Kevin Kelly

P Tampa Bay Rays

Age 29 RHP 6'2" / 195 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	73	0	75	2.51	2.74	24.0%	2.7%	1.6	K 22.7% · BB 2.9% · FIP 2.97
2025	27	MIX3 levels	53	1	52	5.05	4.34	23.9%	4.1%	0.1	K 20.5% · BB 4.7% · FIP 5.39
2026	28	MLBTB	71	0	74	2.44	2.77	22.6%	2.9%	1.6
2027PROJ	29	MLBTB	55	0	58	3.77	3.84	20.5%	3.1%	0.5
2028PROJ95% MLB	30	MLBTB	42	0	44	3.93	4.04	19.9%	3.4%	0.3
2029PROJ95% MLB	31	MLBTB	32	0	34	4.14	4.27	19.1%	3.7%	0.1

Last 3 seasons WAR 3.3 · Next 3 projected WAR 0.9Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs79

K%52

FB Velo32

Form3.00 ERA (proj 3.77) · K 24.5% (proj 20.5%) · BB 3.2% (proj 3.1%) ▲ last 90d · 24 IP through Oct 27

CompsKeith Foulke (age 29) · Burke Badenhop (age 29) · Cory Wade (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9991vR 83

ERA3.77

FIP3.84

K%20.5%

BB%3.1%

K-BB%17.5%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Statcast · Contract

Scouting Grades

STUF4040

CTRL7070

CMD5555

K†5050

Statcast Percentiles

FB Velo

p3293.2

Whiff%

p4124.0%

p5222.6%

xwOBA vs

p790.284

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)
2019	21	ROK MLE	AZL Indians Blue	14	0	17	70	25	2	1	0%	1.2	24.3%	3.6%	20.7%	2.0%	2.08	2.60	—
2019	21	ROK RAW	AZL Indians Blue	14	0	17	70	25	2	1	0%	1.2	35.7%	2.9%	32.9%	1.4%	2.08	1.31	—
2021	23	A+ MLE	Lake County Captains	40	0	56	235	81	7	7	0%	1.4	26.5%	3.4%	23.1%	3.0%	4.66	2.96	—
2021	23	A+ RAW	Lake County Captains	40	0	56	235	81	7	7	0%	1.4	34.5%	3.0%	31.5%	3.0%	4.66	2.21	—
2022	24	MIX MLE	2 levels	48	1	57	251	75	22	1	2%	1.2	25.4%	9.4%	16.0%	0.4%	2.04	2.38	—
2022	24	MIX RAW	2 levels	48	1	57	251	75	22	1	2%	1.2	29.9%	8.8%	21.1%	0.4%	2.04	1.86	—
2023	25	MLB MLE	Tampa Bay Rays	57	0	67	276	56	14	2	0%	1.2	20.3%	5.1%	15.2%	0.7%	3.09	2.44	+1.7
2023	25	MLB RAW	Tampa Bay Rays	57	0	67	276	56	14	2	0%	1.2	20.3%	5.1%	15.2%	0.7%	3.09	2.44	+1.7
2024	26	MIX MLE	2 levels	73	0	75	296	71	8	7	0%	1.0	22.7%	2.9%	19.8%	2.6%	2.51	2.97	+1.4
2024	26	MIX MLE	2 levels	73	0	75	296	71	8	7	0%	1.0	22.7%	2.9%	19.8%	2.6%	2.51	2.97	+1.4
2024	26	MIX RAW	2 levels	73	0	75	296	71	8	7	0%	1.0	24.0%	2.7%	21.3%	2.4%	2.51	2.74	+1.6
2025	27	MIX MLE	3 levels	53	1	52	222	53	9	11	2%	1.0	20.5%	4.7%	15.8%	6.2%	5.05	5.39	-0.5
2025	27	MIX MLE	3 levels	53	1	52	222	53	9	11	2%	1.0	20.5%	4.7%	15.8%	6.2%	5.05	5.39	-0.5
2025	27	MIX RAW	3 levels	53	1	52	222	53	9	11	2%	1.0	23.9%	4.1%	19.8%	5.0%	5.05	4.34	+0.1
2026	28	MLB MLE	Tampa Bay Rays	71	0	74	279	63	8	6	0%	1.0	22.6%	2.9%	19.7%	2.2%	2.44	2.77	+1.6
2026	28	MLB MLE	Tampa Bay Rays	71	0	74	279	63	8	6	0%	1.0	22.6%	2.9%	19.7%	2.2%	2.44	2.77	+1.6
2026	28	MLB RAW	Tampa Bay Rays	71	0	74	279	63	8	6	0%	1.0	22.6%	2.9%	19.7%	2.2%	2.44	2.77	+1.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			237	0	251	1004	217	38	26	0%	1.1	21.6%	3.8%	17.8%	2.6%	3.23	3.17	+4.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	TB	55	0	58	245	50	8	8	0%	1.1	20.5%	3.1%	17.5%	3.1%	3.77	3.84	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	TB	44	0	46	194	38	7	6	0%	1.0	19.9%	3.4%	16.5%	3.3%	3.93	4.04	+0.3
2029	31	MLB MLE	TB	34	0	36	152	29	6	5	0%	1.1	19.1%	3.7%	15.4%	3.5%	4.14	4.27	+0.1
2028	30	MLB CTX	TB	42	0	44	186	37	6	6	0%	1.0	19.9%	3.4%	16.5%	3.3%	3.93	4.04	+0.3
2029	31	MLB CTX	TB	32	0	34	144	27	5	5	0%	1.1	19.1%	3.7%	15.4%	3.5%	4.14	4.27	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		311	0	329	1333	281	50	37	0%	1.1	21.1%	3.7%	17.4%	2.8%	3.42	3.32	+4.8
/ 200 IP	—	RAW		189	0	200	811	171	30	23	0%	1.1	21.1%	3.7%	17.4%	2.8%	3.42	3.32	+2.9
Career	—	MLE		356	2	398	1629	375	75	39	1%	1.1	23.0%	4.6%	18.4%	2.4%	3.14	3.07	+4.5
/ 200 IP	—	MLE		179	1	200	818	188	38	20	1%	1.1	23.0%	4.6%	18.4%	2.4%	3.14	3.07	+2.7

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 AAADurham Bulls · 11 IPFIP 0.62 → 0.98 (+0.36)K% 32.6% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.61%	—	×0.860	28.04%
BB% (unintentional) /BF	2.17%	—	×0.900	1.96%
HR / BF /BF	0.00%	÷1.380	×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 176).

Result: FIP 0.62 → 0.98, 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 AAAColumbus Clippers · 33 IPFIP 2.14 → 2.52 (+0.38)K% 28.9% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.86%	—	×0.880	25.40%
BB% (unintentional) /BF	8.72%	—	×1.050	9.16%
HR / BF /BF	0.67%	÷1.001	×1.100	0.74%

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 100).

Result: FIP 2.14 → 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).

2022 AAAkron RubberDucks · 24 IPFIP 1.57 → 2.18 (+0.62)K% 31.4% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.37%	—	×0.810	25.41%
BB% (unintentional) /BF	8.82%	—	×1.100	9.71%
HR / BF /BF	0.00%	÷1.014	×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 103).

Result: FIP 1.57 → 2.18, 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+Lake County Captains · 56 IPFIP 2.20 → 2.96 (+0.76)K% 34.5% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.47%	—	×0.770	26.54%
BB% (unintentional) /BF	2.98%	—	×1.150	3.43%
HR / BF /BF	2.98%	÷1.222	×1.250	3.05%

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 144).

Result: FIP 2.20 → 2.96, 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 ROKAZL Indians Blue · 17 IPFIP 1.23 → 2.60 (+1.37)K% 35.7% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.71%	—	×0.680	24.29%
BB% (unintentional) /BF	2.86%	—	×1.250	3.57%
HR / BF /BF	1.43%	÷1.000	×1.400	2.00%

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 1.23 → 2.60, 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
Kevin Kelly (OGILVIE)	—	—	3.84	20.5%	3.1%	3.1%	—	4.14	19.5%	16.0%	82	+0.30	—	—	—
Keith Foulke R 2002 · 3.21 FIP	29	SU	3.21	19.0%	3.6%	2.3%	.252	3.40	23.0%	18.0%	215	+0.19	2.47	787	74
Burke Badenhop R 2012 · 3.38 FIP	29	SU	3.38	16.0%	2.7%	2.4%	.275	3.17	14.2%	9.7%	199	-0.21	2.67	512	74
Cory Wade R 2012 · 4.15 FIP	29	SU	4.15	22.2%	4.1%	4.4%	.322	—	—	—	—	—	3.48	178	73
Mike Fyhrie R 2000 · 3.08 FIP	30	SU	3.08	19.5%	5.0%	1.8%	.309	3.87	13.7%	4.4%	69	+0.79	3.08	173	73
Jeff Zimmerman R 2001 · 3.58 FIP	28	SU	3.58	26.4%	5.5%	3.7%	.216	—	—	—	—	—	3.58	229	73
Anthony Varvaro R 2014 · 3.22 FIP	29	SU	3.22	22.9%	5.5%	2.5%	.272	3.30	20.9%	11.2%	40	+0.08	3.02	208	73
Matt Belisle R 2009 · 4.56 FIP	29	SU	4.56	16.5%	3.0%	4.5%	.287	2.52	21.6%	18.2%	244	-2.04	2.31	920	71
Justin Speier R 2003 · 3.92 FIP	29	SU	3.92	20.7%	5.3%	3.5%	.276	3.77	20.9%	14.5%	187	-0.15	3.27	675	71
Jose Jimenez R 2002 · 3.35 FIP	29	SU	3.35	15.3%	2.3%	2.3%	.280	4.12	10.3%	4.3%	138	+0.77	3.10	521	70
Braden Looper R 2004 · 2.90 FIP	29	SU	2.90	17.3%	3.8%	1.5%	.302	4.22	11.8%	5.5%	308	+1.32	2.90	1,173	70
Shane Greene R 2018 · 4.42 FIP	29	SU	4.42	23.3%	6.5%	4.5%	.304	3.93	23.0%	15.2%	114	-0.49	2.86	563	70
Junichi Tazawa R 2015 · 2.94 FIP	29	SU	2.94	22.7%	4.9%	2.1%	.345	4.62	20.6%	12.8%	147	+1.68	1.59	427	70
Paul Sewald R 2019 · 3.75 FIP	29	SU	3.75	22.8%	6.0%	3.3%	.330	3.20	34.6%	28.3%	129	-0.55	2.71	611	70
Blake Treinen R 2017 · 3.15 FIP	29	SU	3.15	22.8%	6.8%	2.0%	.332	2.94	26.6%	18.0%	165	-0.21	1.53	601	69
David Carpenter R 2014 · 2.84 FIP	29	SU	2.84	25.9%	6.2%	2.1%	.327	4.98	15.8%	5.8%	50	+2.14	2.66	275	69
Jon Rauch R 2008 · 3.86 FIP	29	SU	3.86	22.4%	4.7%	3.7%	.284	3.89	17.1%	10.7%	180	+0.03	2.87	595	69
Alex Wilson R 2016 · 3.35 FIP	29	SU	3.35	16.5%	5.4%	1.8%	.278	4.34	17.7%	12.7%	183	+0.99	2.93	382	68
Adam Ottavino R 2014 · 2.70 FIP	28	SU	2.70	25.7%	5.5%	2.0%	.337	3.80	28.2%	15.9%	80	+1.10	2.10	733	68
Jake Sanchez R 2019 · 2.83 FIP	29	SU	2.83	23.8%	4.7%	2.1%	.311	—	—	—	—	—	1.86	361	68
Jesus Pirela R 2019 · 3.24 FIP	30	SU	3.24	22.5%	5.3%	2.5%	.277	—	—	—	—	—	3.24	161	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	2.0	56	21.0%	4.0%	1.10	3.47
Matt Capps ('12)	2.2	63	17.5%	4.6%	1.08	3.52
Edward Mujica ('17)	2.8	69	19.1%	3.9%	1.30	3.92
Junichi Tazawa ('18)	2.0	49	22.2%	6.5%	1.12	4.12
Tim Crews ('87-'92, 3 WAR*)	2.1	71	20.8%*	6.2%*	1.09*	4.11*
Donn Pall ('88-'98, 3 WAR*)	2.5	63	17.1%*	6.2%*	1.20*	3.86*
Tony Castillo ('88-'98, 4 WAR*)	2.6	59	18.5%*	7.3%*	0.98*	3.76*