Reese Olson — OGILVIE

Reese Olson P Detroit Tigers

Age 27 RHP 6'1" / 160 lbs MLB Svc 2.0 · Ctrl thru 2029 peak 1.5 · 2026 ILInjured 60-Day (D60)

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

showingROS

wRC+ AGAINSTvL 10698vR 90

ERA3.82

FIP3.83

K%23.2%

BB%7.8%

K-BB%15.3%

ROS IP1

Value2026 · WAR

Runs saved vs league avg · 1 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$0M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF5555

CTRL5050

CMD5050

K†5555

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p7829.7%

p5322.8%

xwOBA vs

p490.313

CH+2.9 (26%)

FB+2.9 (47%)

SL+0.8 (22%)

SI (28%)

CU (6%)

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

Status Pre-Arb SUPER-2

MLB Debut 2023

Service 2.715 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$0.1M	+0.1	$0.3M	+$0.2M
2027	Arb-2	$5M	+1.0	$7M	+$3M
2028	Arb-3	$6M	+0.8	$3M	+$0.0M (cut)
2029	Arb-4	$10M	+0.8	$3M	+$0.0M (cut)
Totals		$5M		$13M	+$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	19	ROK MLE	AZL Brewers	4	2	10	45	6	4	0	50%	2.6	13.3%	8.9%	4.4%	0.0%	5.23	3.10	—
2018	19	ROK RAW	AZL Brewers	4	2	10	45	6	4	0	50%	2.6	13.3%	8.9%	4.4%	0.0%	5.23	3.10	—
2019	20	A MLE	Wisconsin Timber Rattlers	27	14	95	425	84	47	8	52%	3.5	14.6%	13.0%	1.6%	2.4%	4.66	4.83	—
2019	20	A RAW	Wisconsin Timber Rattlers	27	14	95	425	84	47	8	52%	3.5	19.8%	11.1%	8.7%	1.9%	4.66	3.91	—
2021	22	MIX MLE	2 levels	21	21	105	439	114	51	6	100%	5.0	20.2%	13.2%	7.0%	2.0%	3.96	4.14	—
2021	22	MIX RAW	2 levels	21	21	105	439	114	51	6	100%	5.0	26.0%	11.6%	14.4%	1.4%	3.96	3.13	—
2022	23	AA MLE	Erie SeaWolves	26	25	120	508	168	38	15	96%	4.6	26.8%	8.2%	18.6%	3.8%	4.14	3.98	—
2022	23	AA RAW	Erie SeaWolves	26	25	120	508	168	38	15	96%	4.6	33.1%	7.5%	25.6%	3.0%	4.14	2.87	—
2023	24	MIX MLE	2 levels	31	28	140	597	150	55	19	90%	4.5	23.8%	8.8%	14.9%	3.5%	4.62	4.12	+1.3
2023	24	MIX MLE	2 levels	31	28	140	597	150	55	19	90%	4.5	23.8%	8.8%	14.9%	3.5%	4.62	4.12	+1.3
2023	24	MIX RAW	2 levels	31	28	140	597	150	55	19	90%	4.5	25.1%	9.2%	15.9%	3.2%	4.62	3.90	+1.7
2024	25	MIX MLE	2 levels	24	24	117	483	107	35	7	100%	4.9	21.7%	7.1%	14.6%	1.6%	3.38	3.03	+2.7
2024	25	MIX MLE	2 levels	24	24	117	483	107	35	7	100%	4.9	21.7%	7.1%	14.6%	1.6%	3.38	3.03	+2.7
2024	25	MIX RAW	2 levels	24	24	117	483	107	35	7	100%	4.9	22.2%	7.2%	14.9%	1.4%	3.38	2.95	+2.9
2025	26	MIX MLE	2 levels	16	16	79	326	79	25	7	100%	4.9	22.8%	8.1%	14.7%	1.8%	3.19	3.20	+1.7
2025	26	MIX MLE	2 levels	16	16	79	326	79	25	7	100%	4.9	22.8%	8.1%	14.7%	1.8%	3.19	3.20	+1.7
2025	26	MIX RAW	2 levels	16	16	79	326	79	25	7	100%	4.9	24.2%	7.7%	16.6%	2.1%	3.19	3.20	+1.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			56	53	285	1172	269	89	26	95%	5.1	23.0%	7.6%	15.4%	2.2%	3.60	3.34	+5.5
▸ 2026 season — projected remainder (no 2026 stats recorded)
2026	27	MLB	DET	1	1	1	4	1	0	0	100%	1.0	23.2%	7.8%	15.3%	2.4%	3.82	3.83	+0.0
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	28	MLB MLE	DET	14	14	85	360	83	29	9	100%	6.1	23.1%	8.0%	15.1%	2.5%	3.87	3.91	+1.0
2028	29	MLB MLE	DET	14	14	82	344	77	28	9	100%	5.8	22.5%	8.2%	14.3%	2.6%	3.99	4.07	+0.8
2029	30	MLB MLE	DET	13	13	77	323	77	25	9	100%	5.9	23.8%	7.7%	16.0%	2.8%	4.00	4.01	+0.8
2030	31	MLB MLE	DET	12	12	71	301	69	24	9	100%	6.0	23.0%	8.1%	14.9%	3.1%	4.14	4.24	+0.6
2031	32	MLB MLE	DET	11	11	66	279	62	24	9	100%	6.0	22.2%	8.5%	13.8%	3.3%	4.35	4.49	+0.3
2032	33	MLB MLE	DET	10	10	61	256	55	23	9	100%	6.1	21.4%	8.9%	12.4%	3.6%	4.60	4.77	+0.1
2027	28	MLB CTX	DET	14	14	81	342	79	27	8	100%	5.8	23.1%	8.0%	15.1%	2.4%	3.81	3.85	+1.0
2028	29	MLB CTX	DET	13	13	77	325	73	27	8	100%	5.9	22.5%	8.2%	14.3%	2.5%	3.93	4.01	+0.8
2029	30	MLB CTX	DET	12	12	73	308	73	24	8	100%	6.1	23.8%	7.7%	16.0%	2.7%	3.93	3.94	+0.8
2030	31	MLB CTX	DET	11	11	68	287	66	23	8	100%	6.2	23.0%	8.1%	14.9%	2.9%	4.07	4.17	+0.5
2031	32	MLB CTX	DET	10	10	63	266	59	23	8	100%	6.3	22.2%	8.5%	13.8%	3.2%	4.27	4.41	+0.3
2032	33	MLB CTX	DET	10	10	58	245	52	22	8	100%	5.8	21.4%	8.9%	12.4%	3.4%	4.52	4.69	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		126	123	704	2943	671	234	76	98%	5.6	22.8%	8.0%	14.8%	2.6%	3.88	3.60	+11.1
/ 200 IP	—	RAW		36	35	200	836	191	66	22	98%	5.6	22.8%	8.0%	14.8%	2.6%	3.88	3.60	+3.2
Career	—	MLE		149	130	666	2823	614	273	72	87%	4.5	21.8%	9.7%	12.1%	2.6%	4.05	3.89	+8.9
/ 200 IP	—	MLE		45	39	200	848	184	82	22	87%	4.5	21.8%	9.7%	12.1%	2.6%	4.05	3.89	+2.5

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
Reese Olson (OGILVIE)	—	—	3.83	23.2%	7.8%	2.4%	—	4.00	23.1%	15.1%	243	+0.17	—	—	—
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	70
Matt Andriese R 2017 · 4.71 FIP	27	SP	4.71	20.3%	7.2%	4.4%	.290	3.99	24.5%	17.5%	181	-0.72	3.08	744	66
Matt Harvey R 2016 · 3.35 FIP	27	SP	3.35	18.9%	6.0%	2.0%	.350	4.88	18.2%	10.3%	330	+1.53	2.90	806	65
Taylor Jungmann R 2017 · 3.88 FIP	27	SP-	3.88	18.8%	11.1%	1.8%	.279	—	—	—	—	—	3.59	435	64
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	63
Aaron Civale R 2022 · 3.63 FIP	27	SP	3.63	24.4%	5.4%	3.5%	.294	4.08	21.7%	14.5%	385	+0.45	3.33	1,198	62
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	62
Taijuan Walker R 2020 · 4.24 FIP	27	SP	4.24	22.2%	8.4%	3.6%	.236	4.04	20.4%	12.1%	489	-0.20	3.51	1,276	62
Tanner Houck R 2023 · 4.12 FIP	27	SP	4.12	21.4%	8.9%	3.1%	.291	3.57	19.6%	12.7%	233	-0.55	2.27	733	62
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	61
Nathan Eovaldi R 2016 · 4.71 FIP	26	SP	4.71	18.5%	7.2%	4.1%	.272	4.29	22.6%	15.6%	179	-0.42	2.44	1,378	61
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	61
Hector Noesí R 2015 · 4.37 FIP	28	SP-	4.37	17.6%	8.1%	3.2%	.261	—	—	—	—	—	4.37	250	61
Frankie Montas R 2020 · 4.74 FIP	27	SP	4.74	25.3%	9.7%	4.6%	.326	3.39	25.2%	18.3%	331	-1.35	2.82	1,009	60
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	60
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	60
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	60
Tyler Chatwood R 2017 · 4.54 FIP	27	SP-	4.54	19.0%	11.9%	2.8%	.279	4.53	20.6%	5.2%	199	-0.01	3.30	537	60
Jameson Taillon R 2019 · 3.56 FIP	27	SP	3.56	19.0%	4.4%	2.7%	.256	3.90	21.8%	16.2%	322	+0.34	3.12	1,401	60
Zach Plesac R 2022 · 4.30 FIP	27	SP	4.30	17.6%	6.7%	3.4%	.285	6.44	13.5%	5.0%	286	+2.14	3.27	965	60

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	2.6	74	22.8%	8.1%	1.11	4.08
Archie Bradley ('21)	2.2	74	23.2%	9.8%	0.85	3.93
Nick Wittgren ('23)	1.6	41	21.6%	7.0%	1.15	4.04
Chris Devenski ('24)	1.9	62	26.0%	6.9%	1.25	3.61
Michael Fulmer ('23)	3.4	96	20.3%	7.6%	0.99	3.94
Noé Ramirez ('22)	1.3	52	24.8%	9.0%	1.33	4.19
Jarlín García ('22)	1.5	61	19.6%	7.8%	1.33	3.79