Lucas Elissalt — OGILVIE

Lucas Elissalt P West Michigan Whitecaps

Age 22 RHP 6'4" / 190 lbs A+ Svc 0.0 · Ctrl thru 2033 peak 1.5 · 2029

2026 ROS PROJECTION93 act + 6 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 122113vR 105

ERA4.65

FIP4.65

K%19.8%

BB%10.8%

K-BB%9.0%

ROS IP6

Value2026 · WAR

Runs saved vs league avg · 98 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$16M ctrl surplus

Grades · Contract

Scouting Grades

OFP—40

STUF4550

CTRL—50

CMD3050

K†4555

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

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2028
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.5	$2M	+$1M
2029	Pre-Arb	$0.8M	+0.6	$2M	+$1M
2030	Pre-Arb	$0.9M	+0.7	$2M	+$1M
2031	Arb-1	$3M	+0.7	$2M	+$0.3M
2032	Arb-2	$4M	+0.6	$2M	+$0.0M (cut)
2033	Arb-3	$5M	+0.4	$0.9M	+$0.0M (cut)
Totals		$5M		$10M	+$4M

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)
2025	21	MIX MLE	2 levels	22	16	90	372	100	35	4	73%	4.1	20.1%	11.0%	9.1%	1.6%	2.51	3.68	—
2025	21	MIX MLE	2 levels	22	16	90	372	100	35	4	73%	4.1	20.1%	11.0%	9.1%	1.6%	2.51	3.68	—
2025	21	MIX RAW	2 levels	22	16	90	372	100	35	4	73%	4.1	26.9%	9.4%	17.5%	1.1%	2.51	2.62	—
▸ 2026 season
YTD	22	AA MLE	Erie SeaWolves	23	21	93	395	116	36	12	91%	4.0	22.9%	10.4%	12.5%	3.8%	3.98	4.55	—
YTD	22	AA MLE	Erie SeaWolves	23	21	93	395	116	36	12	91%	4.0	22.9%	10.4%	12.5%	3.8%	3.98	4.55	—
▸ 2026 season — so far · projected rest · full
2026	22	A+ RAW	DET	18	16	75	309	87	29	9	89%	4.2	28.2%	9.4%	18.8%	2.9%	3.72	3.51	—
2026	22	AA RAW	DET	5	5	18	86	29	7	3	100%	3.5	33.7%	8.1%	25.6%	3.5%	5.09	3.20	—
ROS	22	MLB MLE	DET	1	1	6	24	5	3	1	100%	5.7	19.8%	10.8%	9.0%	2.7%	4.65	4.65	+0.0
2026 TOT	22	MLB MLE	DET	—	—	98	419	121	39	13	—	—	28.8%	9.2%	19.6%	3.0%	4.02	4.55	+0.4
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	23	MLB MLE	DET	18	18	94	398	83	39	11	100%	5.2	20.9%	9.8%	11.1%	2.7%	4.50	4.43	+0.5
2028	24	MLB MLE	DET	17	17	97	408	88	38	11	100%	5.7	21.6%	9.2%	12.3%	2.7%	4.37	4.30	+0.7
2029	25	MLB MLE	DET	17	17	98	413	91	37	11	100%	5.8	22.0%	8.9%	13.1%	2.7%	4.28	4.22	+0.8
2030	26	MLB MLE	DET	16	16	98	413	92	37	11	100%	6.1	22.2%	8.8%	13.3%	2.7%	4.23	4.20	+0.8
2031	27	MLB MLE	DET	16	16	96	407	90	36	11	100%	6.0	22.2%	8.9%	13.2%	2.7%	4.23	4.24	+0.7
2032	28	MLB MLE	DET	16	16	93	394	87	36	11	100%	5.8	22.0%	9.1%	13.0%	2.8%	4.28	4.32	+0.6
2033	29	MLB MLE	DET	15	15	89	377	82	35	11	100%	5.9	21.8%	9.3%	12.5%	3.0%	4.38	4.45	+0.5
2034	30	MLB MLE	DET	14	14	84	354	76	34	11	100%	6.0	21.4%	9.6%	11.8%	3.2%	4.53	4.63	+0.3
2035	31	MLB MLE	DET	13	13	78	330	76	30	11	100%	6.0	23.0%	9.2%	13.9%	3.4%	4.55	4.56	+0.3
2036	32	MLB MLE	DET	12	12	72	305	69	29	11	100%	6.0	22.6%	9.6%	13.0%	3.7%	4.69	4.79	+0.1
2037	33	MLB MLE	DET	11	11	66	280	62	28	11	100%	6.0	22.1%	10.0%	12.1%	3.9%	4.90	5.04	-0.1
2027	23	MLB CTX	DET	9	9	47	198	42	20	5	100%	5.2	20.9%	9.8%	11.1%	2.6%	4.44	4.37	+0.3
2028	24	MLB CTX	DET	12	12	68	287	62	27	7	100%	5.7	21.6%	9.2%	12.3%	2.6%	4.31	4.24	+0.5
2029	25	MLB CTX	DET	14	14	79	334	73	30	9	100%	5.6	22.0%	8.9%	13.1%	2.6%	4.22	4.16	+0.6
2030	26	MLB CTX	DET	14	14	85	359	80	32	9	100%	6.1	22.2%	8.8%	13.3%	2.6%	4.17	4.14	+0.7
2031	27	MLB CTX	DET	14	14	87	367	81	33	10	100%	6.2	22.2%	8.9%	13.2%	2.6%	4.17	4.18	+0.7
2032	28	MLB CTX	DET	14	14	86	363	80	33	10	100%	6.1	22.0%	9.1%	13.0%	2.7%	4.21	4.25	+0.6
2033	29	MLB CTX	DET	14	14	83	350	76	33	10	100%	5.9	21.8%	9.3%	12.5%	2.9%	4.31	4.38	+0.4
2034	30	MLB CTX	DET	13	13	78	329	71	32	10	100%	6.0	21.4%	9.6%	11.8%	3.0%	4.46	4.56	+0.2
2035	31	MLB CTX	DET	12	12	74	312	72	29	10	100%	6.2	23.0%	9.2%	13.9%	3.3%	4.47	4.48	+0.3
2036	32	MLB CTX	DET	12	12	69	291	66	28	10	100%	5.8	22.6%	9.6%	13.0%	3.5%	4.60	4.70	+0.1
2037	33	MLB CTX	DET	10	10	63	266	59	27	10	100%	6.3	22.1%	10.0%	12.1%	3.8%	4.81	4.95	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		139	139	819	3459	761	320	100	100%	5.9	22.0%	9.3%	12.8%	2.9%	4.36	4.00	+8.8
/ 200 IP	—	RAW		34	34	200	844	186	78	24	100%	5.9	22.0%	9.3%	12.8%	2.9%	4.36	4.00	+2.1
Career	—	MLE		45	37	182	767	165	82	21	82%	4.1	21.5%	10.7%	10.9%	2.7%	3.26	4.13	+5.2
/ 200 IP	—	MLE		49	41	200	841	181	90	23	82%	4.1	21.5%	10.7%	10.9%	2.7%	3.26	4.13	+1.1

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
Lucas Elissalt (OGILVIE)	—	—	4.65	19.8%	10.8%	2.7%	—	4.32	21.5%	12.2%	289	-0.33	—	—	—
Noah Denoyer R 2021 · 4.51 FIP	23	SP-	4.51	21.5%	12.1%	3.1%	.275	4.13	25.3%	15.3%	121	-0.38	3.26	181	89
Bryce Conley R 2018 · 4.71 FIP	23	SP-	4.71	20.2%	12.2%	3.2%	.269	4.88	17.4%	3.3%	197	+0.17	4.22	560	89
Jared Karros R 2023 · 4.77 FIP	22	SP	4.77	19.0%	8.9%	3.9%	.290	5.26	17.8%	8.3%	120	+0.49	3.36	191	87
Christian Roa R 2021 · 4.94 FIP	22	SP	4.94	19.6%	12.4%	3.5%	.321	4.92	22.1%	6.6%	260	-0.02	4.21	412	87
Mike Vasil R 2022 · 3.63 FIP	22	SP	3.63	21.9%	10.5%	1.9%	.264	4.56	18.5%	9.7%	359	+0.93	3.63	429	87
Ryan Atkinson R 2016 · 4.58 FIP	23	SP-	4.58	18.4%	11.3%	2.9%	.315	4.48	21.6%	9.0%	305	-0.10	4.14	338	87
Chih-Jung Liu R 2021 · 4.41 FIP	22	SP	4.41	18.8%	10.5%	2.9%	.331	6.08	21.6%	9.0%	233	+1.67	4.41	283	87
Tyler Uberstine R 2022 · 4.19 FIP	23	SP-	4.19	19.5%	10.5%	2.6%	.302	4.32	22.2%	14.8%	121	+0.13	3.16	258	86
Tanner Burns R 2021 · 4.34 FIP	22	SP	4.34	22.2%	10.6%	3.2%	.292	5.32	19.2%	6.3%	244	+0.98	4.34	382	86
Johnathan Harmon R 2023 · 4.30 FIP	22	SP-	4.30	17.8%	10.2%	2.6%	.293	5.14	15.1%	6.3%	193	+0.84	3.52	282	86
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	85
Pat Gallagher R 2023 · 3.83 FIP	23	SP-	3.83	21.9%	8.3%	2.8%	.284	3.43	20.4%	11.2%	217	-0.40	3.07	280	85
Chad Patrick R 2022 · 3.86 FIP	23	SP	3.86	20.3%	9.9%	2.2%	.315	4.22	21.7%	13.8%	422	+0.36	3.71	565	85
Levi Thomas R 2021 · 5.22 FIP	23	SP-	5.22	18.1%	11.9%	3.9%	.328	5.16	20.8%	3.3%	31	-0.06	5.16	116	85
Miguel Almonte R 2015 · 3.88 FIP	22	SP-	3.88	18.0%	10.1%	1.8%	.300	4.41	19.4%	7.9%	143	+0.53	3.06	247	84
Tyler Skulina R 2015 · 4.28 FIP	23	SP	4.28	18.3%	11.6%	2.3%	.242	5.34	13.0%	-1.0%	147	+1.06	4.28	222	84
Curtis Taylor R 2017 · 3.95 FIP	22	SP	3.95	19.3%	9.9%	2.2%	.305	3.40	23.5%	13.7%	96	-0.55	2.58	408	84
CJ Van Eyk R 2021 · 4.79 FIP	22	SP	4.79	21.8%	12.7%	3.5%	.302	4.64	15.2%	5.3%	127	-0.15	4.17	438	84
John Klein R 2023 · 4.47 FIP	21	SP	4.47	17.4%	11.4%	2.5%	.287	4.09	19.4%	9.7%	290	-0.38	3.21	343	84
Nick Sinacola R 2022 · 4.44 FIP	22	SP-	4.44	19.3%	10.4%	3.0%	.335	4.05	18.2%	10.0%	254	-0.39	3.56	357	84

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	5.1	86	21.8%	9.4%	1.15	4.44
Daniel Norris ('22)	2.8	70	21.7%	8.5%	1.37	4.70
Buck Farmer ('24)	2.5	50	21.6%	10.5%	1.23	4.59
Vince Velasquez ('23)	3.8	85	24.9%	9.3%	1.48	4.88
Chad Kuhl ('24)	3.3	84	20.0%	10.4%	1.31	4.98
Matt Wisler ('22)	2.5	63	20.1%	7.6%	1.40	4.59
Michael Fulmer ('23)	3.4	96	20.3%	7.6%	0.99	3.94