5	235	308	414	+56	-10	14.1	14.8
/162	664	23	1	+11.9	-2.1	3.0	pk7: 16
#3Robinson Chirinoslast yr '22 career totals — 10 seasons, 2,427 PA	3.7	2,427	95	5	227	320	420	+43	-10	12.9	13.8
/162	664	26	1	+11.9	-2.8	3.5	pk7: 15
#4Kelly Shoppachlast yr '13 career totals — 8 seasons, 1,839 PA	2.8	1,839	70	1	225	314	417	+33	+14	11.3	11.5
/162	664	25	0	+11.9	+5.0	4.1	pk7: 12
#5Stephen Vogtlast yr '22 career totals — 9 seasons, 2,571 PA	3.9	2,571	82	5	241	303	410	+36	-11	9.3	9.4
/162	664	21	1	+9.2	-2.8	2.4	pk7: 9
OGOGILVIE CAREER PROJECTION career totals — every cell rolls up across 6 projected seasons	3.3	2,200	57	14	218	310	354	+39	-12	7.2	6.8
/162	664	17	4	+11.9	-3.6	2.2	pk7: 6
#6Devin Mesoracolast yr '18 career totals — 8 seasons, 1,574 PA	2.4	1,574	58	4	232	309	406	+28	-13	6.0	6.2
/162	664	24	2	+11.9	-5.3	2.5	pk7: 6

Career Path Comps

What happened to players with a similar stat profile at this age · Y-axis: wRC+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

		Scouting				At Match Age									Next 3 Yrs									Peak 3 Yrs
Comp	Age	HIT	PWR	SPD	EYE	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR	AVG/OBP/SLG	ISO	BABIP	HR	SB	K%	BB%	wRC+	WAR
Matthew Wood (OGILVIE)	25	30→40	35	30	55	217/316/357	139	243	9	3	18%	11%	94	+0.5	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—	—
✕Kris Watts 2009 · AA	25	47→53	43→45	38→30	47	227/280/340	113	265	9	3	18%	6%	75	-0.5	237/310/348	111	278	9	3	17%	8%	88	+0.5	237/319/345	108	278	9	1	17%	8%	90	+0.3
✕Zach Dillon 2008 · A	25	49	42→45	37→30	50	237/294/349	113	272	8	3	16%	7%	82	-0.0	227/288/332	105	260	8	6	15%	7%	76	-0.4	212/286/291	80	223	5	0	8%	9%	72	-0.1
✕Tanner Morris 2023 · AAA	25	51→52	40	39→40	53	239/326/331	91	310	8	4	24%	10%	91	+0.6	230/311/321	91	307	7	5	25%	10%	82	+0.0	242/323/328	86	321	7	1	24%	10%	86	+0.2
✕Patrick Mazeika 2019 · AA	25	47→51	42→45	43→30	52	228/303/334	106	261	10	3	17%	8%	83	+0.1	216/276/346	130	249	14	3	19%	6%	76	-0.4	209/270/330	121	237	14	0	18%	6%	67	-0.6
✕Bruce Maxwell 2016 · AA	25	46→49	38→45	38→30	46	220/274/291	71	277	6	2	22%	7%	61	-1.5	238/298/349	111	308	10	3	24%	8%	84	+0.1	237/303/356	119	313	11	1	26%	9%	85	+0.1
✕Michael Papierski 2022 · AAA	26	43→44	41→40	36→40	51	209/301/308	99	281	9	4	27%	10%	77	-0.3	206/287/304	98	267	9	3	25%	9%	70	-0.8	193/276/282	89	250	9	1	25%	9%	60	-0.8
✕Greg Cullen 2022 · AA	25	46→44	42→40	43→40	52	222/314/329	107	293	9	4	26%	10%	86	+0.3	234/325/337	103	316	10	6	26%	11%	92	+0.7	234/334/325	92	316	9	5	26%	11%	91	+0.3
✕Orlando Mercado 2009 · AA	24	44	42→45	39→40	57	213/306/312	99	245	10	4	17%	11%	80	-0.2	231/299/303	72	267	5	4	14%	8%	74	-0.6	235/297/297	62	270	4	2	14%	8%	69	-0.5
✕Casey McElroy 2015 · AA	25	46→49	43→40	40→30	48	224/289/330	105	263	11	3	19%	7%	76	-0.4	226/282/317	91	280	7	4	21%	6%	70	-0.8	228/281/311	83	285	4	1	20%	6%	66	-0.8
✕Marco Rivera 2010 · AAA	26	48	41→40	40	51	230/297/326	95	279	9	7	20%	8%	78	-0.3	241/292/333	92	297	8	8	21%	6%	77	-0.3	260/297/316	56	319	4	2	19%	4%	74	-0.2
✕Kyle Phillips 2009 · AA	25	50→52	43→45	39→30	46	246/291/354	108	284	12	2	18%	6%	82	-0.0	237/283/338	101	279	10	2	19%	6%	75	-0.5	229/275/321	92	266	10	0	18%	5%	66	-0.6
✕Phil Clarke 2023 · AA	25	45	40	44→45	50	216/296/304	88	262	8	4	20%	8%	74	-0.6	226/307/313	87	264	8	8	17%	9%	80	-0.2	229/313/307	77	262	7	7	15%	9%	77	-0.1
✕Juan Carlos Gamboa 2016 · AAA	25	52	42→45	40→50	46	250/303/359	109	304	9	9	20%	6%	88	+0.4	249/301/356	107	312	10	9	22%	6%	86	+0.3	258/316/353	95	331	10	5	24%	7%	91	+0.3
✕Nolan Fontana 2016 · AAA	25	46→43	39→40	41→50	55	212/311/307	94	304	5	9	28%	12%	80	-0.2	195/277/291	96	277	7	10	29%	10%	63	-1.3	184/288/307	123	253	11	12	29%	12%	71	-0.3
●Taylor Green 2011 · AA	24	48→56	45→50	37→30	49	234/290/358	124	264	12	2	17%	7%	83	+0.1	242/299/384	142	285	15	3	20%	7%	93	+0.8	239/296/374	136	279	14	1	20%	7%	87	+0.2
✕Griff Erickson 2014 · AA	26	42→50	45	38→40	49	210/285/335	125	263	13	4	25%	9%	76	-0.4	215/280/336	121	270	12	5	24%	7%	74	-0.5	215/276/328	113	262	11	2	22%	7%	69	-0.3
✕Jett Bandy 2015 · AA	25	44	46→50	38→45	44	221/282/348	126	254	14	4	19%	5%	78	-0.3	224/282/357	133	266	15	4	22%	5%	80	-0.1	215/279/349	134	253	17	4	22%	5%	77	-0.2
✕Drew Macias 2008 · AAA	25	47→53	41→45	40→50	48	226/290/328	102	275	8	7	20%	8%	76	-0.4	225/302/332	107	271	9	10	19%	9%	82	-0.0	219/303/322	103	263	9	11	19%	9%	78	-0.2
✕Luis Sierra 2012 · AA	25	45	41→40	40→45	41	220/261/318	98	279	8	4	24%	5%	62	-1.4	213/263/292	79	270	4	5	21%	6%	57	-1.8	226/284/294	68	280	0	0	18%	7%	61	-0.6
✕Michael Pérez 2018 · AA	25	44	40→50	40	43	213/267/311	98	280	7	3	26%	6%	63	-1.3	220/277/334	114	286	12	3	26%	7%	73	-0.6	196/260/325	129	246	16	0	27%	8%	63	-0.6

Career Stats + Projections

Career Comps

Career Path Comps