Tylor Megill — OGILVIE

Tylor Megill P New York Mets

Age 31 RHP 6'7" / 230 lbs MLB Svc 4.0 · Ctrl thru 2027 peak 1.1 · 2026 ILInjured 60-Day (D60)

2026 ROS PROJECTION0 act + 1 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 10798vR 90

ERA4.17

FIP4.01

K%25.9%

BB%10.3%

K-BB%15.6%

ROS IP1

Value2026 · WAR

Runs saved vs league avg · 1 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control-$2M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF6060

CTRL4040

CMD5555

K†6060

Statcast Percentiles

FB Velo

p6295.4

Whiff%

p8430.7%

p8829.2%

xwOBA vs

p560.306

FB+1.5 (62%)

SI (20%)

CU (7%)

SL-1.6 (23%)

CH-1.9 (7%)

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

Status Arb-2

MLB Debut 2021

Service 4.180 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$0.2M	+0.0	$0.2M	-$0.0M
2027	Arb-3	$6M	+0.5	$2M	+$0.0M (cut)
Totals		$0.2M		$2M	-$0.0M

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)
2019	24	MIX MLE	3 levels	22	11	72	302	92	25	2	50%	3.3	22.2%	10.4%	11.9%	0.9%	3.52	3.02	—
2019	24	MIX RAW	3 levels	22	11	72	302	92	25	2	50%	3.3	30.5%	8.3%	22.2%	0.7%	3.52	1.94	—
2021	26	MIX MLE	3 levels	26	26	130	543	158	39	22	100%	5.0	27.3%	7.4%	19.9%	4.1%	4.15	3.99	+1.4
2021	26	MIX RAW	3 levels	26	26	130	543	158	39	22	100%	5.0	29.1%	7.2%	21.9%	4.1%	4.15	3.77	+1.8
2022	27	MIX MLE	3 levels	22	12	57	240	65	16	8	55%	2.6	25.5%	6.5%	19.0%	3.5%	5.56	3.70	+0.8
2022	27	MIX RAW	3 levels	22	12	57	240	65	16	8	55%	2.6	27.1%	6.7%	20.4%	3.3%	5.56	3.49	+1.0
2023	28	MIX MLE	2 levels	31	31	153	690	119	69	21	100%	4.9	16.9%	9.8%	7.1%	3.1%	5.40	4.62	+0.5
2023	28	MIX MLE	2 levels	31	31	153	690	119	69	21	100%	4.9	16.9%	9.8%	7.1%	3.1%	5.40	4.62	+0.5
2023	28	MIX RAW	2 levels	31	31	153	690	119	69	21	100%	4.9	17.2%	10.0%	7.2%	3.0%	5.40	4.68	+0.4
2024	29	MIX MLE	4 levels	27	26	127	535	158	52	13	96%	4.7	26.7%	9.7%	17.0%	2.4%	3.84	3.36	+2.4
2024	29	MIX MLE	4 levels	27	26	127	535	158	52	13	96%	4.7	26.7%	9.7%	17.0%	2.4%	3.84	3.36	+2.4
2024	29	MIX RAW	4 levels	27	26	127	535	158	52	13	96%	4.7	29.5%	9.7%	19.8%	2.4%	3.84	3.17	+2.7
2025	30	MIX MLE	3 levels	20	20	88	396	118	43	8	100%	4.4	27.3%	11.0%	16.3%	2.1%	4.18	3.34	+1.7
2025	30	MIX MLE	3 levels	20	20	88	396	118	43	8	100%	4.4	27.3%	11.0%	16.3%	2.1%	4.18	3.34	+1.7
2025	30	MIX RAW	3 levels	20	20	88	396	118	43	8	100%	4.4	29.8%	10.9%	18.9%	2.0%	4.18	3.07	+2.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			88	81	410	1788	435	163	58	92%	4.7	24.3%	9.1%	15.2%	3.2%	4.46	4.01	+4.3
▸ 2026 season — projected remainder (no 2026 stats recorded)
2026	31	MLB	NYM	1	1	1	4	1	0	0	100%	1.0	25.9%	10.3%	15.6%	2.6%	4.17	4.01	+0.0
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	32	MLB MLE	NYM	11	11	66	280	70	30	8	100%	6.0	25.1%	10.7%	14.4%	2.8%	4.23	4.27	+0.5
2028	33	MLB MLE	NYM	10	10	61	256	62	28	8	100%	6.1	24.3%	11.1%	13.1%	3.1%	4.42	4.55	+0.2
2027	32	MLB CTX	NYM	11	11	66	279	70	30	8	100%	6.0	25.1%	10.7%	14.4%	2.8%	4.23	4.27	+0.5
2028	33	MLB CTX	NYM	10	10	61	258	62	29	8	100%	6.1	24.3%	11.1%	13.1%	3.1%	4.42	4.55	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		109	102	537	2324	567	221	74	94%	4.9	24.4%	9.5%	14.9%	3.2%	4.43	3.99	+5.8
/ 200 IP	—	RAW		41	38	200	866	211	82	28	94%	4.9	24.4%	9.5%	14.9%	3.2%	4.43	3.99	+2.2
Career	—	MLE		148	126	627	2706	644	250	76	85%	4.2	23.8%	9.2%	14.6%	2.8%	4.45	3.80	+5.1
/ 200 IP	—	MLE		47	40	200	864	205	80	24	85%	4.2	23.8%	9.2%	14.6%	2.8%	4.45	3.80	+1.9

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
Tylor Megill (OGILVIE)	—	—	4.01	25.9%	10.3%	2.6%	—	4.40	24.7%	13.8%	127	+0.39	—	—	—
Garrett Richards R 2018 · 3.99 FIP	30	SP	3.99	26.9%	10.5%	3.3%	.276	4.36	19.4%	10.3%	188	+0.37	2.31	577	70
Yu Darvish R 2018 · 4.50 FIP	31	SP	4.50	27.2%	11.7%	4.0%	.282	3.48	30.5%	24.0%	421	-1.02	1.97	1,253	68
Brad Peacock R 2019 · 4.22 FIP	31	SP-	4.22	25.1%	8.1%	4.0%	.261	4.15	22.8%	12.5%	96	-0.07	2.97	533	66
Matt Shoemaker R 2018 · 3.17 FIP	31	SP	3.17	25.4%	7.7%	2.3%	.310	4.87	19.3%	11.5%	188	+1.70	3.17	592	62
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	60
Chase Anderson R 2019 · 4.39 FIP	31	SP	4.39	20.9%	8.1%	3.7%	.259	5.39	19.2%	10.0%	218	+1.00	3.30	1,146	59
Nate Karns R 2017 · 4.46 FIP	29	SP	4.46	27.1%	6.4%	5.2%	.276	—	—	—	—	—	3.88	287	58
Matt Cain R 2016 · 4.95 FIP	31	SP-	4.95	18.1%	7.8%	4.4%	.313	4.82	13.2%	5.6%	124	-0.13	4.82	294	58
Ricky Nolasco R 2015 · 3.22 FIP	32	SP	3.22	20.2%	6.9%	1.7%	.382	4.41	17.9%	11.7%	379	+1.19	3.22	425	58
Tom Koehler R 2017 · 4.66 FIP	31	SP-	4.66	22.4%	9.0%	4.2%	.298	—	—	—	—	—	4.38	474	57
Félix Hernández R 2017 · 4.56 FIP	31	SP	4.56	22.0%	7.0%	4.4%	.278	5.08	18.0%	9.7%	227	+0.52	3.60	682	57
Chris Bassitt R 2020 · 3.53 FIP	31	SP	3.53	21.1%	6.5%	2.5%	.273	3.54	23.2%	16.7%	539	+0.01	3.02	1,554	56
Jair Jurrjens R 2017 · 4.27 FIP	31	SP	4.27	16.3%	7.9%	2.8%	.335	—	—	—	—	—	4.27	125	55
Joe Biagini R 2021 · 4.80 FIP	31	SP	4.80	18.0%	10.6%	3.4%	.309	4.53	16.4%	6.6%	39	-0.27	2.66	624	54
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	54
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	54
Bud Norris R 2016 · 4.00 FIP	31	SP-	4.00	20.6%	9.1%	2.7%	.305	3.58	27.5%	19.3%	120	-0.42	3.51	316	54
Jose Samayoa R 2019 · 4.05 FIP	29	SP	4.05	19.4%	7.0%	3.1%	.314	—	—	—	—	—	3.44	262	54
Dillon Gee R 2017 · 3.85 FIP	31	SP-	3.85	18.0%	5.9%	2.8%	.302	—	—	—	—	—	3.67	380	54
Tyler Herron R 2017 · 4.02 FIP	30	SP	4.02	16.4%	8.7%	2.2%	.377	—	—	—	—	—	4.02	117	54

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	1.0	64	25.1%	10.7%	1.10	4.27
José Cisnero ('23)	1.1	42	24.8%	11.3%	0.94	3.84
Noé Ramirez ('22)	1.3	52	24.8%	9.0%	1.33	4.19
Keegan Thompson ('24)	1.1	57	23.0%	11.3%	1.19	3.64
José Ruiz ('24)	1.3	52	22.2%	10.4%	1.41	4.41
Colin Poche ('24)	1.0	52	27.0%	9.2%	1.34	3.63
Lucas Sims ('24)	1.4	47	27.6%	11.6%	1.24	4.22