Renaldito Florian

P FCL Rays

Age 25 RHP 5'11" / 161 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	21	ROKTB	11	15	5.40	6.30	18.1%	22.2%	—	K 12.3% · BB 27.8% · FIP 7.92
2024	22	ROKTB	13	21	6.10	4.31	21.1%	13.7%	—	K 14.3% · BB 17.1% · FIP 5.67
2027PROJ	25	MLBTB	11	12	4.61	4.61	22.9%	11.2%	-0.0
2028PROJ43% MLB	26	MLBTB	9	9	4.57	4.56	23.1%	10.9%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsGarrett Mock (age 25) · Grant Balfour (age 25) · Chris Jefferson (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 105

ERA4.61

FIP4.61

K%22.9%

BB%11.2%

K-BB%11.7%

Proj IP12

Value2027 · WAR

Runs saved vs league avg · 12 IP

Grades · Contract

Scouting Grades

K†5555

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 industry-standard fWAR.

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 Rays	12	5	30	142	32	18	1	42%	2.5	15.3%	15.8%	-0.5%	0.9%	3.64	4.32	—
2022	20	ROK RAW	DSL Rays	12	5	30	142	32	18	1	42%	2.5	22.5%	12.7%	9.9%	0.7%	3.64	3.20	—
2023	21	ROK MLE	FCL Rays	11	0	15	72	13	16	2	0%	1.4	12.3%	27.8%	-15.5%	4.3%	5.40	7.92	—
2023	21	ROK RAW	FCL Rays	11	0	15	72	13	16	2	0%	1.4	18.1%	22.2%	-4.2%	2.8%	5.40	6.30	—
2024	22	ROK MLE	FCL Rays	13	0	21	95	20	13	2	0%	1.6	14.3%	17.1%	-2.8%	2.9%	6.10	5.67	—
2024	22	ROK MLE	FCL Rays	13	0	21	95	20	13	2	0%	1.6	14.3%	17.1%	-2.8%	2.9%	6.10	5.67	—
2024	22	ROK RAW	FCL Rays	13	0	21	95	20	13	2	0%	1.6	21.1%	13.7%	7.4%	2.1%	6.10	4.31	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	TB	11	0	12	51	12	6	2	0%	1.1	22.9%	11.2%	11.7%	3.0%	4.61	4.61	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	TB	19	0	20	84	20	9	3	0%	1.1	23.1%	10.9%	12.2%	3.0%	4.57	4.56	-0.0
2028	26	MLB CTX	TB	9	0	9	38	9	4	1	0%	1.0	23.1%	10.9%	12.2%	3.0%	4.57	4.56	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	0	9	36	8	4	1	0%	1.1	23.1%	10.9%	12.2%	3.0%	4.57	4.18	+0.0
/ 200 IP	—	RAW		190	0	200	844	187	94	23	0%	1.1	23.1%	10.9%	12.2%	3.0%	4.57	4.18	+0.9
Career	—	MLE		36	5	65	309	44	59	7	14%	1.8	14.3%	19.0%	-4.7%	2.3%	4.82	5.58	-0.0
/ 200 IP	—	MLE		110	15	200	946	135	180	22	14%	1.8	14.3%	19.0%	-4.7%	2.3%	4.82	5.58	-0.0

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
Renaldito Florian (OGILVIE)	—	—	4.61	22.9%	11.2%	3.0%	—	4.56	23.1%	12.2%	20	-0.05	—	—	—
Garrett Mock R 2008 · 3.57 FIP	25	SU	3.57	25.6%	11.1%	2.2%	.300	4.06	17.1%	7.4%	91	+0.49	3.57	132	86
Grant Balfour R 2003 · 4.13 FIP	25	SU	4.13	26.1%	10.4%	3.5%	.275	3.79	24.4%	12.8%	39	-0.34	2.04	533	86
Chris Jefferson R 2022 · 3.53 FIP	25	SU	3.53	22.4%	10.2%	1.9%	.330	4.99	16.5%	3.9%	101	+1.46	3.53	140	84
Francisco Del Rosario R 2006 · 5.13 FIP	25	SU	5.13	19.4%	13.0%	3.7%	.290	3.93	19.7%	10.3%	26	-1.20	3.93	194	83
Jonathan Albaladejo R 2008 · 3.46 FIP	25	SU	3.46	22.4%	10.3%	1.7%	.368	5.02	14.0%	3.8%	46	+1.56	2.30	173	82
Jesus Pirela R 2015 · 3.84 FIP	26	SU	3.84	23.7%	11.6%	2.3%	.305	3.92	17.1%	13.9%	45	+0.08	3.24	161	81
Josh Zeid R 2013 · 4.00 FIP	26	SU	4.00	20.3%	9.3%	2.6%	.287	4.75	16.2%	4.8%	183	+0.75	4.00	313	81
Jason Stoffel R 2015 · 3.61 FIP	26	SU	3.61	23.4%	10.1%	2.2%	.267	3.49	27.2%	19.2%	59	-0.12	3.49	103	81
Luis Vizcaino R 2000 · 4.11 FIP	25	SU	4.11	18.8%	11.5%	2.1%	.354	4.31	22.7%	14.9%	180	+0.20	3.07	564	81
Barrett Loseke R 2022 · 4.42 FIP	25	SU	4.42	21.7%	10.1%	3.4%	.311	5.24	23.5%	12.2%	22	+0.82	4.42	152	81
Brad Boxberger R 2013 · 4.40 FIP	25	SU	4.40	25.5%	13.8%	3.1%	.296	3.54	32.3%	22.2%	152	-0.86	2.63	478	81
Garrett Apker R 2024 · 4.01 FIP	24	SU	4.01	19.8%	11.2%	2.1%	.288	8.46	15.4%	-7.6%	11	+4.45	4.01	101	80
Guillermo Moscoso R 2009 · 3.56 FIP	25	SU	3.56	18.8%	9.4%	1.6%	.311	4.33	15.8%	8.5%	178	+0.77	3.56	486	80
Jackson Hicks R 2023 · 3.90 FIP	25	SU	3.90	22.6%	10.5%	2.5%	.336	—	—	—	—	—	2.17	116	80
Nolan Clenney R 2021 · 3.73 FIP	25	SU	3.73	25.5%	8.4%	3.1%	.340	4.35	22.4%	13.7%	185	+0.62	3.73	223	80
Michael Wuertz R 2004 · 4.46 FIP	25	SU	4.46	24.2%	12.9%	3.2%	.243	3.39	26.1%	16.6%	189	-1.07	2.27	414	80
Blake Goldsberry R 2022 · 3.43 FIP	25	SU	3.43	23.6%	8.3%	2.3%	.257	5.26	23.6%	12.0%	44	+1.83	3.43	117	80
Fernando Salas R 2010 · 4.27 FIP	25	SU	4.27	21.8%	9.8%	3.2%	.276	3.29	23.5%	16.8%	162	-0.98	2.60	539	80
Jon Leicester R 2004 · 4.69 FIP	25	SU	4.69	20.0%	8.6%	4.0%	.280	4.44	11.0%	2.0%	32	-0.25	3.76	113	79
Luke Bell R 2024 · 3.62 FIP	23	SU	3.62	20.4%	9.9%	1.8%	.295	5.69	13.1%	1.3%	66	+2.07	3.62	110	79