Cole Sulser

P Tampa Bay Rays

Age 37 RHP 6'0" / 200 lbs MLB peak 0.4 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	34	MIX2 levels	43	3	60	1.96	3.70	25.5%	11.1%	0.6	K 22.9% · BB 10.3% · FIP 3.93
2025	35	MIX2 levels	48	0	57	1.57	2.40	25.5%	5.0%	1.5	K 23.3% · BB 4.8% · FIP 2.38
2026	36	MIX2 levels	57	2	63	4.12	3.56	23.5%	6.3%	0.7	K 23.7% · BB 5.5% · FIP 3.47
2027PROJ	37	MLBTB	52	0	55	3.84	3.90	23.1%	6.5%	0.4
2028PROJ86% MLB	38	MLBTB	26	0	27	4.13	4.33	22.0%	7.2%	0.1
2029PROJ72% MLB	39	MLBTB	10	0	11	4.51	4.76	20.8%	7.9%	-0.0

Last 3 seasons WAR 2.8 · Next 3 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%58

xwOBA vs42

FB Velo19

CompsJuan Sandoval (age 36) · Keiichi Yabu (age 36) · Chris Nichting (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109101vR 93

ERA3.84

FIP3.90

K%23.1%

BB%6.5%

K-BB%16.6%

Proj IP55

Value2027 · WAR

Runs saved vs league avg · 55 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL4040

CMD4545

K†5555

Statcast Percentiles

FB Velo

p1992.3

Whiff%

p6227.1%

p5823.7%

xwOBA vs

p420.321

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	26	MIX MLE	3 levels	42	3	64	276	70	16	2	7%	1.5	19.5%	6.9%	12.5%	1.0%	4.34	2.89	—
2016	26	MIX RAW	3 levels	42	3	64	276	70	16	2	7%	1.5	25.4%	5.8%	19.6%	0.7%	4.34	2.07	—
2017	27	MIX MLE	2 levels	45	0	63	269	70	26	5	0%	1.4	22.6%	10.2%	12.4%	1.9%	2.70	3.52	—
2017	27	MIX RAW	2 levels	45	0	63	269	70	26	5	0%	1.4	26.0%	9.7%	16.4%	1.9%	2.70	3.15	—
2018	28	MIX MLE	2 levels	47	0	61	248	95	17	4	0%	1.3	31.5%	7.7%	23.8%	1.8%	3.86	2.39	—
2018	28	MIX RAW	2 levels	47	0	61	248	95	17	4	0%	1.3	38.3%	6.9%	31.5%	1.6%	3.86	1.67	—
2019	29	MIX MLE	2 levels	56	4	73	302	98	27	4	7%	1.3	28.7%	9.2%	19.5%	1.4%	2.95	2.63	+1.7
2019	29	MIX RAW	2 levels	56	4	73	302	98	27	4	7%	1.3	32.5%	8.9%	23.5%	1.3%	2.95	2.24	+2.0
2020	30	MLB MLE	Baltimore Orioles	19	0	23	100	19	16	2	0%	1.2	19.0%	16.0%	3.0%	1.8%	5.56	4.51	+0.0
2020	30	MLB RAW	Baltimore Orioles	19	0	23	100	19	16	2	0%	1.2	19.0%	16.0%	3.0%	2.0%	5.56	4.69	-0.0
2021	31	MLB MLE	Baltimore Orioles	60	0	63	257	73	23	5	0%	1.1	28.4%	8.9%	19.5%	1.8%	2.70	2.80	+1.3
2021	31	MLB RAW	Baltimore Orioles	60	0	63	257	73	23	5	0%	1.1	28.4%	8.9%	19.5%	1.9%	2.70	2.91	+1.2
2022	32	MIX MLE	3 levels	47	1	43	186	54	17	8	2%	0.9	25.5%	10.1%	15.4%	4.2%	5.06	4.55	+0.0
2022	32	MIX RAW	3 levels	47	1	43	186	54	17	8	2%	0.9	29.0%	9.1%	19.9%	4.3%	5.06	4.20	+0.2
2023	33	MIX MLE	3 levels	22	4	30	136	34	15	8	18%	1.3	19.9%	7.6%	12.3%	3.1%	5.76	4.06	+0.2
2023	33	MIX RAW	3 levels	22	4	30	136	34	15	8	18%	1.3	25.0%	11.0%	14.0%	5.9%	5.76	5.83	-0.4
2024	34	MIX MLE	2 levels	43	3	60	235	60	26	6	7%	1.4	22.9%	10.3%	12.6%	2.6%	1.96	3.93	+0.4
2024	34	MIX MLE	2 levels	43	3	60	235	60	26	6	7%	1.4	22.9%	10.3%	12.6%	2.6%	1.96	3.93	+0.4
2024	34	MIX RAW	2 levels	43	3	60	235	60	26	6	7%	1.4	25.5%	11.1%	14.5%	2.6%	1.96	3.70	+0.6
2025	35	MIX MLE	2 levels	48	0	57	220	56	11	3	0%	1.2	23.3%	4.8%	18.5%	1.2%	1.57	2.38	+1.5
2025	35	MIX MLE	2 levels	48	0	57	220	56	11	3	0%	1.2	23.3%	4.8%	18.5%	1.2%	1.57	2.38	+1.5
2025	35	MIX RAW	2 levels	48	0	57	220	56	11	3	0%	1.2	25.5%	5.0%	20.5%	1.4%	1.57	2.40	+1.5
2026	36	MIX MLE	2 levels	57	2	63	268	63	17	8	4%	1.1	23.7%	5.5%	18.2%	3.0%	4.12	3.47	+0.8
2026	36	MIX MLE	2 levels	57	2	63	268	63	17	8	4%	1.1	23.7%	5.5%	18.2%	3.0%	4.12	3.47	+0.8
2026	36	MIX RAW	2 levels	57	2	63	268	63	17	8	4%	1.1	23.5%	6.3%	17.2%	3.0%	4.12	3.56	+0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			208	4	228	950	236	87	24	2%	1.1	24.8%	9.2%	15.7%	2.5%	3.71	3.54	+2.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	37	MLB	TB	52	0	55	232	54	15	7	0%	1.1	23.1%	6.5%	16.6%	2.8%	3.84	3.90	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	38	MLB MLE	TB	30	0	31	132	29	10	4	0%	1.0	22.0%	7.2%	14.8%	3.3%	4.13	4.33	+0.1
2029	39	MLB MLE	TB	14	0	15	64	13	5	2	0%	1.1	20.8%	7.9%	12.9%	3.7%	4.51	4.76	-0.0
2030	40	MLB MLE	TB	6	0	7	28	5	2	1	0%	1.1	19.7%	8.6%	11.1%	4.2%	4.92	5.20	-0.0
2028	38	MLB CTX	TB	26	0	27	114	25	8	4	0%	1.0	22.0%	7.2%	14.8%	3.3%	4.13	4.33	+0.1
2029	39	MLB CTX	TB	10	0	11	46	10	4	2	0%	1.1	20.8%	7.9%	12.9%	3.7%	4.51	4.76	-0.0
2030	40	MLB CTX	TB	4	0	4	17	3	1	1	0%	1.0	19.7%	8.6%	11.1%	4.2%	4.92	5.20	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		248	4	270	1126	274	100	30	2%	1.1	24.3%	8.9%	15.4%	2.7%	3.80	3.64	+2.9
/ 200 IP	—	RAW		184	3	200	835	203	74	22	2%	1.1	24.3%	8.9%	15.4%	2.7%	3.80	3.64	+2.2
Career	—	MLE		486	17	600	2497	614	211	52	3%	1.2	24.6%	8.5%	16.1%	2.1%	3.42	3.23	+2.7
/ 200 IP	—	MLE		162	6	200	832	205	70	17	3%	1.2	24.6%	8.5%	16.1%	2.1%	3.42	3.23	+1.9

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 · 7 IPFIP 4.55 → 4.82 (+0.27)K% 21.9% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.88%	—	×0.860	18.81%
BB% (unintentional) /BF	12.50%	—	×0.900	11.25%
HR / BF /BF	3.12%	÷1.000	×1.100	3.44%

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 4.55 → 4.82, 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).

2025 AAADurham Bulls · 35 IPFIP 2.22 → 2.31 (+0.09)K% 26.2% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.15%	—	×0.860	22.49%
BB% (unintentional) /BF	3.85%	—	×0.900	3.46%
HR / BF /BF	1.54%	÷1.380	×1.100	1.23%

Result: FIP 2.22 → 2.31, 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 AAADurham Bulls · 43 IPFIP 3.82 → 4.06 (+0.24)K% 26.6% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.63%	—	×0.860	22.90%
BB% (unintentional) /BF	10.65%	—	×0.900	9.59%
HR / BF /BF	2.96%	÷1.061	×1.100	3.07%

Result: FIP 3.82 → 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 AAADurham Bulls · 21 IPFIP 3.94 → 4.06 (+0.11)K% 23.2% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.16%	—	×0.860	19.92%
BB% (unintentional) /BF	8.42%	—	×0.900	7.58%
HR / BF /BF	3.16%	÷1.137	×1.100	3.06%

Result: FIP 3.94 → 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).

2022 AAAJacksonville Jumbo Shrimp · 6 IPFIP 4.79 → 5.41 (+0.62)K% 33.3% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.880	29.33%
BB% (unintentional) /BF	6.67%	—	×1.050	7.00%
HR / BF /BF	6.67%	÷1.032	×1.100	7.11%

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 106).

Result: FIP 4.79 → 5.41, 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 · 66 IPFIP 2.26 → 2.63 (+0.37)K% 32.6% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.60%	—	×0.880	28.69%
BB% (unintentional) /BF	8.79%	—	×1.050	9.23%
HR / BF /BF	1.47%	÷1.128	×1.100	1.43%

Result: FIP 2.26 → 2.63, 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 AAAColumbus Clippers · 52 IPFIP 2.02 → 2.39 (+0.38)K% 35.8% → 31.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.78%	—	×0.880	31.49%
BB% (unintentional) /BF	7.34%	—	×1.050	7.71%
HR / BF /BF	1.83%	÷1.135	×1.100	1.78%

Result: FIP 2.02 → 2.39, 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).

2018 AAAkron RubberDucks · 9 IPFIP -1.26 → -0.31 (+0.95)K% 56.7% → 45.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	56.67%	—	×0.810	45.90%
BB% (unintentional) /BF	3.33%	—	×1.100	3.67%
HR / BF /BF	0.00%	÷0.840	×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 68).

Result: FIP -1.26 → -0.31, 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
Cole Sulser (OGILVIE)	—	—	3.90	23.1%	6.5%	2.8%	—	4.47	21.6%	14.2%	46	+0.57	—	—	—
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	72
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	71
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	70
Matt Bush R 2023 · 3.79 FIP	37	SU	3.79	26.2%	8.7%	3.3%	.225	—	—	—	—	—	2.87	249	70
Scott Atchison R 2013 · 3.80 FIP	37	SU	3.80	14.4%	6.2%	2.1%	.273	3.60	16.7%	12.9%	92	-0.20	2.52	340	68
Erubiel Gonzalez R 2016 · 2.99 FIP	37	SU	2.99	16.4%	6.5%	0.8%	.333	3.51	13.3%	10.8%	35	+0.52	2.99	119	66
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	66
Pete Walker R 2006 · 4.45 FIP	37	SU	4.45	19.6%	8.0%	3.6%	.337	—	—	—	—	—	4.45	327	65
Roy Corcoran R 2015 · 2.87 FIP	35	SU	2.87	17.7%	8.2%	0.4%	.359	—	—	—	—	—	2.87	129	63
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	61
Hector Navarro R 2017 · 3.53 FIP	37	SU	3.53	11.5%	5.6%	1.3%	.283	—	—	—	—	—	2.30	126	58
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	57
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	55
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	52
Tony Pena Jr. R 2017 · 3.43 FIP	36	SU	3.43	10.9%	4.3%	1.3%	.312	—	—	—	—	—	2.80	128	51
Yoshihisa Hirano R 2020 · 5.02 FIP	36	SU	5.02	17.5%	12.7%	3.3%	.381	—	—	—	—	—	3.45	132	46
Hisanori Takahashi L 2012 · 4.04 FIP	37	SU	4.04	24.5%	6.1%	4.1%	.295	—	—	—	—	—	3.50	240	39
Heriberto Ruelas L 2017 · 3.42 FIP	35	SU	3.42	17.2%	6.7%	1.7%	.294	—	—	—	—	—	2.95	117	38
Logan Duran R 2019 · 3.66 FIP	37	SP-	3.66	15.5%	8.9%	1.4%	.427	—	—	—	—	—	3.42	187	32
Brian Shouse L 2006 · 4.19 FIP	37	SU	4.19	13.2%	7.5%	2.3%	.269	3.37	15.3%	11.0%	127	-0.82	2.32	339	31

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	1.7	37	24.0%	9.0%	1.06	3.83
Neftalí Feliz ('21)	2.0	49	22.9%	9.7%	1.05	3.55
Ryan Tepera ('23)	1.8	52	24.3%	8.8%	1.13	3.62
JT Chargois ('24)	1.2	33	23.3%	9.3%	0.97	3.35
Tony Fossas ('88-'99, 2 WAR*)	2.1	42	21.9%*	9.3%*	0.99*	3.88*
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*