Casey Legumina

P Tampa Bay Rays

Age 30 RHP 6'2" / 195 lbs MLB peak 0.1 · 2027 ILForty Man (40M)

Overview

MLBRP40M40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	45	0	68	3.99	4.02	22.6%	7.1%	0.4	K 20.8% · BB 6.9% · FIP 4.06
2025	28	MIX2 levels	58	1	60	4.80	3.75	25.8%	10.6%	0.6	K 25.1% · BB 10.5% · FIP 4.11
2026	29	MLBTB	55	6	72	3.77	3.50	18.0%	5.2%	0.9
2027PROJ	30	MLBTB	45	0	47	4.30	4.30	19.9%	7.3%	0.1
2028PROJ95% MLB	31	MLBTB	34	0	36	4.44	4.53	19.1%	7.6%	0.0
2029PROJ95% MLB	32	MLBTB	23	0	24	4.65	4.78	18.3%	8.0%	-0.1

Last 3 seasons WAR 1.9 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs46

FB Velo29

K%21

Form3.71 ERA (proj 4.30) · K 21.1% (proj 19.9%) · BB 5.3% (proj 7.3%) ▲ last 90d · 27 IP through Oct 27

CompsKiko Calero (age 30) · Angel Castro (age 32) · Neil Wagner (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 113104vR 96

ERA4.30

FIP4.30

K%19.9%

BB%7.3%

K-BB%12.6%

Proj IP48

Value2027 · WAR

Runs saved vs league avg · 48 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL3535

CMD5050

K†4545

Statcast Percentiles

FB Velo

p2993.0

Whiff%

p1820.8%

p2118.0%

xwOBA vs

p460.316

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)
2021	24	MIX MLE	2 levels	15	9	49	200	63	16	4	60%	3.3	23.3%	9.3%	14.0%	3.2%	3.28	4.08	—
2021	24	MIX RAW	2 levels	15	9	49	200	63	16	4	60%	3.3	31.5%	8.0%	23.5%	2.0%	3.28	2.57	—
2022	25	MIX MLE	2 levels	33	16	86	385	92	34	11	48%	2.6	19.2%	9.8%	9.4%	3.5%	4.80	4.63	—
2022	25	MIX RAW	2 levels	33	16	86	385	92	34	11	48%	2.6	23.9%	8.8%	15.1%	2.9%	4.80	3.81	—
2023	26	MIX MLE	3 levels	38	1	45	211	51	22	6	3%	1.2	21.4%	10.0%	11.5%	2.8%	4.96	4.11	+0.2
2023	26	MIX RAW	3 levels	38	1	45	211	51	22	6	3%	1.2	24.2%	10.4%	13.7%	2.8%	4.96	4.03	+0.3
2024	27	MIX MLE	2 levels	45	0	68	283	64	20	10	0%	1.5	20.8%	6.9%	13.9%	3.4%	3.99	4.06	+0.4
2024	27	MIX MLE	2 levels	45	0	68	283	64	20	10	0%	1.5	20.8%	6.9%	13.9%	3.4%	3.99	4.06	+0.4
2024	27	MIX RAW	2 levels	45	0	68	283	64	20	10	0%	1.5	22.6%	7.1%	15.5%	3.5%	3.99	4.02	+0.4
2025	28	MIX MLE	2 levels	58	1	60	264	68	28	7	2%	1.0	25.1%	10.5%	14.6%	3.3%	4.80	4.11	+0.3
2025	28	MIX MLE	2 levels	58	1	60	264	68	28	7	2%	1.0	25.1%	10.5%	14.6%	3.3%	4.80	4.11	+0.3
2025	28	MIX RAW	2 levels	58	1	60	264	68	28	7	2%	1.0	25.8%	10.6%	15.2%	2.7%	4.80	3.75	+0.6
2026	29	MLB MLE	Tampa Bay Rays	55	6	72	305	55	16	7	11%	1.3	18.0%	5.2%	12.8%	2.4%	3.77	3.54	+0.9
2026	29	MLB MLE	Tampa Bay Rays	55	6	72	305	55	16	7	11%	1.3	18.0%	5.2%	12.8%	2.4%	3.77	3.54	+0.9
2026	29	MLB RAW	Tampa Bay Rays	55	6	72	305	55	16	7	11%	1.3	18.0%	5.2%	12.8%	2.3%	3.77	3.50	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			120	7	143	632	128	50	19	6%	1.2	20.3%	7.9%	12.3%	3.0%	4.90	4.08	+0.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	TB	45	0	47	198	39	14	6	0%	1.0	19.9%	7.3%	12.6%	2.9%	4.30	4.30	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	TB	37	0	38	162	31	12	5	0%	1.0	19.1%	7.6%	11.5%	3.1%	4.44	4.53	+0.0
2029	32	MLB MLE	TB	24	0	26	108	20	9	4	0%	1.1	18.3%	8.0%	10.3%	3.3%	4.65	4.78	-0.1
2028	31	MLB CTX	TB	34	0	36	152	29	12	5	0%	1.1	19.1%	7.6%	11.5%	3.1%	4.44	4.53	+0.0
2029	32	MLB CTX	TB	23	0	24	101	19	8	3	0%	1.0	18.3%	8.0%	10.3%	3.3%	4.65	4.78	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		178	7	204	888	176	70	27	4%	1.1	19.8%	7.9%	12.0%	3.1%	4.79	4.10	+1.1
/ 200 IP	—	RAW		174	7	200	871	173	69	26	4%	1.1	19.8%	7.9%	12.0%	3.1%	4.79	4.10	+1.1
Career	—	MLE		244	33	380	1648	346	140	51	14%	1.6	21.0%	8.5%	12.5%	3.1%	4.28	4.11	+0.7
/ 200 IP	—	MLE		128	17	200	867	182	74	27	14%	1.6	21.0%	8.5%	12.5%	3.1%	4.28	4.11	+0.7

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.

2025 AAATacoma Rainiers · 10 IPFIP 2.07 → 2.27 (+0.20)K% 28.9% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.89%	—	×0.860	24.84%
BB% (unintentional) /BF	11.11%	—	×0.900	10.00%
HR / BF /BF	0.00%	÷1.204	×1.100	0.00%

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 141).

Result: FIP 2.07 → 2.27, 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).

2024 AAALouisville Bats · 58 IPFIP 3.89 → 4.06 (+0.17)K% 24.2% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.15%	—	×0.860	20.77%
BB% (unintentional) /BF	7.63%	—	×0.900	6.86%
HR / BF /BF	3.39%	÷1.111	×1.100	3.36%

Result: FIP 3.89 → 4.06, 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 AAALouisville Bats · 32 IPFIP 3.10 → 3.35 (+0.25)K% 26.5% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.53%	—	×0.860	22.82%
BB% (unintentional) /BF	8.84%	—	×0.900	7.96%
HR / BF /BF	2.04%	÷1.054	×1.100	2.13%

Result: FIP 3.10 → 3.35, 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 AAWichita Wind Surge · 73 IPFIP 4.13 → 5.01 (+0.88)K% 22.9% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.89%	—	×0.810	18.54%
BB% (unintentional) /BF	9.04%	—	×1.100	9.94%
HR / BF /BF	3.31%	÷0.985	×1.200	4.04%

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 97).

Result: FIP 4.13 → 5.01, 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+Cedar Rapids Kernels · 13 IPFIP 1.51 → 2.24 (+0.73)K% 30.2% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.19%	—	×0.770	23.25%
BB% (unintentional) /BF	7.55%	—	×1.150	8.68%
HR / BF /BF	0.00%	÷0.948	×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 90).

Result: FIP 1.51 → 2.24, 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 AFort Myers Mighty Mussels · 45 IPFIP 2.67 → 4.08 (+1.40)K% 31.5% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.46%	—	×0.740	23.28%
BB% (unintentional) /BF	7.87%	—	×1.180	9.28%
HR / BF /BF	2.25%	÷0.908	×1.300	3.22%

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 82).

Result: FIP 2.67 → 4.08, 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 A+Cedar Rapids Kernels · 5 IPFIP 1.56 → 2.36 (+0.79)K% 31.8% → 24.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.82%	—	×0.770	24.50%
BB% (unintentional) /BF	9.09%	—	×1.150	10.45%
HR / BF /BF	0.00%	÷0.920	×1.250	0.00%

Result: FIP 1.56 → 2.36, 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).

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
Casey Legumina (OGILVIE)	—	—	4.30	19.9%	7.3%	2.9%	—	4.63	18.8%	11.0%	64	+0.33	—	—	—
Kiko Calero R 2005 · 3.51 FIP	30	SU	3.51	22.7%	7.0%	2.6%	.252	3.23	23.3%	13.9%	99	-0.28	2.27	298	79
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	79
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	78
Spencer Bivens R 2024 · 4.07 FIP	30	SU	4.07	18.0%	5.8%	3.2%	.265	3.88	18.2%	10.9%	157	-0.19	3.52	391	78
Matt Lindstrom R 2010 · 3.75 FIP	30	SU	3.75	17.6%	7.8%	2.1%	.356	2.94	17.8%	11.4%	162	-0.81	2.40	443	77
Manny Acosta R 2011 · 3.75 FIP	30	SU	3.75	22.5%	7.4%	2.9%	.321	4.49	21.3%	10.2%	47	+0.74	3.08	350	76
Mark Serrano R 2016 · 3.16 FIP	30	SU	3.16	17.7%	6.5%	1.3%	.290	4.36	21.1%	14.0%	88	+1.20	3.16	120	76
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	76
Felipe Arredondo R 2017 · 4.76 FIP	30	SW	4.76	14.8%	7.3%	3.6%	.311	4.65	16.2%	9.1%	64	-0.11	3.92	337	76
Kerry Ligtenberg R 2001 · 3.20 FIP	30	SU	3.20	22.0%	8.7%	1.6%	.267	3.95	18.5%	11.1%	181	+0.75	2.94	381	76
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	75
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	75
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	75
Saul Rivera R 2008 · 3.19 FIP	30	SU	3.19	17.5%	8.9%	0.8%	.322	5.00	11.9%	6.2%	38	+1.81	3.09	276	74
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	74
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	74
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	73
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	73
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	73
Yoanner Negrin R 2015 · 3.79 FIP	31	SW	3.79	15.1%	7.5%	1.9%	.256	3.29	15.0%	8.5%	270	-0.50	3.15	485	73

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	51	19.8%	8.2%	1.17	4.69
J. C. Gutierrez ('07-'14, -0 WAR*)	1.4	57	19.8%*	8.5%*	1.19*	4.72*
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
Tyler Walker ('10)	1.5	50	18.9%	8.5%	1.11	4.23
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*