Rayner Urbaez

P DSL Rangers Red

Age 24 RHP 6'0" / 175 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	20	ROKDSL Rangers R…	12	11	38	4.26	2.31	34.8%	9.1%	—	K 23.6% · BB 11.4% · FIP 3.88
2024	21	ROKDSL Rangers R…	17	0	27	0.33	2.51	22.1%	9.6%	—	K 15.0% · BB 12.0% · FIP 3.35
2027PROJ	24	MLBTEX	15	0	16	4.45	4.45	22.9%	10.0%	0.0
2028PROJ43% MLB	25	MLBTEX	9	0	9	4.38	4.35	23.3%	9.5%	0.0

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

Contract

No contract data on file.

CompsJonathan Papelbon (age 24) · Kyle Zimmer (age 23) · Ryan Conroy (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 118110vR 101

ERA4.45

FIP4.45

K%22.9%

BB%10.0%

K-BB%12.9%

Proj IP16

Value2027 · WAR

Runs saved vs league avg · 16 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	19	ROK MLE	DSL TEX Blue	16	1	38	153	54	10	1	6%	2.4	24.0%	8.2%	15.8%	0.8%	1.89	2.55	—
2022	19	ROK RAW	DSL TEX Blue	16	1	38	153	54	10	1	6%	2.4	35.3%	6.5%	28.8%	0.7%	1.89	1.39	—
2023	20	ROK MLE	DSL Rangers Red	12	11	38	164	57	15	3	92%	3.2	23.6%	11.4%	12.2%	2.4%	4.26	3.88	—
2023	20	ROK RAW	DSL Rangers Red	12	11	38	164	57	15	3	92%	3.2	34.8%	9.1%	25.6%	1.8%	4.26	2.31	—
2024	21	ROK MLE	DSL Rangers Red	17	0	27	104	23	10	0	0%	1.6	15.0%	12.0%	3.0%	0.0%	0.33	3.35	—
2024	21	ROK MLE	DSL Rangers Red	17	0	27	104	23	10	0	0%	1.6	15.0%	12.0%	3.0%	0.0%	0.33	3.35	—
2024	21	ROK RAW	DSL Rangers Red	17	0	27	104	23	10	0	0%	1.6	22.1%	9.6%	12.5%	0.0%	0.33	2.51	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	TEX	15	0	16	68	15	7	2	0%	1.1	22.9%	10.0%	12.9%	3.0%	4.45	4.45	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	TEX	19	0	20	84	20	8	3	0%	1.1	23.3%	9.5%	13.8%	3.0%	4.38	4.35	+0.0
2028	25	MLB CTX	TEX	9	0	9	38	9	4	1	0%	1.0	23.3%	9.5%	13.8%	3.0%	4.38	4.35	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	0	9	36	8	3	1	0%	1.1	23.3%	9.5%	13.8%	3.0%	4.38	3.97	+0.1
/ 200 IP	—	RAW		190	0	200	844	187	70	23	0%	1.1	23.3%	9.5%	13.8%	3.0%	4.38	3.97	+1.4
Career	—	MLE		45	12	103	421	91	44	5	27%	2.3	21.6%	10.4%	11.3%	1.2%	2.36	3.27	+0.0
/ 200 IP	—	MLE		87	23	200	817	177	85	10	27%	2.3	21.6%	10.4%	11.3%	1.2%	2.36	3.27	+0.5

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
Rayner Urbaez (OGILVIE)	—	—	4.45	22.9%	10.0%	3.0%	—	4.35	23.3%	13.8%	20	-0.10	—	—	—
Jonathan Papelbon R 2005 · 3.93 FIP	24	SW	3.93	23.0%	10.1%	2.7%	.305	1.90	31.3%	26.8%	196	-2.03	1.33	726	87
Kyle Zimmer R 2015 · 3.74 FIP	23	SW	3.74	21.8%	8.6%	2.5%	.293	4.55	20.4%	9.0%	33	+0.81	2.08	276	82
Ryan Conroy R 2021 · 4.01 FIP	24	SU	4.01	22.2%	9.8%	2.8%	.353	4.75	19.3%	6.7%	54	+0.74	4.01	106	81
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	81
Brad Deppermann R 2021 · 4.51 FIP	25	SW	4.51	17.1%	9.6%	3.0%	.289	3.52	20.0%	7.8%	45	-0.99	1.94	143	81
Trent Fennell R 2019 · 4.08 FIP	23	SW	4.08	20.6%	12.2%	2.1%	.328	5.52	19.4%	3.5%	107	+1.44	4.08	163	80
Carlo Reyes R 2022 · 4.06 FIP	24	SW	4.06	20.4%	8.6%	2.9%	.318	3.92	24.1%	12.9%	61	-0.14	2.60	229	79
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	79
Colby Morris R 2021 · 4.11 FIP	24	SU	4.11	20.4%	10.7%	2.5%	.291	5.76	16.2%	4.4%	54	+1.65	4.11	105	78
Tyler Mitzel R 2019 · 4.34 FIP	23	SU	4.34	24.1%	12.0%	3.2%	.245	4.10	22.4%	14.3%	96	-0.24	4.03	142	78
Brandon Beckel R 2024 · 3.75 FIP	22	SU	3.75	19.4%	10.3%	1.8%	.250	4.23	19.5%	10.5%	147	+0.48	3.75	194	77
Ricardo Velez R 2023 · 4.44 FIP	24	SU	4.44	22.4%	10.9%	3.4%	.261	4.09	18.8%	8.1%	138	-0.35	3.83	166	77
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	76
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	76
Stolmy Pimentel R 2014 · 4.13 FIP	24	SU	4.13	25.7%	9.5%	3.6%	.319	4.17	14.8%	4.3%	143	+0.04	3.87	176	76
Kyle Schepel R 2015 · 4.63 FIP	24	SU	4.63	23.1%	10.7%	3.9%	.233	3.64	22.1%	10.4%	120	-0.99	3.54	156	76
Danny Hrbek R 2019 · 3.98 FIP	24	SU	3.98	21.3%	7.5%	3.1%	.312	—	—	—	—	—	3.98	100	76
Garrett McMillan R 2024 · 3.30 FIP	23	SU	3.30	21.2%	8.2%	1.7%	.324	3.53	18.9%	14.6%	48	+0.23	3.30	118	75
William Kempner R 2023 · 4.02 FIP	22	SU	4.02	21.5%	12.2%	2.2%	.277	3.17	28.8%	15.2%	112	-0.85	3.14	173	75
Jimmy Kingsbury R 2023 · 5.11 FIP	24	SW	5.11	18.2%	9.9%	4.2%	.304	3.67	18.0%	9.9%	189	-1.44	3.51	330	75