Clarke Schmidt — OGILVIE

Clarke Schmidt P Scranton/Wilkes-Barre RailRiders

Age 30 RHP 6'1" / 210 lbs AAA Svc 4.0 · Ctrl thru 2027 peak 1.3 · 2026 ILInjured 60-Day (D60)

2026 FULL-SEASON PROJECTIONpark-neutral Marcel · 86 proj IP

wRC+ AGAINSTvL 9991vR 83

ERA3.99

FIP4.08

K%23.8%

BB%8.7%

K-BB%15.1%

ROS IP86

Value2026 · WAR

Runs saved vs league avg · 86 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control-$1M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF5555

CTRL4545

CMD5050

K†5560

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p5826.6%

p5523.1%

xwOBA vs

p900.272

SL+8.3 (25%)

CT+4.9 (43%)

SI (8%)

CU (18%)

FB-4.2 (13%)

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

Status Arb-2

MLB Debut 2020

Service 4.860 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$0.4M	+0.0	$0.1M	-$0.3M
2027	Arb-3	$6M	+0.6	$2M	+$0.0M (cut)
Totals		$0.4M		$2M	-$0.3M

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)
2018	22	ROK MLE	GCL Yankees East	6	5	15	59	20	4	1	83%	2.5	23.1%	8.5%	14.6%	2.4%	4.20	3.53	—
2018	22	ROK RAW	GCL Yankees East	6	5	15	59	20	4	1	83%	2.5	33.9%	6.8%	27.1%	1.7%	4.20	2.10	—
2019	23	MIX MLE	3 levels	19	18	91	375	102	28	4	95%	4.8	20.0%	8.4%	11.6%	1.1%	3.47	3.09	—
2019	23	MIX RAW	3 levels	19	18	91	375	102	28	4	95%	4.8	27.2%	7.5%	19.7%	1.1%	3.47	2.35	—
2020	24	MLB MLE	New York Yankees	3	1	6	33	7	5	0	33%	2.1	21.2%	15.2%	6.1%	0.0%	7.11	3.23	+0.1
2020	24	MLB RAW	New York Yankees	3	1	6	33	7	5	0	33%	2.1	21.2%	15.2%	6.1%	0.0%	7.11	3.26	+0.1
2021	25	MIX MLE	5 levels	12	10	44	196	52	17	7	83%	3.7	25.4%	7.6%	17.8%	3.5%	2.84	3.81	+0.6
2021	25	MIX RAW	5 levels	12	10	44	196	52	17	7	83%	3.7	26.5%	8.7%	17.9%	3.6%	2.84	3.96	+0.5
2022	26	MIX MLE	2 levels	37	11	91	375	102	29	6	30%	2.5	25.7%	7.9%	17.9%	1.5%	3.18	2.77	+2.0
2022	26	MIX RAW	2 levels	37	11	91	375	102	29	6	30%	2.5	27.2%	7.7%	19.5%	1.6%	3.18	2.67	+2.1
2023	27	MLB MLE	New York Yankees	33	32	159	694	149	46	24	97%	4.8	21.5%	6.6%	14.8%	3.2%	4.64	3.90	+1.9
2023	27	MLB MLE	New York Yankees	33	32	159	694	149	46	24	97%	4.8	21.5%	6.6%	14.8%	3.2%	4.64	3.90	+1.9
2023	27	MLB RAW	New York Yankees	33	32	159	694	149	46	24	97%	4.8	21.5%	6.6%	14.8%	3.5%	4.64	4.06	+1.6
2024	28	MIX MLE	3 levels	19	19	97	396	111	32	10	100%	5.1	26.3%	8.5%	17.8%	2.1%	2.89	3.12	+2.1
2024	28	MIX MLE	3 levels	19	19	97	396	111	32	10	100%	5.1	26.3%	8.5%	17.8%	2.1%	2.89	3.12	+2.1
2024	28	MIX RAW	3 levels	19	19	97	396	111	32	10	100%	5.1	28.0%	8.1%	19.9%	2.5%	2.89	3.14	+2.1
2025	29	MIX MLE	2 levels	16	16	86	343	84	31	9	100%	5.4	23.1%	9.5%	13.6%	2.7%	3.03	3.82	+1.1
2025	29	MIX MLE	2 levels	16	16	86	343	84	31	9	100%	5.4	23.1%	9.5%	13.6%	2.7%	3.03	3.82	+1.1
2025	29	MIX RAW	2 levels	16	16	86	343	84	31	9	100%	5.4	24.5%	9.0%	15.5%	2.6%	3.03	3.59	+1.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			97	67	393	1670	384	136	47	69%	4.1	23.0%	8.1%	14.9%	2.8%	3.82	3.74	+5.5
▸ 2026 season
YTD	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	5	2	7	26	11	1	1	40%	1.4	—	—	—	—	3.86	—	—
YTD	30	AAA MLE	Scranton/Wilkes-Barre RailRiders	5	2	7	26	11	1	1	40%	1.4	—	—	—	—	3.86	—	—
▸ 2026 season — so far · projected rest · full
2026	30	AA RAW	NYY	3	1	3	12	7	0	1	33%	1.0	58.3%	0.0%	58.3%	8.3%	6.00	2.75	—
2026	30	AAA RAW	NYY	2	1	4	14	4	1	0	50%	2.0	28.6%	7.1%	21.4%	0.0%	2.25	1.59	—
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	31	MLB MLE	NYY	13	13	80	339	78	31	10	100%	6.2	23.1%	9.0%	14.0%	3.0%	4.18	4.31	+0.6
2028	32	MLB MLE	NYY	12	12	74	313	76	27	10	100%	6.2	24.3%	8.6%	15.6%	3.2%	4.25	4.30	+0.5
2029	33	MLB MLE	NYY	11	11	68	288	67	26	10	100%	6.2	23.4%	9.1%	14.3%	3.5%	4.45	4.58	+0.3
2030	34	MLB MLE	NYY	10	10	62	262	59	25	10	100%	6.2	22.5%	9.6%	12.9%	3.8%	4.71	4.88	+0.0
2027	31	MLB CTX	NYY	13	13	80	338	78	31	11	100%	6.2	23.1%	9.0%	14.0%	3.2%	4.29	4.42	+0.6
2028	32	MLB CTX	NYY	12	12	74	312	76	27	11	100%	6.2	24.3%	8.6%	15.6%	3.4%	4.37	4.42	+0.5
2029	33	MLB CTX	NYY	11	11	68	287	67	26	11	100%	6.2	23.4%	9.1%	14.3%	3.7%	4.58	4.71	+0.3
2030	34	MLB CTX	NYY	10	10	62	262	59	25	11	100%	6.2	22.5%	9.6%	12.9%	4.1%	4.85	5.02	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		144	114	678	2871	665	245	90	79%	4.7	23.1%	8.5%	14.6%	3.1%	4.11	3.95	+7.7
/ 200 IP	—	RAW		43	34	200	847	196	72	27	79%	4.7	23.1%	8.5%	14.6%	3.1%	4.11	3.95	+2.3
Career	—	MLE		150	114	596	2497	586	199	59	76%	4.0	23.4%	8.0%	15.5%	2.4%	3.60	3.43	+6.8
/ 200 IP	—	MLE		50	38	200	838	197	67	20	76%	4.0	23.4%	8.0%	15.5%	2.4%	3.60	3.43	+2.0

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
Clarke Schmidt (OGILVIE)	—	—	4.08	23.8%	8.7%	2.8%	—	4.39	23.6%	14.7%	222	+0.31	—	—	—
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	62
Josh A. Smith R 2018 · 2.91 FIP	30	SP-	2.91	21.7%	5.2%	1.8%	.337	4.28	19.5%	12.2%	157	+1.37	2.91	598	61
Collin McHugh R 2017 · 3.60 FIP	30	SP	3.60	21.0%	7.2%	2.5%	.309	3.35	29.5%	21.0%	147	-0.25	1.77	806	61
Matt Harvey R 2019 · 5.21 FIP	30	SP	5.21	18.1%	10.2%	4.3%	.299	5.13	16.2%	8.6%	194	-0.08	2.90	806	61
Chi Chi González R 2022 · 4.30 FIP	30	SP-	4.30	17.6%	8.0%	3.0%	.315	5.36	10.8%	5.2%	122	+1.06	4.01	800	59
Kenta Maeda R 2018 · 2.89 FIP	30	SP-	2.89	28.8%	7.3%	2.3%	.312	3.55	27.4%	20.7%	327	+0.66	2.87	1,092	59
Mitch Atkins R 2016 · 3.65 FIP	30	SP-	3.65	21.4%	8.2%	2.4%	.341	4.77	14.3%	6.2%	78	+1.12	3.65	205	59
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	59
Trevor Cahill R 2018 · 3.37 FIP	30	SP	3.37	22.7%	9.8%	1.7%	.268	5.01	19.9%	10.6%	164	+1.64	3.37	556	58
David Hale R 2018 · 4.22 FIP	30	SP-	4.22	15.4%	7.5%	2.7%	.299	3.65	17.1%	11.3%	114	-0.57	3.30	493	57
Hector Noesí R 2015 · 4.37 FIP	28	SP-	4.37	17.6%	8.1%	3.2%	.261	—	—	—	—	—	4.37	250	56
Tyler Chatwood R 2020 · 3.30 FIP	30	SP	3.30	29.1%	10.5%	2.4%	.400	3.54	26.2%	11.7%	32	+0.24	3.30	537	56
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	55
Nate Karns R 2017 · 4.46 FIP	29	SP	4.46	27.1%	6.4%	5.2%	.276	—	—	—	—	—	3.88	287	55
Raynel Espinal R 2022 · 4.41 FIP	30	SP-	4.41	23.9%	10.5%	3.6%	.326	—	—	—	—	—	2.48	507	55
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	54
Burch Smith R 2019 · 3.96 FIP	29	SW	3.96	22.6%	12.3%	2.2%	.271	4.19	14.9%	9.0%	43	+0.23	3.50	382	53
Yohan Pino R 2015 · 4.13 FIP	31	SP-	4.13	17.8%	5.8%	3.3%	.312	5.33	15.2%	11.6%	35	+1.20	4.13	133	53
Matt Cain R 2015 · 4.88 FIP	30	SP-	4.88	17.1%	6.8%	4.3%	.296	4.87	15.2%	7.6%	214	-0.01	4.82	294	53
Austin Bibens-Dirkx R 2015 · 3.97 FIP	30	SP	3.97	17.4%	7.1%	2.6%	.315	4.94	15.9%	8.7%	305	+0.97	3.97	567	52

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	1.8	73	23.5%	9.0%	1.25	4.29
Noé Ramirez ('22)	1.3	52	24.8%	9.0%	1.33	4.19
Robert Stephenson ('23)	1.7	57	26.2%	9.9%	1.39	4.33
José Ruiz ('24)	1.3	52	22.2%	10.4%	1.41	4.41
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
Archie Bradley ('21)	2.2	74	23.2%	9.8%	0.85	3.93