Riley Frey

P Rome Emperors

Age 25 LHP 6'1" / 185 lbs A+

Overview

A+PROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	MIX2 levels	18	12	84	2.36	2.90	21.8%	6.5%	—	K 16.6% · BB 7.5% · FIP 3.87
2025	23	MIX3 levels	22	9	80	4.37	3.22	24.7%	7.1%	—	K 19.2% · BB 7.9% · FIP 4.90
2026	24	MIX2 levels	28	0	39	3.49	3.54	25.9%	4.4%	—	K 19.2% · BB 5.1% · FIP 5.14
2027PROJ	25	MLBATL	—	—	0	4.63	4.63	18.5%	6.9%	—
2028PROJ43% MLB	26	MLBATL	24	0	25	4.58	4.57	19.2%	7.1%	-0.0
2029PROJ63% MLB	27	MLBATL	31	0	33	4.58	4.59	19.5%	7.4%	-0.0

Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control50Command50

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 98%

CompsCharlie Furbush (age 25) · Pat Misch (age 25) · Luis Perez (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 105113vR 121

ERA4.63

FIP4.63

K%18.5%

BB%6.9%

K-BB%11.6%

Proj IP60

Value2027 · WAR

Runs saved vs league avg · 60 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL5050

CMD5050

K†4545

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)
2023	21	MIX MLE	2 levels	6	6	21	88	28	6	2	100%	3.5	22.5%	7.5%	15.0%	3.4%	5.57	4.00	—
2023	21	MIX RAW	2 levels	6	6	21	88	28	6	2	100%	3.5	31.8%	6.8%	25.0%	2.3%	5.57	2.53	—
2024	22	MIX MLE	2 levels	18	12	84	339	74	22	5	67%	4.7	16.6%	7.5%	9.1%	2.2%	2.36	3.87	—
2024	22	MIX MLE	2 levels	18	12	84	339	74	22	5	67%	4.7	16.6%	7.5%	9.1%	2.2%	2.36	3.87	—
2024	22	MIX RAW	2 levels	18	12	84	339	74	22	5	67%	4.7	21.8%	6.5%	15.3%	1.5%	2.36	2.90	—
2025	23	MIX MLE	3 levels	22	9	80	336	83	24	8	41%	3.7	19.2%	7.9%	11.3%	4.4%	4.37	4.90	—
2025	23	MIX MLE	3 levels	22	9	80	336	83	24	8	41%	3.7	19.2%	7.9%	11.3%	4.4%	4.37	4.90	—
2025	23	MIX RAW	3 levels	22	9	80	336	83	24	8	41%	3.7	24.7%	7.1%	17.6%	2.4%	4.37	3.22	—
2026	24	MIX MLE	2 levels	28	0	39	158	41	7	6	0%	1.4	19.2%	5.1%	14.2%	5.5%	3.49	5.14	—
2026	24	MIX MLE	2 levels	28	0	39	158	41	7	6	0%	1.4	19.2%	5.1%	14.2%	5.5%	3.49	5.14	—
2026	24	MIX RAW	2 levels	28	0	39	158	41	7	6	0%	1.4	25.9%	4.4%	21.5%	3.8%	3.49	3.54	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	ATL	—	—	0	—	—	—	—	—	—	18.5%	6.9%	11.6%	3.3%	4.63	4.63	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	ATL	55	0	58	246	47	18	8	0%	1.1	19.2%	7.1%	12.1%	3.3%	4.58	4.57	-0.0
2029	27	MLB MLE	ATL	49	0	52	219	43	16	7	0%	1.1	19.5%	7.4%	12.2%	3.3%	4.58	4.59	-0.0
2030	28	MLB MLE	ATL	46	0	48	202	40	15	7	0%	1.0	19.6%	7.6%	12.0%	3.4%	4.63	4.66	-0.1
2031	29	MLB MLE	ATL	42	0	44	186	36	15	7	0%	1.0	19.5%	7.9%	11.6%	3.6%	4.72	4.78	-0.1
2032	30	MLB MLE	ATL	38	0	40	167	32	14	6	0%	1.0	19.1%	8.2%	10.9%	3.8%	4.86	4.96	-0.2
2028	26	MLB CTX	ATL	24	0	25	106	20	8	3	0%	1.0	19.2%	7.1%	12.1%	3.3%	4.58	4.57	-0.0
2029	27	MLB CTX	ATL	31	0	33	139	27	10	5	0%	1.1	19.5%	7.4%	12.2%	3.3%	4.58	4.59	-0.0
2030	28	MLB CTX	ATL	34	0	36	152	30	12	5	0%	1.1	19.6%	7.6%	12.0%	3.4%	4.63	4.66	-0.0
2031	29	MLB CTX	ATL	34	0	36	152	30	12	5	0%	1.1	19.5%	7.9%	11.6%	3.6%	4.72	4.78	-0.1
2032	30	MLB CTX	ATL	32	0	34	144	27	12	5	0%	1.1	19.1%	8.2%	10.9%	3.8%	4.86	4.96	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		156	0	163	690	134	53	24	0%	1.0	19.4%	7.7%	11.7%	3.5%	4.68	4.34	+0.4
/ 200 IP	—	RAW		190	0	200	844	164	65	29	0%	1.1	19.4%	7.7%	11.7%	3.5%	4.68	4.34	+0.5
Career	—	MLE		74	27	224	921	171	67	34	36%	3.0	18.5%	7.2%	11.3%	3.7%	3.58	4.48	-0.4
/ 200 IP	—	MLE		66	24	200	822	152	59	30	36%	3.0	18.5%	7.2%	11.3%	3.7%	3.58	4.48	-0.3

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 A+Rome Emperors · 33 IPFIP 3.97 → 5.14 (+1.17)K% 25.0% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.770	19.25%
BB% (unintentional) /BF	4.41%	—	×1.150	5.07%
HR / BF /BF	4.41%	÷1.000	×1.250	5.51%

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 100).

Result: FIP 3.97 → 5.14, 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 AAColumbus Clingstones · 6 IPFIP 0.99 → 1.56 (+0.57)K% 31.8% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.82%	—	×0.810	25.77%
BB% (unintentional) /BF	4.55%	—	×1.100	5.00%
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 → 1.56, 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).

2025 A+Rome Emperors · 67 IPFIP 3.45 → 4.90 (+1.45)K% 24.9% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.91%	—	×0.770	19.18%
BB% (unintentional) /BF	6.86%	—	×1.150	7.89%
HR / BF /BF	2.89%	÷0.819	×1.250	4.41%

Result: FIP 3.45 → 4.90, 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).

2025 AAugusta GreenJackets · 10 IPFIP 2.30 → 3.04 (+0.74)K% 23.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.740	17.62%
BB% (unintentional) /BF	9.52%	—	×1.180	11.24%
HR / BF /BF	0.00%	÷1.281	×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 156).

Result: FIP 2.30 → 3.04, 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+Rome Emperors · 61 IPFIP 3.56 → 4.62 (+1.06)K% 18.5% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.55%	—	×0.770	14.28%
BB% (unintentional) /BF	7.26%	—	×1.150	8.35%
HR / BF /BF	2.02%	÷0.831	×1.250	3.03%

Result: FIP 3.56 → 4.62, 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).

2024 AAugusta GreenJackets · 23 IPFIP 1.06 → 1.83 (+0.78)K% 30.8% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.77%	—	×0.740	22.77%
BB% (unintentional) /BF	4.40%	—	×1.180	5.19%
HR / BF /BF	0.00%	÷1.010	×1.300	0.00%

Result: FIP 1.06 → 1.83, 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 AAugusta GreenJackets · 18 IPFIP 2.73 → 4.00 (+1.27)K% 30.4% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.38%	—	×0.740	22.48%
BB% (unintentional) /BF	6.33%	—	×1.180	7.47%
HR / BF /BF	2.53%	÷0.976	×1.300	3.37%

Result: FIP 2.73 → 4.00, 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
Riley Frey (OGILVIE)	—	—	4.63	18.5%	6.9%	3.3%	—	4.60	19.4%	12.1%	158	-0.03	—	—	—
Charlie Furbush L 2011 · 4.95 FIP	25	SW	4.95	18.0%	7.5%	4.4%	.310	2.67	28.8%	21.4%	154	-2.28	2.40	261	81
Pat Misch L 2007 · 3.51 FIP	25	SW	3.51	14.8%	5.7%	1.7%	.321	4.71	12.7%	7.3%	152	+1.20	3.50	265	81
Luis Perez L 2011 · 4.35 FIP	26	SU	4.35	18.4%	8.8%	3.1%	.317	3.32	22.3%	13.2%	42	-1.03	3.32	173	81
Nick Maronde L 2015 · 3.85 FIP	25	SW	3.85	18.3%	8.9%	2.1%	.359	3.62	16.3%	8.9%	48	-0.23	3.62	133	80
Wesley Wright L 2010 · 4.85 FIP	25	SW	4.85	19.6%	8.8%	4.2%	.310	3.38	23.9%	16.5%	106	-1.47	3.03	375	79
Jose Alvarez L 2013 · 5.02 FIP	24	SW	5.02	18.0%	8.7%	4.2%	.294	2.98	20.4%	14.8%	124	-2.04	2.78	414	77
Matt Crouse L 2015 · 3.99 FIP	25	SW	3.99	12.0%	6.3%	2.0%	.276	4.40	12.2%	4.3%	268	+0.41	3.99	342	77
Pedro Feliciano L 2003 · 3.74 FIP	26	SU	3.74	19.7%	8.3%	2.3%	.309	3.52	20.2%	11.1%	79	-0.22	2.69	378	76
Irwin Delgado L 2015 · 4.77 FIP	26	SW	4.77	14.4%	9.6%	3.0%	.349	3.53	16.2%	7.6%	237	-1.24	3.52	383	76
Braulio Lara L 2015 · 3.96 FIP	26	SU	3.96	16.7%	8.7%	2.1%	.367	5.20	18.9%	3.9%	67	+1.24	3.96	118	76
Brent Headrick L 2023 · 4.49 FIP	25	SW	4.49	23.1%	7.6%	4.3%	.299	2.91	28.6%	21.1%	143	-1.58	2.36	414	75
Nick Dombkowski L 2024 · 4.92 FIP	25	SW	4.92	16.5%	10.9%	3.3%	.273	5.17	18.2%	10.6%	183	+0.25	3.71	425	75
Chris Narveson L 2009 · 4.01 FIP	27	SW	4.01	22.4%	7.3%	3.4%	.277	4.00	18.5%	10.0%	329	-0.01	4.00	625	75
Sean Mellen L 2022 · 4.01 FIP	24	SU	4.01	21.3%	10.4%	2.5%	.285	—	—	—	—	—	4.01	101	75
Robby Scott L 2015 · 4.06 FIP	25	SU	4.06	17.3%	7.2%	2.8%	.307	3.64	23.3%	15.8%	162	-0.42	2.39	285	75
Jake Kalish L 2016 · 3.89 FIP	25	SU	3.89	17.8%	6.9%	2.6%	.231	3.90	17.0%	11.9%	352	+0.01	2.68	740	74
Carson Teel L 2021 · 5.34 FIP	25	SW	5.34	16.2%	6.7%	5.0%	.296	4.26	17.7%	10.6%	63	-1.08	3.43	248	74
Brian Duensing L 2009 · 3.98 FIP	26	SW	3.98	14.8%	8.4%	1.9%	.286	3.90	15.2%	9.3%	401	-0.08	2.57	799	74
Eric Jokisch L 2014 · 5.18 FIP	25	SW	5.18	15.2%	6.1%	4.7%	.306	4.28	12.8%	4.9%	264	-0.90	3.78	427	74
Caden Favors L 2024 · 3.73 FIP	22	SW	3.73	18.2%	4.5%	2.9%	.351	4.82	20.0%	8.8%	236	+1.09	3.73	248	74

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	1.5	50	19.2%	7.4%	1.33	4.66
J. C. Gutierrez ('07-'14, -0 WAR*)	1.4	57	19.8%*	8.5%*	1.19*	4.72*
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Juan Carlos Oviedo ('14)	1.9	56	18.9%	8.0%	1.16	4.28
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Larry Casian ('90-'98, 0 WAR*)	1.2	40	14.7%*	6.8%*	1.25*	4.37*
Cris Carpenter ('88-'96, 2 WAR*)	2.1	69	18.3%*	7.4%*	1.15*	4.29*