Anthony Banda

P Minnesota Twins

Age 33 LHP 6'2" / 221 lbs MLB peak 0.1 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	MIX2 levels	60	2	67	2.84	2.83	27.3%	6.5%	1.4	K 26.0% · BB 6.3% · FIP 2.87
2025	31	MLBLAD	71	1	65	3.18	4.12	22.8%	10.4%	0.3
2026	32	MLBMIN	39	0	34	4.46	3.54	21.2%	9.0%	0.4
2027PROJ	33	MLBMIN	20	0	21	4.01	4.17	23.6%	9.5%	0.1
2028PROJ95% MLB	34	MLBMIN	24	0	25	4.29	4.48	22.7%	10.0%	0.0

Last 3 seasons WAR 2.1 · Next 2 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo51

K%43

xwOBA vs39

CompsHideki Okajima (age 33) · Juan Pablo Perez (age 34) · Brandon Mann (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 97105vR 113

ERA4.01

FIP4.17

K%23.6%

BB%9.5%

K-BB%14.1%

Proj IP21

Value2027 · WAR

Runs saved vs league avg · 21 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5194.6

Whiff%

p5926.7%

p4321.2%

xwOBA vs

p390.325

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	21	A+ MLE	Visalia Rawhide	28	27	152	626	152	39	8	96%	5.4	18.7%	7.2%	11.5%	1.6%	3.32	3.33	—
2015	21	A+ RAW	Visalia Rawhide	28	27	152	626	152	39	8	96%	5.4	24.3%	6.2%	18.1%	1.3%	3.32	2.55	—
2016	22	MIX MLE	2 levels	26	26	150	642	152	54	10	100%	5.8	19.9%	9.0%	10.9%	1.6%	2.88	3.43	—
2016	22	MIX RAW	2 levels	26	26	150	642	152	54	10	100%	5.8	23.7%	8.4%	15.3%	1.6%	2.88	3.02	—
2017	23	MIX MLE	2 levels	30	26	148	646	141	60	16	87%	4.9	19.7%	9.7%	10.0%	2.6%	5.49	4.09	+2.3
2017	23	MIX RAW	2 levels	30	26	148	646	141	60	16	87%	4.9	21.8%	9.3%	12.5%	2.5%	5.49	3.82	+2.8
2018	24	MIX MLE	2 levels	11	9	57	238	59	21	4	82%	5.2	22.3%	9.2%	13.1%	1.9%	3.65	3.40	+1.4
2018	24	MIX RAW	2 levels	11	9	57	238	59	21	4	82%	5.2	24.8%	8.8%	16.0%	1.7%	3.65	3.05	+1.7
2019	25	MIX MLE	4 levels	16	8	37	163	35	14	7	50%	2.3	19.8%	9.6%	10.2%	5.7%	5.79	5.77	-0.2
2019	25	MIX RAW	4 levels	16	8	37	163	35	14	7	50%	2.3	21.5%	8.6%	12.9%	4.3%	5.79	4.79	+0.3
2020	26	MLB MLE	Tampa Bay Rays	4	0	7	36	4	5	1	0%	1.8	11.1%	13.9%	-2.8%	2.8%	10.29	5.45	-0.1
2020	26	MLB RAW	Tampa Bay Rays	4	0	7	36	4	5	1	0%	1.8	11.1%	13.9%	-2.8%	2.8%	10.29	5.96	-0.1
2021	27	MIX MLE	2 levels	43	5	83	385	84	32	15	12%	1.9	20.2%	8.6%	11.6%	4.2%	5.62	4.76	-0.2
2021	27	MIX RAW	2 levels	43	5	83	385	84	32	15	12%	1.9	21.8%	8.3%	13.5%	3.9%	5.62	4.58	-0.0
2022	28	MIX MLE	2 levels	42	2	38	184	41	17	5	5%	0.9	22.2%	8.1%	14.1%	2.8%	6.16	3.78	+0.3
2022	28	MIX RAW	2 levels	42	2	38	184	41	17	5	5%	0.9	22.3%	9.2%	13.0%	2.7%	6.16	3.99	+0.2
2023	29	MIX MLE	2 levels	43	10	72	351	68	37	10	23%	1.7	16.9%	9.1%	7.8%	3.0%	7.47	4.46	+0.1
2023	29	MIX RAW	2 levels	43	10	72	351	68	37	10	23%	1.7	19.4%	10.5%	8.8%	2.8%	7.47	4.55	-0.0
2024	30	MIX MLE	2 levels	60	2	67	275	75	18	6	3%	1.1	26.0%	6.3%	19.7%	2.1%	2.84	2.87	+1.3
2024	30	MIX MLE	2 levels	60	2	67	275	75	18	6	3%	1.1	26.0%	6.3%	19.7%	2.1%	2.84	2.87	+1.3
2024	30	MIX RAW	2 levels	60	2	67	275	75	18	6	3%	1.1	27.3%	6.5%	20.7%	2.2%	2.84	2.83	+1.4
2025	31	MLB MLE	Los Angeles Dodgers	71	1	65	268	61	28	8	1%	0.9	22.8%	10.4%	12.3%	2.9%	3.18	4.07	+0.4
2025	31	MLB MLE	Los Angeles Dodgers	71	1	65	268	61	28	8	1%	0.9	22.8%	10.4%	12.3%	2.9%	3.18	4.07	+0.4
2025	31	MLB RAW	Los Angeles Dodgers	71	1	65	268	61	28	8	1%	0.9	22.8%	10.4%	12.3%	3.0%	3.18	4.12	+0.3
2026	32	MLB MLE	Minnesota Twins	39	0	34	156	33	14	3	0%	0.9	21.2%	9.0%	12.2%	1.9%	4.46	3.50	+0.4
2026	32	MLB MLE	Minnesota Twins	39	0	34	156	33	14	3	0%	0.9	21.2%	9.0%	12.2%	1.9%	4.46	3.50	+0.4
2026	32	MLB RAW	Minnesota Twins	39	0	34	156	33	14	3	0%	0.9	21.2%	9.0%	12.2%	1.9%	4.46	3.54	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			248	9	268	1181	253	99	30	4%	1.1	21.4%	8.4%	13.0%	2.5%	4.44	3.78	+2.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	MIN	20	0	21	89	21	8	2	0%	1.1	23.6%	9.5%	14.1%	2.7%	4.01	4.17	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	MIN	25	0	26	110	25	11	3	0%	1.0	22.7%	10.0%	12.7%	3.0%	4.29	4.48	+0.0
2028	34	MLB CTX	MIN	24	0	25	106	24	11	3	0%	1.0	22.7%	10.0%	12.7%	3.0%	4.29	4.48	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		272	9	292	1286	277	109	33	3%	1.1	21.5%	8.5%	13.0%	2.6%	4.43	3.78	+2.7
/ 200 IP	—	RAW		186	6	200	879	189	75	23	3%	1.1	21.5%	8.5%	13.0%	2.6%	4.43	3.78	+1.8
Career	—	MLE		413	116	910	3970	805	347	100	28%	2.2	20.3%	8.8%	11.5%	2.5%	4.43	3.88	+2.5
/ 200 IP	—	MLE		91	25	200	873	177	76	22	28%	2.2	20.3%	8.8%	11.5%	2.5%	4.43	3.88	+1.7

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 AAAColumbus Clippers · 17 IPFIP 1.88 → 2.25 (+0.36)K% 37.9% → 32.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.88%	—	×0.860	32.58%
BB% (unintentional) /BF	9.09%	—	×0.900	8.18%
HR / BF /BF	1.52%	÷1.060	×1.100	1.57%

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 112).

Result: FIP 1.88 → 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).

2023 AAARochester Red Wings · 65 IPFIP 4.29 → 4.46 (+0.17)K% 19.6% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.62%	—	×0.860	16.87%
BB% (unintentional) /BF	10.13%	—	×0.900	9.11%
HR / BF /BF	2.85%	÷1.058	×1.100	2.96%

Result: FIP 4.29 → 4.46, 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 3.88 → 4.29 (+0.41)K% 22.4% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.45%	—	×0.880	19.76%
BB% (unintentional) /BF	12.24%	—	×1.050	12.86%
HR / BF /BF	2.04%	÷1.006	×1.100	2.23%

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 3.88 → 4.29, 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 AAASyracuse Mets · 50 IPFIP 4.43 → 4.83 (+0.41)K% 22.4% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.41%	—	×0.880	19.72%
BB% (unintentional) /BF	8.62%	—	×1.050	9.05%
HR / BF /BF	3.88%	÷1.039	×1.100	4.11%

Result: FIP 4.43 → 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).

2019 AAADurham Bulls · 28 IPFIP 5.56 → 5.77 (+0.21)K% 22.5% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.50%	—	×0.880	19.80%
BB% (unintentional) /BF	9.17%	—	×1.050	9.62%
HR / BF /BF	5.83%	÷1.128	×1.100	5.69%

Result: FIP 5.56 → 5.77, 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 AAADurham Bulls · 42 IPFIP 2.98 → 3.44 (+0.46)K% 26.9% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.92%	—	×0.880	23.69%
BB% (unintentional) /BF	9.89%	—	×1.050	10.38%
HR / BF /BF	1.65%	÷0.970	×1.100	1.87%

Result: FIP 2.98 → 3.44, 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 AAAReno Aces · 122 IPFIP 4.02 → 4.39 (+0.36)K% 21.8% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.85%	—	×0.880	19.22%
BB% (unintentional) /BF	9.60%	—	×1.050	10.08%
HR / BF /BF	2.82%	÷1.044	×1.100	2.97%

Result: FIP 4.02 → 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 AAMobile BayBears · 76 IPFIP 2.68 → 3.23 (+0.55)K% 25.8% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.85%	—	×0.810	20.94%
BB% (unintentional) /BF	8.62%	—	×1.100	9.48%
HR / BF /BF	1.23%	÷1.160	×1.200	1.27%

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 132).

Result: FIP 2.68 → 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).

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 Banda (OGILVIE)	—	—	—	—	—	2.7%	—	4.48	22.7%	12.7%	26	+0.31	—	—	—
Hideki Okajima L 2009 · 3.95 FIP	33	SU	3.95	20.5%	7.0%	3.1%	.268	4.27	15.5%	8.5%	46	+0.32	3.05	238	68
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	67
Brandon Mann L 2017 · 4.24 FIP	33	SU	4.24	19.8%	11.3%	2.5%	.286	3.59	17.8%	6.4%	52	-0.65	3.59	190	67
Doug Creek L 2002 · 4.99 FIP	33	SU	4.99	21.4%	12.6%	3.8%	.288	5.79	17.1%	7.9%	36	+0.80	4.48	277	66
Scott Sauerbeck L 2005 · 3.75 FIP	33	SU	3.75	22.3%	8.9%	2.5%	.298	5.05	14.0%	0.0%	25	+1.30	2.79	386	64
Kelly Wunsch L 2005 · 3.82 FIP	33	SU	3.82	21.0%	11.4%	1.9%	.261	—	—	—	—	—	3.36	175	64
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	64
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	63
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	63
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	63
Brian Moran L 2022 · 4.20 FIP	33	SU	4.20	21.7%	7.0%	3.7%	.304	3.72	21.5%	14.5%	152	-0.48	1.80	421	63
Anthony Gose L 2024 · 3.78 FIP	33	SU	3.78	26.4%	11.3%	2.7%	.279	5.07	21.5%	10.1%	97	+1.29	3.78	233	63
Zach Phillips L 2019 · 3.67 FIP	32	SU	3.67	19.1%	8.5%	2.0%	.355	—	—	—	—	—	2.33	202	62
Colt Hynes L 2017 · 3.75 FIP	32	SW	3.75	14.1%	4.6%	2.3%	.306	—	—	—	—	—	3.42	169	61
Tim Byrdak L 2007 · 3.25 FIP	33	SU	3.25	24.6%	11.1%	1.5%	.280	4.96	20.1%	7.6%	155	+1.71	2.85	320	61
Ryan O'Rourke L 2019 · 4.08 FIP	31	SU	4.08	22.1%	14.3%	1.9%	.290	—	—	—	—	—	3.05	145	59
Tom Martin L 2003 · 3.82 FIP	33	SU	3.82	24.3%	9.5%	2.9%	.226	3.99	16.2%	8.6%	106	+0.17	3.40	303	58
Joey Eischen L 2003 · 4.00 FIP	33	SU	4.00	18.1%	5.4%	3.2%	.309	3.44	19.6%	10.3%	69	-0.56	2.13	294	58
Edward Paredes L 2019 · 5.10 FIP	32	SU	5.10	21.5%	7.3%	5.3%	.364	—	—	—	—	—	2.36	130	57
Ryan Sherriff L 2023 · 3.78 FIP	33	SU	3.78	21.9%	11.0%	2.1%	.297	—	—	—	—	—	2.96	245	57

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	40	21.7%	9.8%	1.00	4.39
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Jacob Barnes ('25)	1.7	48	22.0%	9.2%	1.15	4.79
Wesley Wright ('15)	1.5	51	22.0%	10.1%	1.11	4.16
Tony Fossas ('88-'99, 2 WAR*)	2.1	42	21.9%*	9.3%*	0.99*	3.88*
Mike Munoz ('89-'00, 1 WAR*)	1.8	46	17.6%*	10.2%*	0.93*	4.46*
Bob Allen ('61-'67, -1 WAR*)	1.4	55	21.4%*	10.4%*	0.89*	4.79*