Matthew Boyd — OGILVIE

Matthew Boyd P Chicago Cubs

Age 35 LHP 6'3" / 223 lbs MLB Svc 9.0 · Ctrl thru 2026 peak 2.5 · 2026

2026 ROS PROJECTION126 act + 12 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 95103vR 111

ERA3.78

FIP3.92

K%20.0%

BB%6.7%

K-BB%13.2%

ROS IP12

Value2026 · WAR

Runs saved vs league avg · 138 IP

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF4545

CTRL5555

CMD5555

K†5050

Statcast Percentiles

FB Velo

p2592.7

Whiff%

p2922.4%

p2919.1%

xwOBA vs

p340.331

CH+1.5 (27%)

SL+0.6 (15%)

SI (1%)

CU (13%)

FB-1.0 (45%)

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

Status FA

MLB Debut 2015

Service 9.331 yrs.days

Team Control Through 2026

First FA Year 2027

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$1M	+0.1	$0.3M	-$0.9M
Totals		$1M		$0.3M	-$0.9M

Options · projected decision
2027	MUTUAL OPT	$14.5M / $0.0M buyout	DECLINE
2028	MUTUAL OPT	$15.0M / $2.0M buyout	DECLINE

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 WAR & MLE are computed

Stats are park-neutral MLB equivalents. The "TEAM" column shows current org affiliation only — we do NOT project at that team's park.
Rates (K%, BB%, HR-BF) are park-stripped; MiLB stat lines are translated to their MLB-equivalent via per-level MLE factors.
WAR is computed from projected runs prevented vs a replacement pitcher (the marginal arm a team would call up if this pitcher were unavailable) — calibrated to industry-standard fWAR.

Year	Age	Lvl	Team	G	GS	IP	BF	K	BB	HR	GS%	IP/G	K%	BB%	K-BB%	HR%	ERA	FIP	WAR
▸ Career — actual stats, one row per year (as recorded, no adjustments)
▸ Career — adjusted (each season translated to a park/league-neutral MLB-equivalent line; levels combined per year)
▸ Model inputs — neutral MLE (past 3 seasons + 2026 so far)
2015	24	MIX MLE	3 levels	32	31	172	687	151	47	25	97%	5.4	19.4%	7.2%	12.2%	3.9%	3.61	4.53	+0.7
2015	24	MIX RAW	3 levels	32	31	172	687	151	47	25	97%	5.4	22.0%	6.8%	15.1%	3.6%	3.61	4.05	+1.7
2016	25	MIX MLE	2 levels	31	29	161	671	139	46	22	94%	5.2	19.7%	7.0%	12.7%	3.6%	3.63	4.27	+1.2
2016	25	MIX RAW	2 levels	31	29	161	671	139	46	22	94%	5.2	20.7%	6.9%	13.9%	3.3%	3.63	4.00	+1.7
2017	26	MIX MLE	2 levels	34	33	186	804	163	63	25	97%	5.5	19.5%	7.9%	11.6%	3.3%	4.60	4.24	+1.4
2017	26	MIX RAW	2 levels	34	33	186	804	163	63	25	97%	5.5	20.3%	7.8%	12.4%	3.1%	4.60	4.11	+1.7
2018	27	MLB MLE	Detroit Tigers	31	31	170	709	159	51	27	100%	5.5	22.4%	7.2%	15.2%	4.0%	4.39	4.30	+1.2
2018	27	MLB RAW	Detroit Tigers	31	31	170	709	159	51	27	100%	5.5	22.4%	7.2%	15.2%	3.8%	4.39	4.19	+1.4
2019	28	MLB MLE	Detroit Tigers	32	32	185	788	238	49	39	100%	5.8	30.2%	6.2%	24.0%	5.2%	4.56	4.17	+1.6
2019	28	MLB RAW	Detroit Tigers	32	32	185	788	238	49	39	100%	5.8	30.2%	6.2%	24.0%	4.9%	4.56	4.06	+1.8
2020	29	MLB MLE	Detroit Tigers	12	12	60	271	60	22	15	100%	5.0	22.1%	8.1%	14.0%	5.8%	6.71	5.43	-0.4
2020	29	MLB RAW	Detroit Tigers	12	12	60	271	60	22	15	100%	5.0	22.1%	8.1%	14.0%	5.5%	6.71	5.44	-0.4
2021	30	MIX MLE	2 levels	18	18	88	368	78	23	9	100%	4.9	19.9%	6.8%	13.1%	2.8%	3.48	3.82	+1.1
2021	30	MIX RAW	2 levels	18	18	88	368	78	23	9	100%	4.9	21.2%	6.2%	14.9%	2.4%	3.48	3.44	+1.6
2022	31	MIX MLE	2 levels	16	0	21	82	27	5	1	0%	1.3	24.5%	9.4%	15.1%	0.0%	1.69	2.22	+0.6
2022	31	MIX RAW	2 levels	16	0	21	82	27	5	1	0%	1.3	32.9%	6.1%	26.8%	1.2%	1.69	1.88	+0.7
2023	32	MLB MLE	Detroit Tigers	15	15	71	303	73	25	11	100%	4.7	24.1%	8.3%	15.8%	3.8%	5.45	4.19	+0.6
2023	32	MLB MLE	Detroit Tigers	15	15	71	303	73	25	11	100%	4.7	24.1%	8.3%	15.8%	3.8%	5.45	4.19	+0.6
2023	32	MLB RAW	Detroit Tigers	15	15	71	303	73	25	11	100%	4.7	24.1%	8.3%	15.8%	3.6%	5.45	4.11	+0.7
2024	33	MIX MLE	4 levels	13	13	61	243	73	15	4	100%	4.7	27.7%	7.8%	19.9%	2.4%	2.05	3.08	+1.4
2024	33	MIX MLE	4 levels	13	13	61	243	73	15	4	100%	4.7	27.7%	7.8%	19.9%	2.4%	2.05	3.08	+1.4
2024	33	MIX RAW	4 levels	13	13	61	243	73	15	4	100%	4.7	30.0%	6.2%	23.9%	1.6%	2.05	2.30	+2.0
2025	34	MLB MLE	Chicago Cubs	31	31	180	718	154	42	19	100%	5.8	21.4%	5.8%	15.6%	2.7%	3.21	3.54	+3.0
2025	34	MLB MLE	Chicago Cubs	31	31	180	718	154	42	19	100%	5.8	21.4%	5.8%	15.6%	2.7%	3.21	3.54	+3.0
2025	34	MLB RAW	Chicago Cubs	31	31	180	718	154	42	19	100%	5.8	21.4%	5.8%	15.6%	2.6%	3.21	3.46	+3.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			232	218	1197	5064	1131	362	191	94%	5.2	22.3%	7.1%	15.2%	3.8%	4.53	4.19	+10.0
▸ 2026 season
YTD	35	MLB MLE	Chicago Cubs	23	23	126	519	106	36	18	100%	5.5	19.2%	7.1%	12.1%	3.7%	4.21	4.43	+0.7
YTD	35	MLB MLE	Chicago Cubs	23	23	126	519	106	36	18	100%	5.5	19.2%	7.1%	12.1%	3.7%	4.21	4.43	+0.7
▸ 2026 season — so far · projected rest · full
2026	35	A+ RAW	CHC	1	1	4	14	7	0	0	100%	4.0	50.0%	0.0%	50.0%	0.0%	0.00	-1.12	—
2026	35	AAA RAW	CHC	3	3	13	55	13	3	3	100%	4.2	23.6%	5.5%	18.2%	5.5%	7.11	4.79	—
2026	35	MLB RAW	CHC	19	19	109	450	86	33	15	100%	5.8	19.1%	7.3%	11.8%	3.3%	4.03	4.24	+0.8
SO FAR	35	MLB RAW	CHC	19	19	109	450	86	33	15	100%	5.8	19.1%	7.3%	11.8%	3.3%	4.03	4.24	+0.8
ROS	35	MLB MLE	CHC	2	2	12	52	10	4	2	100%	6.2	20.0%	6.7%	13.2%	3.0%	3.78	3.92	+0.1
ROS	35	MLB CTX	CHC	2	2	12	51	10	3	1	100%	6.0	20.0%	6.7%	13.2%	2.9%	3.72	3.86	+0.1
2026 TOT	35	MLB MLE	CHC	—	—	138	571	116	40	20	—	—	20.4%	6.9%	13.5%	3.4%	4.18	4.38	+0.8
FULL	35	MLB A+C	CHC	—	—	122	514	116	40	20	—	—	22.7%	7.7%	15.0%	3.8%	4.74	4.25	+0.7
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	36	MLB MLE	CHC	22	22	130	549	105	41	19	100%	5.9	19.1%	7.5%	11.7%	3.5%	4.50	4.70	+0.3
2028	37	MLB MLE	CHC	19	19	113	479	86	39	19	100%	6.0	18.1%	8.1%	9.9%	3.9%	4.86	5.10	-0.3
2027	36	MLB CTX	CHC	22	22	130	549	105	41	18	100%	5.9	19.1%	7.5%	11.7%	3.3%	4.43	4.63	+0.3
2028	37	MLB CTX	CHC	19	19	113	477	86	39	18	100%	5.9	18.1%	8.1%	9.9%	3.7%	4.78	5.02	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		275	261	1453	6144	1333	445	229	95%	5.3	21.7%	7.2%	14.4%	3.7%	4.53	4.23	+11.5
/ 200 IP	—	RAW		38	36	200	846	183	61	32	95%	5.3	21.7%	7.2%	14.4%	3.7%	4.53	4.23	+1.6
Career	—	MLE		288	268	1483	6163	1366	437	228	93%	5.1	22.2%	7.1%	15.1%	3.7%	4.06	4.16	+10.1
/ 200 IP	—	MLE		39	36	200	831	184	59	31	93%	5.1	22.2%	7.1%	15.1%	3.7%	4.06	4.16	+1.4

Career Path Comps

What happened to similar pitchers from this age · Y-axis: ERA+ (100 = league avg, 150 = elite, 80 = below) · Bands: P10–P90 outer, P25–P75 inner · Gold: OGILVIE projection

			Profile at Match Age					Next 3 Yrs				Career
Comp	Age	Role	FIP	K%	BB%	HR/BF	BABIP	FIP	K%	K-BB%	IP	ΔFIP	Low FIP	IP	Match
Matthew Boyd (OGILVIE)	—	—	4.00	21.8%	6.3%	2.8%	—	4.89	18.6%	10.9%	243	+0.89	—	—	—
Jorge De La Rosa L 2016 · 4.56 FIP	35	SP	4.56	17.3%	10.1%	3.0%	.315	4.08	19.9%	11.2%	107	-0.48	3.86	405	74
Jon Lester L 2019 · 4.08 FIP	35	SP	4.08	21.6%	6.8%	3.5%	.344	5.15	14.9%	7.4%	202	+1.07	2.81	1,144	65
CC Sabathia L 2015 · 4.31 FIP	35	SP	4.31	18.9%	6.5%	3.6%	.311	3.97	20.1%	12.1%	481	-0.34	3.76	756	64
Cole Hamels L 2019 · 3.84 FIP	35	SP	3.84	23.2%	8.9%	2.9%	.308	—	—	—	—	—	3.21	893	62
C.J. Wilson L 2015 · 3.69 FIP	34	SP	3.69	19.9%	8.0%	2.3%	.272	—	—	—	—	—	3.69	132	60
Randy Wolf L 2015 · 3.40 FIP	38	SP	3.40	16.6%	7.7%	1.3%	.329	—	—	—	—	—	3.40	174	60
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	60
Eric Stults L 2015 · 4.27 FIP	35	SP	4.27	14.5%	5.9%	3.0%	.266	—	—	—	—	—	4.27	138	59
Jonathan Sánchez L 2019 · 4.73 FIP	36	SP	4.73	18.1%	8.3%	3.9%	.339	—	—	—	—	—	4.73	109	59
Orlando Lara L 2019 · 4.09 FIP	34	SP	4.09	22.0%	7.8%	3.4%	.329	—	—	—	—	—	3.85	426	59
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.66	119	58
J.A. Happ L 2018 · 3.65 FIP	35	SP	3.65	26.3%	7.0%	3.5%	.266	4.88	19.7%	12.5%	363	+1.23	3.37	1,053	58
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	56
Barry Zito L 2015 · 4.52 FIP	37	SP	4.52	13.6%	10.7%	2.2%	.259	—	—	—	—	—	4.52	138	54
Wandy Rodriguez L 2015 · 3.83 FIP	36	SP-	3.83	19.4%	8.5%	2.4%	.312	—	—	—	—	—	3.83	101	51
Arturo Lopez L 2017 · 4.34 FIP	34	SP	4.34	10.3%	5.4%	2.6%	.342	5.46	12.2%	5.4%	117	+1.12	4.34	445	50
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	49
Jason Vargas L 2018 · 4.71 FIP	35	SP	4.71	20.8%	7.2%	4.5%	.300	4.33	19.1%	9.7%	150	-0.38	4.02	478	49
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	48
Andrew Albers L 2021 · 4.60 FIP	35	SP	4.60	16.9%	3.7%	4.5%	.312	—	—	—	—	—	2.98	508	48

Career Comps

Retired MLB careers whose totals most resemble what we're projecting for this player. Pool: 133 completed pitcher careers (2015-2024).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	2.0	130	19.8%	7.2%	1.29	4.36
Kutter Crawford ('24)	2.0	130	23.9%	7.2%	1.45	4.47
Mike Foltynewicz ('21)	4.0	134	21.4%	7.7%	1.46	4.45
Zach Plesac ('23)	2.3	93	18.4%	6.3%	1.39	4.20
James Kaprielian ('23)	1.6	105	20.5%	9.6%	1.26	4.58
Cole Irvin ('24)	2.9	118	17.1%	5.6%	1.28	4.46
Yonny Chirinos ('24)	1.7	84	18.9%	6.6%	1.38	4.37