Evan Gates

P Reading Fightin Phils

Age 29 RHP 6'0" / 210 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	39	0	70	4.22	3.51	23.1%	10.1%	—	K 19.2% · BB 10.2% · FIP 3.93
2025	27	AASF	41	1	70	3.23	3.44	27.8%	10.8%	—	K 22.5% · BB 11.8% · FIP 4.05
2026	28	MIX2 levels	43	2	62	4.04	4.08	21.6%	9.2%	—	K 18.6% · BB 8.9% · FIP 4.51
2027PROJ	29	MLBPHI	1	0	1	4.72	4.72	20.0%	10.2%	-0.0
2028PROJ31% MLB	30	MLBPHI	15	0	16	4.79	4.86	20.0%	10.4%	-0.1
2029PROJ51% MLB	31	MLBPHI	21	0	22	4.91	5.02	19.9%	10.6%	-0.1

Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff50Control45Command50

Career WAR0.0 WAR median (P10 -0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsJim Miller (age 30) · Dustin Molleken (age 30) · Joe Nelson (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.72

FIP4.72

K%20.0%

BB%10.2%

K-BB%9.8%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF5050

CTRL4545

CMD5050

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	23	ROK MLE	ACL Giants Black	9	0	10	42	14	2	3	0%	1.1	33.3%	4.8%	28.6%	7.1%	4.50	4.81	—
2021	23	ROK RAW	ACL Giants Black	9	0	10	42	14	2	3	0%	1.1	33.3%	4.8%	28.6%	7.1%	4.50	4.80	—
2022	24	MIX MLE	3 levels	42	0	55	214	70	19	5	0%	1.3	23.8%	9.1%	14.6%	3.3%	1.95	4.04	—
2022	24	MIX RAW	3 levels	42	0	55	214	70	19	5	0%	1.3	32.7%	8.9%	23.8%	2.3%	1.95	2.77	—
2023	25	AA MLE	Richmond Flying Squirrels	42	0	55	262	72	30	3	0%	1.3	22.3%	12.6%	9.7%	1.5%	4.39	3.65	—
2023	25	AA RAW	Richmond Flying Squirrels	42	0	55	262	72	30	3	0%	1.3	27.5%	11.5%	16.0%	1.1%	4.39	2.83	—
2024	26	MIX MLE	2 levels	39	0	70	308	71	31	6	0%	1.8	19.2%	10.2%	9.0%	2.1%	4.22	3.93	—
2024	26	MIX MLE	2 levels	39	0	70	308	71	31	6	0%	1.8	19.2%	10.2%	9.0%	2.1%	4.22	3.93	—
2024	26	MIX RAW	2 levels	39	0	70	308	71	31	6	0%	1.8	23.1%	10.1%	13.0%	1.9%	4.22	3.51	—
2025	27	AA MLE	Richmond Flying Squirrels	41	1	70	288	80	31	7	2%	1.7	22.5%	11.8%	10.7%	2.5%	3.23	4.05	—
2025	27	AA MLE	Richmond Flying Squirrels	41	1	70	288	80	31	7	2%	1.7	22.5%	11.8%	10.7%	2.5%	3.23	4.05	—
2025	27	AA RAW	Richmond Flying Squirrels	41	1	70	288	80	31	7	2%	1.7	27.8%	10.8%	17.0%	2.4%	3.23	3.44	—
2026	28	MIX MLE	2 levels	43	2	62	273	59	25	8	5%	1.4	18.6%	8.9%	9.7%	3.4%	4.04	4.51	—
2026	28	MIX MLE	2 levels	43	2	62	273	59	25	8	5%	1.4	18.6%	8.9%	9.7%	3.4%	4.04	4.51	—
2026	28	MIX RAW	2 levels	43	2	62	273	59	25	8	5%	1.4	21.6%	9.2%	12.5%	2.9%	4.04	4.08	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	PHI	1	0	1	4	1	0	0	0%	1.0	20.0%	10.2%	9.8%	3.0%	4.72	4.72	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	PHI	49	0	52	219	44	23	7	0%	1.1	20.0%	10.4%	9.6%	3.2%	4.79	4.86	-0.2
2029	31	MLB MLE	PHI	41	0	43	181	36	19	6	0%	1.0	19.9%	10.6%	9.2%	3.4%	4.91	5.02	-0.2
2028	30	MLB CTX	PHI	15	0	16	68	14	7	2	0%	1.1	20.0%	10.4%	9.6%	3.2%	4.79	4.86	-0.1
2029	31	MLB CTX	PHI	21	0	22	93	18	10	3	0%	1.0	19.9%	10.6%	9.2%	3.4%	4.91	5.02	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		36	0	38	161	32	17	5	0%	1.1	19.9%	10.5%	9.4%	3.3%	4.86	4.57	-0.0
/ 200 IP	—	RAW		190	0	200	844	167	89	26	0%	1.1	19.9%	10.5%	9.4%	3.3%	4.86	4.57	-0.0
Career	—	MLE		216	3	323	1387	298	144	37	1%	1.5	21.5%	10.4%	11.1%	2.7%	3.62	4.06	-0.4
/ 200 IP	—	MLE		134	2	200	859	184	89	23	1%	1.5	21.5%	10.4%	11.1%	2.7%	3.62	4.06	-0.9

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 AAReading Fightin Phils · 59 IPFIP 3.73 → 4.51 (+0.78)K% 23.0% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.98%	—	×0.810	18.62%
BB% (unintentional) /BF	8.06%	—	×1.100	8.87%
HR / BF /BF	2.82%	÷1.000	×1.200	3.39%

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 3.73 → 4.51, 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).

2026 AAALehigh Valley IronPigs · 4 IPFIP 7.15 → 7.21 (+0.06)K% 8.0% → 6.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	8.00%	—	×0.860	6.88%
BB% (unintentional) /BF	20.00%	—	×0.900	18.00%
HR / BF /BF	4.00%	÷1.000	×1.100	4.40%

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 7.15 → 7.21, 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 AARichmond Flying Squirrels · 70 IPFIP 3.45 → 4.05 (+0.60)K% 27.8% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.78%	—	×0.810	22.50%
BB% (unintentional) /BF	10.76%	—	×1.100	11.84%
HR / BF /BF	2.43%	÷1.183	×1.200	2.47%

Result: FIP 3.45 → 4.05, 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 AAASacramento River Cats · 35 IPFIP 4.51 → 4.80 (+0.29)K% 19.0% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.05%	—	×0.860	16.38%
BB% (unintentional) /BF	8.33%	—	×0.900	7.50%
HR / BF /BF	3.57%	÷1.010	×1.100	3.89%

Result: FIP 4.51 → 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 AARichmond Flying Squirrels · 35 IPFIP 2.29 → 2.89 (+0.60)K% 27.9% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.86%	—	×0.810	22.56%
BB% (unintentional) /BF	12.14%	—	×1.100	13.36%
HR / BF /BF	0.00%	÷1.062	×1.200	0.00%

Result: FIP 2.29 → 2.89, 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 AARichmond Flying Squirrels · 55 IPFIP 2.86 → 3.65 (+0.79)K% 27.5% → 22.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.48%	—	×0.810	22.26%
BB% (unintentional) /BF	11.45%	—	×1.100	12.60%
HR / BF /BF	1.15%	÷0.906	×1.200	1.52%

Result: FIP 2.86 → 3.65, 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).

2022 A+Eugene Emeralds · 23 IPFIP 3.42 → 4.37 (+0.95)K% 30.1% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.11%	—	×0.770	23.18%
BB% (unintentional) /BF	8.60%	—	×1.150	9.89%
HR / BF /BF	3.23%	÷1.120	×1.250	3.60%

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 124).

Result: FIP 3.42 → 4.37, 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 ASan Jose Giants · 24 IPFIP 2.50 → 3.68 (+1.17)K% 32.9% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.94%	—	×0.740	24.38%
BB% (unintentional) /BF	7.06%	—	×1.180	8.33%
HR / BF /BF	2.35%	÷1.063	×1.300	2.88%

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 113).

Result: FIP 2.50 → 3.68, 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
Evan Gates (OGILVIE)	—	—	4.72	20.0%	10.2%	3.0%	—	4.93	19.9%	9.5%	95	+0.21	—	—	—
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	88
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	86
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	85
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	85
Tyler Walker R 2005 · 4.19 FIP	29	SU	4.19	19.4%	7.5%	3.2%	.303	3.61	19.7%	11.3%	93	-0.58	2.38	289	84
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	84
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	84
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	84
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	84
Coleman Huntley III R 2022 · 4.05 FIP	29	SU	4.05	24.4%	10.9%	3.0%	.311	2.38	20.9%	12.6%	25	-1.67	2.38	160	83
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	83
Bo Schultz R 2015 · 4.30 FIP	29	SU	4.30	18.3%	7.9%	3.2%	.218	3.49	15.1%	8.9%	77	-0.81	2.73	141	83
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	81
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	80
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	80
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	80
Kevin Gryboski R 2003 · 3.67 FIP	29	SU	3.67	16.8%	8.9%	1.6%	.295	3.92	9.4%	0.2%	82	+0.25	3.67	178	79
Justin Miller R 2016 · 3.74 FIP	29	SU	3.74	20.8%	9.7%	2.1%	.353	4.72	22.5%	16.5%	127	+0.98	2.63	292	79
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	78
Matt Lindstrom R 2009 · 4.12 FIP	29	SU	4.12	17.8%	10.0%	2.3%	.320	3.16	17.7%	11.7%	154	-0.96	2.40	443	78

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	0.8	54	20.0%	10.4%	1.22	4.79
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*