Camilo Doval

P San Francisco Giants

Age 30 RHP 6'2" / 205 lbs MLB peak 0.3 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	67	65	4.73	3.24	29.2%	13.1%	1.0	K 28.8% · BB 13.7% · FIP 3.49
2025	28	MLBNYY	69	65	3.58	3.25	25.9%	12.2%	1.0
2026	29	MLBSF	66	61	4.15	3.96	24.2%	11.4%	0.4
2027PROJ	30	MLBSF	51	54	4.16	4.12	27.0%	11.9%	0.3
2028PROJ95% MLB	31	MLBSF	36	38	4.27	4.35	26.2%	12.2%	0.1
2029PROJ95% MLB	32	MLBSF	26	27	4.47	4.60	25.4%	12.6%	-0.0

Last 3 seasons WAR 2.4 · Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

xwOBA vs63

K%61

Form3.43 ERA (proj 4.16) · K 28.4% (proj 27.0%) · BB 15.8% (proj 11.9%) ▼ last 90d · 21 IP through Oct 27

CompsRyne Stanek (age 30) · Fernando Rodriguez Jr. (age 31) · Jose Veras (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10698vR 90

ERA4.16

FIP4.12

K%27.0%

BB%11.9%

K-BB%15.1%

Proj IP54

Value2027 · WAR

Runs saved vs league avg · 54 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL2525

CMD5050

K†6060

Statcast Percentiles

FB Velo

p9098.2

Whiff%

p7028.5%

p6124.2%

xwOBA vs

p630.299

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	19	ROK MLE	DSL Giants	12	0	22	87	24	10	0	0%	1.8	18.8%	14.4%	4.4%	0.0%	1.66	3.34	—
2016	19	ROK RAW	DSL Giants	12	0	22	87	24	10	0	0%	1.8	27.6%	11.5%	16.1%	0.0%	1.66	2.27	—
2017	20	ROK MLE	AZL Giants	17	0	32	133	51	13	0	0%	1.9	26.1%	12.2%	13.9%	0.0%	3.90	2.45	—
2017	20	ROK RAW	AZL Giants	17	0	32	133	51	13	0	0%	1.9	38.3%	9.8%	28.6%	0.0%	3.90	1.15	—
2018	21	A MLE	Augusta GreenJackets	44	0	53	228	78	27	2	0%	1.2	25.3%	14.0%	11.3%	1.1%	3.06	3.32	—
2018	21	A RAW	Augusta GreenJackets	44	0	53	228	78	27	2	0%	1.2	34.2%	11.8%	22.4%	0.9%	3.06	2.18	—
2019	22	A+ MLE	San Jose Giants	45	0	56	244	80	34	2	0%	1.3	25.2%	16.0%	9.2%	1.1%	3.83	3.59	—
2019	22	A+ RAW	San Jose Giants	45	0	56	244	80	34	2	0%	1.3	32.8%	13.9%	18.9%	0.8%	3.83	2.53	—
2021	24	MIX MLE	2 levels	57	0	58	253	81	31	7	0%	1.0	29.9%	12.7%	17.2%	3.0%	4.06	3.84	+0.5
2021	24	MIX RAW	2 levels	57	0	58	253	81	31	7	0%	1.0	32.0%	12.3%	19.8%	2.8%	4.06	3.48	+0.7
2022	25	MLB MLE	San Francisco Giants	68	0	68	286	80	28	4	0%	1.0	28.0%	9.8%	18.2%	1.5%	2.53	2.81	+1.4
2022	25	MLB RAW	San Francisco Giants	68	0	68	286	80	28	4	0%	1.0	28.0%	9.8%	18.2%	1.4%	2.53	2.75	+1.5
2023	26	MLB MLE	San Francisco Giants	69	0	68	281	87	20	3	0%	1.0	31.0%	7.1%	23.8%	1.2%	2.93	2.02	+2.1
2023	26	MLB RAW	San Francisco Giants	69	0	68	281	87	20	3	0%	1.0	31.0%	7.1%	23.8%	1.1%	2.93	1.99	+2.1
2024	27	MIX MLE	2 levels	67	0	65	291	85	38	5	0%	1.0	28.8%	13.7%	15.1%	2.0%	4.73	3.49	+0.8
2024	27	MIX MLE	2 levels	67	0	65	291	85	38	5	0%	1.0	28.8%	13.7%	15.1%	2.0%	4.73	3.49	+0.8
2024	27	MIX RAW	2 levels	67	0	65	291	85	38	5	0%	1.0	29.2%	13.1%	16.2%	1.7%	4.73	3.24	+1.0
2025	28	MLB MLE	New York Yankees	69	0	65	278	72	34	4	0%	0.9	25.9%	12.2%	13.7%	1.3%	3.58	3.20	+1.0
2025	28	MLB MLE	New York Yankees	69	0	65	278	72	34	4	0%	0.9	25.9%	12.2%	13.7%	1.3%	3.58	3.20	+1.0
2025	28	MLB RAW	New York Yankees	69	0	65	278	72	34	4	0%	0.9	25.9%	12.2%	13.7%	1.4%	3.58	3.25	+1.0
2026	29	MLB MLE	San Francisco Giants	66	0	61	273	66	31	7	0%	0.9	24.2%	11.4%	12.8%	2.8%	4.15	4.02	+0.4
2026	29	MLB MLE	San Francisco Giants	66	0	61	273	66	31	7	0%	0.9	24.2%	11.4%	12.8%	2.8%	4.15	4.02	+0.4
2026	29	MLB RAW	San Francisco Giants	66	0	61	273	66	31	7	0%	0.9	24.2%	11.4%	12.8%	2.6%	4.15	3.96	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			363	0	347	1498	420	157	27	0%	1.0	28.0%	10.5%	17.6%	1.8%	3.52	3.05	+6.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	SF	51	0	54	228	61	27	6	0%	1.1	27.0%	11.9%	15.1%	2.6%	4.16	4.12	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	SF	38	0	40	168	44	21	5	0%	1.1	26.2%	12.2%	14.0%	2.8%	4.27	4.35	+0.1
2029	32	MLB MLE	SF	27	0	29	121	31	15	4	0%	1.1	25.4%	12.6%	12.8%	3.0%	4.47	4.60	-0.0
2028	31	MLB CTX	SF	36	0	38	160	42	20	4	0%	1.1	26.2%	12.2%	14.0%	2.8%	4.27	4.35	+0.1
2029	32	MLB CTX	SF	26	0	27	114	29	14	3	0%	1.0	25.4%	12.6%	12.8%	3.0%	4.47	4.60	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		425	0	413	1773	491	191	35	0%	1.0	27.7%	10.8%	16.9%	2.0%	3.66	3.21	+6.6
/ 200 IP	—	RAW		206	0	200	860	238	93	17	0%	1.0	27.7%	10.8%	16.9%	2.0%	3.66	3.21	+3.2
Career	—	MLE		514	0	547	2354	635	285	37	0%	1.1	27.0%	12.1%	14.9%	1.6%	3.54	3.23	+6.3
/ 200 IP	—	MLE		188	0	200	861	232	104	14	0%	1.1	27.0%	12.1%	14.9%	1.6%	3.54	3.23	+3.0

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.

2024 AAASacramento River Cats · 6 IPFIP 0.78 → 1.13 (+0.35)K% 35.0% → 30.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.00%	—	×0.860	30.10%
BB% (unintentional) /BF	5.00%	—	×0.900	4.50%
HR / BF /BF	0.00%	÷1.010	×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 102).

Result: FIP 0.78 → 1.13, 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 AAASacramento River Cats · 31 IPFIP 3.77 → 4.31 (+0.54)K% 30.6% → 26.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.56%	—	×0.880	26.89%
BB% (unintentional) /BF	16.67%	—	×1.050	17.50%
HR / BF /BF	2.08%	÷0.995	×1.100	2.30%

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 99).

Result: FIP 3.77 → 4.31, 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).

2019 A+San Jose Giants · 56 IPFIP 2.55 → 3.59 (+1.05)K% 32.8% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.79%	—	×0.770	25.25%
BB% (unintentional) /BF	13.93%	—	×1.150	16.02%
HR / BF /BF	0.82%	÷0.947	×1.250	1.08%

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 89).

Result: FIP 2.55 → 3.59, 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 AAugusta GreenJackets · 53 IPFIP 2.19 → 3.32 (+1.13)K% 34.2% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.21%	—	×0.740	25.32%
BB% (unintentional) /BF	11.84%	—	×1.180	13.97%
HR / BF /BF	0.88%	÷1.057	×1.300	1.08%

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 111).

Result: FIP 2.19 → 3.32, 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 ROKAZL Giants · 32 IPFIP 1.10 → 2.45 (+1.35)K% 38.3% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.35%	—	×0.680	26.08%
BB% (unintentional) /BF	9.77%	—	×1.250	12.22%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 1.10 → 2.45, 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).

2016 ROKDSL Giants · 22 IPFIP 2.23 → 3.34 (+1.11)K% 27.6% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.59%	—	×0.680	18.76%
BB% (unintentional) /BF	11.49%	—	×1.250	14.37%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 2.23 → 3.34, 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).

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
Camilo Doval (OGILVIE)	—	—	4.12	27.0%	11.9%	2.6%	—	4.45	25.9%	13.5%	69	+0.33	—	—	—
Ryne Stanek R 2021 · 3.73 FIP	30	SU	3.73	28.6%	11.7%	2.8%	.230	3.70	26.5%	15.7%	161	-0.03	2.96	771	72
Fernando Rodriguez Jr. R 2015 · 3.34 FIP	31	SU	3.34	26.5%	9.6%	2.3%	.241	3.89	23.3%	13.2%	105	+0.55	3.34	335	71
Jose Veras R 2011 · 3.37 FIP	30	SU	3.37	25.9%	10.2%	2.1%	.254	3.67	24.9%	13.6%	176	+0.30	3.37	422	70
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	70
Yennier Cano R 2024 · 3.40 FIP	30	SU	3.40	26.1%	9.2%	2.4%	.310	3.30	21.6%	13.7%	108	-0.10	2.43	381	69
AJ Ramos R 2017 · 3.86 FIP	30	SU	3.86	27.9%	12.8%	2.7%	.288	5.02	25.0%	8.0%	20	+1.16	2.55	410	69
Tom Wilhelmsen R 2014 · 3.45 FIP	30	SU	3.45	22.7%	9.5%	1.9%	.196	4.64	17.5%	7.8%	148	+1.19	2.72	398	69
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	69
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	68
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	68
Gregory Infante R 2017 · 2.97 FIP	30	SU	2.97	22.8%	8.2%	1.4%	.251	4.07	22.0%	17.4%	50	+1.10	2.97	230	68
Ryan Tepera R 2018 · 3.90 FIP	30	SU	3.90	25.9%	8.7%	3.4%	.282	3.20	28.4%	19.9%	104	-0.70	2.35	445	68
Brad Lidge R 2007 · 3.38 FIP	30	SU	3.38	30.7%	9.1%	3.1%	.274	3.39	26.9%	16.3%	174	+0.01	1.56	595	68
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	68
Joel Hanrahan R 2012 · 4.54 FIP	30	SU	4.54	26.4%	14.2%	3.4%	.224	—	—	—	—	—	2.08	397	68
Chad Fox R 2001 · 3.17 FIP	30	SU	3.17	27.9%	10.1%	2.1%	.221	3.70	23.2%	9.6%	43	+0.53	2.82	194	68
Danny Farquhar R 2017 · 3.62 FIP	30	SU	3.62	22.3%	11.0%	1.8%	.247	—	—	—	—	—	1.67	351	68
Troy Percival R 2000 · 4.46 FIP	30	SU	4.46	22.2%	11.8%	3.2%	.252	3.15	28.2%	18.8%	163	-1.31	2.15	709	68
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	67
Fernando Rodney R 2007 · 3.48 FIP	30	SU	3.48	24.2%	9.4%	2.2%	.287	3.90	19.7%	8.1%	184	+0.42	1.85	933	67

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	2.4	52	27.6%	11.7%	0.79	3.72
B.J. Ryan ('09)	2.7	54	27.5%	11.6%	0.70	3.37
Michael Wuertz ('11)	2.1	52	25.3%	11.3%	0.96	3.71
Paul Shuey ('07)	2.6	59	24.1%	12.0%	0.73	3.87
Rod Scurry ('80-'88, 5 WAR*)	2.3	58	29.6%*	13.6%*	0.91*	3.67*
Randy Myers ('85-'98, 16 WAR*)	4.4	74	29.4%*	10.4%*	0.92*	3.47*
Tippy Martinez ('74-'88, 9 WAR*)	4.2	76	27.7%*	12.0%*	0.77*	3.82*