Nick Davila

P Seattle Mariners

Age 28 RHP 6'3" / 230 lbs MLB ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MANROOKIE

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	A+SEA	13	22	4.98	2.73	31.1%	3.3%	—	K 24.0% · BB 3.8% · FIP 3.51
2025	26	AASEA	39	51	3.55	3.34	18.3%	10.1%	—	K 14.9% · BB 11.1% · FIP 4.01
2026	27	MIX3 levels	40	47	3.86	3.51	14.6%	8.5%	0.6	K 10.9% · BB 10.9% · FIP 4.51
2027PROJ	28	MLBSEA	23	24	5.13	5.34	12.1%	11.9%	-0.2
2028PROJ79% MLB	29	MLBSEA	29	30	5.25	5.40	12.7%	11.9%	-0.3
2029PROJ84% MLB	30	MLBSEA	25	26	5.38	5.53	12.8%	12.0%	-0.3

Last 3 seasons WAR 0.6 · Next 3 projected WAR -0.8Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo54

xwOBA vs26

K%10

Career WAR0.0 WAR median (P10 -0.1 / P90 0.7, comp-based) · star 0% · didn't stick 96%

CompsAlex Caldera (age 29) · Jared Fernandez (age 29) · Fernando Villalobos (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 135126vR 118

ERA5.13

FIP5.34

K%12.1%

BB%11.9%

K-BB%0.2%

Proj IP33

Value2027 · WAR

Runs saved vs league avg · 33 IP

Grades · Statcast · Contract

Scouting Grades

STUF3535

CTRL4545

CMD3535

K†3030

Statcast Percentiles

FB Velo

p5494.8

Whiff%

p1015.8%

p1010.9%

xwOBA vs

p260.340

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)
2021	22	A MLE	Lakeland Flying Tigers	27	13	94	406	99	32	6	48%	3.5	18.0%	9.3%	8.7%	2.1%	3.54	3.88	—
2021	22	A RAW	Lakeland Flying Tigers	27	13	94	406	99	32	6	48%	3.5	24.4%	7.9%	16.5%	1.5%	3.54	2.84	—
2022	23	A MLE	Lakeland Flying Tigers	13	11	57	252	53	13	7	85%	4.4	15.6%	6.1%	9.5%	2.8%	3.65	4.11	—
2022	23	A RAW	Lakeland Flying Tigers	13	11	57	252	53	13	7	85%	4.4	21.0%	5.2%	15.9%	2.8%	3.65	3.52	—
2023	24	MIX MLE	3 levels	22	18	118	502	109	30	12	82%	5.3	16.9%	6.7%	10.2%	2.9%	4.51	4.11	—
2023	24	MIX RAW	3 levels	22	18	118	502	109	30	12	82%	5.3	21.7%	6.0%	15.7%	2.4%	4.51	3.34	—
2024	25	A+ MLE	Everett AquaSox	13	0	22	90	28	3	3	0%	1.7	24.0%	3.8%	20.1%	3.5%	4.98	3.51	—
2024	25	A+ MLE	Everett AquaSox	13	0	22	90	28	3	3	0%	1.7	24.0%	3.8%	20.1%	3.5%	4.98	3.51	—
2024	25	A+ RAW	Everett AquaSox	13	0	22	90	28	3	3	0%	1.7	31.1%	3.3%	27.8%	3.3%	4.98	2.73	—
2025	26	AA MLE	Arkansas Travelers	39	0	51	218	40	22	2	0%	1.3	14.9%	11.1%	3.8%	1.4%	3.55	4.01	—
2025	26	AA MLE	Arkansas Travelers	39	0	51	218	40	22	2	0%	1.3	14.9%	11.1%	3.8%	1.4%	3.55	4.01	—
2025	26	AA RAW	Arkansas Travelers	39	0	51	218	40	22	2	0%	1.3	18.3%	10.1%	8.3%	0.9%	3.55	3.34	—
2026	27	MIX MLE	3 levels	40	0	47	199	29	17	2	0%	1.2	10.9%	10.9%	0.0%	1.7%	3.86	4.51	+0.0
2026	27	MIX MLE	3 levels	40	0	47	199	29	17	2	0%	1.2	10.9%	10.9%	0.0%	1.7%	3.86	4.51	+0.0
2026	27	MIX RAW	3 levels	40	0	47	199	29	17	2	0%	1.2	14.6%	8.5%	6.0%	1.0%	3.86	3.51	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			24	0	27	119	13	13	2	0%	1.1	10.9%	10.9%	0.0%	1.7%	4.94	4.53	+0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SEA	23	0	24	101	12	12	3	0%	1.0	12.1%	11.9%	0.2%	2.5%	5.13	5.34	-0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SEA	36	0	38	160	20	19	4	0%	1.1	12.7%	11.9%	0.8%	2.7%	5.25	5.40	-0.4
2029	30	MLB MLE	SEA	29	0	31	130	17	16	4	0%	1.1	12.8%	12.0%	0.8%	2.9%	5.38	5.53	-0.3
2028	29	MLB CTX	SEA	29	0	30	127	16	15	3	0%	1.0	12.7%	11.9%	0.8%	2.7%	5.25	5.40	-0.3
2029	30	MLB CTX	SEA	25	0	26	110	14	13	3	0%	1.0	12.8%	12.0%	0.8%	2.9%	5.38	5.53	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		77	0	83	356	43	41	9	0%	1.1	12.1%	11.6%	0.5%	2.4%	5.19	4.88	-0.3
/ 200 IP	—	RAW		186	0	200	853	103	98	22	0%	1.1	12.1%	11.6%	0.5%	2.4%	5.19	4.88	-0.8
Career	—	MLE		154	42	387	1667	273	136	40	27%	2.5	16.4%	8.2%	8.2%	2.4%	3.97	4.05	-0.7
/ 200 IP	—	MLE		80	22	200	861	141	70	20	27%	2.5	16.4%	8.2%	8.2%	2.4%	3.97	4.05	-1.5

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.

2026 AAATacoma Rainiers · 10 IPFIP 2.82 → 2.90 (+0.07)K% 13.0% → 11.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.04%	—	×0.860	11.22%
BB% (unintentional) /BF	6.52%	—	×0.900	5.87%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 2.82 → 2.90, 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).

2026 AAArkansas Travelers · 9 IPFIP 0.99 → 1.50 (+0.51)K% 29.4% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.41%	—	×0.810	23.82%
BB% (unintentional) /BF	2.94%	—	×1.100	3.24%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 0.99 → 1.50, 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 AAArkansas Travelers · 51 IPFIP 3.33 → 4.01 (+0.67)K% 18.3% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.35%	—	×0.810	14.86%
BB% (unintentional) /BF	10.09%	—	×1.100	11.10%
HR / BF /BF	0.92%	÷0.800	×1.200	1.38%

Result: FIP 3.33 → 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).

2024 A+Everett AquaSox · 22 IPFIP 2.72 → 3.51 (+0.78)K% 31.1% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.11%	—	×0.770	23.96%
BB% (unintentional) /BF	3.33%	—	×1.150	3.83%
HR / BF /BF	3.33%	÷1.175	×1.250	3.55%

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 135).

Result: FIP 2.72 → 3.51, 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 A+Everett AquaSox · 81 IPFIP 3.71 → 4.63 (+0.92)K% 21.5% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.47%	—	×0.770	16.53%
BB% (unintentional) /BF	5.65%	—	×1.150	6.50%
HR / BF /BF	3.11%	÷1.012	×1.250	3.84%

Result: FIP 3.71 → 4.63, 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).

2023 AAATacoma Rainiers · 19 IPFIP 2.99 → 3.10 (+0.12)K% 20.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.860	17.20%
BB% (unintentional) /BF	6.67%	—	×0.900	6.00%
HR / BF /BF	1.33%	÷1.157	×1.100	1.27%

Result: FIP 2.99 → 3.10, 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 AModesto Nuts · 18 IPFIP 1.89 → 2.58 (+0.70)K% 24.7% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.66%	—	×0.740	18.25%
BB% (unintentional) /BF	6.85%	—	×1.180	8.08%
HR / BF /BF	0.00%	÷0.883	×1.300	0.00%

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 77).

Result: FIP 1.89 → 2.58, 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 ALakeland Flying Tigers · 57 IPFIP 3.50 → 4.11 (+0.60)K% 21.0% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.03%	—	×0.740	15.56%
BB% (unintentional) /BF	5.16%	—	×1.180	6.09%
HR / BF /BF	2.78%	÷1.279	×1.300	2.82%

Result: FIP 3.50 → 4.11, 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
Nick Davila (OGILVIE)	—	—	5.34	12.1%	11.9%	2.5%	—	5.46	12.7%	0.8%	69	+0.12	—	—	—
Alex Caldera R 2015 · 5.57 FIP	29	SW	5.57	10.4%	13.1%	3.1%	.333	4.54	11.9%	0.8%	84	-1.03	4.54	120	87
Jared Fernandez R 2001 · 4.66 FIP	29	SW	4.66	8.8%	10.5%	1.8%	.267	3.95	14.0%	5.6%	89	-0.71	3.57	101	83
Fernando Villalobos R 2015 · 5.33 FIP	30	SU	5.33	8.3%	13.1%	2.3%	.365	4.36	11.4%	3.1%	109	-0.97	4.00	152	78
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	76
Jorge Campillo R 2007 · 4.84 FIP	28	SU	4.84	14.3%	9.5%	3.2%	.348	3.93	16.3%	10.8%	159	-0.91	3.93	172	76
Dustin Antolin R 2017 · 4.35 FIP	27	SW	4.35	16.2%	14.4%	1.4%	.368	—	—	—	—	—	2.95	159	76
Donovan Hand R 2013 · 4.72 FIP	27	SW	4.72	12.9%	7.0%	3.3%	.279	4.30	11.1%	6.8%	97	-0.42	4.30	305	75
Brandon Puffer R 2004 · 5.23 FIP	28	SU	5.23	13.5%	11.2%	3.4%	.328	—	—	—	—	—	3.55	108	74
Tony Fiore R 2000 · 5.61 FIP	28	SU	5.61	10.8%	9.5%	4.0%	.321	4.76	14.3%	3.5%	127	-0.85	4.60	142	74
Kyle McMyne R 2017 · 4.84 FIP	27	SU	4.84	12.5%	12.8%	2.1%	.330	—	—	—	—	—	3.93	181	74
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	74
Oscar Verdugo R 2017 · 6.31 FIP	27	SU	6.31	10.3%	13.8%	4.2%	.277	—	—	—	—	—	5.01	144	74
Rodolfo Aguirre R 2015 · 4.29 FIP	30	SW	4.29	12.4%	6.9%	2.5%	.288	4.81	11.4%	1.3%	125	+0.52	3.39	212	74
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	74
Raymar Navarro R 2017 · 4.29 FIP	26	SW	4.29	11.8%	10.8%	1.5%	.333	—	—	—	—	—	4.29	108	74
Grant Black R 2022 · 5.20 FIP	28	SU	5.20	14.0%	11.0%	3.5%	.250	5.49	15.9%	4.6%	79	+0.29	4.46	215	73
Benjamin Sandoval R 2015 · 4.66 FIP	28	SU	4.66	8.6%	7.8%	2.4%	.253	5.16	5.8%	-5.7%	62	+0.50	4.66	146	73
Fernando Cruz R 2015 · 5.29 FIP	25	SU	5.29	15.6%	12.2%	3.6%	.284	—	—	—	—	—	2.50	371	73
Mark Peterson R 2017 · 4.78 FIP	26	SU	4.78	13.7%	11.9%	2.4%	.349	—	—	—	—	—	4.65	185	73
Hunter Adkins R 2017 · 4.82 FIP	26	SW	4.82	11.8%	11.3%	2.3%	.285	—	—	—	—	—	4.64	160	72

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	0.7	33	12.2%	11.7%	0.96	5.18
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Tom Martin ('07)	1.6	53	15.8%	10.1%	1.02	4.92
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*
Steve Frey ('89-'96, 0 WAR*)	1.5	38	14.9%*	11.2%*	1.12*	4.00*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*