Mat Olsen

P ACL Giants

Age 27 RHP 5'11" / 185 lbs ROK

Overview

ROKPROSPECT

MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	23	MIX2 levels	41	0	56	5.14	2.17	34.3%	6.9%	—	K 26.8% · BB 7.9% · FIP 3.24
2024	24	AASF	35	0	47	4.02	3.08	19.9%	8.7%	—	K 16.1% · BB 9.5% · FIP 3.58
2025	25	MIX2 levels	7	0	9	6.23	2.52	18.9%	8.1%	—	K 18.9% · BB 8.1% · FIP 2.53
2026	26	No MLB games played
2027PROJ	27	MLBSF	—	—	0	4.52	4.52	20.7%	9.3%	—
2028PROJ36% MLB	28	MLBSF	8	0	8	4.55	4.58	20.8%	9.5%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsC.C. Lee (age 27) · Michael Dimock (age 27) · Neil Wagner (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119111vR 103

ERA4.52

FIP4.52

K%20.7%

BB%9.3%

K-BB%11.4%

Proj IP28

Value2027 · WAR

Runs saved vs league avg · 28 IP

Grades · Contract

Scouting Grades

K†5050

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 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)
2021	21	ROK MLE	ACL Giants Orange	3	0	3	9	5	0	0	0%	1.0	55.6%	0.0%	55.6%	0.0%	0.00	-1.59	—
2021	21	ROK RAW	ACL Giants Orange	3	0	3	9	5	0	0	0%	1.0	55.6%	0.0%	55.6%	0.0%	0.00	-0.23	—
2022	22	MIX MLE	2 levels	36	0	58	255	83	25	1	0%	1.6	24.8%	11.3%	13.5%	0.4%	3.41	2.68	—
2022	22	MIX RAW	2 levels	36	0	58	255	83	25	1	0%	1.6	32.5%	9.8%	22.7%	0.4%	3.41	1.76	—
2023	23	MIX MLE	2 levels	41	0	56	245	84	17	5	0%	1.4	26.8%	7.9%	18.9%	2.6%	5.14	3.24	—
2023	23	MIX RAW	2 levels	41	0	56	245	84	17	5	0%	1.4	34.3%	6.9%	27.3%	2.0%	5.14	2.17	—
2024	24	AA MLE	Richmond Flying Squirrels	35	0	47	196	39	17	2	0%	1.3	16.1%	9.5%	6.6%	1.2%	4.02	3.58	—
2024	24	AA MLE	Richmond Flying Squirrels	35	0	47	196	39	17	2	0%	1.3	16.1%	9.5%	6.6%	1.2%	4.02	3.58	—
2024	24	AA RAW	Richmond Flying Squirrels	35	0	47	196	39	17	2	0%	1.3	19.9%	8.7%	11.2%	1.0%	4.02	3.08	—
2025	25	MIX MLE	2 levels	7	0	9	37	7	3	0	0%	1.2	18.9%	8.1%	10.8%	0.0%	6.23	2.53	—
2025	25	MIX MLE	2 levels	7	0	9	37	7	3	0	0%	1.2	18.9%	8.1%	10.8%	0.0%	6.23	2.53	—
2025	25	MIX RAW	2 levels	7	0	9	37	7	3	0	0%	1.2	18.9%	8.1%	10.8%	0.0%	6.23	2.52	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	SF	—	—	0	—	—	—	—	—	—	20.7%	9.3%	11.4%	2.9%	4.52	4.52	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	SF	22	0	23	97	20	9	3	0%	1.0	20.8%	9.5%	11.4%	3.0%	4.55	4.58	-0.0
2028	28	MLB CTX	SF	8	0	8	34	7	3	1	0%	1.0	20.8%	9.5%	11.4%	3.0%	4.55	4.58	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	0	8	35	7	3	1	0%	1.0	20.8%	9.5%	11.4%	3.0%	4.55	4.21	+0.0
/ 200 IP	—	RAW		190	0	200	844	168	72	24	0%	1.1	20.8%	9.5%	11.4%	3.0%	4.55	4.21	+0.8
Career	—	MLE		122	0	173	742	173	70	10	0%	1.4	23.3%	9.4%	13.8%	1.3%	4.22	3.05	-0.0
/ 200 IP	—	MLE		141	0	200	859	200	81	11	0%	1.4	23.3%	9.4%	13.8%	1.3%	4.22	3.05	-0.1

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 ROKACL Giants · 6 IPFIP 0.69 → 1.46 (+0.77)K% 28.6% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.680	19.43%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	0.00%	÷1.128	×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 126).

Result: FIP 0.69 → 1.46, 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).

2024 AARichmond Flying Squirrels · 47 IPFIP 3.08 → 3.58 (+0.50)K% 19.9% → 16.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.90%	—	×0.810	16.12%
BB% (unintentional) /BF	8.67%	—	×1.100	9.54%
HR / BF /BF	1.02%	÷1.062	×1.200	1.15%

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 112).

Result: FIP 3.08 → 3.58, 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 A+Eugene Emeralds · 37 IPFIP 1.78 → 2.76 (+0.98)K% 36.3% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.31%	—	×0.770	27.96%
BB% (unintentional) /BF	8.28%	—	×1.150	9.52%
HR / BF /BF	1.27%	÷1.076	×1.250	1.48%

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 115).

Result: FIP 1.78 → 2.76, 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 AARichmond Flying Squirrels · 19 IPFIP 2.96 → 4.11 (+1.16)K% 30.7% → 24.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.68%	—	×0.810	24.85%
BB% (unintentional) /BF	4.55%	—	×1.100	5.00%
HR / BF /BF	3.41%	÷0.906	×1.200	4.52%

Result: FIP 2.96 → 4.11, 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 A+Eugene Emeralds · 41 IPFIP 2.23 → 3.09 (+0.86)K% 31.1% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.05%	—	×0.770	23.91%
BB% (unintentional) /BF	11.58%	—	×1.150	13.32%
HR / BF /BF	0.53%	÷1.120	×1.250	0.59%

Result: FIP 2.23 → 3.09, 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 ASan Jose Giants · 17 IPFIP 0.57 → 1.48 (+0.92)K% 36.9% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.92%	—	×0.740	27.32%
BB% (unintentional) /BF	4.62%	—	×1.180	5.45%
HR / BF /BF	0.00%	÷1.063	×1.300	0.00%

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 113).

Result: FIP 0.57 → 1.48, 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
Mat Olsen (OGILVIE)	—	—	4.52	20.7%	9.3%	2.9%	—	4.58	20.8%	11.4%	23	+0.06	—	—	—
C.C. Lee R 2014 · 3.77 FIP	27	SU	3.77	20.5%	8.7%	2.4%	.310	2.80	25.7%	17.6%	96	-0.97	2.59	149	90
Michael Dimock R 2017 · 4.12 FIP	27	SU	4.12	18.9%	7.8%	2.9%	.339	3.37	23.5%	12.8%	29	-0.75	3.08	166	87
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	87
Francisco Del Rosario R 2007 · 3.93 FIP	26	SU	3.93	19.7%	9.4%	2.4%	.356	—	—	—	—	—	3.93	194	86
Fernando Rodriguez Jr. R 2011 · 3.85 FIP	27	SU	3.85	24.7%	10.8%	2.7%	.315	3.90	25.2%	16.5%	70	+0.05	3.34	335	85
Tyler Walker R 2004 · 4.28 FIP	28	SU	4.28	17.5%	8.4%	2.9%	.311	3.77	18.5%	10.4%	101	-0.51	2.38	289	85
Brandon Gomes R 2011 · 3.74 FIP	27	SU	3.74	20.0%	10.0%	1.9%	.284	4.17	22.3%	15.2%	71	+0.43	3.48	190	84
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	84
Hueston Morrill R 2024 · 4.54 FIP	24	SU	4.54	19.8%	8.7%	3.7%	.302	3.24	19.0%	8.2%	54	-1.30	3.09	102	84
Jason Motte R 2009 · 4.62 FIP	27	SU	4.62	22.1%	9.0%	4.1%	.297	2.84	26.9%	21.0%	192	-1.78	2.22	387	84
Francisco Rodriguez R 2010 · 4.33 FIP	27	SU	4.33	17.2%	11.0%	2.4%	.283	5.00	11.9%	3.4%	14	+0.67	3.16	334	84
Santiago Casilla R 2007 · 3.58 FIP	27	SU	3.58	23.7%	7.8%	2.7%	.257	3.60	19.8%	10.7%	154	+0.02	2.76	647	84
Jack Hartman R 2024 · 4.34 FIP	26	SU	4.34	20.9%	8.8%	3.4%	.310	4.29	17.6%	5.6%	46	-0.05	3.46	161	84
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	83
J.J. Putz R 2004 · 4.57 FIP	27	SU	4.57	17.1%	7.3%	3.6%	.283	2.58	28.5%	23.0%	210	-1.99	1.43	563	83
Jose Veras R 2008 · 3.67 FIP	27	SU	3.67	24.9%	9.1%	2.8%	.281	4.10	23.8%	11.7%	169	+0.43	3.37	422	83
Taylor Williams R 2018 · 3.52 FIP	27	SU	3.52	24.2%	8.9%	2.4%	.309	4.35	22.5%	12.7%	108	+0.83	2.51	309	83
Cody Satterwhite R 2015 · 3.71 FIP	28	SU	3.71	20.2%	9.8%	1.9%	.333	4.04	17.7%	10.2%	75	+0.33	3.69	147	83
Ryan Kelly R 2015 · 3.52 FIP	27	SU	3.52	20.3%	7.5%	2.1%	.241	3.21	20.8%	14.2%	43	-0.31	2.49	131	83
Greg Burke R 2009 · 3.93 FIP	26	SU	3.93	16.2%	8.8%	2.0%	.295	—	—	—	—	—	3.61	139	83

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	0.3	26	20.8%	9.4%	1.15	4.53
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*