Tommy Hunter — OGILVIE

Tommy Hunter P New York Mets

Age 40 RHP 6'3" / 250 lbs MLB

2026 ROS PROJECTION0 act + 4 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 118110vR 101

ERA4.42

FIP4.45

K%22.2%

BB%8.5%

K-BB%13.7%

ROS IP4

Value2026 · WAR

Runs saved vs league avg · 4 IP

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF4545

CTRL6060

CMD5555

K†5555

Statcast Percentiles

FB Velo

p2392.6

Whiff%

p1018.0%

p2718.9%

xwOBA vs

p220.345

FB+3.5

CH-1.9

CT-3.3

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

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	29	MLB MLE	Chicago Cubs	58	0	60	249	47	12	7	0%	1.0	18.9%	4.8%	14.1%	2.9%	4.18	3.72	+0.6
2015	29	MLB RAW	Chicago Cubs	58	0	60	249	47	12	7	0%	1.0	18.9%	4.8%	14.1%	2.8%	4.18	3.65	+0.6
2016	30	MIX MLE	2 levels	47	2	49	199	33	9	3	4%	1.0	16.0%	4.6%	11.4%	1.4%	3.12	3.12	+0.8
2016	30	MIX RAW	2 levels	47	2	49	199	33	9	3	4%	1.0	16.6%	4.5%	12.1%	1.5%	3.12	3.10	+0.8
2017	31	MIX MLE	2 levels	62	1	60	235	67	14	6	2%	1.0	28.1%	6.1%	21.9%	2.7%	2.87	2.99	+1.1
2017	31	MIX RAW	2 levels	62	1	60	235	67	14	6	2%	1.0	28.5%	6.0%	22.6%	2.6%	2.87	2.87	+1.2
2018	32	MIX MLE	3 levels	67	0	66	279	54	15	6	0%	1.0	18.9%	5.2%	13.7%	2.1%	3.66	3.30	+1.0
2018	32	MIX RAW	3 levels	67	0	66	279	54	15	6	0%	1.0	19.4%	5.4%	14.0%	2.2%	3.66	3.33	+1.0
2019	33	MIX MLE	3 levels	9	3	10	34	11	0	1	33%	1.1	32.4%	0.0%	32.4%	2.9%	0.87	1.98	+0.3
2019	33	MIX RAW	3 levels	9	3	10	34	11	0	1	33%	1.1	32.4%	0.0%	32.4%	2.9%	0.87	2.23	+0.3
2020	34	MLB MLE	Philadelphia Phillies	24	0	25	102	25	6	2	0%	1.0	24.5%	5.9%	18.6%	1.8%	4.01	2.78	+0.5
2020	34	MLB RAW	Philadelphia Phillies	24	0	25	102	25	6	2	0%	1.0	24.5%	5.9%	18.6%	2.0%	4.01	2.86	+0.5
2021	35	MLB MLE	New York Mets	4	1	8	33	6	3	0	25%	2.0	18.2%	9.1%	9.1%	0.0%	0.00	2.72	+0.2
2021	35	MLB RAW	New York Mets	4	1	8	33	6	3	0	25%	2.0	18.2%	9.1%	9.1%	0.0%	0.00	2.73	+0.2
2022	36	MIX MLE	4 levels	29	1	40	170	40	8	6	3%	1.4	22.1%	4.5%	17.6%	4.0%	2.92	3.98	+0.3
2022	36	MIX RAW	4 levels	29	1	40	170	40	8	6	3%	1.4	23.5%	4.7%	18.8%	3.5%	2.92	3.65	+0.4
2023	37	MIX MLE	2 levels	16	0	26	114	20	6	6	0%	1.6	18.9%	4.7%	14.2%	5.7%	6.31	5.22	-0.2
2023	37	MIX MLE	2 levels	16	0	26	114	20	6	6	0%	1.6	18.9%	4.7%	14.2%	5.7%	6.31	5.22	-0.2
2023	37	MIX RAW	2 levels	16	0	26	114	20	6	6	0%	1.6	17.5%	5.3%	12.3%	5.3%	6.31	5.28	-0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			282	1	301	1239	263	67	32	0%	1.1	21.2%	5.4%	15.8%	2.6%	3.56	3.40	+4.1
▸ 2026 season — projected remainder (no 2026 stats recorded)
2026	40	MLB	NYM	4	0	4	17	4	1	1	0%	1.0	22.2%	8.5%	13.7%	3.2%	4.42	4.45	+0.0
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	41	MLB MLE	NYM	36	0	38	162	34	15	6	0%	1.1	21.0%	9.2%	11.8%	3.7%	4.70	4.89	-0.1
2027	41	MLB CTX	NYM	31	0	33	139	29	13	5	0%	1.1	21.0%	9.2%	11.8%	3.7%	4.70	4.89	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		313	1	334	1378	292	80	37	0%	1.1	21.2%	5.8%	15.4%	2.7%	3.67	3.52	+4.1
/ 200 IP	—	RAW		188	1	200	825	175	48	22	0%	1.1	21.2%	5.8%	15.4%	2.7%	3.67	3.52	+2.4
Career	—	MLE		316	8	344	1415	299	72	38	3%	1.1	21.1%	5.1%	16.0%	2.7%	3.51	3.45	+4.0
/ 200 IP	—	MLE		184	5	200	823	174	42	22	3%	1.1	21.1%	5.1%	16.0%	2.7%	3.51	3.45	+2.3

	Profile at Match Age	Next 3 Yrs	Career
Tommy Hunter (OGILVIE)	—	—	4.45	22.2%	8.5%	3.2%	—	4.89	21.0%	11.8%	38	+0.44	—	—	—
Joaquín Benoit R 2017 · 4.48 FIP	40	SU	4.48	21.6%	9.9%	3.5%	.259	—	—	—	—	—	3.58	164	83
Jason Grilli R 2017 · 5.58 FIP	40	SU	5.58	26.1%	9.8%	6.3%	.321	—	—	—	—	—	2.05	133	69
Peter Moylan R 2018 · 4.77 FIP	39	SU	4.77	17.8%	11.6%	3.1%	.322	—	—	—	—	—	3.11	174	65
Luis Ayala R 2017 · 4.00 FIP	39	SU	4.00	15.9%	11.7%	1.4%	.340	—	—	—	—	—	3.03	119	61
Erubiel Gonzalez R 2017 · 3.51 FIP	38	SU	3.51	13.3%	2.5%	2.2%	.388	—	—	—	—	—	2.99	119	60
Ryan Vogelsong R 2016 · 4.79 FIP	39	SP-	4.79	16.7%	10.4%	3.2%	.270	—	—	—	—	—	4.45	217	32
Horacio Ramirez L 2019 · 4.65 FIP	39	SU	4.65	5.7%	6.0%	2.3%	.233	—	—	—	—	—	3.39	199	25
Juan Antonio Pena L 2019 · 4.56 FIP	41	SW	4.56	13.7%	14.1%	1.5%	.313	—	—	—	—	—	4.20	149	20

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	0.4	41	21.6%	8.8%	1.33	4.55
José Ruiz ('24)	1.3	52	22.2%	10.4%	1.41	4.41
Noé Ramirez ('22)	1.3	52	24.8%	9.0%	1.33	4.19
Mike Mayers ('23)	1.2	47	24.3%	7.8%	1.50	4.47
Alex Young ('23)	1.3	52	19.5%	8.6%	1.61	4.43
Joe Biagini ('19)	1.6	81	19.1%	7.8%	1.28	4.86
Josh Winckowski ('24)	1.2	77	18.3%	8.2%	1.13	4.21

			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
Tommy Hunter (OGILVIE)	—	—	4.45	22.2%	8.5%	3.2%	—	4.89	21.0%	11.8%	38	+0.44	—	—	—
Joaquín Benoit R 2017 · 4.48 FIP	40	SU	4.48	21.6%	9.9%	3.5%	.259	—	—	—	—	—	3.58	164	83
Jason Grilli R 2017 · 5.58 FIP	40	SU	5.58	26.1%	9.8%	6.3%	.321	—	—	—	—	—	2.05	133	69
Peter Moylan R 2018 · 4.77 FIP	39	SU	4.77	17.8%	11.6%	3.1%	.322	—	—	—	—	—	3.11	174	65
Luis Ayala R 2017 · 4.00 FIP	39	SU	4.00	15.9%	11.7%	1.4%	.340	—	—	—	—	—	3.03	119	61
Erubiel Gonzalez R 2017 · 3.51 FIP	38	SU	3.51	13.3%	2.5%	2.2%	.388	—	—	—	—	—	2.99	119	60
Ryan Vogelsong R 2016 · 4.79 FIP	39	SP-	4.79	16.7%	10.4%	3.2%	.270	—	—	—	—	—	4.45	217	32
Horacio Ramirez L 2019 · 4.65 FIP	39	SU	4.65	5.7%	6.0%	2.3%	.233	—	—	—	—	—	3.39	199	25
Juan Antonio Pena L 2019 · 4.56 FIP	41	SW	4.56	13.7%	14.1%	1.5%	.313	—	—	—	—	—	4.20	149	20

Contract

Career Stats + Projections

Career Path Comps

Career Comps