Anthony Gose

PosP

B/TL/L

Born1990-08-10

Age (2027)36

No MLB projection yet. Career stats below are historical.

Overview

AARP40-MAN

Pitching

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	33	MIX2 levels	44	49	3.86	3.92	29.4%	11.7%	0.4	K 26.4% · BB 11.2% · FIP 3.78
2025	34	AAAARI	35	37	4.62	5.21	24.3%	13.6%	—	K 20.9% · BB 12.2% · FIP 5.66
2026	35	MIX2 levels	53	60	3.92	4.44	24.9%	11.9%	0.1	K 21.8% · BB 10.8% · FIP 4.70
2027PROJ	36	MLBKC	23	24	4.64	5.04	22.6%	10.6%	-0.1
2028PROJ67% MLB	37	MLBKC	13	14	4.88	5.20	21.6%	11.1%	-0.1

Last 3 seasons WAR 0.4 · Next 2 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Hitting

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR	MLE AVG/OBP/SLG
2015	24	MLBDET	535	.254/.321/.367	5	23	99	0.7
2016	25	AAA/AADET	379	.203/.277/.312	7	17	30	—	.171/.227/.251
2016	25	MLBDET	101	.209/.287/.341	2	0	82	-0.0
2018	27	AA/A+2 orgs	47	.238/.289/.286	0	2	17	—	.191/.244/.239
2019	28	No MLB games played
2020	29	No MLB games played
2021	30	No MLB games played
2022	31	No MLB games played
2023	32	No MLB games played
2024	33	No MLB games played
2025	34	No MLB games played
2026	35	No MLB games played

Last 3 seasons WAR 0.7

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsBrian Shouse (age 36) · Raul Valdes (age 35) · Tim Byrdak (age 36)

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)
2017	26	A+ MLE	Lakeland Flying Tigers	11	0	11	45	14	6	0	0%	1.0	31.1%	13.3%	17.8%	0.0%	7.59	2.16	—
2017	26	A+ RAW	Lakeland Flying Tigers	11	0	11	45	14	6	0	0%	1.0	31.1%	13.3%	17.8%	0.0%	7.59	2.16	—
2018	27	MIX MLE	2 levels	28	0	26	121	24	25	5	0%	0.9	15.3%	26.6%	-11.3%	5.8%	5.19	8.36	—
2018	27	MIX RAW	2 levels	28	0	26	121	24	25	5	0%	0.9	19.8%	20.7%	-0.8%	4.1%	5.19	6.64	—
2019	28	MIX MLE	2 levels	32	0	29	135	35	27	0	0%	0.9	19.2%	22.5%	-3.3%	0.0%	2.48	4.33	—
2019	28	MIX RAW	2 levels	32	0	29	135	35	27	0	0%	0.9	25.9%	20.0%	5.9%	0.0%	2.48	3.48	—
2021	30	MIX MLE	2 levels	34	1	40	168	58	29	4	3%	1.2	29.9%	19.7%	10.3%	3.0%	3.18	4.69	-0.1
2021	30	MIX RAW	2 levels	34	1	40	168	58	29	4	3%	1.2	34.5%	17.3%	17.3%	2.4%	3.18	3.68	+0.4
2022	31	MLB MLE	Cleveland Guardians	22	0	21	92	28	13	4	0%	1.0	30.4%	14.1%	16.3%	4.4%	4.71	4.71	-0.0
2022	31	MLB RAW	Cleveland Guardians	22	0	21	92	28	13	4	0%	1.0	30.4%	14.1%	16.3%	4.3%	4.71	4.77	-0.1
2024	33	MIX MLE	2 levels	44	0	49	214	63	25	7	0%	1.1	26.4%	11.2%	15.2%	2.7%	3.86	3.78	+0.4
2024	33	MIX MLE	2 levels	44	0	49	214	63	25	7	0%	1.1	26.4%	11.2%	15.2%	2.7%	3.86	3.78	+0.4
2024	33	MIX RAW	2 levels	44	0	49	214	63	25	7	0%	1.1	29.4%	11.7%	17.8%	3.3%	3.86	3.92	+0.4
2025	34	AAA MLE	Reno Aces	35	0	37	169	41	23	7	0%	1.1	20.9%	12.2%	8.6%	5.0%	4.62	5.66	—
2025	34	AAA MLE	Reno Aces	35	0	37	169	41	23	7	0%	1.1	20.9%	12.2%	8.6%	5.0%	4.62	5.66	—
2025	34	AAA RAW	Reno Aces	35	0	37	169	41	23	7	0%	1.1	24.3%	13.6%	10.7%	4.1%	4.62	5.21	—
2026	35	MIX MLE	2 levels	53	0	60	261	65	31	9	0%	1.1	21.8%	10.8%	11.0%	3.8%	3.92	4.70	-0.1
2026	35	MIX MLE	2 levels	53	0	60	261	65	31	9	0%	1.1	21.8%	10.8%	11.0%	3.8%	3.92	4.70	-0.1
2026	35	MIX RAW	2 levels	53	0	60	261	65	31	9	0%	1.1	24.9%	11.9%	13.0%	3.4%	3.92	4.44	+0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			45	0	46	189	48	18	7	0%	1.0	25.4%	9.5%	15.9%	3.7%	3.55	4.17	+0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	KC	23	0	24	101	23	11	4	0%	1.0	22.6%	10.6%	12.0%	3.9%	4.64	5.04	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	KC	20	0	21	88	19	10	4	0%	1.0	21.6%	11.1%	10.5%	4.2%	5.05	5.37	-0.2
2028	37	MLB CTX	KC	13	0	14	59	13	7	2	0%	1.1	21.6%	11.1%	10.5%	3.9%	4.88	5.20	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		58	0	60	248	61	25	9	0%	1.0	24.5%	9.9%	14.6%	3.7%	3.86	4.34	+0.1
/ 200 IP	—	RAW		196	0	200	832	204	84	30	0%	1.0	24.5%	9.9%	14.6%	3.7%	3.86	4.34	+0.5
Career	—	MLE		259	1	272	1205	285	188	40	0%	1.1	23.7%	15.6%	8.1%	3.3%	4.07	4.90	+0.0
/ 200 IP	—	MLE		190	1	200	886	210	138	30	0%	1.1	23.7%	15.6%	8.1%	3.3%	4.07	4.90	+0.0

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.

2026 AAAOmaha Storm Chasers · 46 IPFIP 4.61 → 4.97 (+0.36)K% 27.6% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.62%	—	×0.860	23.75%
BB% (unintentional) /BF	13.81%	—	×0.900	12.43%
HR / BF /BF	3.81%	÷1.000	×1.100	4.19%

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 4.61 → 4.97, 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).

2025 AAAReno Aces · 37 IPFIP 5.05 → 5.66 (+0.61)K% 24.3% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.26%	—	×0.860	20.86%
BB% (unintentional) /BF	13.61%	—	×0.900	12.25%
HR / BF /BF	4.14%	÷0.904	×1.100	5.04%

Result: FIP 5.05 → 5.66, 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 AAAColumbus Clippers · 45 IPFIP 3.52 → 3.78 (+0.26)K% 30.7% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.73%	—	×0.860	26.43%
BB% (unintentional) /BF	12.50%	—	×0.900	11.25%
HR / BF /BF	2.60%	÷1.060	×1.100	2.70%

Result: FIP 3.52 → 3.78, 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 AAAColumbus Clippers · 33 IPFIP 4.13 → 4.69 (+0.56)K% 34.0% → 29.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.03%	—	×0.880	29.94%
BB% (unintentional) /BF	18.75%	—	×1.050	19.69%
HR / BF /BF	2.78%	÷1.034	×1.100	2.95%

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 107).

Result: FIP 4.13 → 4.69, 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 AAAkron RubberDucks · 18 IPFIP 3.69 → 4.33 (+0.64)K% 23.7% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.66%	—	×0.810	19.16%
BB% (unintentional) /BF	20.43%	—	×1.100	22.47%
HR / BF /BF	0.00%	÷0.863	×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 73).

Result: FIP 3.69 → 4.33, 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).

2019 A+Lynchburg Hillcats · 11 IPFIP 2.90 → 3.86 (+0.96)K% 31.0% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.95%	—	×0.770	23.83%
BB% (unintentional) /BF	19.05%	—	×1.150	21.90%
HR / BF /BF	0.00%	÷0.850	×1.250	0.00%

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 70).

Result: FIP 2.90 → 3.86, 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 AAFrisco RoughRiders · 19 IPFIP 7.46 → 8.36 (+0.91)K% 18.9% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.95%	—	×0.810	15.35%
BB% (unintentional) /BF	24.21%	—	×1.100	26.63%
HR / BF /BF	5.26%	÷1.088	×1.200	5.81%

Result: FIP 7.46 → 8.36, 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 A+Down East Wood Ducks · 7 IPFIP 2.13 → 2.72 (+0.59)K% 23.1% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.770	17.77%
BB% (unintentional) /BF	7.69%	—	×1.150	8.85%
HR / BF /BF	0.00%	÷1.393	×1.250	0.00%

Result: FIP 2.13 → 2.72, 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
Anthony Gose (OGILVIE)	—	—	—	—	—	3.9%	—	5.37	21.6%	10.5%	21	+0.33	—	—	—
Brian Shouse L 2005 · 4.24 FIP	36	SU	4.24	15.0%	6.0%	3.0%	.271	3.35	15.0%	9.6%	137	-0.89	2.32	339	66
Raul Valdes L 2013 · 4.07 FIP	35	SU	4.07	24.3%	5.3%	4.3%	.350	—	—	—	—	—	2.29	160	64
Tim Byrdak L 2010 · 4.48 FIP	36	SU	4.48	17.1%	11.8%	2.4%	.308	2.92	27.6%	18.1%	68	-1.56	2.85	320	60
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	37
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	37
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	37
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	37
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	36
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	35
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	34
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	32
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	32
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	31
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	31
Jay Jackson R 2024 · 5.31 FIP	36	SU	5.31	25.4%	7.9%	6.1%	.304	—	—	—	—	—	2.36	261	30
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	29
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	29
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	27
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	25
Leo Rosales R 2017 · 4.24 FIP	36	SU	4.24	7.8%	8.2%	1.4%	.203	—	—	—	—	—	3.85	130	24

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	0.5	32	23.7%	10.4%	1.50	4.21
J.J. Hoover ('18)	1.4	57	23.8%	11.4%	1.42	4.17
José Ruiz ('25)	1.4	57	22.3%	10.4%	1.44	4.62
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Jeff Jones ('80-'84, -2 WAR*)	1.0	41	22.0%*	12.4%*	1.48*	4.53*
Bill Scherrer ('82-'88, 1 WAR*)	1.6	62	20.7%*	10.2%*	1.19*	4.44*

Anthony Gose

Career Stats + Projections

How the minor-league lines were translated

Career Path Comps

Career Comps