Reese Olson

P Detroit Tigers

Age 28 RHP 6'1" / 160 lbs MLB Svc 3.0 · Ctrl thru 2029 peak 1.1 · 2028 ILInjured 60-Day (D60)

Overview

MLBSPIL-6040-MANArb-1FA 2030

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	24	MIX2 levels	31	28	140	4.62	3.90	25.1%	9.2%	2.5	K 24.0% · BB 8.8% · FIP 4.10
2024	25	MIX2 levels	24	24	117	3.38	2.95	22.2%	7.2%	3.6	K 21.7% · BB 7.1% · FIP 3.03
2025	26	MIX2 levels	16	16	79	3.19	3.20	24.2%	7.7%	2.1	K 22.8% · BB 8.1% · FIP 3.20
2026	27	No MLB games played
2027PROJ	28	MLBDET	8	8	48	3.86	3.90	23.2%	7.9%	0.9
2028PROJ95% MLB	29	MLBDET	11	11	68	3.92	4.00	22.6%	8.1%	1.1
2029PROJ95% MLB	30	MLBDET	10	10	58	4.09	4.20	21.9%	8.4%	0.8

Last 3 seasons WAR 8.3 · Next 3 projected WAR 2.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2029Service3.715First FA2030

2027Arb-1$2M2028Arb-2$4M2029Arb-3$4M

Skills · percentileStatcast 2025

K%53

xwOBA vs49

FB Velo47

CompsErik Hiljus (age 28) · Fabio Castillo (age 28) · Ariel Peña (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10799vR 91

ERA3.86

FIP3.90

K%23.2%

BB%7.9%

K-BB%15.3%

Proj IP48

Value2027 · WAR

Runs saved vs league avg · 48 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$12M ctrl surplus

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL5050

CMD5050

K†5555

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p7829.7%

p5322.8%

xwOBA vs

p490.313

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

Status Arb-1

MLB Debut 2023

Service 3.715 yrs.days

Team Control Through 2029

First FA Year 2030

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$2M	+0.9	$4M	+$2M
2028	Arb-2	$4M	+1.1	$8M	+$4M
2029	Arb-3	$4M	+0.8	$3M	+$0.0M (cut)
Totals		$6M		$15M	+$6M

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 the standard WAR scale.

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 + 2027 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	24.0%	8.8%	15.2%	3.5%	4.62	4.10	+2.2
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	+2.5
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	+3.5
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	+3.5
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	+3.6
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	+2.1
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	+2.1
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	+2.1
▸ 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	+7.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	DET	8	8	48	203	47	16	5	100%	6.0	23.2%	7.9%	15.3%	2.5%	3.86	3.90	+0.9
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	DET	12	12	71	301	68	25	8	100%	6.0	22.6%	8.1%	14.4%	2.7%	3.98	4.06	+1.1
2029	30	MLB MLE	DET	10	10	61	257	56	22	7	100%	6.1	21.9%	8.4%	13.4%	2.9%	4.16	4.27	+0.8
2030	31	MLB MLE	DET	8	8	50	211	44	18	7	100%	6.2	21.1%	8.8%	12.3%	3.1%	4.37	4.50	+0.5
2031	32	MLB MLE	DET	6	6	38	161	33	15	5	100%	6.4	20.3%	9.2%	11.1%	3.3%	4.60	4.76	+0.3
2028	29	MLB CTX	DET	11	11	68	287	65	23	7	100%	6.2	22.6%	8.1%	14.4%	2.5%	3.92	4.00	+1.1
2029	30	MLB CTX	DET	10	10	58	245	54	21	7	100%	5.8	21.9%	8.4%	13.4%	2.7%	4.09	4.20	+0.8
2030	31	MLB CTX	DET	8	8	47	198	42	17	6	100%	5.9	21.1%	8.8%	12.3%	3.0%	4.30	4.43	+0.5
2031	32	MLB CTX	DET	6	6	36	152	31	14	5	100%	6.0	20.3%	9.2%	11.1%	3.2%	4.52	4.68	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		91	88	494	2056	460	164	51	97%	5.4	22.4%	8.0%	14.4%	2.5%	3.84	3.58	+10.9
/ 200 IP	—	RAW		37	36	200	832	186	66	21	97%	5.4	22.4%	8.0%	14.4%	2.5%	3.84	3.58	+4.4
Career	—	MLE		149	130	666	2823	616	273	72	87%	4.5	21.8%	9.7%	12.1%	2.6%	4.05	3.89	+9.9
/ 200 IP	—	MLE		45	39	200	848	185	82	22	87%	4.5	21.8%	9.7%	12.1%	2.6%	4.05	3.89	+3.9

How the minor-league lines were translated

One row per minor-league stint. Open a row to see each step: the raw rate, the park adjustment, the league/level factor, the age adjustment (hitters) and the resulting MLE rate. Factors are the same ones listed on the MLE Factors page.

2025 AAAToledo Mud Hens · 10 IPFIP 3.51 → 4.55 (+1.04)K% 34.1% → 29.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.15%	—	×0.860	29.37%
BB% (unintentional) /BF	4.88%	—	×0.900	4.39%
HR / BF /BF	4.88%	÷0.872	×1.100	6.15%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 74).

Result: FIP 3.51 → 4.55, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2023 AAAToledo Mud Hens · 37 IPFIP 3.99 → 4.50 (+0.50)K% 26.9% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.86%	—	×0.860	23.10%
BB% (unintentional) /BF	12.57%	—	×0.900	11.31%
HR / BF /BF	2.86%	÷0.901	×1.100	3.49%

Result: FIP 3.99 → 4.50, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2022 AAErie SeaWolves · 120 IPFIP 2.88 → 3.98 (+1.10)K% 33.1% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.07%	—	×0.810	26.79%
BB% (unintentional) /BF	7.48%	—	×1.100	8.23%
HR / BF /BF	2.95%	÷0.926	×1.200	3.83%

Factors used: pitcher AA level factors — K ×0.81, BB ×1.10, HR ×1.20. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 85).

Result: FIP 2.88 → 3.98, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2021 A+West Michigan Whitecaps · 80 IPFIP 2.97 → 4.12 (+1.15)K% 27.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.76%	—	×0.770	21.38%
BB% (unintentional) /BF	11.04%	—	×1.150	12.70%
HR / BF /BF	1.49%	÷0.841	×1.250	2.22%

Factors used: pitcher A+ level factors — K ×0.77, BB ×1.15, HR ×1.25. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 68).

Result: FIP 2.97 → 4.12, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2021 AAErie SeaWolves · 25 IPFIP 3.63 → 4.19 (+0.57)K% 20.2% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.19%	—	×0.810	16.36%
BB% (unintentional) /BF	13.46%	—	×1.100	14.81%
HR / BF /BF	0.96%	÷1.055	×1.200	1.09%

Result: FIP 3.63 → 4.19, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2019 AWisconsin Timber Rattlers · 95 IPFIP 3.86 → 4.83 (+0.97)K% 19.8% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.76%	—	×0.740	14.63%
BB% (unintentional) /BF	11.06%	—	×1.180	13.05%
HR / BF /BF	1.88%	÷1.022	×1.300	2.39%

Factors used: pitcher A level factors — K ×0.74, BB ×1.18, HR ×1.30. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 104).

Result: FIP 3.86 → 4.83, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

2018 ROKAZL Brewers · 10 IPFIP 3.10 → 3.74 (+0.64)K% 13.3% → 9.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.33%	—	×0.680	9.07%
BB% (unintentional) /BF	8.89%	—	×1.250	11.11%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP 3.10 → 3.74, computed from the rates in the table with the same formula before and after. The MLE line is not regressed to the mean — regression is applied when seasons are blended into a projection (how).

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)	—	—	3.90	23.2%	7.9%	2.5%	—	4.25	21.9%	13.5%	182	+0.35	—	—	—
Erik Hiljus R 2001 · 3.35 FIP	28	SP-	3.35	23.1%	6.9%	2.4%	.321	6.07	14.1%	4.4%	46	+2.72	3.35	112	75
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	71
Ariel Peña R 2017 · 3.99 FIP	28	SP	3.99	22.5%	12.0%	2.3%	.304	6.07	19.9%	-5.7%	21	+2.08	3.74	223	69
Jonathan Pintaro R 2024 · 3.42 FIP	26	SP	3.42	18.9%	9.4%	1.3%	.264	4.07	23.9%	12.1%	153	+0.65	3.42	223	69
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	68
Omar Bencomo R 2017 · 4.50 FIP	28	SP-	4.50	18.9%	6.3%	4.0%	.333	4.48	14.9%	10.1%	186	-0.02	3.70	381	68
Todd Redmond R 2013 · 4.14 FIP	28	SP-	4.14	23.5%	6.5%	4.0%	.266	3.57	17.0%	10.1%	170	-0.57	3.21	247	68
Gary Glover R 2005 · 4.20 FIP	28	SP-	4.20	20.4%	7.0%	3.5%	.327	4.50	15.2%	8.3%	132	+0.30	4.02	516	68
Yariel Rodríguez R 2024 · 3.76 FIP	27	SP	3.76	24.9%	11.4%	2.4%	.275	3.72	24.1%	12.7%	89	-0.04	2.32	196	67
Ryan Watson R 2024 · 4.15 FIP	25	SP-	4.15	18.6%	4.9%	3.7%	.342	5.48	13.1%	5.4%	98	+1.33	4.15	165	67
Nate Karns R 2016 · 3.88 FIP	28	SP-	3.88	24.2%	10.6%	2.7%	.322	4.46	27.1%	20.7%	45	+0.58	3.88	299	65
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	65
Braydon Tucker R 2024 · 3.25 FIP	25	SP-	3.25	18.3%	7.1%	1.5%	.291	4.70	15.3%	6.3%	208	+1.45	3.25	314	65
Brian Edgington R 2024 · 3.99 FIP	25	SP	3.99	19.5%	6.5%	3.1%	.321	5.28	19.3%	7.0%	58	+1.29	3.99	171	65
Ramon Ramirez R 2008 · 4.31 FIP	25	SP-	4.31	20.0%	10.5%	2.9%	.200	—	—	—	—	—	3.65	182	65
Stan Spencer R 2000 · 4.42 FIP	30	SP	4.42	19.2%	8.7%	3.4%	.259	—	—	—	—	—	3.61	119	64
Austin Bergner R 2024 · 4.84 FIP	27	SP	4.84	22.2%	12.5%	3.7%	.325	4.42	18.7%	7.3%	107	-0.42	4.06	464	64
Kyle Snyder R 2006 · 4.47 FIP	28	SP-	4.47	19.9%	5.9%	4.2%	.373	4.83	16.9%	4.5%	54	+0.36	3.80	236	64
David Phelps R 2015 · 3.94 FIP	28	SP	3.94	16.0%	6.8%	2.4%	.299	2.82	29.9%	20.6%	142	-1.12	2.50	672	64
Andrew Triggs R 2017 · 4.38 FIP	28	SP	4.38	17.7%	6.7%	3.5%	.288	4.68	23.6%	13.7%	41	+0.30	1.66	242	63

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 historical, 1901-2023), also matched on career-to-date at the same age. * Historical (Lahman) careers: rates era-adjusted to 2001-24 league levels; WAR is an OGILVIE proxy.

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	2.8	70	22.5%	8.1%	0.98	3.87
Gary Lucas ('80-'87, 6 WAR*)	3.3	84	20.3%*	8.1%*	0.84*	3.58*
Cecil Upshaw ('66-'75, 6 WAR*)	2.8	70	18.2%*	7.7%*	0.94*	3.77*
Daniel Hudson ('24)	4.3	71	22.8%	7.7%	1.01	3.74
Tom Johnson ('74-'78, 3 WAR*)	1.4	68	21.7%*	7.8%*	0.86*	3.69*
Adam Warren ('19)	2.5	70	20.8%	8.3%	1.02	3.53
David Phelps ('22)	3.4	76	22.9%	9.4%	0.94	3.80