Tyler Duffey

P Omaha Storm Chasers

Age 36 RHP 6'3" / 220 lbs AAA peak 0.1 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	31	MIX2 levels	51	0	55	5.07	4.37	21.6%	7.9%	0.1	K 20.9% · BB 8.0% · FIP 4.41
2023	32	MIX3 levels	40	2	51	3.51	4.15	29.9%	11.8%	0.2	K 25.0% · BB 11.4% · FIP 4.83
2024	33	MIX2 levels	32	0	40	2.95	2.97	26.0%	11.2%	0.7	K 23.0% · BB 7.8% · FIP 3.00
2025	34	No MLB games played
2026	35	No MLB games played
2027PROJ	36	MLBKC	22	0	23	4.31	4.33	22.7%	9.1%	0.1
2028PROJ	37	MLBKC	107	0	112	4.56	4.73	21.6%	9.7%	-0.2
2029PROJ	38	MLBKC	76	0	80	4.92	5.16	20.4%	10.4%	-0.5

Last 3 seasons WAR 1.1 · Next 3 projected WAR -0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsKeiichi Yabu (age 36) · Juan Sandoval (age 36) · Francisco Del Rosario (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.31

FIP4.33

K%22.7%

BB%9.1%

K-BB%13.6%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

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	24	MIX MLE	3 levels	32	32	196	801	175	50	5	100%	6.1	19.5%	6.5%	13.0%	0.6%	2.71	2.62	+7.0
2015	24	MIX RAW	3 levels	32	32	196	801	175	50	5	100%	6.1	21.8%	6.2%	15.6%	0.6%	2.71	2.41	+7.7
2016	25	MIX MLE	2 levels	31	31	164	721	139	41	29	100%	5.3	18.9%	5.8%	13.1%	4.1%	5.77	4.48	+1.7
2016	25	MIX RAW	2 levels	31	31	164	721	139	41	29	100%	5.3	19.3%	5.7%	13.6%	4.0%	5.77	4.46	+1.8
2017	26	MLB MLE	Minnesota Twins	56	0	71	310	67	13	9	0%	1.3	21.6%	4.2%	17.4%	2.9%	4.94	3.39	+1.0
2017	26	MLB RAW	Minnesota Twins	56	0	71	310	67	13	9	0%	1.3	21.6%	4.2%	17.4%	2.9%	4.94	3.41	+1.0
2018	27	MIX MLE	2 levels	50	1	84	353	82	22	11	2%	1.7	21.1%	6.5%	14.6%	3.5%	4.18	4.04	+0.5
2018	27	MIX RAW	2 levels	50	1	84	353	82	22	11	2%	1.7	23.2%	6.2%	17.0%	3.1%	4.18	3.64	+0.9
2019	28	MIX MLE	2 levels	65	0	71	291	104	18	8	0%	1.1	34.8%	6.3%	28.6%	2.7%	2.27	2.45	+1.8
2019	28	MIX RAW	2 levels	65	0	71	291	104	18	8	0%	1.1	35.7%	6.2%	29.6%	2.7%	2.27	2.40	+1.8
2020	29	MLB MLE	Minnesota Twins	22	0	24	92	31	6	2	0%	1.1	33.7%	6.5%	27.2%	2.2%	1.88	2.27	+0.7
2020	29	MLB RAW	Minnesota Twins	22	0	24	92	31	6	2	0%	1.1	33.7%	6.5%	27.2%	2.2%	1.88	2.35	+0.6
2021	30	MLB MLE	Minnesota Twins	64	0	62	254	61	27	4	0%	1.0	24.0%	10.6%	13.4%	1.6%	3.18	3.28	+0.9
2021	30	MLB RAW	Minnesota Twins	64	0	62	254	61	27	4	0%	1.0	24.0%	10.6%	13.4%	1.6%	3.18	3.28	+0.9
2022	31	MIX MLE	2 levels	51	0	55	241	52	19	9	0%	1.1	20.9%	8.0%	12.9%	3.8%	5.07	4.41	+0.1
2022	31	MIX RAW	2 levels	51	0	55	241	52	19	9	0%	1.1	21.6%	7.9%	13.7%	3.7%	5.07	4.37	+0.1
2023	32	MIX MLE	3 levels	40	2	51	204	61	24	8	5%	1.3	25.0%	11.4%	13.7%	4.4%	3.51	4.83	-0.2
2023	32	MIX RAW	3 levels	40	2	51	204	61	24	8	5%	1.3	29.9%	11.8%	18.1%	3.9%	3.51	4.15	+0.2
2024	33	MIX MLE	2 levels	32	0	40	169	44	19	2	0%	1.2	23.0%	7.8%	15.2%	1.6%	2.95	3.00	+0.7
2024	33	MIX MLE	2 levels	32	0	40	169	44	19	2	0%	1.2	23.0%	7.8%	15.2%	1.6%	2.95	3.00	+0.7
2024	33	MIX RAW	2 levels	32	0	40	169	44	19	2	0%	1.2	26.0%	11.2%	14.8%	1.2%	2.95	2.97	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			305	37	486	2073	479	134	67	12%	1.6	23.1%	6.5%	16.6%	3.2%	4.57	3.75	+4.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	KC	22	0	23	97	22	9	3	0%	1.0	22.7%	9.1%	13.6%	2.9%	4.31	4.33	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	KC	107	0	112	472	102	46	16	0%	1.0	21.6%	9.7%	11.9%	3.4%	4.56	4.73	-0.2
2029	38	MLB MLE	KC	76	0	80	338	69	35	13	0%	1.1	20.4%	10.4%	10.0%	3.8%	4.92	5.16	-0.5
2028	37	MLB CTX	KC	107	0	112	473	102	46	16	0%	1.0	21.6%	9.7%	11.9%	3.4%	4.56	4.73	-0.2
2029	38	MLB CTX	KC	76	0	80	338	69	35	13	0%	1.1	20.4%	10.4%	10.0%	3.8%	4.92	5.16	-0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		488	37	678	2884	650	215	96	8%	1.4	22.5%	7.5%	15.1%	3.3%	4.61	3.96	+4.7
/ 200 IP	—	RAW		144	11	200	851	192	63	28	8%	1.4	22.5%	7.5%	15.1%	3.3%	4.61	3.96	+1.4
Career	—	MLE		443	66	818	3436	768	236	90	15%	1.8	22.3%	6.9%	15.5%	2.6%	3.86	3.53	+3.8
/ 200 IP	—	MLE		108	16	200	840	188	58	22	15%	1.8	22.3%	6.9%	15.5%	2.6%	3.86	3.53	+1.1

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.

2024 AAAOmaha Storm Chasers · 31 IPFIP 2.80 → 3.00 (+0.20)K% 26.8% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.77%	—	×0.860	23.02%
BB% (unintentional) /BF	8.66%	—	×0.900	7.80%
HR / BF /BF	1.57%	÷1.111	×1.100	1.56%

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 122).

Result: FIP 2.80 → 3.00, 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 AAAIowa Cubs · 45 IPFIP 4.35 → 4.83 (+0.48)K% 29.1% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.12%	—	×0.860	25.04%
BB% (unintentional) /BF	12.64%	—	×0.900	11.37%
HR / BF /BF	3.85%	÷0.965	×1.100	4.38%

Result: FIP 4.35 → 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).

2022 AAAScranton/Wilkes-Barre RailRiders · 11 IPFIP 3.25 → 3.63 (+0.38)K% 23.2% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.21%	—	×0.880	20.43%
BB% (unintentional) /BF	8.93%	—	×1.050	9.38%
HR / BF /BF	1.79%	÷1.006	×1.100	1.95%

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 101).

Result: FIP 3.25 → 3.63, 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 AAARochester Red Wings · 14 IPFIP 0.79 → 1.27 (+0.48)K% 41.5% → 36.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.51%	—	×0.880	36.53%
BB% (unintentional) /BF	9.43%	—	×1.050	9.91%
HR / BF /BF	0.00%	÷0.958	×1.100	0.00%

Result: FIP 0.79 → 1.27, 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).

2018 AAARochester Red Wings · 59 IPFIP 2.98 → 3.57 (+0.59)K% 25.6% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.61%	—	×0.880	22.54%
BB% (unintentional) /BF	7.32%	—	×1.050	7.68%
HR / BF /BF	2.03%	÷0.879	×1.100	2.54%

Result: FIP 2.98 → 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).

2016 AAARochester Red Wings · 31 IPFIP 4.38 → 4.92 (+0.54)K% 20.0% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.880	17.60%
BB% (unintentional) /BF	9.60%	—	×1.050	10.08%
HR / BF /BF	3.20%	÷0.951	×1.100	3.70%

Result: FIP 4.38 → 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).

2015 AAARochester Red Wings · 85 IPFIP 2.27 → 2.52 (+0.25)K% 19.5% → 17.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.48%	—	×0.880	17.15%
BB% (unintentional) /BF	5.16%	—	×1.050	5.42%
HR / BF /BF	0.29%	÷0.956	×1.100	0.33%

Result: FIP 2.27 → 2.52, 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).

2015 AAChattanooga Lookouts · 53 IPFIP 1.65 → 2.14 (+0.48)K% 25.7% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.71%	—	×0.810	20.83%
BB% (unintentional) /BF	5.71%	—	×1.100	6.29%
HR / BF /BF	0.00%	÷1.232	×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 146).

Result: FIP 1.65 → 2.14, 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).

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
Tyler Duffey (OGILVIE)	—	—	—	—	—	2.9%	—	4.91	21.1%	11.1%	192	+0.58	—	—	—
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	56
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	54
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	49
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	49
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	48
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	48
Pete Walker R 2005 · 4.79 FIP	36	SU	4.79	12.0%	9.2%	2.8%	.261	4.45	19.6%	11.6%	30	-0.34	4.45	327	44
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	44
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	44
Daniel Bard R 2021 · 3.62 FIP	36	SU	3.62	26.3%	11.5%	2.3%	.337	3.64	24.6%	10.3%	110	+0.02	2.56	456	43
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	43
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	41
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	41
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	41
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	40
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	40
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	35
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	35
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	34
Jay Jackson R 2024 · 5.31 FIP	36	SU	5.31	25.4%	7.9%	6.1%	.304	—	—	—	—	—	2.36	261	34

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	4.2	77	22.6%	8.1%	1.26	4.55
Brett Cecil ('18)	3.8	76	20.7%	8.3%	1.14	4.29
Carlos Villanueva ('16)	5.0	91	20.4%	7.6%	1.25	4.31
Odell Jones ('75-'88, 2 WAR*)	2.7	78	20.8%*	8.8%*	1.18*	4.62*
Juan Nicasio ('20)	3.6	80	21.3%	8.3%	1.04	4.71
Tom Walker ('72-'77, 1 WAR*)	2.1	83	20.9%*	7.5%*	1.28*	4.32*
Rich Bordi ('80-'88, 1 WAR*)	1.9	74	20.8%*	7.3%*	1.22*	4.55*