Dylan Bundy — OGILVIE

Dylan Bundy P Syracuse Mets

Age 33 RHP 6'1" / 225 lbs AAA peak 0.5 · 2026

2026 ROS PROJECTION0 act + 5 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 119111vR 103

ERA4.49

FIP4.64

K%21.1%

BB%8.8%

K-BB%12.2%

ROS IP5

Value2026 · WAR

Runs saved vs league avg · 5 IP

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF5050

CTRL6060

CMD5050

K†5050

Statcast Percentiles

FB Velo

p1089.0

Whiff%

p2221.3%

p1015.8%

xwOBA vs

p380.326

FB-2.5

CH-5.2

SL-7.1

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	22	AA MLE	Bowie Baysox	8	8	22	90	25	5	0	100%	2.8	22.5%	6.1%	16.4%	0.0%	3.68	1.97	—
2015	22	AA RAW	Bowie Baysox	8	8	22	90	25	5	0	100%	2.8	27.8%	5.6%	22.2%	0.0%	3.68	1.51	—
2016	23	MLB MLE	Baltimore Orioles	36	14	110	474	104	38	18	39%	3.0	21.9%	8.0%	13.9%	3.4%	4.02	4.14	+0.5
2016	23	MLB RAW	Baltimore Orioles	36	14	110	474	104	38	18	39%	3.0	21.9%	8.0%	13.9%	3.8%	4.02	4.38	+0.2
2017	24	MLB MLE	Baltimore Orioles	28	28	170	698	152	51	26	100%	6.1	21.8%	7.3%	14.5%	3.4%	4.24	4.03	+1.8
2017	24	MLB RAW	Baltimore Orioles	28	28	170	698	152	51	26	100%	6.1	21.8%	7.3%	14.5%	3.7%	4.24	4.20	+1.4
2018	25	MLB MLE	Baltimore Orioles	31	31	172	750	184	53	41	100%	5.5	24.5%	7.1%	17.5%	4.9%	5.45	4.63	+0.5
2018	25	MLB RAW	Baltimore Orioles	31	31	172	750	184	53	41	100%	5.5	24.5%	7.1%	17.5%	5.5%	5.45	4.99	-0.2
2019	26	MLB MLE	Baltimore Orioles	30	30	162	700	162	58	29	100%	5.4	23.1%	8.3%	14.9%	3.7%	4.79	4.25	+1.2
2019	26	MLB RAW	Baltimore Orioles	30	30	162	700	162	58	29	100%	5.4	23.1%	8.3%	14.9%	4.1%	4.79	4.50	+0.7
2020	27	MLB MLE	Los Angeles Angels	11	11	66	267	72	16	5	100%	6.0	27.0%	6.0%	21.0%	1.8%	3.29	2.59	+2.0
2020	27	MLB RAW	Los Angeles Angels	11	11	66	267	72	16	5	100%	6.0	27.0%	6.0%	21.0%	1.9%	3.29	2.63	+1.9
2021	28	MLB MLE	Los Angeles Angels	23	19	91	397	84	34	20	83%	3.9	21.2%	8.6%	12.6%	4.9%	6.06	5.11	-0.2
2021	28	MLB RAW	Los Angeles Angels	23	19	91	397	84	34	20	83%	3.9	21.2%	8.6%	12.6%	5.0%	6.06	5.24	-0.4
2022	29	MLB MLE	Minnesota Twins	29	29	140	595	94	28	24	100%	4.8	15.8%	4.7%	11.1%	4.0%	4.89	4.56	+0.5
2022	29	MLB RAW	Minnesota Twins	29	29	140	595	94	28	24	100%	4.8	15.8%	4.7%	11.1%	4.0%	4.89	4.59	+0.5
2023	30	AAA MLE	Syracuse Mets	6	6	25	121	21	7	12	100%	4.2	14.4%	5.2%	9.2%	10.9%	10.08	8.51	—
2023	30	AAA MLE	Syracuse Mets	6	6	25	121	21	7	12	100%	4.2	14.4%	5.2%	9.2%	10.9%	10.08	8.51	—
2023	30	AAA RAW	Syracuse Mets	6	6	25	121	21	7	12	100%	4.2	17.4%	5.8%	11.6%	9.9%	10.08	8.50	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			188	162	909	3881	852	278	163	86%	4.8	22.0%	7.2%	14.8%	4.2%	4.75	4.47	+4.5
▸ 2026 season — projected remainder (no 2026 stats recorded)
2026	33	MLB	NYM	1	1	5	21	4	2	1	100%	5.0	21.1%	8.8%	12.2%	3.3%	4.49	4.64	+0.0
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	34	MLB MLE	NYM	8	8	49	206	41	19	7	100%	6.1	20.2%	9.3%	10.8%	3.6%	4.76	4.94	-0.0
2028	35	MLB MLE	NYM	7	7	44	185	35	18	7	100%	6.2	19.2%	9.9%	9.3%	4.0%	5.07	5.28	-0.2
2027	34	MLB CTX	NYM	8	8	49	207	42	19	7	100%	6.1	20.2%	9.3%	10.8%	3.6%	4.76	4.94	-0.0
2028	35	MLB CTX	NYM	7	7	44	186	36	18	7	100%	6.3	19.2%	9.9%	9.3%	4.0%	5.07	5.28	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		203	177	1001	4271	929	315	178	87%	4.9	21.7%	7.4%	14.4%	4.2%	4.77	4.48	+4.9
/ 200 IP	—	RAW		41	35	200	853	186	63	36	87%	4.9	21.7%	7.4%	14.4%	4.2%	4.77	4.48	+1.0
Career	—	MLE		202	176	956	4092	890	290	164	87%	4.7	21.7%	7.1%	14.7%	4.0%	4.87	4.37	+4.3
/ 200 IP	—	MLE		42	37	200	856	186	61	34	87%	4.7	21.7%	7.1%	14.7%	4.0%	4.87	4.37	+0.9

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
Dylan Bundy (OGILVIE)	—	—	4.64	21.1%	8.8%	3.3%	—	5.10	19.7%	10.1%	92	+0.46	—	—	—
Tim Lincecum R 2016 · 4.88 FIP	32	SP	4.88	17.9%	10.4%	3.6%	.351	5.87	14.4%	-1.1%	13	+0.99	4.20	166	76
Josh Lindblom R 2020 · 3.50 FIP	33	SP	3.50	27.2%	8.4%	3.0%	.308	4.46	21.7%	13.8%	255	+0.96	3.50	348	74
Jair Jurrjens R 2017 · 4.27 FIP	31	SP	4.27	16.3%	7.9%	2.8%	.335	—	—	—	—	—	4.27	125	71
Tyler Cloyd R 2019 · 5.21 FIP	32	SP	5.21	18.9%	9.5%	4.6%	.388	—	—	—	—	—	3.89	250	69
Brandon McCarthy R 2016 · 4.84 FIP	33	SP	4.84	22.5%	11.5%	4.0%	.288	3.82	19.0%	12.4%	171	-1.02	3.09	248	68
Hector Ambriz R 2016 · 3.63 FIP	32	SP	3.63	16.0%	6.4%	2.0%	.273	6.40	10.4%	2.9%	91	+2.77	3.63	155	68
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	67
Shaun Marcum R 2015 · 4.04 FIP	33	SP	4.04	17.8%	6.0%	3.1%	.281	—	—	—	—	—	4.04	123	67
Guillermo Moscoso R 2017 · 3.77 FIP	33	SP	3.77	14.5%	6.9%	1.8%	.270	4.64	14.9%	7.5%	176	+0.87	3.77	264	66
Kris Medlen R 2018 · 5.20 FIP	32	SP	5.20	16.2%	10.0%	4.0%	.306	—	—	—	—	—	4.59	261	66
Chris Smith R 2015 · 3.79 FIP	34	SP	3.79	20.0%	8.1%	2.5%	.306	4.41	18.4%	10.2%	285	+0.62	3.79	413	65
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	64
Mitch Talbot R 2018 · 3.82 FIP	34	SP	3.82	13.7%	5.6%	2.1%	.281	5.01	13.2%	8.9%	59	+1.19	3.82	162	62
Lucas Harrell R 2017 · 3.57 FIP	32	SP	3.57	16.2%	10.5%	0.9%	.283	—	—	—	—	—	3.57	139	62
César Valdez R 2017 · 3.91 FIP	32	SP-	3.91	16.4%	5.3%	2.8%	.296	2.65	18.7%	15.4%	162	-1.26	1.91	882	62
Kameron Loe R 2016 · 3.84 FIP	34	SP	3.84	11.9%	5.3%	2.0%	.356	3.38	17.1%	9.1%	133	-0.46	3.38	201	62
Jake Peavy R 2015 · 4.07 FIP	34	SP	4.07	17.3%	5.7%	3.1%	.278	4.35	19.6%	12.9%	119	+0.28	4.07	262	61
Scott Carroll R 2017 · 5.71 FIP	32	SP	5.71	14.4%	8.6%	5.0%	.300	—	—	—	—	—	3.92	248	61
Austin Bibens-Dirkx R 2018 · 4.89 FIP	33	SP-	4.89	17.9%	7.6%	4.3%	.322	4.82	15.9%	9.5%	147	-0.07	3.97	567	61
Dylan Axelrod R 2016 · 4.28 FIP	31	SP	4.28	13.7%	6.3%	2.8%	.302	—	—	—	—	—	4.28	251	61

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	0.7	49	20.2%	9.3%	1.40	4.75
José Ruiz ('24)	1.3	52	22.2%	10.4%	1.41	4.41
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
Austin Voth ('24)	1.7	58	22.2%	8.2%	1.50	4.63
Mike Mayers ('23)	1.2	47	24.3%	7.8%	1.50	4.47
Noé Ramirez ('22)	1.3	52	24.8%	9.0%	1.33	4.19