Ignacio Briceno

P Lakeland Flying Tigers

Age 26 LHP 5'11" / 155 lbs A

Overview

APROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	ROKDET	17	1	26	4.10	2.23	21.7%	7.8%	—	K 14.8% · BB 9.8% · FIP 3.09
2025	24	ADET	32	0	50	3.06	2.70	19.7%	10.1%	—	K 14.6% · BB 11.9% · FIP 3.38
2027PROJ	26	MLBDET	—	—	0	5.46	5.46	15.1%	13.5%	—
2028PROJ36% MLB	27	MLBDET	17	0	18	5.36	5.38	15.9%	13.2%	-0.2
2029PROJ59% MLB	28	MLBDET	23	0	24	5.34	5.38	16.4%	13.0%	-0.2

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control40Command30

CompsJustin Wright (age 26) · Brian Moran (age 26) · Ryne Slack (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121129vR 137

ERA5.46

FIP5.46

K%15.1%

BB%13.5%

K-BB%1.6%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF3535

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)
2021	20	ROK MLE	DSL Tigers	14	0	24	107	20	11	2	0%	1.7	12.7%	12.9%	-0.1%	2.7%	2.22	5.16	—
2021	20	ROK RAW	DSL Tigers	14	0	24	107	20	11	2	0%	1.7	18.7%	10.3%	8.4%	1.9%	2.22	3.88	—
2022	21	ROK MLE	DSL Tigers 2	17	0	28	109	30	6	0	0%	1.7	18.7%	6.9%	11.8%	0.0%	1.59	2.39	—
2022	21	ROK RAW	DSL Tigers 2	17	0	28	109	30	6	0	0%	1.7	27.5%	5.5%	22.0%	0.0%	1.59	1.62	—
2023	22	ROK MLE	DSL Tigers 2	18	0	27	118	30	12	2	0%	1.5	17.3%	12.7%	4.6%	2.4%	2.63	4.54	—
2023	22	ROK RAW	DSL Tigers 2	18	0	27	118	30	12	2	0%	1.5	25.4%	10.2%	15.3%	1.7%	2.63	3.17	—
2024	23	ROK MLE	FCL Tigers	17	1	26	115	25	9	0	6%	1.5	14.8%	9.8%	5.0%	0.0%	4.10	3.09	—
2024	23	ROK MLE	FCL Tigers	17	1	26	115	25	9	0	6%	1.5	14.8%	9.8%	5.0%	0.0%	4.10	3.09	—
2024	23	ROK RAW	FCL Tigers	17	1	26	115	25	9	0	6%	1.5	21.7%	7.8%	13.9%	0.0%	4.10	2.23	—
2025	24	A MLE	Lakeland Flying Tigers	32	0	50	218	43	22	0	0%	1.6	14.6%	11.9%	2.7%	0.0%	3.06	3.38	—
2025	24	A MLE	Lakeland Flying Tigers	32	0	50	218	43	22	0	0%	1.6	14.6%	11.9%	2.7%	0.0%	3.06	3.38	—
2025	24	A RAW	Lakeland Flying Tigers	32	0	50	218	43	22	0	0%	1.6	19.7%	10.1%	9.6%	0.0%	3.06	2.70	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	DET	—	—	0	—	—	—	—	—	—	15.1%	13.5%	1.6%	2.8%	5.46	5.46	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	DET	47	0	49	209	33	27	6	0%	1.1	15.9%	13.2%	2.8%	2.9%	5.36	5.38	-0.5
2029	28	MLB MLE	DET	40	0	42	176	29	23	5	0%	1.0	16.4%	13.0%	3.4%	3.0%	5.34	5.38	-0.4
2030	29	MLB MLE	DET	36	0	37	157	26	21	5	0%	1.0	16.5%	13.0%	3.5%	3.1%	5.39	5.46	-0.4
2028	27	MLB CTX	DET	17	0	18	76	12	10	2	0%	1.1	15.9%	13.2%	2.8%	2.9%	5.36	5.38	-0.2
2029	28	MLB CTX	DET	23	0	24	101	17	13	3	0%	1.0	16.4%	13.0%	3.4%	3.0%	5.34	5.38	-0.2
2030	29	MLB CTX	DET	25	0	26	110	18	14	3	0%	1.0	16.5%	13.0%	3.5%	3.1%	5.39	5.46	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		65	0	69	290	47	38	9	0%	1.1	16.3%	13.1%	3.2%	3.0%	5.36	5.03	-0.4
/ 200 IP	—	RAW		190	0	200	844	137	111	26	0%	1.1	16.3%	13.1%	3.2%	3.0%	5.36	5.03	-1.1
Career	—	MLE		98	1	156	667	103	73	6	1%	1.6	15.5%	11.0%	4.5%	0.9%	2.76	3.66	-1.3
/ 200 IP	—	MLE		125	1	200	853	132	94	7	1%	1.6	15.5%	11.0%	4.5%	0.9%	2.76	3.66	-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 ALakeland Flying Tigers · 50 IPFIP 2.71 → 3.38 (+0.66)K% 19.7% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.72%	—	×0.740	14.60%
BB% (unintentional) /BF	10.09%	—	×1.180	11.91%
HR / BF /BF	0.00%	÷0.864	×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 73).

Result: FIP 2.71 → 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).

2024 ROKFCL Tigers · 26 IPFIP 2.26 → 3.09 (+0.84)K% 21.7% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.74%	—	×0.680	14.78%
BB% (unintentional) /BF	7.83%	—	×1.250	9.78%
HR / BF /BF	0.00%	÷0.952	×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 90).

Result: FIP 2.26 → 3.09, 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 Tigers 2 · 27 IPFIP 3.17 → 4.54 (+1.37)K% 25.4% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.42%	—	×0.680	17.29%
BB% (unintentional) /BF	10.17%	—	×1.250	12.71%
HR / BF /BF	1.69%	÷1.009	×1.400	2.35%

Result: FIP 3.17 → 4.54, 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 Tigers 2 · 28 IPFIP 1.47 → 2.39 (+0.92)K% 27.5% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.52%	—	×0.680	18.72%
BB% (unintentional) /BF	5.50%	—	×1.250	6.88%
HR / BF /BF	0.00%	÷0.933	×1.400	0.00%

Result: FIP 1.47 → 2.39, 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).

2021 ROKDSL Tigers · 24 IPFIP 3.85 → 5.16 (+1.31)K% 18.7% → 12.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.69%	—	×0.680	12.71%
BB% (unintentional) /BF	10.28%	—	×1.250	12.85%
HR / BF /BF	1.87%	÷0.956	×1.400	2.74%

Result: FIP 3.85 → 5.16, 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
Ignacio Briceno (OGILVIE)	—	—	5.46	15.1%	13.5%	2.8%	—	5.40	16.2%	3.2%	128	-0.06	—	—	—
Justin Wright L 2016 · 4.42 FIP	26	SU	4.42	14.7%	13.7%	1.5%	.302	—	—	—	—	—	2.28	109	86
Brian Moran L 2015 · 4.50 FIP	26	SU	4.50	17.7%	14.1%	2.0%	.318	2.74	25.0%	17.4%	80	-1.76	1.80	421	83
Ryne Slack L 2018 · 5.59 FIP	26	SU	5.59	13.9%	12.1%	3.9%	.310	—	—	—	—	—	4.07	212	83
Stephen Peterson L 2015 · 4.59 FIP	27	SU	4.59	13.0%	9.5%	2.5%	.284	3.04	17.3%	6.3%	55	-1.55	3.04	120	82
Fabian Williamson L 2015 · 5.31 FIP	26	SU	5.31	17.4%	17.9%	2.6%	.289	4.16	20.0%	8.2%	77	-1.15	3.39	154	82
Sean Keselica L 2019 · 4.47 FIP	26	SU	4.47	18.0%	14.5%	1.9%	.314	—	—	—	—	—	2.79	235	82
Estevan Gonzalez L 2017 · 5.21 FIP	25	SU	5.21	12.1%	13.3%	2.6%	.291	—	—	—	—	—	4.58	195	82
Ty Madrigal L 2022 · 5.75 FIP	25	SU	5.75	17.6%	15.2%	4.0%	.304	—	—	—	—	—	4.56	107	82
Chandler Jozwiak L 2024 · 5.33 FIP	25	SU	5.33	16.9%	15.3%	3.1%	.259	—	—	—	—	—	2.86	161	81
Heath Murray L 2001 · 5.40 FIP	28	SU	5.40	14.0%	11.6%	3.6%	.333	6.02	20.0%	7.3%	12	+0.62	4.69	159	81
Stephen Randolph L 2003 · 4.83 FIP	29	SU	4.83	18.5%	14.8%	2.6%	.247	5.69	15.8%	-3.0%	82	+0.86	4.83	155	81
Jose Meraz L 2015 · 4.71 FIP	27	SU	4.71	13.3%	12.0%	2.2%	.331	4.06	15.3%	6.7%	44	-0.65	3.78	110	81
Kirby Bellow L 2018 · 4.42 FIP	26	SU	4.42	13.6%	14.0%	1.3%	.255	—	—	—	—	—	2.84	108	80
Trevor Seidenberger L 2016 · 6.29 FIP	24	SU	6.29	13.1%	14.9%	4.4%	.309	—	—	—	—	—	4.64	101	79
Tom Windle L 2018 · 4.56 FIP	26	SU	4.56	19.0%	11.8%	2.9%	.269	4.37	17.2%	1.8%	74	-0.19	3.68	330	79
Matt Mikulski L 2024 · 6.18 FIP	25	SU	6.18	15.3%	17.1%	4.0%	.275	4.98	19.5%	-8.3%	18	-1.20	4.92	223	79
Joey DeNato L 2017 · 4.76 FIP	25	SU	4.76	12.3%	15.1%	1.4%	.271	—	—	—	—	—	2.90	167	79
Joe Kemlage L 2023 · 5.35 FIP	24	SU	5.35	17.6%	11.7%	4.1%	.349	—	—	—	—	—	4.42	128	79
Randy Labaut L 2023 · 4.72 FIP	26	SU	4.72	17.0%	13.9%	2.4%	.244	4.93	18.4%	6.1%	98	+0.21	1.91	302	79
Kyle Hunter L 2015 · 4.32 FIP	26	SW	4.32	12.5%	11.5%	1.5%	.258	4.49	12.6%	4.6%	144	+0.17	4.32	188	79

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	1.0	50	15.8%	13.2%	1.13	5.40
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
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*