Dawil Almonte

P Fayetteville Woodpeckers

Age 25 RHP 5'9" / 187 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	20	ROKDSL HOU Blue	13	5	40	2.68	2.46	25.6%	6.2%	—	K 17.4% · BB 7.8% · FIP 3.59
2024	22	MIX2 levels	29	0	44	4.09	4.24	23.4%	8.2%	—	K 17.9% · BB 10.7% · FIP 4.88
2025	23	MIX2 levels	33	0	58	3.55	3.63	16.9%	10.2%	—	K 12.6% · BB 11.9% · FIP 4.31
2026	24	No MLB games played
2027PROJ	25	MLBHOU	—	—	0	5.71	5.71	12.8%	13.6%	—
2028PROJ43% MLB	26	MLBHOU	20	0	21	5.52	5.48	14.8%	13.1%	-0.2
2029PROJ63% MLB	27	MLBHOU	25	0	26	5.43	5.43	15.5%	12.9%	-0.3

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff30Control40Command30

CompsJeff Soptic (age 25) · Juan Paniagua (age 25) · Jarod Wright (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 142133vR 125

ERA5.71

FIP5.71

K%12.8%

BB%13.6%

K-BB%-0.8%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL4040

CMD3030

K†3030

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)
2022	20	ROK MLE	DSL HOU Blue	13	5	40	160	41	10	2	38%	3.1	17.4%	7.8%	9.6%	1.8%	2.68	3.59	—
2022	20	ROK RAW	DSL HOU Blue	13	5	40	160	41	10	2	38%	3.1	25.6%	6.2%	19.4%	1.2%	2.68	2.46	—
2024	22	MIX MLE	2 levels	29	0	44	184	43	15	7	0%	1.5	17.9%	10.7%	7.2%	3.5%	4.09	4.88	—
2024	22	MIX MLE	2 levels	29	0	44	184	43	15	7	0%	1.5	17.9%	10.7%	7.2%	3.5%	4.09	4.88	—
2024	22	MIX RAW	2 levels	29	0	44	184	43	15	7	0%	1.5	23.4%	8.2%	15.2%	3.8%	4.09	4.24	—
2025	23	MIX MLE	2 levels	33	0	58	255	43	26	3	0%	1.8	12.6%	11.9%	0.7%	1.4%	3.55	4.31	—
2025	23	MIX MLE	2 levels	33	0	58	255	43	26	3	0%	1.8	12.6%	11.9%	0.7%	1.4%	3.55	4.31	—
2025	23	MIX RAW	2 levels	33	0	58	255	43	26	3	0%	1.8	16.9%	10.2%	6.7%	1.2%	3.55	3.63	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	HOU	—	—	0	—	—	—	—	—	—	12.8%	13.6%	-0.8%	2.9%	5.71	5.71	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	HOU	47	0	50	210	31	28	6	0%	1.1	14.8%	13.1%	1.7%	2.9%	5.52	5.48	-0.5
2029	27	MLB MLE	HOU	40	0	42	178	27	23	5	0%	1.1	15.5%	12.9%	2.5%	3.0%	5.43	5.43	-0.4
2030	28	MLB MLE	HOU	37	0	38	162	26	21	5	0%	1.0	15.7%	12.9%	2.8%	3.1%	5.43	5.46	-0.4
2031	29	MLB MLE	HOU	34	0	36	150	24	20	5	0%	1.0	15.7%	13.0%	2.7%	3.2%	5.50	5.56	-0.4
2028	26	MLB CTX	HOU	20	0	21	89	13	12	3	0%	1.1	14.8%	13.1%	1.7%	2.9%	5.52	5.48	-0.2
2029	27	MLB CTX	HOU	25	0	26	110	17	14	3	0%	1.0	15.5%	12.9%	2.5%	3.0%	5.43	5.43	-0.3
2030	28	MLB CTX	HOU	28	0	29	122	19	16	4	0%	1.0	15.7%	12.9%	2.8%	3.1%	5.43	5.46	-0.3
2031	29	MLB CTX	HOU	28	0	29	122	19	16	4	0%	1.0	15.7%	13.0%	2.7%	3.2%	5.50	5.56	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		100	0	105	445	69	58	14	0%	1.1	15.5%	13.0%	2.5%	3.0%	5.47	5.11	-0.7
/ 200 IP	—	RAW		190	0	200	844	131	110	27	0%	1.1	15.5%	13.0%	2.5%	3.0%	5.47	5.11	-1.3
Career	—	MLE		75	5	143	599	93	63	13	7%	1.9	15.5%	10.5%	5.1%	2.1%	3.47	4.29	-1.8
/ 200 IP	—	MLE		105	7	200	840	130	88	18	7%	1.9	15.5%	10.5%	5.1%	2.1%	3.47	4.29	-2.1

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.

2025 AFayetteville Woodpeckers · 46 IPFIP 3.35 → 4.13 (+0.78)K% 17.8% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.84%	—	×0.740	13.20%
BB% (unintentional) /BF	9.19%	—	×1.180	10.84%
HR / BF /BF	1.08%	÷1.005	×1.300	1.40%

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 101).

Result: FIP 3.35 → 4.13, 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).

2025 A+Asheville Tourists · 13 IPFIP 4.31 → 4.80 (+0.49)K% 14.3% → 11.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.29%	—	×0.770	11.00%
BB% (unintentional) /BF	12.86%	—	×1.150	14.79%
HR / BF /BF	1.43%	÷1.297	×1.250	1.38%

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 159).

Result: FIP 4.31 → 4.80, 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 AFayetteville Woodpeckers · 39 IPFIP 3.87 → 4.88 (+1.01)K% 24.2% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.740	17.94%
BB% (unintentional) /BF	9.09%	—	×1.180	10.73%
HR / BF /BF	3.03%	÷1.118	×1.300	3.52%

Result: FIP 3.87 → 4.88, 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 ROKDSL HOU Blue · 40 IPFIP 2.41 → 3.59 (+1.18)K% 25.6% → 17.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.62%	—	×0.680	17.42%
BB% (unintentional) /BF	6.25%	—	×1.250	7.81%
HR / BF /BF	1.25%	÷0.989	×1.400	1.77%

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 98).

Result: FIP 2.41 → 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).

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
Dawil Almonte (OGILVIE)	—	—	5.71	12.8%	13.6%	2.9%	—	5.46	15.3%	2.3%	130	-0.25	—	—	—
Jeff Soptic R 2016 · 5.52 FIP	25	SU	5.52	13.6%	15.3%	3.0%	.326	—	—	—	—	—	5.30	124	87
Juan Paniagua R 2015 · 4.69 FIP	25	SU	4.69	15.7%	11.9%	2.6%	.262	4.63	16.2%	1.8%	93	-0.06	4.57	151	86
Jarod Wright R 2022 · 5.73 FIP	25	SU	5.73	12.7%	13.2%	3.7%	.282	4.46	13.2%	3.8%	53	-1.27	4.46	170	85
Conner O'Neil R 2019 · 5.78 FIP	24	SU	5.78	12.8%	13.6%	3.7%	.340	6.92	16.4%	4.1%	26	+1.14	2.89	115	85
Julian Arballo R 2015 · 5.13 FIP	27	SU	5.13	15.1%	13.8%	2.8%	.335	4.46	12.6%	0.6%	116	-0.67	4.45	214	85
Clate Schmidt R 2019 · 5.66 FIP	25	SU	5.66	13.5%	13.9%	3.5%	.290	—	—	—	—	—	3.51	160	85
Kender Villegas R 2017 · 4.70 FIP	24	SU	4.70	13.3%	13.3%	1.9%	.269	—	—	—	—	—	3.26	131	85
Ian Villers R 2024 · 4.55 FIP	23	SU	4.55	13.2%	11.9%	1.9%	.311	4.23	15.6%	5.2%	59	-0.32	4.23	107	85
Justin Camp R 2018 · 4.56 FIP	25	SU	4.56	13.2%	11.9%	1.9%	.296	—	—	—	—	—	2.59	140	84
Tyler Burch R 2023 · 4.92 FIP	25	SU	4.92	15.0%	12.6%	2.7%	.285	—	—	—	—	—	4.56	119	84
Stephen Johnson R 2016 · 5.15 FIP	25	SU	5.15	16.7%	12.7%	3.4%	.268	—	—	—	—	—	3.12	141	84
Cole Hillier R 2024 · 4.64 FIP	23	SU	4.64	16.9%	14.7%	2.0%	.297	4.45	18.1%	4.5%	111	-0.19	3.80	169	83
Zach Nuding R 2015 · 4.76 FIP	25	SU	4.76	12.5%	10.5%	2.5%	.236	5.03	12.6%	3.3%	106	+0.27	4.76	146	83
Rob Huber R 2016 · 4.73 FIP	24	SU	4.73	15.7%	14.7%	2.0%	.333	—	—	—	—	—	3.90	117	83
Rafael Dolis R 2012 · 5.19 FIP	24	SU	5.19	13.9%	12.7%	3.0%	.287	4.02	15.8%	1.5%	66	-1.17	2.80	200	82
Mitchell Osnowitz R 2015 · 4.54 FIP	24	SU	4.54	13.2%	13.8%	1.5%	.330	5.30	16.5%	-2.2%	23	+0.76	4.54	132	82
El'Hajj Muhammad R 2016 · 4.58 FIP	25	SU	4.58	13.6%	10.0%	2.5%	.285	5.01	7.1%	-2.5%	11	+0.43	4.58	113	82
Reece Karalus R 2018 · 4.73 FIP	24	SU	4.73	15.4%	11.9%	2.6%	.299	—	—	—	—	—	4.73	149	82
Dillon McNamara R 2017 · 5.01 FIP	25	SW	5.01	13.3%	11.1%	3.0%	.229	3.00	21.2%	12.3%	69	-2.01	1.73	244	82
Scott Griggs R 2016 · 5.11 FIP	25	SU	5.11	11.3%	13.2%	2.4%	.278	4.19	19.7%	8.0%	112	-0.92	3.06	176	82

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	1.2	47	14.6%	13.2%	1.15	5.54
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
C.J. Nitkowski ('05)	2.4	68	15.8%	11.9%	1.07	5.37
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*