Connor Van Scoyoc

Connor Van Scoyoc P Harrisburg Senators

Age 26 RHP 6'6" / 234 lbs AA peak 0.6 · 2027

2026 ROS PROJECTION74 act + 5 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 133125vR 117

ERA5.26

FIP5.26

K%10.0%

BB%9.4%

K-BB%0.6%

ROS IP5

Value2026 · WAR

Runs saved vs league avg · 80 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL5555

CMD3535

K†3030

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)
2019	19	ROK MLE	AZL Angels	12	5	40	199	50	36	1	42%	3.4	17.1%	22.6%	-5.5%	0.7%	5.13	4.91	—
2019	19	ROK RAW	AZL Angels	12	5	40	199	50	36	1	42%	3.4	25.1%	18.1%	7.0%	0.5%	5.13	3.62	—
2021	21	MIX MLE	2 levels	12	8	42	202	51	24	2	67%	3.5	18.1%	14.4%	3.7%	1.2%	6.48	4.06	—
2021	21	MIX RAW	2 levels	12	8	42	202	51	24	2	67%	3.5	25.2%	11.9%	13.4%	1.0%	6.48	3.00	—
2022	22	A MLE	Inland Empire 66ers	23	22	120	506	140	39	10	96%	5.2	20.5%	9.1%	11.4%	2.9%	4.28	4.11	—
2022	22	A RAW	Inland Empire 66ers	23	22	120	506	140	39	10	96%	5.2	27.7%	7.7%	20.0%	2.0%	4.28	2.83	—
2023	23	MIX MLE	2 levels	23	23	128	538	114	45	14	100%	5.6	16.6%	9.5%	7.1%	3.1%	3.80	4.58	—
2023	23	MIX MLE	2 levels	23	23	128	538	114	45	14	100%	5.6	16.6%	9.5%	7.1%	3.1%	3.80	4.58	—
2023	23	MIX RAW	2 levels	23	23	128	538	114	45	14	100%	5.6	21.2%	8.4%	12.8%	2.6%	3.80	3.80	—
2024	24	AA MLE	Hartford Yard Goats	23	22	115	489	73	43	12	96%	5.0	12.1%	9.7%	2.4%	3.2%	4.46	5.07	—
2024	24	AA MLE	Hartford Yard Goats	23	22	115	489	73	43	12	96%	5.0	12.1%	9.7%	2.4%	3.2%	4.46	5.07	—
2024	24	AA RAW	Hartford Yard Goats	23	22	115	489	73	43	12	96%	5.0	14.9%	8.8%	6.1%	2.5%	4.46	4.31	—
2025	25	AAA MLE	Albuquerque Isotopes	41	0	86	368	46	29	6	0%	2.1	10.4%	7.1%	3.3%	1.8%	4.19	4.09	—
2025	25	AAA MLE	Albuquerque Isotopes	41	0	86	368	46	29	6	0%	2.1	10.4%	7.1%	3.3%	1.8%	4.19	4.09	—
2025	25	AAA RAW	Albuquerque Isotopes	41	0	86	368	46	29	6	0%	2.1	12.5%	7.9%	4.6%	1.6%	4.19	3.95	—
▸ 2026 season
YTD	26	AAA MLE	Rochester Red Wings	30	5	74	321	69	25	12	17%	2.5	17.4%	8.3%	9.2%	4.4%	4.84	5.07	—
YTD	26	AAA MLE	Rochester Red Wings	30	5	74	321	69	25	12	17%	2.5	17.4%	8.3%	9.2%	4.4%	4.84	5.07	—
▸ 2026 season — so far · projected rest · full
2026	26	AA RAW	WSH	22	5	64	267	65	20	8	23%	2.9	24.3%	7.5%	16.9%	3.0%	3.82	3.64	—
2026	26	AAA RAW	WSH	8	0	11	54	4	5	4	0%	1.3	7.4%	9.3%	-1.9%	7.4%	10.97	7.71	—
ROS	26	MLB MLE	WSH	5	0	5	23	2	2	1	0%	1.1	10.0%	9.4%	0.6%	2.6%	5.26	5.26	-0.0
2026 TOT	26	MLB MLE	WSH	—	—	80	344	71	27	13	—	—	20.7%	7.9%	12.8%	3.7%	4.87	5.08	-0.3
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	27	MLB MLE	WSH	101	0	106	447	50	41	12	0%	1.0	11.2%	9.3%	1.9%	2.7%	5.18	5.19	-0.7
2028	28	MLB MLE	WSH	101	0	106	447	53	42	13	0%	1.0	11.9%	9.3%	2.6%	2.8%	5.17	5.21	-0.8
2029	29	MLB MLE	WSH	96	0	101	427	52	40	13	0%	1.1	12.2%	9.4%	2.7%	3.0%	5.22	5.29	-0.8
2030	30	MLB MLE	WSH	90	0	95	401	48	39	13	0%	1.1	12.0%	9.7%	2.3%	3.2%	5.34	5.44	-0.9
2027	27	MLB CTX	WSH	38	0	40	169	19	16	5	0%	1.1	11.2%	9.3%	1.9%	2.7%	5.18	5.19	-0.3
2028	28	MLB CTX	WSH	60	0	63	266	32	25	8	0%	1.1	11.9%	9.3%	2.6%	2.8%	5.17	5.21	-0.5
2029	29	MLB CTX	WSH	68	0	71	300	36	28	9	0%	1.0	12.2%	9.4%	2.7%	3.0%	5.22	5.29	-0.6
2030	30	MLB CTX	WSH	70	0	74	312	38	30	10	0%	1.1	12.0%	9.7%	2.3%	3.2%	5.34	5.44	-0.7
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		237	0	249	1051	125	99	31	0%	1.1	11.9%	9.5%	2.4%	3.0%	5.24	4.92	-1.1
/ 200 IP	—	RAW		190	0	200	844	100	80	25	0%	1.1	11.9%	9.5%	2.4%	3.0%	5.24	4.92	-0.9
Career	—	MLE		164	85	605	2623	417	271	71	52%	3.7	15.9%	10.3%	5.6%	2.7%	4.48	4.56	-1.8
/ 200 IP	—	MLE		54	28	200	867	138	90	24	52%	3.7	15.9%	10.3%	5.6%	2.7%	4.48	4.56	-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
Connor Van Scoyoc (OGILVIE)	—	—	5.26	10.0%	9.4%	2.6%	—	5.23	11.7%	2.4%	313	-0.03	—	—	—
Joel De La Cruz R 2015 · 4.19 FIP	26	SW	4.19	10.3%	6.7%	2.0%	.276	4.61	14.4%	5.8%	120	+0.42	4.19	205	85
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	85
Alex Sanabia R 2015 · 4.44 FIP	26	SP-	4.44	11.4%	7.9%	2.4%	.358	3.66	11.1%	6.2%	161	-0.78	3.42	378	83
Sugar Ray Marimon R 2015 · 4.12 FIP	26	SW	4.12	12.4%	9.1%	1.7%	.283	—	—	—	—	—	4.12	107	82
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	82
Chance Huff R 2023 · 5.57 FIP	23	SW	5.57	11.8%	11.4%	3.7%	.312	5.08	15.7%	0.2%	155	-0.49	4.31	238	81
Brad Allen R 2015 · 4.25 FIP	26	SW	4.25	14.0%	12.6%	1.3%	.315	5.82	14.7%	1.5%	87	+1.57	4.25	149	81
Jake McCasland R 2018 · 4.34 FIP	26	SW	4.34	12.8%	9.5%	2.0%	.313	—	—	—	—	—	3.07	367	80
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	80
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	80
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	79
Bryce Morrow R 2015 · 4.31 FIP	27	SP-	4.31	12.8%	7.9%	2.4%	.316	5.44	10.1%	-0.2%	50	+1.13	4.31	125	79
Kelvis Valerio R 2017 · 4.14 FIP	25	SW	4.14	11.7%	7.1%	2.1%	.269	—	—	—	—	—	4.14	266	79
Drasen Johnson R 2016 · 4.70 FIP	24	SW	4.70	9.6%	5.7%	3.1%	.325	—	—	—	—	—	4.70	110	78
Tyler Santana R 2023 · 4.43 FIP	25	SW	4.43	15.4%	10.3%	2.4%	.306	4.90	15.1%	4.9%	191	+0.47	3.37	399	77
Colin Bates R 2015 · 4.57 FIP	27	SP-	4.57	10.5%	6.5%	2.8%	.301	—	—	—	—	—	4.57	111	77
Aaron Northcraft R 2016 · 4.19 FIP	26	SW	4.19	16.1%	8.3%	2.5%	.309	3.32	24.1%	13.4%	34	-0.87	3.32	252	77
Cullen Kafka R 2023 · 4.95 FIP	24	SW	4.95	14.2%	12.1%	2.8%	.330	—	—	—	—	—	3.64	148	77
Paul Clemens R 2015 · 5.37 FIP	27	SP-	5.37	14.3%	14.1%	3.1%	.310	4.62	16.9%	7.3%	200	-0.75	4.58	247	77
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	76

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	2.4	96	11.5%	9.4%	1.11	5.23
Ty Blach ('24)	2.5	84	12.8%	6.9%	1.23	5.56
Luis Perdomo ('22)	2.3	90	16.6%	7.8%	1.08	5.09
Chi Chi González ('22)	1.3	64	13.3%	9.0%	1.41	5.44
Sal Romano ('21)	1.3	86	17.0%	8.8%	1.29	5.10
Eddie Butler ('18)	1.2	62	13.3%	9.8%	1.49	5.74
Josh Fleming ('24)	1.3	51	14.6%	7.5%	1.17	4.77