Ty Madden

P Toledo Mud Hens

Age 27 RHP 6'3" / 215 lbs AAA

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	23	AADET	26	25	118	3.43	3.66	29.7%	10.2%	—	K 24.0% · BB 11.2% · FIP 4.52
2024	24	MIX3 levels	28	23	120	6.47	4.19	26.2%	9.5%	1.7	K 22.7% · BB 8.8% · FIP 5.04
2026	26	MIX2 levels	38	12	98	3.87	4.26	20.6%	10.3%	0.3	K 19.3% · BB 9.6% · FIP 4.39
2027PROJ	27	MLBDET	7	7	44	4.39	4.72	20.3%	9.8%	0.3
2028PROJ85% MLB	28	MLBDET	8	8	46	4.59	4.76	20.3%	9.7%	0.3
2029PROJ88% MLB	29	MLBDET	7	7	40	4.75	4.88	19.9%	9.8%	0.2

Last 3 seasons WAR 2.0 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%61

FB Velo36

Form4.05 ERA (proj 4.39) · K 18.8% (proj 20.3%) · BB 5.0% (proj 9.8%) ▲ last 90d · 20 IP through Oct 27

CompsRicky Castro (age 24) · Clay Condrey (age 27) · Zach Stewart (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10597vR 89

ERA4.39

FIP4.72

K%20.3%

BB%9.8%

K-BB%10.5%

Proj IP54

Value2027 · WAR

Runs saved vs league avg · 54 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3693.5

Whiff%

p4925.1%

p6124.3%

xwOBA vs

p900.263

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)
2022	22	MIX MLE	2 levels	26	26	123	501	133	38	16	100%	4.7	20.8%	8.6%	12.2%	4.5%	3.01	4.90	—
2022	22	MIX RAW	2 levels	26	26	123	501	133	38	16	100%	4.7	26.5%	7.6%	19.0%	3.2%	3.01	3.56	—
2023	23	AA MLE	Erie SeaWolves	26	25	118	492	146	50	16	96%	4.5	24.0%	11.2%	12.9%	3.7%	3.43	4.52	—
2023	23	AA RAW	Erie SeaWolves	26	25	118	492	146	50	16	96%	4.5	29.7%	10.2%	19.5%	3.3%	3.43	3.66	—
2024	24	MIX MLE	3 levels	28	23	120	539	141	51	20	82%	4.3	22.7%	8.8%	14.0%	5.0%	6.47	5.04	+0.5
2024	24	MIX MLE	3 levels	28	23	120	539	141	51	20	82%	4.3	22.7%	8.8%	14.0%	5.0%	6.47	5.04	+0.5
2024	24	MIX RAW	3 levels	28	23	120	539	141	51	20	82%	4.3	26.2%	9.5%	16.7%	3.7%	6.47	4.19	+1.7
2026	26	MIX MLE	2 levels	38	12	98	417	86	43	12	32%	2.6	19.3%	9.6%	9.7%	3.1%	3.87	4.39	+0.2
2026	26	MIX MLE	2 levels	38	12	98	417	86	43	12	32%	2.6	19.3%	9.6%	9.7%	3.1%	3.87	4.39	+0.2
2026	26	MIX RAW	2 levels	38	12	98	417	86	43	12	32%	2.6	20.6%	10.3%	10.3%	2.9%	3.87	4.26	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			26	2	70	290	63	22	7	8%	2.7	21.7%	7.6%	14.1%	2.4%	3.60	3.54	+0.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	DET	7	7	44	186	38	18	6	100%	6.3	20.3%	9.8%	10.5%	3.1%	4.39	4.72	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	DET	9	9	54	228	46	22	7	100%	6.0	20.3%	9.7%	10.6%	3.2%	4.59	4.76	+0.4
2029	29	MLB MLE	DET	8	8	46	192	38	19	6	100%	5.7	19.9%	9.8%	10.1%	3.4%	4.75	4.88	+0.3
2030	30	MLB MLE	DET	6	6	36	152	29	15	5	100%	6.0	19.3%	10.0%	9.3%	3.5%	4.92	5.05	+0.1
2028	28	MLB CTX	DET	8	8	46	194	39	19	6	100%	5.8	20.3%	9.7%	10.6%	3.2%	4.59	4.76	+0.3
2029	29	MLB CTX	DET	7	7	40	169	34	17	6	100%	5.7	19.9%	9.8%	10.1%	3.4%	4.75	4.88	+0.2
2030	30	MLB CTX	DET	5	5	32	135	26	13	5	100%	6.4	19.3%	10.0%	9.3%	3.5%	4.92	5.05	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		46	22	188	788	162	71	24	48%	4.1	20.6%	9.0%	11.6%	3.0%	4.31	4.15	+0.9
/ 200 IP	—	RAW		49	23	200	839	172	76	26	47%	4.1	20.6%	9.0%	11.6%	3.0%	4.31	4.15	+0.9
Career	—	MLE		118	86	458	1949	426	185	81	73%	3.9	21.8%	9.5%	12.3%	4.1%	4.21	4.73	+2.4
/ 200 IP	—	MLE		52	38	200	851	186	81	35	73%	3.9	21.8%	9.5%	12.3%	4.1%	4.21	4.73	+2.3

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.

2026 AAAToledo Mud Hens · 51 IPFIP 4.91 → 5.13 (+0.21)K% 17.5% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.54%	—	×0.860	15.09%
BB% (unintentional) /BF	12.72%	—	×0.900	11.45%
HR / BF /BF	3.07%	÷1.000	×1.100	3.38%

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 100).

Result: FIP 4.91 → 5.13, 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 AAAToledo Mud Hens · 79 IPFIP 4.66 → 5.83 (+1.17)K% 27.6% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.57%	—	×0.860	23.71%
BB% (unintentional) /BF	10.81%	—	×0.900	9.73%
HR / BF /BF	4.59%	÷0.792	×1.100	6.38%

Result: FIP 4.66 → 5.83, 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).

2024 AAErie SeaWolves · 18 IPFIP 1.73 → 2.53 (+0.80)K% 32.4% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.35%	—	×0.810	26.21%
BB% (unintentional) /BF	4.41%	—	×1.100	4.85%
HR / BF /BF	1.47%	÷0.941	×1.200	1.87%

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 88).

Result: FIP 1.73 → 2.53, 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 AAErie SeaWolves · 118 IPFIP 3.67 → 4.52 (+0.85)K% 29.7% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.67%	—	×0.810	24.04%
BB% (unintentional) /BF	10.16%	—	×1.100	11.18%
HR / BF /BF	3.25%	÷1.055	×1.200	3.70%

Result: FIP 3.67 → 4.52, 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+West Michigan Whitecaps · 87 IPFIP 3.57 → 4.89 (+1.32)K% 23.4% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.40%	—	×0.770	18.02%
BB% (unintentional) /BF	7.24%	—	×1.150	8.33%
HR / BF /BF	2.79%	÷0.847	×1.250	4.11%

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 69).

Result: FIP 3.57 → 4.89, 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 · 36 IPFIP 3.58 → 4.92 (+1.35)K% 34.5% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.51%	—	×0.810	27.95%
BB% (unintentional) /BF	8.45%	—	×1.100	9.30%
HR / BF /BF	4.23%	÷0.926	×1.200	5.47%

Result: FIP 3.58 → 4.92, 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
Ty Madden (OGILVIE)	—	—	—	—	—	3.1%	—	4.88	19.9%	10.1%	135	+0.16	—	—	—
Ricky Castro R 2024 · 3.99 FIP	24	SP-	3.99	20.4%	8.6%	2.8%	.287	5.11	19.0%	10.6%	178	+1.12	3.99	241	81
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	78
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	77
Chase Whitley R 2016 · 4.10 FIP	27	SP-	4.10	19.5%	7.0%	3.2%	.217	3.22	18.0%	11.8%	81	-0.88	3.09	235	75
Nick Payero R 2024 · 4.21 FIP	24	SP-	4.21	16.5%	6.3%	3.1%	.285	5.81	16.6%	4.6%	107	+1.60	4.21	178	75
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	75
Shawn Dubin R 2023 · 4.87 FIP	27	SP-	4.87	20.0%	12.9%	3.3%	.292	3.97	21.8%	11.4%	79	-0.90	3.02	341	74
Justin Topa R 2018 · 4.15 FIP	27	SP-	4.15	15.1%	7.9%	2.4%	.374	2.69	19.2%	12.6%	40	-1.46	2.67	284	74
Alejandro Martinez R 2015 · 4.46 FIP	26	SP-	4.46	17.5%	10.9%	2.7%	.393	4.24	9.2%	3.9%	53	-0.22	4.24	166	74
Aaron Northcraft R 2016 · 4.19 FIP	26	SW	4.19	16.1%	8.3%	2.5%	.309	3.32	24.1%	13.4%	34	-0.87	3.32	252	74
Bryce Morrow R 2015 · 4.31 FIP	27	SP-	4.31	12.8%	7.9%	2.4%	.316	5.44	10.1%	-0.2%	50	+1.13	4.31	125	73
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	72
Rorik Maltrud R 2024 · 3.91 FIP	24	SP-	3.91	20.4%	9.6%	2.4%	.300	4.40	18.6%	9.4%	193	+0.49	3.91	298	71
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	71
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	71
Kyle Lloyd R 2018 · 4.23 FIP	27	SP-	4.23	18.2%	9.8%	2.6%	.336	4.75	17.2%	9.3%	110	+0.52	3.50	572	71
Lisalverto Bonilla R 2017 · 4.61 FIP	27	SW	4.61	18.2%	10.5%	3.1%	.304	4.70	15.8%	3.2%	11	+0.09	3.22	242	70
Joaquín Benoit R 2004 · 4.49 FIP	27	SP-	4.49	20.8%	6.8%	4.2%	.302	3.31	23.7%	14.5%	249	-1.18	1.99	1,064	70
Jimmy Endersby R 2024 · 4.54 FIP	26	SP-	4.54	17.3%	8.0%	3.4%	.257	2.86	17.2%	12.8%	36	-1.68	2.86	357	70
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	70

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	1.3	43	20.5%	9.2%	1.18	4.36
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
John Johnstone ('00)	1.4	56	19.4%	9.5%	1.23	4.01
Tyler Walker ('10)	1.5	50	18.9%	8.5%	1.11	4.23
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bill Scherrer ('82-'88, 1 WAR*)	1.6	62	20.7%*	10.2%*	1.19*	4.44*