Bryan Baker

P Tampa Bay Rays

Age 32 RHP 6'6" / 235 lbs MLB peak 0.5 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	29	MIX2 levels	51	55	5.10	3.85	29.1%	10.1%	0.5	K 26.4% · BB 9.4% · FIP 4.13
2025	30	MLBTB	73	69	4.06	3.89	30.3%	6.2%	0.5
2026	31	MLBTB	65	62	1.44	2.92	25.8%	8.6%	1.2
2027PROJ	32	MLBTB	53	56	3.62	3.70	27.9%	7.3%	0.6
2028PROJ95% MLB	33	MLBTB	42	44	3.84	3.98	27.1%	7.8%	0.3
2029PROJ90% MLB	34	MLBTB	31	33	4.11	4.28	26.2%	8.3%	0.1

Last 3 seasons WAR 2.2 · Next 3 projected WAR 1.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs90

FB Velo75

K%70

Form1.29 ERA (proj 3.62) · K 23.5% (proj 27.9%) · BB 10.6% (proj 7.3%) ▼▼ last 90d · 21 IP through Oct 27

CompsAkinori Otsuka (age 32) · Jay Jackson (age 31) · Chris Hatcher (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9587vR 78

ERA3.62

FIP3.70

K%27.9%

BB%7.3%

K-BB%20.6%

Proj IP56

Value2027 · WAR

Runs saved vs league avg · 56 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL6060

CMD6565

K†6565

Statcast Percentiles

FB Velo

p7596.3

Whiff%

p6227.2%

p7025.8%

xwOBA vs

p900.272

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	21	ROK MLE	Grand Junction Rockies	11	11	48	216	41	12	10	100%	4.4	12.9%	6.9%	6.0%	6.5%	6.00	6.45	—
2016	21	ROK RAW	Grand Junction Rockies	11	11	48	216	41	12	10	100%	4.4	19.0%	5.6%	13.4%	4.6%	6.00	4.85	—
2017	22	A MLE	Asheville Tourists	26	2	54	214	57	13	3	8%	2.1	19.7%	7.2%	12.5%	1.5%	1.66	3.15	—
2017	22	A RAW	Asheville Tourists	26	2	54	214	57	13	3	8%	2.1	26.6%	6.1%	20.6%	1.4%	1.66	2.44	—
2018	23	A+ MLE	Dunedin Blue Jays	49	0	51	241	67	37	9	0%	1.0	21.4%	17.7%	3.8%	4.1%	3.68	5.76	—
2018	23	A+ RAW	Dunedin Blue Jays	49	0	51	241	67	37	9	0%	1.0	27.8%	15.4%	12.4%	3.7%	3.68	4.93	—
2019	24	MIX MLE	2 levels	49	0	54	232	71	34	3	0%	1.1	25.7%	15.8%	9.9%	1.7%	3.17	3.85	—
2019	24	MIX RAW	2 levels	49	0	54	232	71	34	3	0%	1.1	30.6%	14.7%	15.9%	1.3%	3.17	3.08	—
2021	26	MIX MLE	2 levels	40	0	42	170	49	17	1	0%	1.1	25.4%	10.8%	14.7%	0.6%	1.28	2.65	+1.0
2021	26	MIX RAW	2 levels	40	0	42	170	49	17	1	0%	1.1	28.8%	10.0%	18.8%	0.6%	1.28	2.30	+1.1
2022	27	MLB MLE	Baltimore Orioles	66	2	70	291	76	25	3	3%	1.1	26.1%	8.6%	17.5%	1.0%	3.49	2.55	+1.7
2022	27	MLB RAW	Baltimore Orioles	66	2	70	291	76	25	3	3%	1.1	26.1%	8.6%	17.5%	1.0%	3.49	2.55	+1.7
2023	28	MIX MLE	2 levels	59	0	58	252	69	30	6	0%	1.0	26.4%	11.6%	14.8%	2.5%	4.32	3.70	+0.6
2023	28	MIX RAW	2 levels	59	0	58	252	69	30	6	0%	1.0	27.4%	11.9%	15.5%	2.4%	4.32	3.61	+0.6
2024	29	MIX MLE	2 levels	51	0	55	227	66	23	8	0%	1.1	26.4%	9.4%	17.0%	3.8%	5.10	4.13	+0.3
2024	29	MIX MLE	2 levels	51	0	55	227	66	23	8	0%	1.1	26.4%	9.4%	17.0%	3.8%	5.10	4.13	+0.3
2024	29	MIX RAW	2 levels	51	0	55	227	66	23	8	0%	1.1	29.1%	10.1%	18.9%	3.5%	5.10	3.85	+0.5
2025	30	MLB MLE	Tampa Bay Rays	73	0	69	274	83	17	13	0%	0.9	30.3%	6.2%	24.1%	4.6%	4.06	3.86	+0.6
2025	30	MLB MLE	Tampa Bay Rays	73	0	69	274	83	17	13	0%	0.9	30.3%	6.2%	24.1%	4.6%	4.06	3.86	+0.6
2025	30	MLB RAW	Tampa Bay Rays	73	0	69	274	83	17	13	0%	0.9	30.3%	6.2%	24.1%	4.7%	4.06	3.89	+0.5
2026	31	MLB MLE	Tampa Bay Rays	65	0	62	244	63	21	4	0%	1.0	25.8%	8.6%	17.2%	1.7%	1.44	2.94	+1.2
2026	31	MLB MLE	Tampa Bay Rays	65	0	62	244	63	21	4	0%	1.0	25.8%	8.6%	17.2%	1.7%	1.44	2.94	+1.2
2026	31	MLB RAW	Tampa Bay Rays	65	0	62	244	63	21	4	0%	1.0	25.8%	8.6%	17.2%	1.6%	1.44	2.92	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			270	2	270	1092	297	92	27	1%	1.0	27.2%	8.4%	18.8%	2.5%	3.30	3.22	+4.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	TB	53	0	56	236	66	17	7	0%	1.1	27.9%	7.3%	20.6%	3.0%	3.62	3.70	+0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	TB	44	0	47	197	53	15	6	0%	1.1	27.1%	7.8%	19.3%	3.3%	3.84	3.98	+0.3
2029	34	MLB MLE	TB	35	0	37	155	40	13	6	0%	1.0	26.2%	8.3%	17.9%	3.6%	4.11	4.28	+0.1
2030	35	MLB MLE	TB	25	0	26	111	28	10	4	0%	1.1	25.2%	8.8%	16.4%	3.9%	4.42	4.62	-0.0
2028	33	MLB CTX	TB	42	0	44	186	50	14	6	0%	1.0	27.1%	7.8%	19.3%	3.3%	3.84	3.98	+0.3
2029	34	MLB CTX	TB	31	0	33	139	36	12	5	0%	1.1	26.2%	8.3%	17.9%	3.6%	4.11	4.28	+0.1
2030	35	MLB CTX	TB	22	0	23	97	24	9	4	0%	1.0	25.2%	8.8%	16.4%	3.9%	4.42	4.62	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		365	2	370	1515	408	127	42	1%	1.0	27.0%	8.4%	18.6%	2.8%	3.51	3.40	+5.1
/ 200 IP	—	RAW		197	1	200	819	220	69	23	1%	1.0	27.0%	8.4%	18.6%	2.8%	3.51	3.40	+2.7
Career	—	MLE		489	15	564	2361	573	241	66	3%	1.2	24.3%	10.2%	14.0%	2.8%	3.43	3.89	+4.7
/ 200 IP	—	MLE		174	5	200	838	203	86	24	3%	1.2	24.3%	10.2%	14.0%	2.8%	3.43	3.89	+2.5

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 AAANorfolk Tides · 31 IPFIP 3.95 → 4.39 (+0.44)K% 32.1% → 27.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.09%	—	×0.860	27.60%
BB% (unintentional) /BF	11.94%	—	×0.900	10.75%
HR / BF /BF	3.73%	÷0.996	×1.100	4.12%

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 99).

Result: FIP 3.95 → 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).

2023 AAANorfolk Tides · 13 IPFIP 4.00 → 4.34 (+0.34)K% 27.3% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.860	23.45%
BB% (unintentional) /BF	12.12%	—	×0.900	10.91%
HR / BF /BF	3.03%	÷0.995	×1.100	3.35%

Result: FIP 4.00 → 4.34, 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 AAABuffalo Bisons · 41 IPFIP 2.29 → 2.65 (+0.36)K% 28.9% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.92%	—	×0.880	25.45%
BB% (unintentional) /BF	10.24%	—	×1.050	10.75%
HR / BF /BF	0.60%	÷1.081	×1.100	0.61%

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 116).

Result: FIP 2.29 → 2.65, 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 AANew Hampshire Fisher Cats · 32 IPFIP 3.10 → 4.08 (+0.98)K% 30.1% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.08%	—	×0.810	24.36%
BB% (unintentional) /BF	13.53%	—	×1.100	14.89%
HR / BF /BF	1.50%	÷0.860	×1.200	2.10%

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 72).

Result: FIP 3.10 → 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).

2019 AAABuffalo Bisons · 22 IPFIP 3.06 → 3.53 (+0.48)K% 31.3% → 27.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.31%	—	×0.880	27.56%
BB% (unintentional) /BF	16.16%	—	×1.050	16.97%
HR / BF /BF	1.01%	÷1.000	×1.100	1.11%

Result: FIP 3.06 → 3.53, 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+Dunedin Blue Jays · 51 IPFIP 4.75 → 5.76 (+1.02)K% 27.8% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.80%	—	×0.770	21.41%
BB% (unintentional) /BF	15.35%	—	×1.150	17.66%
HR / BF /BF	3.73%	÷1.147	×1.250	4.07%

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 129).

Result: FIP 4.75 → 5.76, 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 AAsheville Tourists · 54 IPFIP 2.39 → 3.15 (+0.76)K% 26.6% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.64%	—	×0.740	19.71%
BB% (unintentional) /BF	6.07%	—	×1.180	7.17%
HR / BF /BF	1.40%	÷1.243	×1.300	1.47%

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 149).

Result: FIP 2.39 → 3.15, 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 ROKGrand Junction Rockies · 48 IPFIP 4.74 → 6.45 (+1.71)K% 19.0% → 12.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.98%	—	×0.680	12.91%
BB% (unintentional) /BF	5.56%	—	×1.250	6.94%
HR / BF /BF	4.63%	÷1.000	×1.400	6.48%

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 4.74 → 6.45, 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
Bryan Baker (OGILVIE)	—	—	3.70	27.9%	7.3%	3.0%	—	4.23	26.3%	18.2%	110	+0.53	—	—	—
Akinori Otsuka R 2004 · 2.61 FIP	32	SU	2.61	27.9%	6.4%	1.9%	.251	2.78	20.3%	13.4%	155	+0.17	2.39	232	71
Jay Jackson R 2019 · 2.80 FIP	31	SU	2.80	32.4%	9.1%	2.3%	.272	3.59	29.4%	19.9%	41	+0.79	2.36	261	71
Chris Hatcher R 2017 · 4.31 FIP	32	SU	4.31	24.5%	7.4%	4.3%	.291	5.32	18.0%	8.4%	36	+1.01	2.51	246	70
Jose Veras R 2013 · 3.51 FIP	32	SU	3.51	23.6%	8.3%	2.5%	.234	4.28	21.9%	10.2%	65	+0.77	3.37	422	70
Jumbo Diaz R 2016 · 3.85 FIP	32	SU	3.85	22.3%	9.2%	2.7%	.247	3.28	23.0%	13.8%	141	-0.57	2.80	319	69
Spencer Patton R 2021 · 3.04 FIP	33	SU	3.04	27.9%	8.7%	2.2%	.305	4.97	21.2%	10.4%	88	+1.93	2.79	239	69
Kazuhiro Sasaki R 2000 · 3.93 FIP	32	SU	3.93	29.4%	9.8%	3.8%	.212	2.88	24.9%	19.3%	161	-1.05	2.76	223	69
Dale Thayer R 2013 · 3.62 FIP	32	SU	3.62	23.7%	7.4%	2.9%	.287	3.85	20.6%	15.0%	103	+0.23	2.75	239	69
Grant Balfour R 2010 · 2.59 FIP	32	SU	2.59	25.2%	6.8%	1.4%	.270	3.50	25.6%	16.7%	199	+0.91	2.04	533	66
George Kontos R 2017 · 3.71 FIP	32	SU	3.71	25.2%	6.5%	3.5%	.287	4.41	14.7%	8.6%	97	+0.70	2.56	421	66
Gregory Infante R 2018 · 4.07 FIP	31	SU	4.07	22.0%	4.6%	4.1%	.291	—	—	—	—	—	2.97	230	66
Jared Burton R 2013 · 3.20 FIP	32	SU	3.20	21.7%	6.0%	2.1%	.279	3.92	18.4%	10.0%	78	+0.72	3.09	367	66
Josh Fields R 2018 · 3.48 FIP	32	SU	3.48	21.4%	6.5%	2.5%	.224	7.56	18.9%	9.5%	25	+4.08	1.80	330	66
Sergio Santos R 2015 · 4.17 FIP	32	SU	4.17	24.7%	8.2%	3.9%	.283	—	—	—	—	—	1.36	178	66
Mark Serrano R 2017 · 3.56 FIP	31	SU	3.56	21.9%	6.4%	2.7%	.240	5.25	20.2%	12.3%	42	+1.69	3.16	120	65
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	65
Steve Delabar R 2015 · 3.74 FIP	32	SU	3.74	25.0%	9.9%	2.7%	.246	4.62	20.4%	4.8%	24	+0.88	2.43	229	65
Hunter Strickland R 2021 · 3.96 FIP	32	SU	3.96	24.0%	9.1%	3.1%	.247	4.38	19.6%	9.6%	147	+0.42	2.30	523	65
Ryan Brasier R 2020 · 2.97 FIP	32	SU	2.97	27.3%	9.1%	1.9%	.324	3.30	23.4%	17.1%	134	+0.33	2.31	426	65
Aaron Barrett R 2019 · 3.81 FIP	31	SU	3.81	23.0%	8.1%	3.0%	.246	4.56	19.9%	6.4%	38	+0.75	1.86	160	65

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	2.2	48	27.1%	8.4%	1.09	3.53
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Héctor Neris ('25)	3.1	57	29.4%	9.2%	1.19	3.47
Josh Fields ('18)	1.4	46	27.5%	8.0%	0.98	3.71
Héctor Rondón ('20)	2.2	54	24.2%	7.4%	1.03	3.49
Joe Hoerner ('63-'77, 8 WAR*)	2.8	51	23.2%*	7.9%*	1.21*	3.52*
Rob Murphy ('85-'95, 6 WAR*)	3.1	69	25.2%*	9.2%*	1.07*	3.94*