Christian Scott — OGILVIE

Christian Scott P New York Mets

Age 27 RHP 6'4" / 215 lbs MLB Svc 2.0 · Ctrl thru 2029 peak 1.1 · 2027

2026 ROS PROJECTION113 act + 10 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 10496vR 87

ERA3.74

FIP3.83

K%25.6%

BB%7.9%

K-BB%17.7%

ROS IP10

Value2026 · WAR

Runs saved vs league avg · 123 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$3M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF4040

CTRL6060

CMD5050

K†5060

Statcast Percentiles

FB Velo

p6495.5

Whiff%

p5726.4%

p8027.8%

xwOBA vs

p590.303

FB+1.4 (53%)

SL-1.2 (37%)

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

Status Pre-Arb SUPER-2

MLB Debut 2024

Service 2.000 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Arb-1	$0.1M	+0.2	$0.7M	+$0.6M
2027	Arb-2	$2M	+0.6	$2M	+$0.2M
2028	Arb-3	$3M	+0.5	$2M	+$0.0M (cut)
2029	Arb-4	$4M	+0.3	$1.0M	+$0.0M (cut)
Totals		$2M		$6M	+$0.7M

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)
2021	22	ROK MLE	FCL Mets	3	0	3	11	1	1	0	0%	1.0	9.1%	9.1%	0.0%	0.0%	3.00	3.48	—
2021	22	ROK RAW	FCL Mets	3	0	3	11	1	1	0	0%	1.0	9.1%	9.1%	0.0%	0.0%	3.00	3.43	—
2022	23	MIX MLE	2 levels	18	9	59	261	77	22	2	50%	3.3	22.1%	9.8%	12.3%	1.0%	4.45	3.05	—
2022	23	MIX RAW	2 levels	18	9	59	261	77	22	2	50%	3.3	29.5%	8.4%	21.1%	0.8%	4.45	2.04	—
2023	24	MIX MLE	3 levels	19	19	88	335	107	12	5	100%	4.6	25.6%	4.1%	21.5%	2.0%	2.57	2.56	—
2023	24	MIX MLE	3 levels	19	19	88	335	107	12	5	100%	4.6	25.6%	4.1%	21.5%	2.0%	2.57	2.56	—
2023	24	MIX RAW	3 levels	19	19	88	335	107	12	5	100%	4.6	31.9%	3.6%	28.4%	1.5%	2.57	1.81	—
2024	25	MIX MLE	2 levels	18	18	90	361	94	24	18	100%	5.0	23.4%	6.3%	17.1%	5.1%	3.71	4.72	+0.2
2024	25	MIX MLE	2 levels	18	18	90	361	94	24	18	100%	5.0	23.4%	6.3%	17.1%	5.1%	3.71	4.72	+0.2
2024	25	MIX RAW	2 levels	18	18	90	361	94	24	18	100%	5.0	26.0%	6.6%	19.4%	5.0%	3.71	4.42	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			30	30	147	628	159	56	18	100%	4.9	25.3%	8.9%	16.4%	2.9%	4.05	3.67	+2.2
▸ 2026 season
YTD	27	MLB MLE	New York Mets	24	24	113	489	137	46	13	100%	4.7	27.4%	9.4%	18.1%	2.7%	3.98	3.47	+2.0
YTD	27	MLB MLE	New York Mets	24	24	113	489	137	46	13	100%	4.7	27.4%	9.4%	18.1%	2.7%	3.98	3.47	+2.0
▸ 2026 season — so far · projected rest · full
2026	27	AAA RAW	NYM	3	3	14	58	17	2	3	100%	4.6	29.3%	3.4%	25.9%	5.2%	5.27	3.90	—
2026	27	MLB RAW	NYM	21	21	99	431	120	44	10	100%	4.7	27.8%	10.2%	17.6%	2.3%	3.81	3.32	+1.9
SO FAR	27	MLB RAW	NYM	21	21	99	431	120	44	10	100%	4.7	27.8%	10.2%	17.6%	2.3%	3.81	3.32	+1.9
ROS	27	MLB MLE	NYM	2	2	10	41	11	3	1	100%	4.9	25.6%	7.9%	17.7%	3.5%	3.74	3.83	+0.1
ROS	27	MLB CTX	NYM	2	2	10	42	11	3	1	100%	5.0	25.6%	7.9%	17.7%	3.4%	3.74	3.83	+0.1
2026 TOT	27	MLB MLE	NYM	—	—	123	530	148	49	14	—	—	27.8%	9.3%	18.5%	2.7%	3.96	3.50	+2.1
FULL	27	MLB A+C	NYM	—	—	109	461	148	49	14	—	—	32.0%	10.7%	21.3%	3.1%	4.46	3.47	+1.9
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	28	MLB MLE	NYM	12	12	73	309	78	26	10	100%	6.1	25.3%	8.5%	16.7%	3.1%	4.06	4.13	+0.7
2028	29	MLB MLE	NYM	12	12	70	295	73	26	10	100%	5.8	24.7%	8.8%	15.9%	3.3%	4.20	4.30	+0.5
2029	30	MLB MLE	NYM	11	11	66	277	66	25	10	100%	6.0	24.0%	9.1%	14.9%	3.5%	4.38	4.50	+0.3
2030	31	MLB MLE	NYM	10	10	61	258	60	24	10	100%	6.1	23.2%	9.4%	13.8%	3.7%	4.59	4.73	+0.1
2027	28	MLB CTX	NYM	12	12	69	291	74	25	9	100%	5.8	25.3%	8.5%	16.7%	3.1%	4.06	4.13	+0.6
2028	29	MLB CTX	NYM	11	11	66	279	69	24	9	100%	6.0	24.7%	8.8%	15.9%	3.3%	4.20	4.30	+0.5
2029	30	MLB CTX	NYM	10	10	62	262	63	24	9	100%	6.2	24.0%	9.1%	14.9%	3.5%	4.38	4.50	+0.3
2030	31	MLB CTX	NYM	10	10	58	245	57	23	9	100%	5.8	23.2%	9.4%	13.8%	3.7%	4.58	4.72	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		75	75	413	1751	433	156	56	100%	5.5	24.7%	8.9%	15.8%	3.2%	4.19	3.89	+5.0
/ 200 IP	—	RAW		36	36	200	849	210	76	27	100%	5.5	24.7%	8.9%	15.8%	3.2%	4.19	3.89	+2.4
Career	—	MLE		82	70	352	1457	363	109	41	85%	4.3	24.9%	7.5%	17.4%	2.8%	3.63	3.49	+3.8
/ 200 IP	—	MLE		47	40	200	828	206	62	23	85%	4.3	24.9%	7.5%	17.4%	2.8%	3.63	3.49	+1.8

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
Christian Scott (OGILVIE)	—	—	4.39	21.9%	6.1%	3.6%	—	4.30	24.7%	15.9%	208	-0.09	—	—	—
Zack Wheeler R 2017 · 4.75 FIP	27	SP	4.75	21.0%	10.1%	3.9%	.327	3.09	23.0%	16.8%	449	-1.66	2.28	1,586	74
Mat Latos R 2015 · 3.60 FIP	27	SP	3.60	20.2%	6.3%	2.6%	.306	5.16	14.5%	4.4%	128	+1.56	3.60	244	73
Connor Grey R 2021 · 3.82 FIP	27	SP-	3.82	22.1%	8.1%	2.8%	.286	4.37	16.2%	7.0%	104	+0.55	2.70	461	72
Raynel Espinal R 2019 · 3.90 FIP	27	SP-	3.90	22.4%	7.1%	3.2%	.313	4.01	22.3%	12.4%	224	+0.11	2.48	507	72
Brendan Beck R 2023 · 3.19 FIP	24	SP	3.19	22.5%	6.7%	2.1%	.289	3.50	21.3%	14.6%	262	+0.31	3.15	293	70
Cameron Foster R 2023 · 4.31 FIP	24	SP	4.31	18.9%	10.3%	2.7%	.329	4.05	20.9%	10.9%	132	-0.26	2.54	213	70
Sawyer Gipson-Long R 2023 · 4.69 FIP	25	SP	4.69	26.3%	7.6%	5.2%	.272	4.55	19.5%	11.7%	166	-0.14	3.87	506	69
Rubby De La Rosa R 2016 · 4.09 FIP	27	SP-	4.09	24.3%	8.6%	3.6%	.248	4.13	27.6%	18.3%	42	+0.04	4.04	281	69
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	69
Hector Noesí R 2015 · 4.37 FIP	28	SP-	4.37	17.6%	8.1%	3.2%	.261	—	—	—	—	—	4.37	250	68
Nate Karns R 2015 · 3.98 FIP	27	SP	3.98	23.3%	8.9%	3.1%	.281	4.07	25.1%	15.9%	140	+0.09	3.88	287	68
Ryan Jennings R 2023 · 3.43 FIP	24	SP-	3.43	23.4%	11.9%	1.5%	.316	4.34	22.5%	9.8%	109	+0.91	3.43	142	68
Joe Wieland R 2016 · 4.27 FIP	26	SP	4.27	18.6%	7.3%	3.3%	.359	—	—	—	—	—	3.38	270	68
Michael Darrell-Hicks R 2023 · 3.71 FIP	25	SP-	3.71	20.3%	8.7%	2.2%	.309	3.50	21.1%	13.0%	142	-0.21	1.87	251	67
Alex Meyer R 2017 · 3.99 FIP	27	SP	3.99	25.5%	12.8%	2.6%	.291	—	—	—	—	—	3.10	230	67
Austin Voth R 2019 · 3.50 FIP	27	SP	3.50	23.5%	6.1%	2.9%	.305	4.56	21.1%	13.5%	209	+1.06	3.41	1,057	67
Daniel Corcino R 2018 · 3.84 FIP	27	SP-	3.84	20.8%	10.0%	2.2%	.265	5.83	17.5%	5.3%	119	+1.99	3.84	299	66
Jesse Scholtens R 2021 · 4.18 FIP	27	SP	4.18	20.8%	8.2%	3.3%	.314	4.58	19.0%	11.3%	215	+0.40	3.40	876	66
Markus Solbach R 2019 · 3.58 FIP	27	SP	3.58	16.9%	6.1%	2.1%	.311	4.62	17.1%	9.1%	111	+1.04	3.34	391	66
Antonio Guzman R 2015 · 3.60 FIP	27	SP	3.60	18.8%	11.2%	1.2%	.328	3.47	20.6%	11.3%	170	-0.13	3.15	254	66

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	1.7	69	23.8%	8.3%	1.32	4.30
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
Austin Voth ('24)	1.7	58	22.2%	8.2%	1.50	4.63
Robert Stephenson ('23)	1.7	57	26.2%	9.9%	1.39	4.33
Jarlín García ('22)	1.5	61	19.6%	7.8%	1.33	3.79
José Ruiz ('24)	1.3	52	22.2%	10.4%	1.41	4.41