Anthony Bender

P Miami Marlins

Age 32 RHP 6'4" / 205 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	62	1	56	4.02	2.78	25.9%	7.5%	1.2	K 25.9% · BB 7.5% · FIP 2.62
2025	30	MLBMIA	51	0	50	2.16	3.34	20.6%	9.3%	0.7
2026	31	MIX2 levels	36	0	35	3.06	2.00	29.9%	8.2%	1.1	K 29.3% · BB 7.9% · FIP 2.03
2027PROJ	32	MLBMIA	35	0	37	3.56	3.66	24.7%	8.5%	0.4
2028PROJ95% MLB	33	MLBMIA	30	0	31	3.79	3.94	23.8%	9.0%	0.2
2029PROJ90% MLB	34	MLBMIA	20	0	21	4.06	4.25	22.9%	9.5%	0.1

Last 3 seasons WAR 3.0 · Next 3 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

K%88

FB Velo82

CompsJumbo Diaz (age 32) · Jose Veras (age 32) · Joe Nelson (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10395vR 87

ERA3.56

FIP3.66

K%24.7%

BB%8.5%

K-BB%16.2%

Proj IP37

Value2027 · WAR

Runs saved vs league avg · 37 IP

Grades · Statcast · Contract

Scouting Grades

STUF4040

CTRL4545

CMD5050

K†6060

Statcast Percentiles

FB Velo

p8296.8

Whiff%

p4124.0%

p8829.3%

xwOBA vs

p900.253

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)
2016	21	ROK MLE	AZL Royals	9	5	33	141	32	4	0	56%	3.6	15.4%	3.5%	11.9%	0.0%	3.03	2.25	—
2016	21	ROK RAW	AZL Royals	9	5	33	141	32	4	0	56%	3.6	22.7%	2.8%	19.9%	0.0%	3.03	1.51	—
2017	22	MIX MLE	2 levels	24	9	77	326	77	19	9	38%	3.2	17.8%	6.5%	11.3%	3.6%	3.96	4.39	—
2017	22	MIX RAW	2 levels	24	9	77	326	77	19	9	38%	3.2	23.6%	5.8%	17.8%	2.8%	3.96	3.36	—
2018	23	A+ MLE	Wilmington Blue Rocks	30	9	93	397	54	37	7	30%	3.1	10.5%	10.7%	-0.2%	2.9%	3.57	5.14	—
2018	23	A+ RAW	Wilmington Blue Rocks	30	9	93	397	54	37	7	30%	3.1	13.6%	9.3%	4.3%	1.8%	3.57	4.11	—
2019	24	MIX MLE	3 levels	29	0	36	146	35	7	3	0%	1.3	16.4%	7.7%	8.8%	1.5%	1.49	3.53	—
2019	24	MIX RAW	3 levels	29	0	36	146	35	7	3	0%	1.3	24.0%	4.8%	19.2%	2.1%	1.49	2.82	—
2021	26	MLB MLE	Miami Marlins	60	1	61	247	71	17	5	2%	1.0	28.7%	6.9%	21.9%	2.1%	2.79	2.71	+1.3
2021	26	MLB RAW	Miami Marlins	60	1	61	247	71	17	5	2%	1.0	28.7%	6.9%	21.9%	2.0%	2.79	2.68	+1.4
2022	27	MIX MLE	4 levels	28	3	25	98	26	10	3	11%	0.9	21.8%	10.3%	11.5%	4.0%	2.92	4.78	-0.1
2022	27	MIX RAW	4 levels	28	3	25	98	26	10	3	11%	0.9	26.5%	10.2%	16.3%	3.1%	2.92	3.79	+0.2
2024	29	MIX MLE	2 levels	62	1	56	239	62	18	4	2%	0.9	25.9%	7.5%	18.4%	1.4%	4.02	2.62	+1.3
2024	29	MIX MLE	2 levels	62	1	56	239	62	18	4	2%	0.9	25.9%	7.5%	18.4%	1.4%	4.02	2.62	+1.3
2024	29	MIX RAW	2 levels	62	1	56	239	62	18	4	2%	0.9	25.9%	7.5%	18.4%	1.7%	4.02	2.78	+1.2
2025	30	MLB MLE	Miami Marlins	51	0	50	204	42	19	3	0%	1.0	20.6%	9.3%	11.3%	1.5%	2.16	3.39	+0.7
2025	30	MLB MLE	Miami Marlins	51	0	50	204	42	19	3	0%	1.0	20.6%	9.3%	11.3%	1.5%	2.16	3.39	+0.7
2025	30	MLB RAW	Miami Marlins	51	0	50	204	42	19	3	0%	1.0	20.6%	9.3%	11.3%	1.5%	2.16	3.34	+0.7
2026	31	MIX MLE	2 levels	36	0	35	147	44	12	1	0%	1.0	29.3%	7.9%	21.4%	0.8%	3.06	2.03	+1.1
2026	31	MIX MLE	2 levels	36	0	35	147	44	12	1	0%	1.0	29.3%	7.9%	21.4%	0.8%	3.06	2.03	+1.1
2026	31	MIX RAW	2 levels	36	0	35	147	44	12	1	0%	1.0	29.9%	8.2%	21.8%	0.7%	3.06	2.00	+1.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			227	1	218	897	230	72	15	0%	1.0	25.6%	8.0%	17.6%	1.7%	2.97	2.88	+4.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	MIA	35	0	37	156	39	13	3	0%	1.1	24.7%	8.5%	16.2%	2.2%	3.56	3.66	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	MIA	31	0	32	136	32	12	3	0%	1.0	23.8%	9.0%	14.9%	2.4%	3.79	3.94	+0.2
2029	34	MLB MLE	MIA	22	0	24	99	23	9	3	0%	1.1	22.9%	9.5%	13.5%	2.7%	4.06	4.25	+0.1
2028	33	MLB CTX	MIA	30	0	31	131	31	12	3	0%	1.0	23.8%	9.0%	14.9%	2.4%	3.79	3.94	+0.2
2029	34	MLB CTX	MIA	20	0	21	89	20	8	2	0%	1.1	22.9%	9.5%	13.5%	2.7%	4.06	4.25	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		276	1	270	1116	281	92	21	0%	1.0	25.2%	8.3%	17.0%	1.8%	3.15	3.03	+4.9
/ 200 IP	—	RAW		205	1	200	827	208	68	16	0%	1.0	25.2%	8.3%	17.0%	1.8%	3.15	3.03	+3.6
Career	—	MLE		329	28	467	1945	385	155	42	9%	1.4	19.8%	8.0%	11.8%	2.2%	3.16	3.63	+4.7
/ 200 IP	—	MLE		141	12	200	833	165	67	18	9%	1.4	19.8%	8.0%	11.8%	2.2%	3.16	3.63	+3.4

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 A+Carolina Mudcats · 17 IPFIP 2.87 → 3.53 (+0.65)K% 21.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.33%	—	×0.770	16.43%
BB% (unintentional) /BF	6.67%	—	×1.150	7.67%
HR / BF /BF	1.33%	÷1.082	×1.250	1.54%

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 116).

Result: FIP 2.87 → 3.53, 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).

2019 AWisconsin Timber Rattlers · 14 IPFIP 2.09 → 3.23 (+1.14)K% 32.6% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.61%	—	×0.740	24.13%
BB% (unintentional) /BF	4.35%	—	×1.180	5.13%
HR / BF /BF	2.17%	÷1.022	×1.300	2.76%

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 104).

Result: FIP 2.09 → 3.23, 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 AABiloxi Shuckers · 6 IPFIP 3.94 → 4.59 (+0.65)K% 16.0% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.810	12.96%
BB% (unintentional) /BF	0.00%	—	×1.100	0.00%
HR / BF /BF	4.00%	÷1.018	×1.200	4.72%

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 104).

Result: FIP 3.94 → 4.59, 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 A+Wilmington Blue Rocks · 93 IPFIP 4.10 → 5.14 (+1.04)K% 13.6% → 10.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.60%	—	×0.770	10.47%
BB% (unintentional) /BF	9.32%	—	×1.150	10.72%
HR / BF /BF	1.76%	÷0.773	×1.250	2.85%

Result: FIP 4.10 → 5.14, 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 ALexington Legends · 73 IPFIP 3.38 → 4.39 (+1.02)K% 24.1% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.10%	—	×0.740	17.84%
BB% (unintentional) /BF	5.54%	—	×1.180	6.53%
HR / BF /BF	2.93%	÷1.062	×1.300	3.59%

Result: FIP 3.38 → 4.39, 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 ROKAZL Royals · 33 IPFIP 1.54 → 2.25 (+0.70)K% 22.7% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.70%	—	×0.680	15.43%
BB% (unintentional) /BF	2.84%	—	×1.250	3.55%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 1.54 → 2.25, 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 Bender (OGILVIE)	—	—	3.66	24.7%	8.5%	2.2%	—	4.07	23.5%	14.3%	56	+0.41	—	—	—
Jumbo Diaz R 2016 · 3.85 FIP	32	SU	3.85	22.3%	9.2%	2.7%	.247	3.28	23.0%	13.8%	141	-0.57	2.80	319	73
Jose Veras R 2013 · 3.51 FIP	32	SU	3.51	23.6%	8.3%	2.5%	.234	4.28	21.9%	10.2%	65	+0.77	3.37	422	72
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	72
Arcenio Leon R 2019 · 3.61 FIP	32	SU	3.61	21.4%	8.1%	2.4%	.314	—	—	—	—	—	3.00	115	71
Spencer Patton R 2021 · 3.04 FIP	33	SU	3.04	27.9%	8.7%	2.2%	.305	4.97	21.2%	10.4%	88	+1.93	2.79	239	71
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	70
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	70
Matt Lindstrom R 2012 · 2.71 FIP	32	SU	2.71	20.0%	6.0%	1.0%	.295	3.34	15.4%	7.9%	117	+0.63	2.40	443	70
Josh Fields R 2018 · 3.48 FIP	32	SU	3.48	21.4%	6.5%	2.5%	.224	7.56	18.9%	9.5%	25	+4.08	1.80	330	70
Sergio Santos R 2015 · 4.17 FIP	32	SU	4.17	24.7%	8.2%	3.9%	.283	—	—	—	—	—	1.36	178	70
Jose Manuel Lopez R 2017 · 3.61 FIP	32	SU	3.61	20.4%	10.0%	1.8%	.331	6.14	17.9%	3.7%	41	+2.53	3.50	170	69
Mark Serrano R 2017 · 3.56 FIP	31	SU	3.56	21.9%	6.4%	2.7%	.240	5.25	20.2%	12.3%	42	+1.69	3.16	120	69
Aaron Barrett R 2019 · 3.81 FIP	31	SU	3.81	23.0%	8.1%	3.0%	.246	4.56	19.9%	6.4%	38	+0.75	1.86	160	69
Jeff Fulchino R 2011 · 4.44 FIP	31	SU	4.44	20.4%	11.1%	3.0%	.302	—	—	—	—	—	3.36	178	69
Ryan Brasier R 2020 · 2.97 FIP	32	SU	2.97	27.3%	9.1%	1.9%	.324	3.30	23.4%	17.1%	134	+0.33	2.31	426	69
Shawn Camp R 2008 · 2.79 FIP	32	SU	2.79	18.7%	4.8%	1.2%	.304	3.63	14.8%	9.2%	218	+0.84	2.79	589	68
Tony Barnette R 2016 · 3.05 FIP	32	SU	3.05	19.9%	6.1%	1.6%	.281	3.26	23.4%	17.0%	84	+0.21	2.61	144	68
Jared Burton R 2013 · 3.20 FIP	32	SU	3.20	21.7%	6.0%	2.1%	.279	3.92	18.4%	10.0%	78	+0.72	3.09	367	68
Steve Delabar R 2015 · 3.74 FIP	32	SU	3.74	25.0%	9.9%	2.7%	.246	4.62	20.4%	4.8%	24	+0.88	2.43	229	68
Santiago Casilla R 2012 · 3.98 FIP	32	SU	3.98	20.2%	6.6%	3.2%	.246	3.23	21.6%	13.7%	166	-0.75	2.76	647	68

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	1.6	44	25.1%	8.8%	0.73	3.21
Kiko Calero ('09)	1.5	50	26.0%	10.1%	0.71	3.24
J.J. Putz ('14)	2.8	57	25.7%	7.9%	0.79	3.08
Andrew Bailey ('17)	1.4	55	24.7%	8.2%	0.95	3.12
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*