Danny Watson

P Scranton/Wilkes-Barre RailRiders

Age 26 RHP 6'7" / 230 lbs AAA peak 0.1 · 2027

Overview

AAAPROSPECT

ETA2028MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	24	AANYY	43	0	57	4.74	2.89	24.3%	3.4%	—	K 19.6% · BB 3.7% · FIP 3.55
2026	25	AAAScranton/Wilk…	43	2	52	4.99	3.65	26.0%	10.1%	—	K 22.4% · BB 9.1% · FIP 3.96
2027PROJ	26	MLBNYY	7	0	7	4.09	4.09	20.7%	5.7%	0.0
2028PROJ43% MLB	27	MLBNYY	24	0	25	4.14	4.15	21.0%	6.1%	0.1
2029PROJ63% MLB	28	MLBNYY	31	0	33	4.21	4.25	21.0%	6.5%	0.1

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control70Command60

Career WAR0.0 WAR median (P10 -0.3 / P90 1.6, comp-based) · star 0% · didn't stick 92%

CompsMike Adams (age 26) · Shawn Camp (age 28) · Ryan Garton (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 111103vR 95

ERA4.09

FIP4.09

K%20.7%

BB%5.7%

K-BB%15.0%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL7070

CMD6060

K†5050

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	20	A MLE	Tampa Tarpons	3	0	3	16	2	4	0	0%	0.9	12.5%	25.0%	-12.5%	0.0%	16.88	5.21	—
2021	20	A RAW	Tampa Tarpons	3	0	3	16	2	4	0	0%	0.9	12.5%	25.0%	-12.5%	0.0%	16.88	6.10	—
2022	21	A MLE	Tampa Tarpons	38	0	58	264	66	35	3	0%	1.5	18.5%	15.6%	2.9%	1.4%	4.01	4.31	—
2022	21	A RAW	Tampa Tarpons	38	0	58	264	66	35	3	0%	1.5	25.0%	13.3%	11.7%	1.1%	4.01	3.31	—
2023	22	MIX MLE	2 levels	45	0	63	251	82	25	6	0%	1.4	25.8%	11.1%	14.7%	2.8%	1.58	3.87	—
2023	22	MIX RAW	2 levels	45	0	63	251	82	25	6	0%	1.4	32.7%	10.0%	22.7%	2.4%	1.58	2.92	—
2024	23	AA MLE	Somerset Patriots	32	0	37	160	26	13	5	0%	1.2	13.2%	8.9%	4.2%	3.7%	5.06	5.12	—
2024	23	AA MLE	Somerset Patriots	32	0	37	160	26	13	5	0%	1.2	13.2%	8.9%	4.2%	3.7%	5.06	5.12	—
2024	23	AA RAW	Somerset Patriots	32	0	37	160	26	13	5	0%	1.2	16.2%	8.1%	8.1%	3.1%	5.06	4.49	—
2025	24	AA MLE	Somerset Patriots	43	0	57	235	57	8	6	0%	1.3	19.6%	3.7%	15.9%	3.0%	4.74	3.55	—
2025	24	AA MLE	Somerset Patriots	43	0	57	235	57	8	6	0%	1.3	19.6%	3.7%	15.9%	3.0%	4.74	3.55	—
2025	24	AA RAW	Somerset Patriots	43	0	57	235	57	8	6	0%	1.3	24.3%	3.4%	20.9%	2.6%	4.74	2.89	—
2026	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	43	2	52	227	59	23	6	5%	1.2	22.4%	9.1%	13.2%	2.9%	4.99	3.96	—
2026	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	43	2	52	227	59	23	6	5%	1.2	22.4%	9.1%	13.2%	2.9%	4.99	3.96	—
2026	25	AAA RAW	Scranton/Wilkes-Barre RailRiders	43	2	52	227	59	23	6	5%	1.2	26.0%	10.1%	15.9%	2.6%	4.99	3.65	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	NYY	7	0	7	30	6	2	1	0%	1.0	20.7%	5.7%	15.0%	3.0%	4.09	4.09	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	NYY	56	0	59	248	52	15	8	0%	1.1	21.0%	6.1%	14.8%	3.0%	4.14	4.15	+0.3
2029	28	MLB MLE	NYY	50	0	53	222	47	14	7	0%	1.1	21.0%	6.5%	14.5%	3.1%	4.21	4.25	+0.2
2030	29	MLB MLE	NYY	45	0	48	201	42	14	7	0%	1.1	20.9%	6.9%	14.0%	3.3%	4.32	4.38	+0.1
2028	27	MLB CTX	NYY	24	0	25	106	22	6	3	0%	1.0	21.0%	6.1%	14.8%	3.0%	4.14	4.15	+0.1
2029	28	MLB CTX	NYY	31	0	33	139	29	9	4	0%	1.1	21.0%	6.5%	14.5%	3.1%	4.21	4.25	+0.1
2030	29	MLB CTX	NYY	33	0	35	148	31	10	5	0%	1.1	20.9%	6.9%	14.0%	3.3%	4.32	4.38	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		88	0	93	391	82	26	12	0%	1.1	21.0%	6.5%	14.4%	3.2%	4.23	3.89	+0.7
/ 200 IP	—	RAW		190	0	200	844	177	56	26	0%	1.1	21.0%	6.5%	14.4%	3.2%	4.23	3.89	+1.6
Career	—	MLE		204	2	270	1153	234	117	30	1%	1.3	20.3%	10.2%	10.1%	2.6%	4.06	4.12	+0.6
/ 200 IP	—	MLE		151	1	200	853	173	87	22	1%	1.3	20.3%	10.2%	10.1%	2.6%	4.06	4.12	+0.7

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 AAAScranton/Wilkes-Barre RailRiders · 52 IPFIP 3.64 → 3.96 (+0.32)K% 26.0% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.99%	—	×0.860	22.35%
BB% (unintentional) /BF	10.13%	—	×0.900	9.12%
HR / BF /BF	2.64%	÷1.000	×1.100	2.91%

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 3.64 → 3.96, 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 AASomerset Patriots · 57 IPFIP 2.88 → 3.55 (+0.66)K% 24.3% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.26%	—	×0.810	19.65%
BB% (unintentional) /BF	3.40%	—	×1.100	3.74%
HR / BF /BF	2.55%	÷1.030	×1.200	2.97%

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 106).

Result: FIP 2.88 → 3.55, 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 AASomerset Patriots · 37 IPFIP 4.47 → 5.12 (+0.65)K% 16.2% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.25%	—	×0.810	13.16%
BB% (unintentional) /BF	8.12%	—	×1.100	8.94%
HR / BF /BF	3.12%	÷1.027	×1.200	3.65%

Result: FIP 4.47 → 5.12, 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 AASomerset Patriots · 38 IPFIP 3.85 → 4.74 (+0.89)K% 28.5% → 23.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.48%	—	×0.810	23.07%
BB% (unintentional) /BF	10.60%	—	×1.100	11.66%
HR / BF /BF	3.31%	÷1.033	×1.200	3.85%

Result: FIP 3.85 → 4.74, 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+Hudson Valley Renegades · 24 IPFIP 1.50 → 2.56 (+1.06)K% 39.0% → 30.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.00%	—	×0.770	30.03%
BB% (unintentional) /BF	9.00%	—	×1.150	10.35%
HR / BF /BF	1.00%	÷1.006	×1.250	1.24%

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 101).

Result: FIP 1.50 → 2.56, 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 ATampa Tarpons · 58 IPFIP 3.29 → 4.31 (+1.02)K% 25.0% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.740	18.50%
BB% (unintentional) /BF	13.26%	—	×1.180	15.64%
HR / BF /BF	1.14%	÷1.026	×1.300	1.44%

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 105).

Result: FIP 3.29 → 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).

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
Danny Watson (OGILVIE)	—	—	4.09	20.7%	5.7%	3.0%	—	4.25	21.0%	14.5%	159	+0.16	—	—	—
Mike Adams R 2004 · 3.53 FIP	26	SU	3.53	17.3%	5.3%	2.2%	.266	4.83	23.0%	8.2%	13	+1.30	1.36	405	87
Shawn Camp R 2004 · 4.18 FIP	28	SU	4.18	17.8%	5.2%	3.5%	.305	3.88	15.5%	10.5%	164	-0.30	2.79	589	87
Ryan Garton R 2016 · 3.14 FIP	26	SU	3.14	21.8%	6.3%	2.0%	.325	3.97	24.1%	12.0%	175	+0.83	3.14	307	87
John Brebbia R 2016 · 4.11 FIP	26	SU	4.11	18.6%	6.6%	3.2%	.346	3.20	27.6%	21.4%	215	-0.91	2.89	576	86
Shay Schanaman R 2024 · 4.34 FIP	24	SU	4.34	21.0%	7.6%	3.7%	.292	6.05	16.4%	2.8%	90	+1.71	4.34	148	86
Santiago Casilla R 2007 · 3.58 FIP	27	SU	3.58	23.7%	7.8%	2.7%	.257	3.60	19.8%	10.7%	154	+0.02	2.76	647	85
Andrew Robinson R 2015 · 3.77 FIP	27	SU	3.77	17.6%	6.3%	2.5%	.246	3.64	22.7%	14.4%	97	-0.13	3.19	160	85
Kaleb Bowman R 2023 · 3.88 FIP	26	SU	3.88	22.0%	7.5%	3.1%	.333	4.65	17.5%	6.2%	170	+0.77	3.88	203	85
Ryan Kelly R 2015 · 3.52 FIP	27	SU	3.52	20.3%	7.5%	2.1%	.241	3.21	20.8%	14.2%	43	-0.31	2.49	131	85
Joe Broussard R 2017 · 3.83 FIP	26	SU	3.83	23.5%	7.9%	3.1%	.316	3.72	21.1%	12.0%	95	-0.11	2.62	304	84
Esmerling De La Rosa R 2017 · 3.40 FIP	26	SU	3.40	20.5%	7.2%	2.0%	.313	4.86	14.1%	5.8%	66	+1.46	2.89	237	83
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	83
Ryan Halstead R 2018 · 4.08 FIP	26	SU	4.08	18.0%	6.7%	3.0%	.296	3.24	16.1%	8.7%	64	-0.84	3.12	222	83
Johnny Magliozzi R 2017 · 3.22 FIP	26	SU	3.22	17.1%	5.9%	1.5%	.294	—	—	—	—	—	3.22	131	83
Ryan Tepera R 2015 · 4.17 FIP	27	SU	4.17	21.1%	7.2%	3.5%	.174	3.40	24.7%	16.0%	206	-0.77	2.35	445	83
Pedro Rodriguez R 2015 · 3.21 FIP	27	SU	3.21	16.4%	4.5%	1.7%	.272	3.70	13.1%	5.2%	43	+0.49	3.21	145	83
J.J. Putz R 2004 · 4.57 FIP	27	SU	4.57	17.1%	7.3%	3.6%	.283	2.58	28.5%	23.0%	210	-1.99	1.43	563	83
Reinier Roibal R 2015 · 3.11 FIP	26	SU	3.11	19.1%	4.5%	1.9%	.262	4.37	16.9%	9.8%	35	+1.26	3.11	133	83
Seth Frankoff R 2015 · 4.01 FIP	26	SU	4.01	19.6%	7.4%	2.9%	.312	4.29	20.0%	11.3%	177	+0.28	2.88	263	82
Ronald Belisario R 2009 · 2.96 FIP	26	SU	2.96	21.4%	7.4%	1.3%	.230	3.23	20.7%	13.0%	126	+0.27	2.10	457	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	1.1	57	20.9%	6.2%	1.20	4.18
Junichi Tazawa ('18)	2.0	49	22.2%	6.5%	1.12	4.12
Dale Thayer ('15)	1.3	63	20.4%	6.3%	1.07	3.47
Tim Crews ('87-'92, 3 WAR*)	2.1	71	20.8%*	6.2%*	1.09*	4.11*
Nick Wittgren ('23)	1.6	41	21.6%	7.0%	1.15	4.04
Cris Carpenter ('88-'96, 2 WAR*)	2.1	69	18.3%*	7.4%*	1.15*	4.29*
Donn Pall ('88-'98, 3 WAR*)	2.5	63	17.1%*	6.2%*	1.20*	3.86*