Garrett Cleavinger

P Tampa Bay Rays

Age 33 LHP 6'1" / 225 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	MLBTB	68	60	3.75	3.58	26.7%	11.7%	0.7
2025	31	MLBTB	67	61	2.35	3.21	33.7%	7.4%	1.0
2026	32	MIX2 levels	57	46	5.12	4.15	29.2%	12.4%	0.2	K 29.8% · BB 11.0% · FIP 3.85
2027PROJ	33	MLBTB	43	45	3.73	3.76	31.9%	9.5%	0.4
2028PROJ95% MLB	34	MLBTB	36	38	3.93	4.06	31.0%	10.0%	0.2

Last 3 seasons WAR 1.9 · Next 2 projected WAR 0.7Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%90

FB Velo79

xwOBA vs45

CompsAnthony Gose (age 33) · Zac Rosscup (age 33) · Raul Valdes (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9098vR 106

ERA3.73

FIP3.76

K%31.9%

BB%9.5%

K-BB%22.4%

Proj IP45

Value2027 · WAR

Runs saved vs league avg · 45 IP

Grades · Statcast · Contract

Scouting Grades

STUF6565

CTRL4545

CMD6060

K†7070

Statcast Percentiles

FB Velo

p7996.6

Whiff%

p6928.3%

p9029.8%

xwOBA vs

p450.317

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	22	MIX MLE	2 levels	37	0	76	314	102	32	5	0%	2.1	24.5%	11.8%	12.7%	2.0%	3.07	3.62	—
2016	22	MIX RAW	2 levels	37	0	76	314	102	32	5	0%	2.1	32.5%	10.2%	22.3%	1.6%	3.07	2.54	—
2017	23	AA MLE	Reading Fightin Phils	38	0	54	256	59	31	5	0%	1.4	18.7%	13.3%	5.3%	1.9%	6.00	4.27	—
2017	23	AA RAW	Reading Fightin Phils	38	0	54	256	59	31	5	0%	1.4	23.0%	12.1%	10.9%	2.0%	6.00	3.84	—
2018	24	MIX MLE	2 levels	12	0	13	71	18	12	0	0%	1.1	25.4%	16.9%	8.5%	0.0%	7.42	3.10	—
2018	24	MIX RAW	2 levels	12	0	13	71	18	12	0	0%	1.1	25.4%	16.9%	8.5%	0.0%	7.42	3.10	—
2019	25	AA MLE	Reading Fightin Phils	34	0	52	228	83	34	2	0%	1.5	29.5%	16.4%	13.1%	0.9%	3.66	3.18	—
2019	25	AA RAW	Reading Fightin Phils	34	0	52	228	83	34	2	0%	1.5	36.4%	14.9%	21.5%	0.9%	3.66	2.36	—
2020	26	MLB MLE	Philadelphia Phillies	1	0	1	4	1	0	1	0%	0.7	25.0%	0.0%	25.0%	25.0%	13.50	14.71	-0.1
2020	26	MLB RAW	Philadelphia Phillies	1	0	1	4	1	0	1	0%	0.7	25.0%	0.0%	25.0%	25.0%	13.50	19.60	-0.1
2021	27	MIX MLE	2 levels	33	1	30	131	46	16	4	3%	0.9	25.0%	13.1%	11.9%	4.6%	2.43	5.15	-0.2
2021	27	MIX RAW	2 levels	33	1	30	131	46	16	4	3%	0.9	35.1%	12.2%	22.9%	3.1%	2.43	3.37	+0.4
2022	28	MIX MLE	2 levels	48	1	61	249	96	27	6	2%	1.3	35.5%	11.2%	24.2%	2.5%	2.95	2.92	+1.2
2022	28	MIX RAW	2 levels	48	1	61	249	96	27	6	2%	1.3	38.6%	10.8%	27.7%	2.4%	2.95	2.56	+1.5
2023	29	MLB MLE	Tampa Bay Rays	15	0	12	48	14	6	2	0%	0.8	29.2%	12.5%	16.7%	4.2%	3.00	4.51	+0.0
2023	29	MLB RAW	Tampa Bay Rays	15	0	12	48	14	6	2	0%	0.8	29.2%	12.5%	16.7%	4.2%	3.00	4.43	+0.0
2024	30	MLB MLE	Tampa Bay Rays	68	0	60	266	71	31	6	0%	0.9	26.7%	11.7%	15.0%	2.3%	3.75	3.60	+0.7
2024	30	MLB MLE	Tampa Bay Rays	68	0	60	266	71	31	6	0%	0.9	26.7%	11.7%	15.0%	2.3%	3.75	3.60	+0.7
2024	30	MLB RAW	Tampa Bay Rays	68	0	60	266	71	31	6	0%	0.9	26.7%	11.7%	15.0%	2.3%	3.75	3.58	+0.7
2025	31	MLB MLE	Tampa Bay Rays	67	0	61	243	82	18	9	0%	0.9	33.7%	7.4%	26.3%	3.6%	2.35	3.16	+1.0
2025	31	MLB MLE	Tampa Bay Rays	67	0	61	243	82	18	9	0%	0.9	33.7%	7.4%	26.3%	3.6%	2.35	3.16	+1.0
2025	31	MLB RAW	Tampa Bay Rays	67	0	61	243	82	18	9	0%	0.9	33.7%	7.4%	26.3%	3.7%	2.35	3.21	+1.0
2026	32	MIX MLE	2 levels	57	0	46	202	59	25	7	0%	0.8	29.8%	11.0%	18.8%	3.4%	5.12	3.85	+0.4
2026	32	MIX MLE	2 levels	57	0	46	202	59	25	7	0%	0.8	29.8%	11.0%	18.8%	3.4%	5.12	3.85	+0.4
2026	32	MIX RAW	2 levels	57	0	46	202	59	25	7	0%	0.8	29.2%	12.4%	16.8%	3.5%	5.12	4.15	+0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			241	1	216	918	275	93	30	0%	0.9	30.0%	10.1%	19.8%	3.3%	3.49	3.65	+2.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	TB	43	0	45	190	61	18	6	0%	1.0	31.9%	9.5%	22.4%	3.2%	3.73	3.76	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	TB	39	0	40	171	53	17	6	0%	1.0	31.0%	10.0%	21.0%	3.5%	3.93	4.06	+0.2
2028	34	MLB CTX	TB	36	0	38	160	50	16	6	0%	1.1	31.0%	10.0%	21.0%	3.5%	3.93	4.06	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		278	1	255	1080	325	109	36	0%	0.9	30.1%	10.1%	20.0%	3.3%	3.56	3.65	+2.7
/ 200 IP	—	RAW		218	1	200	848	255	86	28	0%	0.9	30.1%	10.1%	20.0%	3.3%	3.56	3.65	+2.1
Career	—	MLE		410	2	466	2012	559	243	50	0%	1.1	27.8%	12.1%	15.7%	2.5%	3.75	3.66	+2.5
/ 200 IP	—	MLE		176	1	200	864	240	104	22	0%	1.1	27.8%	12.1%	15.7%	2.5%	3.75	3.66	+2.0

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 AAADurham Bulls · 4 IPFIP 6.72 → 6.96 (+0.24)K% 23.8% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.860	20.48%
BB% (unintentional) /BF	23.81%	—	×0.900	21.43%
HR / BF /BF	4.76%	÷1.000	×1.100	5.24%

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 6.72 → 6.96, 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).

2022 AAADurham Bulls · 38 IPFIP 2.67 → 3.25 (+0.58)K% 40.8% → 35.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.76%	—	×0.880	35.87%
BB% (unintentional) /BF	12.74%	—	×1.050	13.38%
HR / BF /BF	2.55%	÷1.034	×1.100	2.71%

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 2.67 → 3.25, 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).

2021 AAAOklahoma City Dodgers · 12 IPFIP -0.04 → 0.56 (+0.61)K% 53.2% → 46.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	53.19%	—	×0.880	46.81%
BB% (unintentional) /BF	10.64%	—	×1.050	11.17%
HR / BF /BF	0.00%	÷1.016	×1.100	0.00%

Result: FIP -0.04 → 0.56, 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 AAReading Fightin Phils · 52 IPFIP 2.40 → 3.18 (+0.78)K% 36.4% → 29.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.40%	—	×0.810	29.49%
BB% (unintentional) /BF	14.91%	—	×1.100	16.40%
HR / BF /BF	0.88%	÷1.182	×1.200	0.89%

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 136).

Result: FIP 2.40 → 3.18, 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).

2018 AAReading Fightin Phils · 8 IPFIP 3.28 → 4.01 (+0.73)K% 29.2% → 23.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.17%	—	×0.810	23.63%
BB% (unintentional) /BF	20.83%	—	×1.100	22.92%
HR / BF /BF	0.00%	÷1.164	×1.200	0.00%

Result: FIP 3.28 → 4.01, 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).

2018 A+Clearwater Threshers · 5 IPFIP 2.73 → 3.24 (+0.50)K% 17.4% → 13.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.39%	—	×0.770	13.39%
BB% (unintentional) /BF	8.70%	—	×1.150	10.00%
HR / BF /BF	0.00%	÷1.197	×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 139).

Result: FIP 2.73 → 3.24, 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).

2017 AAReading Fightin Phils · 54 IPFIP 3.76 → 4.27 (+0.51)K% 23.0% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.05%	—	×0.810	18.67%
BB% (unintentional) /BF	12.11%	—	×1.100	13.32%
HR / BF /BF	1.95%	÷1.220	×1.200	1.92%

Result: FIP 3.76 → 4.27, 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).

2016 A+Frederick Keys · 37 IPFIP 2.87 → 3.70 (+0.83)K% 29.3% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.34%	—	×0.770	22.59%
BB% (unintentional) /BF	12.57%	—	×1.150	14.46%
HR / BF /BF	1.20%	÷1.214	×1.250	1.23%

Result: FIP 2.87 → 3.70, 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
Garrett Cleavinger (OGILVIE)	—	—	3.76	31.9%	9.5%	3.2%	—	4.06	31.0%	21.0%	40	+0.30	—	—	—
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	64
Zac Rosscup L 2021 · 2.56 FIP	33	SU	2.56	29.1%	11.9%	0.8%	.294	2.83	24.1%	10.2%	29	+0.27	2.56	173	63
Raul Valdes L 2011 · 2.65 FIP	33	SU	2.65	27.3%	7.3%	1.7%	.371	3.23	27.4%	23.0%	66	+0.58	2.29	160	62
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	60
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	60
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	60
Mike Zagurski L 2017 · 2.94 FIP	34	SU	2.94	31.2%	6.8%	2.9%	.294	3.12	30.4%	21.1%	45	+0.18	2.94	120	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
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	57
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	56
Brooks Raley L 2021 · 3.06 FIP	33	SU	3.06	31.7%	7.8%	3.0%	.314	2.71	26.8%	18.8%	108	-0.35	1.74	294	54
Pedro Borbón L 2001 · 3.90 FIP	33	SU	3.90	20.7%	4.1%	3.7%	.258	4.57	21.6%	14.3%	50	+0.67	2.26	264	54
Kelly Wunsch L 2005 · 3.82 FIP	33	SU	3.82	21.0%	11.4%	1.9%	.261	—	—	—	—	—	3.36	175	54
Zach Phillips L 2019 · 3.67 FIP	32	SU	3.67	19.1%	8.5%	2.0%	.355	—	—	—	—	—	2.33	202	49
Heriberto Ruelas L 2015 · 2.95 FIP	33	SU	2.95	19.1%	7.3%	1.0%	.352	3.57	16.2%	8.5%	89	+0.62	2.95	117	49
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	49
Jeff Ibarra L 2019 · 2.85 FIP	31	SU	2.85	20.6%	3.4%	1.9%	.258	—	—	—	—	—	2.85	101	49
Adam Liberatore L 2018 · 4.28 FIP	31	SU	4.28	18.6%	9.1%	2.9%	.354	—	—	—	—	—	2.38	124	49
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	48
Ryan Sherriff L 2023 · 3.78 FIP	33	SU	3.78	21.9%	11.0%	2.1%	.297	—	—	—	—	—	2.96	245	47

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	1.5	50	30.4%	10.2%	1.27	3.59
Ernesto Frieri ('17)	1.5	51	30.1%	11.1%	1.25	3.59
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
Diego Castillo ('24)	1.4	56	27.2%	9.6%	1.07	3.20
Victor Cruz ('78-'83, 5 WAR*)	1.4	54	35.3%*	11.5%*	1.30*	3.24*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*