Cameron Wagoner

P Biloxi Shuckers

Age 26 RHP 6'5" / 187 lbs AA peak 0.4 · 2028

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	21	MIX2 levels	7	3	20	1.83	1.63	32.0%	2.7%	—	K 32.0% · BB 2.7% · FIP 1.47
2023	22	A+MIL	24	22	100	5.67	3.41	19.2%	8.4%	—	K 14.8% · BB 9.6% · FIP 4.10
2026	25	MIX2 levels	33	0	43	1.48	2.02	35.1%	6.5%	—	K 29.0% · BB 6.6% · FIP 2.66
2027PROJ	26	MLBMIL	—	—	0	3.56	3.56	27.7%	7.2%	—
2028PROJ38% MLB	27	MLBMIL	12	0	13	3.66	3.68	27.2%	7.5%	0.1

Next 2 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.2 / P90 2.8, comp-based) · star 0% · didn't stick 87%

CompsJonathan Aro (age 26) · Dylan King (age 25) · Joshua Loeschorn (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10193vR 85

ERA3.56

FIP3.56

K%27.7%

BB%7.2%

K-BB%20.5%

Proj IP25

Value2027 · WAR

Runs saved vs league avg · 25 IP

Grades · Contract

Scouting Grades

K†6565

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	21	MIX MLE	2 levels	7	3	20	75	24	2	1	43%	2.8	32.0%	2.7%	29.3%	1.3%	1.83	1.47	—
2022	21	MIX RAW	2 levels	7	3	20	75	24	2	1	43%	2.8	32.0%	2.7%	29.3%	1.3%	1.83	1.63	—
2023	22	A+ MLE	Wisconsin Timber Rattlers	24	22	100	454	87	38	7	92%	4.2	14.8%	9.6%	5.1%	1.9%	5.67	4.10	—
2023	22	A+ RAW	Wisconsin Timber Rattlers	24	22	100	454	87	38	7	92%	4.2	19.2%	8.4%	10.8%	1.5%	5.67	3.41	—
2026	25	MIX MLE	2 levels	33	0	43	168	59	11	3	0%	1.3	29.0%	6.6%	22.4%	2.1%	1.48	2.66	—
2026	25	MIX MLE	2 levels	33	0	43	168	59	11	3	0%	1.3	29.0%	6.6%	22.4%	2.1%	1.48	2.66	—
2026	25	MIX RAW	2 levels	33	0	43	168	59	11	3	0%	1.3	35.1%	6.5%	28.6%	1.8%	1.48	2.02	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	MIL	—	—	0	—	—	—	—	—	—	27.7%	7.2%	20.5%	2.7%	3.56	3.56	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	MIL	34	0	35	149	41	11	4	0%	1.0	27.2%	7.5%	19.8%	2.8%	3.66	3.68	+0.4
2028	27	MLB CTX	MIL	12	0	13	55	15	4	2	0%	1.1	27.2%	7.5%	19.8%	2.8%	3.66	3.68	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		13	0	13	56	15	4	2	0%	1.0	27.2%	7.5%	19.8%	2.8%	3.66	3.30	+0.2
/ 200 IP	—	RAW		190	0	200	844	226	60	30	0%	1.1	27.2%	7.5%	19.8%	2.8%	3.66	3.30	+3.0
Career	—	MLE		64	25	162	697	140	57	13	39%	2.5	20.1%	8.1%	11.9%	1.9%	4.10	3.47	+0.4
/ 200 IP	—	MLE		79	31	200	859	172	70	16	39%	2.5	20.1%	8.1%	11.9%	1.9%	4.10	3.47	+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.

2026 AABiloxi Shuckers · 27 IPFIP 2.26 → 3.24 (+0.97)K% 36.8% → 29.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.79%	—	×0.810	29.80%
BB% (unintentional) /BF	5.66%	—	×1.100	6.23%
HR / BF /BF	2.83%	÷1.000	×1.200	3.40%

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 2.26 → 3.24, 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 AAANashville Sounds · 16 IPFIP 1.40 → 1.68 (+0.28)K% 32.3% → 27.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.26%	—	×0.860	27.74%
BB% (unintentional) /BF	8.06%	—	×0.900	7.26%
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 1.40 → 1.68, 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).

2023 A+Wisconsin Timber Rattlers · 100 IPFIP 3.39 → 4.10 (+0.71)K% 19.2% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.16%	—	×0.770	14.76%
BB% (unintentional) /BF	8.37%	—	×1.150	9.63%
HR / BF /BF	1.54%	÷1.033	×1.250	1.87%

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 107).

Result: FIP 3.39 → 4.10, 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).

2022 ACarolina Mudcats · 12 IPFIP 1.63 → 2.62 (+0.99)K% 34.8% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.78%	—	×0.740	25.74%
BB% (unintentional) /BF	2.17%	—	×1.180	2.57%
HR / BF /BF	2.17%	÷1.136	×1.300	2.49%

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 127).

Result: FIP 1.63 → 2.62, 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 ROKACL Brewers Gold · 8 IPFIP 1.21 → 2.06 (+0.85)K% 27.6% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.59%	—	×0.680	18.76%
BB% (unintentional) /BF	3.45%	—	×1.250	4.31%
HR / BF /BF	0.00%	÷1.144	×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 129).

Result: FIP 1.21 → 2.06, 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
Cameron Wagoner (OGILVIE)	—	—	3.56	27.7%	7.2%	2.7%	—	3.68	27.2%	19.8%	35	+0.12	—	—	—
Jonathan Aro R 2017 · 3.72 FIP	26	SU	3.72	25.3%	6.9%	3.4%	.252	3.56	14.6%	8.1%	108	-0.16	2.57	323	76
Dylan King R 2022 · 3.78 FIP	25	SW	3.78	26.7%	9.8%	3.1%	.266	—	—	—	—	—	3.78	121	75
Joshua Loeschorn R 2023 · 3.86 FIP	23	SU	3.86	24.5%	7.7%	3.4%	.272	4.43	17.1%	8.4%	83	+0.57	3.08	151	75
Simon Castro R 2015 · 3.28 FIP	27	SU	3.28	26.4%	8.5%	2.4%	.320	3.58	26.0%	17.6%	128	+0.30	3.01	185	74
Sam Wolff R 2017 · 3.40 FIP	26	SU	3.40	26.6%	8.0%	2.8%	.291	2.98	24.1%	13.3%	63	-0.42	2.66	178	72
Michael Dimock R 2016 · 3.91 FIP	26	SU	3.91	26.8%	9.8%	3.3%	.289	3.79	20.9%	11.9%	66	-0.12	3.08	166	72
Cory Rasmus R 2014 · 3.06 FIP	26	SW	3.06	25.3%	7.1%	2.2%	.252	3.58	25.8%	15.9%	61	+0.52	2.34	138	72
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	72
Raynel Espinal R 2018 · 2.60 FIP	26	SU	2.60	29.1%	9.1%	1.5%	.313	3.75	21.4%	13.0%	193	+1.15	2.48	507	71
Trent Harris R 2024 · 3.45 FIP	25	SU	3.45	26.9%	9.5%	2.6%	.258	3.36	24.7%	16.7%	121	-0.09	3.06	198	71
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	71
Matt Jachec R 2024 · 3.29 FIP	23	SU	3.29	25.8%	6.8%	2.7%	.347	3.69	21.8%	12.8%	50	+0.40	3.29	122	70
Jackson Rose R 2022 · 3.33 FIP	26	SW	3.33	21.0%	4.3%	2.6%	.245	4.72	24.1%	11.5%	26	+1.39	3.33	147	70
Andrew Kittredge R 2016 · 3.08 FIP	26	SU	3.08	23.1%	6.6%	2.0%	.353	2.96	25.6%	19.7%	255	-0.12	2.47	691	70
Zac Grotz R 2019 · 2.90 FIP	26	SU	2.90	24.8%	6.0%	2.1%	.300	5.82	12.1%	3.9%	10	+2.92	2.89	183	70
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	70
Zach Franklin R 2024 · 3.24 FIP	25	SU	3.24	26.4%	10.9%	1.8%	.301	4.15	27.5%	18.3%	117	+0.91	3.24	158	70
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	70
Ryan Eades R 2018 · 3.19 FIP	26	SW	3.19	22.4%	7.4%	1.9%	.352	4.24	23.9%	15.3%	64	+1.05	3.19	451	70
Andrew Politi R 2022 · 3.38 FIP	26	SU	3.38	26.1%	8.5%	2.6%	.238	4.70	19.6%	9.9%	69	+1.32	3.38	292	69

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	0.3	30	27.4%	7.3%	1.08	3.62
Josh Fields ('18)	1.4	46	27.5%	8.0%	0.98	3.71
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Giovanny Gallegos ('24)	1.7	56	29.6%	6.6%	1.18	3.49
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*