Kyle Finnegan

P Detroit Tigers

Age 35 RHP 6'2" / 198 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	32	MLBWSH	65	0	64	3.68	4.04	22.1%	7.7%	0.4
2025	33	MIX2 levels	57	1	58	3.43	2.94	24.1%	7.3%	1.1	K 24.0% · BB 7.0% · FIP 2.96
2026	34	MLBDET	63	0	61	4.30	5.37	17.4%	12.6%	-0.6
2027PROJ	35	MLBDET	42	0	44	4.57	4.80	20.9%	10.5%	-0.1
2028PROJ	36	MLBDET	20	0	21	4.93	5.17	19.9%	11.1%	-0.1
2029PROJ	37	MLBDET	9	0	9	5.31	5.57	18.8%	11.7%	-0.1

Last 3 seasons WAR 0.9 · Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo74

K%17

xwOBA vs10

Form8.59 ERA (proj 4.57) · K 14.7% (proj 20.9%) · BB 10.7% (proj 10.5%) ▼▼ last 90d · 15 IP through Oct 27

CompsHirokazu Sawamura (age 34) · Brendan Donnelly (age 35) · Jean Machi (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130121vR 113

ERA4.57

FIP4.80

K%20.9%

BB%10.5%

K-BB%10.4%

Proj IP44

Value2027 · WAR

Runs saved vs league avg · 44 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p7496.2

Whiff%

p5025.2%

p1717.4%

xwOBA vs

p100.362

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)
2015	23	A+ MLE	Stockton Ports	28	24	127	554	96	40	19	86%	4.5	13.3%	8.3%	5.0%	2.5%	5.44	4.40	—
2015	23	A+ RAW	Stockton Ports	28	24	127	554	96	40	19	86%	4.5	17.3%	7.2%	10.1%	3.4%	5.44	4.47	—
2016	24	MIX MLE	2 levels	43	0	64	267	69	30	4	0%	1.5	20.5%	12.6%	7.9%	1.8%	2.54	3.94	—
2016	24	MIX RAW	2 levels	43	0	64	267	69	30	4	0%	1.5	25.8%	11.2%	14.6%	1.5%	2.54	3.16	—
2017	25	MIX MLE	2 levels	46	0	60	261	57	24	8	0%	1.3	18.3%	9.8%	8.5%	4.1%	3.88	5.04	—
2017	25	MIX RAW	2 levels	46	0	60	261	57	24	8	0%	1.3	21.8%	9.2%	12.6%	3.1%	3.88	4.13	—
2018	26	MIX MLE	3 levels	36	2	45	196	48	18	2	6%	1.2	20.3%	9.9%	10.4%	1.2%	4.84	3.30	—
2018	26	MIX RAW	3 levels	36	2	45	196	48	18	2	6%	1.2	24.5%	9.2%	15.3%	1.0%	4.84	2.74	—
2019	27	MIX MLE	2 levels	42	0	51	206	72	18	3	0%	1.2	29.5%	9.3%	20.2%	1.4%	2.31	2.57	—
2019	27	MIX RAW	2 levels	42	0	51	206	72	18	3	0%	1.2	35.0%	8.7%	26.2%	1.5%	2.31	2.09	—
2020	28	MLB MLE	Washington Nationals	25	0	25	107	27	9	2	0%	1.0	25.2%	8.4%	16.8%	1.9%	2.92	3.06	+0.4
2020	28	MLB RAW	Washington Nationals	25	0	25	107	27	9	2	0%	1.0	25.2%	8.4%	16.8%	1.9%	2.92	3.06	+0.4
2021	29	MLB MLE	Washington Nationals	68	0	66	294	68	30	9	0%	1.0	23.1%	10.2%	12.9%	3.1%	3.55	4.12	+0.3
2021	29	MLB RAW	Washington Nationals	68	0	66	294	68	30	9	0%	1.0	23.1%	10.2%	12.9%	3.1%	3.55	4.18	+0.3
2022	30	MLB MLE	Washington Nationals	66	0	67	268	70	20	9	0%	1.0	26.1%	7.5%	18.7%	3.4%	3.51	3.68	+0.7
2022	30	MLB RAW	Washington Nationals	66	0	67	268	70	20	9	0%	1.0	26.1%	7.5%	18.7%	3.4%	3.51	3.66	+0.7
2023	31	MLB MLE	Washington Nationals	67	0	69	288	63	23	11	0%	1.0	21.9%	8.0%	13.9%	3.8%	3.76	4.36	+0.2
2023	31	MLB RAW	Washington Nationals	67	0	69	288	63	23	11	0%	1.0	21.9%	8.0%	13.9%	3.8%	3.76	4.34	+0.2
2024	32	MLB MLE	Washington Nationals	65	0	64	271	60	21	9	0%	1.0	22.1%	7.7%	14.4%	3.3%	3.68	4.03	+0.4
2024	32	MLB MLE	Washington Nationals	65	0	64	271	60	21	9	0%	1.0	22.1%	7.7%	14.4%	3.3%	3.68	4.03	+0.4
2024	32	MLB RAW	Washington Nationals	65	0	64	271	60	21	9	0%	1.0	22.1%	7.7%	14.4%	3.3%	3.68	4.04	+0.4
2025	33	MIX MLE	2 levels	57	1	58	232	56	17	4	2%	1.0	24.0%	7.0%	17.0%	1.8%	3.43	2.96	+1.1
2025	33	MIX MLE	2 levels	57	1	58	232	56	17	4	2%	1.0	24.0%	7.0%	17.0%	1.8%	3.43	2.96	+1.1
2025	33	MIX RAW	2 levels	57	1	58	232	56	17	4	2%	1.0	24.1%	7.3%	16.8%	1.7%	3.43	2.94	+1.1
2026	34	MLB MLE	Detroit Tigers	63	0	61	270	47	34	10	0%	1.0	17.4%	12.6%	4.8%	3.9%	4.30	5.35	-0.6
2026	34	MLB MLE	Detroit Tigers	63	0	61	270	47	34	10	0%	1.0	17.4%	12.6%	4.8%	3.9%	4.30	5.35	-0.6
2026	34	MLB RAW	Detroit Tigers	63	0	61	270	47	34	10	0%	1.0	17.4%	12.6%	4.8%	3.7%	4.30	5.37	-0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			410	0	408	1727	390	153	54	0%	1.0	22.6%	8.9%	13.7%	3.1%	3.66	4.03	+2.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	DET	42	0	44	186	39	19	6	0%	1.0	20.9%	10.5%	10.4%	3.2%	4.57	4.80	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	DET	20	0	21	90	18	10	3	0%	1.1	19.9%	11.1%	8.8%	3.6%	4.93	5.17	-0.1
2029	37	MLB MLE	DET	9	0	9	40	7	5	2	0%	1.0	18.8%	11.7%	7.0%	4.0%	5.31	5.57	-0.1
2028	36	MLB CTX	DET	20	0	21	89	18	10	3	0%	1.1	19.9%	11.1%	8.8%	3.6%	4.93	5.17	-0.1
2029	37	MLB CTX	DET	9	0	9	38	7	4	2	0%	1.0	18.8%	11.7%	7.0%	4.0%	5.31	5.57	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		439	0	439	1856	415	168	59	0%	1.0	22.4%	9.0%	13.3%	3.2%	3.76	4.09	+2.4
/ 200 IP	—	RAW		200	0	200	846	189	77	27	0%	1.0	22.4%	9.0%	13.3%	3.2%	3.76	4.09	+1.1
Career	—	MLE		606	27	755	3214	668	297	89	4%	1.2	20.8%	9.2%	11.5%	2.8%	3.86	4.04	+2.2
/ 200 IP	—	MLE		160	7	200	851	177	79	24	4%	1.2	20.8%	9.2%	11.5%	2.8%	3.86	4.04	+1.0

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.

2019 AAALas Vegas Aviators · 28 IPFIP 3.21 → 3.57 (+0.36)K% 31.6% → 27.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.58%	—	×0.880	27.79%
BB% (unintentional) /BF	10.53%	—	×1.050	11.05%
HR / BF /BF	2.63%	÷1.119	×1.100	2.59%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 124).

Result: FIP 3.21 → 3.57, 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 AAMidland RockHounds · 23 IPFIP 0.62 → 1.33 (+0.71)K% 39.1% → 31.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.13%	—	×0.810	31.70%
BB% (unintentional) /BF	6.52%	—	×1.100	7.17%
HR / BF /BF	0.00%	÷0.954	×1.200	0.00%

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 91).

Result: FIP 0.62 → 1.33, 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 AAMidland RockHounds · 25 IPFIP 2.03 → 2.59 (+0.56)K% 27.2% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.18%	—	×0.810	22.02%
BB% (unintentional) /BF	9.71%	—	×1.100	10.68%
HR / BF /BF	0.00%	÷0.922	×1.200	0.00%

Result: FIP 2.03 → 2.59, 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 AAANashville Sounds · 18 IPFIP 3.77 → 4.19 (+0.42)K% 20.7% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.73%	—	×0.880	18.24%
BB% (unintentional) /BF	8.54%	—	×1.050	8.96%
HR / BF /BF	2.44%	÷0.988	×1.100	2.72%

Result: FIP 3.77 → 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).

2017 AAMidland RockHounds · 37 IPFIP 3.13 → 4.14 (+1.01)K% 23.8% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.84%	—	×0.810	19.31%
BB% (unintentional) /BF	4.64%	—	×1.100	5.10%
HR / BF /BF	2.65%	÷0.862	×1.200	3.69%

Result: FIP 3.13 → 4.14, 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).

2017 AAANashville Sounds · 24 IPFIP 5.44 → 6.27 (+0.83)K% 19.1% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.09%	—	×0.880	16.80%
BB% (unintentional) /BF	15.45%	—	×1.050	16.23%
HR / BF /BF	3.64%	÷0.868	×1.100	4.61%

Result: FIP 5.44 → 6.27, 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).

2016 AAMidland RockHounds · 42 IPFIP 3.44 → 4.15 (+0.71)K% 23.6% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.56%	—	×0.810	19.09%
BB% (unintentional) /BF	10.92%	—	×1.100	12.01%
HR / BF /BF	1.72%	÷0.999	×1.200	2.07%

Result: FIP 3.44 → 4.15, 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).

2016 A+Stockton Ports · 22 IPFIP 2.65 → 3.56 (+0.91)K% 30.1% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.11%	—	×0.770	23.18%
BB% (unintentional) /BF	11.83%	—	×1.150	13.60%
HR / BF /BF	1.08%	÷1.066	×1.250	1.26%

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 113).

Result: FIP 2.65 → 3.56, 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
Kyle Finnegan (OGILVIE)	—	—	—	—	—	3.2%	—	5.17	19.9%	8.8%	21	+0.37	—	—	—
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	79
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	78
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	72
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	69
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	68
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	66
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	65
Brian Schlitter R 2021 · 4.70 FIP	35	SU	4.70	14.9%	9.1%	3.1%	.318	—	—	—	—	—	3.27	300	65
Yoshihisa Hirano R 2019 · 3.72 FIP	35	SU	3.72	26.2%	8.6%	3.2%	.303	5.02	17.5%	4.8%	12	+1.30	3.45	132	64
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	63
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	63
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	63
Toby Borland R 2004 · 4.28 FIP	35	SU	4.28	20.9%	8.1%	3.5%	.259	—	—	—	—	—	2.92	248	62
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	60
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	58
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	58
Fernando Rodriguez Jr. R 2019 · 5.11 FIP	35	SW	5.11	25.0%	11.2%	4.9%	.312	—	—	—	—	—	3.34	335	58
Spencer Patton R 2023 · 4.33 FIP	35	SU	4.33	18.9%	9.7%	2.9%	.295	—	—	—	—	—	2.79	239	57
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	56
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	56

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	2.4	48	22.2%	9.9%	1.23	3.83
David Riske ('10)	2.5	55	20.8%	10.0%	1.19	3.67
Dominic Leone ('24)	2.1	54	23.9%	10.4%	1.26	3.94
Al Reyes ('08)	2.1	54	23.2%	10.7%	1.11	3.84
Tony Fossas ('88-'99, 2 WAR*)	2.1	42	21.9%*	9.3%*	0.99*	3.88*
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Bobby Thigpen ('86-'94, 7 WAR*)	2.8	71	20.5%*	9.4%*	1.09*	3.60*