Fraynel Nova

P Columbia Fireflies

Age 25 RHP 6'0" / 190 lbs A

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	ROKKC	10	1	24	6.38	3.10	21.9%	7.0%	—	K 14.9% · BB 8.8% · FIP 4.37
2025	23	AKC	42	0	62	3.77	3.60	19.0%	10.0%	—	K 14.0% · BB 11.8% · FIP 4.39
2027PROJ	25	MLBKC	—	—	0	5.62	5.62	13.7%	13.4%	—
2028PROJ43% MLB	26	MLBKC	20	0	21	5.45	5.42	15.4%	13.0%	-0.2
2029PROJ63% MLB	27	MLBKC	26	0	27	5.37	5.38	16.0%	12.8%	-0.2

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

CompsJuan Paniagua (age 25) · Julian Arballo (age 27) · Jeff Soptic (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 140132vR 124

ERA5.62

FIP5.62

K%13.7%

BB%13.4%

K-BB%0.3%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL4040

CMD3030

K†3040

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 KC Glass	8	5	20	79	19	5	1	62%	2.5	16.4%	7.9%	8.4%	2.0%	2.75	3.83	—
2022	20	ROK RAW	DSL KC Glass	8	5	20	79	19	5	1	62%	2.5	24.1%	6.3%	17.7%	1.3%	2.75	2.59	—
2023	21	ROK MLE	DSL Royals Blue	13	0	24	95	24	5	1	0%	1.8	17.2%	6.6%	10.6%	1.6%	3.04	3.38	—
2023	21	ROK RAW	DSL Royals Blue	13	0	24	95	24	5	1	0%	1.8	25.3%	5.3%	20.0%	1.1%	3.04	2.25	—
2024	22	ROK MLE	ACL Royals	10	1	24	114	25	8	2	10%	2.4	14.9%	8.8%	6.1%	2.6%	6.38	4.37	—
2024	22	ROK MLE	ACL Royals	10	1	24	114	25	8	2	10%	2.4	14.9%	8.8%	6.1%	2.6%	6.38	4.37	—
2024	22	ROK RAW	ACL Royals	10	1	24	114	25	8	2	10%	2.4	21.9%	7.0%	14.9%	1.8%	6.38	3.10	—
2025	23	A MLE	Columbia Fireflies	42	0	62	269	51	27	4	0%	1.5	14.0%	11.8%	2.2%	1.8%	3.77	4.39	—
2025	23	A MLE	Columbia Fireflies	42	0	62	269	51	27	4	0%	1.5	14.0%	11.8%	2.2%	1.8%	3.77	4.39	—
2025	23	A RAW	Columbia Fireflies	42	0	62	269	51	27	4	0%	1.5	19.0%	10.0%	8.9%	1.5%	3.77	3.60	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	KC	—	—	0	—	—	—	—	—	—	13.7%	13.4%	0.3%	2.9%	5.62	5.62	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	KC	47	0	50	210	32	27	6	0%	1.1	15.4%	13.0%	2.5%	2.9%	5.45	5.42	-0.5
2029	27	MLB MLE	KC	40	0	42	179	29	23	5	0%	1.1	16.0%	12.8%	3.3%	3.0%	5.37	5.38	-0.4
2030	28	MLB MLE	KC	37	0	39	164	27	21	5	0%	1.0	16.3%	12.7%	3.5%	3.1%	5.37	5.41	-0.4
2031	29	MLB MLE	KC	34	0	36	152	25	20	5	0%	1.1	16.2%	12.9%	3.3%	3.2%	5.44	5.51	-0.4
2028	26	MLB CTX	KC	20	0	21	89	14	12	3	0%	1.1	15.4%	13.0%	2.5%	2.9%	5.45	5.42	-0.2
2029	27	MLB CTX	KC	26	0	27	114	18	15	3	0%	1.0	16.0%	12.8%	3.3%	3.0%	5.37	5.38	-0.2
2030	28	MLB CTX	KC	28	0	29	122	20	16	4	0%	1.0	16.3%	12.7%	3.5%	3.1%	5.37	5.41	-0.3
2031	29	MLB CTX	KC	28	0	29	122	20	16	4	0%	1.0	16.2%	12.9%	3.3%	3.2%	5.44	5.51	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		101	0	106	449	72	58	14	0%	1.1	16.0%	12.8%	3.2%	3.1%	5.41	5.05	-0.6
/ 200 IP	—	RAW		190	0	200	844	136	109	26	0%	1.1	16.0%	12.8%	3.2%	3.1%	5.41	5.05	-1.2
Career	—	MLE		73	6	129	557	84	54	11	8%	1.8	15.1%	9.8%	5.3%	2.0%	3.97	4.14	-1.7
/ 200 IP	—	MLE		113	9	200	861	130	84	17	8%	1.8	15.1%	9.8%	5.3%	2.0%	3.97	4.14	-2.0

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 AColumbia Fireflies · 62 IPFIP 3.59 → 4.39 (+0.81)K% 19.0% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.96%	—	×0.740	14.03%
BB% (unintentional) /BF	10.04%	—	×1.180	11.84%
HR / BF /BF	1.49%	÷1.086	×1.300	1.78%

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 117).

Result: FIP 3.59 → 4.39, 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 ROKACL Royals · 24 IPFIP 3.10 → 4.37 (+1.27)K% 21.9% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.93%	—	×0.680	14.91%
BB% (unintentional) /BF	7.02%	—	×1.250	8.77%
HR / BF /BF	1.75%	÷0.949	×1.400	2.59%

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 90).

Result: FIP 3.10 → 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).

2023 ROKDSL Royals Blue · 24 IPFIP 2.21 → 3.38 (+1.17)K% 25.3% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.26%	—	×0.680	17.18%
BB% (unintentional) /BF	5.26%	—	×1.250	6.58%
HR / BF /BF	1.05%	÷0.903	×1.400	1.63%

Result: FIP 2.21 → 3.38, 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 KC Glass · 20 IPFIP 2.57 → 3.83 (+1.26)K% 24.1% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.05%	—	×0.680	16.35%
BB% (unintentional) /BF	6.33%	—	×1.250	7.91%
HR / BF /BF	1.27%	÷0.879	×1.400	2.02%

Result: FIP 2.57 → 3.83, 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).

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
Fraynel Nova (OGILVIE)	—	—	5.62	13.7%	13.4%	2.9%	—	5.40	15.9%	3.0%	131	-0.22	—	—	—
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	88
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	87
Jeff Soptic R 2016 · 5.52 FIP	25	SU	5.52	13.6%	15.3%	3.0%	.326	—	—	—	—	—	5.30	124	86
Stephen Johnson R 2016 · 5.15 FIP	25	SU	5.15	16.7%	12.7%	3.4%	.268	—	—	—	—	—	3.12	141	86
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
Tyler Burch R 2023 · 4.92 FIP	25	SU	4.92	15.0%	12.6%	2.7%	.285	—	—	—	—	—	4.56	119	85
Kender Villegas R 2017 · 4.70 FIP	24	SU	4.70	13.3%	13.3%	1.9%	.269	—	—	—	—	—	3.26	131	85
Justin Camp R 2018 · 4.56 FIP	25	SU	4.56	13.2%	11.9%	1.9%	.296	—	—	—	—	—	2.59	140	85
Clate Schmidt R 2019 · 5.66 FIP	25	SU	5.66	13.5%	13.9%	3.5%	.290	—	—	—	—	—	3.51	160	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
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	84
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	84
Rob Huber R 2016 · 4.73 FIP	24	SU	4.73	15.7%	14.7%	2.0%	.333	—	—	—	—	—	3.90	117	84
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	84
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
Philip Walby R 2017 · 4.49 FIP	25	SU	4.49	12.7%	12.0%	1.7%	.311	—	—	—	—	—	3.46	137	83
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	83
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	83
Nick Trogrlic-Iverson R 2023 · 4.59 FIP	25	SU	4.59	15.1%	10.4%	2.6%	.301	—	—	—	—	—	3.30	218	83
Reece Karalus R 2018 · 4.73 FIP	24	SU	4.73	15.4%	11.9%	2.6%	.299	—	—	—	—	—	4.73	149	83

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	15.3%	13.0%	1.16	5.47
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
C.J. Nitkowski ('05)	2.4	68	15.8%	11.9%	1.07	5.37
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*