Ryan Lobus

P Round Rock Express

Age 26 RHP 6'2" / 180 lbs AAA peak 0.2 · 2027

Overview

AAAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX3 levels	27	12	94	2.96	2.47	35.8%	5.9%	—	K 27.0% · BB 7.2% · FIP 3.68
2025	24	AATEX	45	3	67	3.48	2.79	28.9%	9.2%	—	K 23.4% · BB 10.1% · FIP 3.59
2026	25	MIX2 levels	44	0	61	4.90	3.20	24.7%	7.5%	—	K 20.7% · BB 7.6% · FIP 3.71
2027PROJ	26	MLBTEX	1	0	1	4.18	4.18	22.7%	8.4%	0.0
2028PROJ38% MLB	27	MLBTEX	21	0	22	4.22	4.23	22.8%	8.5%	0.1
2029PROJ60% MLB	28	MLBTEX	30	0	31	4.29	4.32	22.7%	8.7%	0.1

Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.2 / P90 1.7, comp-based) · star 0% · didn't stick 92%

CompsR.J. Alaniz (age 26) · Colton Murray (age 26) · Jhan Mariñez (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 113104vR 96

ERA4.18

FIP4.18

K%22.7%

BB%8.4%

K-BB%14.4%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

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	22	ROK MLE	ACL Rangers	4	0	4	24	6	4	1	0%	1.0	25.0%	16.7%	8.3%	4.2%	18.00	5.39	—
2023	22	ROK RAW	ACL Rangers	4	0	4	24	6	4	1	0%	1.0	25.0%	16.7%	8.3%	4.2%	18.00	6.35	—
2024	23	MIX MLE	3 levels	27	12	94	374	134	22	11	44%	3.5	27.0%	7.2%	19.7%	3.5%	2.96	3.68	—
2024	23	MIX MLE	3 levels	27	12	94	374	134	22	11	44%	3.5	27.0%	7.2%	19.7%	3.5%	2.96	3.68	—
2024	23	MIX RAW	3 levels	27	12	94	374	134	22	11	44%	3.5	35.8%	5.9%	29.9%	2.9%	2.96	2.47	—
2025	24	AA MLE	Frisco RoughRiders	45	3	67	284	82	26	5	7%	1.5	23.4%	10.1%	13.3%	2.2%	3.48	3.59	—
2025	24	AA MLE	Frisco RoughRiders	45	3	67	284	82	26	5	7%	1.5	23.4%	10.1%	13.3%	2.2%	3.48	3.59	—
2025	24	AA RAW	Frisco RoughRiders	45	3	67	284	82	26	5	7%	1.5	28.9%	9.2%	19.7%	1.8%	3.48	2.79	—
2026	25	MIX MLE	2 levels	44	0	61	267	66	20	6	0%	1.4	20.7%	7.6%	13.1%	2.5%	4.90	3.71	—
2026	25	MIX MLE	2 levels	44	0	61	267	66	20	6	0%	1.4	20.7%	7.6%	13.1%	2.5%	4.90	3.71	—
2026	25	MIX RAW	2 levels	44	0	61	267	66	20	6	0%	1.4	24.7%	7.5%	17.2%	2.2%	4.90	3.20	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	TEX	1	0	1	4	1	0	0	0%	1.0	22.7%	8.4%	14.4%	2.8%	4.18	4.18	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	TEX	56	0	58	246	56	21	7	0%	1.0	22.8%	8.5%	14.3%	2.9%	4.22	4.23	+0.2
2029	28	MLB MLE	TEX	49	0	52	219	50	19	7	0%	1.1	22.7%	8.7%	14.0%	3.0%	4.29	4.32	+0.1
2030	29	MLB MLE	TEX	45	0	47	198	45	18	6	0%	1.0	22.5%	9.0%	13.5%	3.2%	4.39	4.45	+0.1
2028	27	MLB CTX	TEX	21	0	22	93	21	8	3	0%	1.0	22.8%	8.5%	14.3%	2.9%	4.22	4.23	+0.1
2029	28	MLB CTX	TEX	30	0	31	131	30	11	4	0%	1.0	22.7%	8.7%	14.0%	3.0%	4.29	4.32	+0.1
2030	29	MLB CTX	TEX	31	0	33	139	31	12	4	0%	1.1	22.5%	9.0%	13.5%	3.2%	4.39	4.45	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		82	0	86	363	82	32	11	0%	1.0	22.6%	8.8%	13.9%	3.0%	4.31	3.97	+0.6
/ 200 IP	—	RAW		190	0	200	844	191	74	26	0%	1.1	22.6%	8.8%	13.9%	3.0%	4.31	3.97	+1.4
Career	—	MLE		120	15	226	949	229	80	27	12%	1.9	24.1%	8.4%	15.7%	2.9%	3.90	3.71	+0.4
/ 200 IP	—	MLE		106	13	200	839	202	71	24	12%	1.9	24.1%	8.4%	15.7%	2.9%	3.90	3.71	+0.5

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 AAARound Rock Express · 29 IPFIP 3.44 → 3.82 (+0.38)K% 25.2% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.19%	—	×0.860	21.66%
BB% (unintentional) /BF	6.67%	—	×0.900	6.00%
HR / BF /BF	2.96%	÷1.000	×1.100	3.26%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. 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 3.44 → 3.82, 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 AAFrisco RoughRiders · 32 IPFIP 2.94 → 3.60 (+0.66)K% 24.2% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.810	19.64%
BB% (unintentional) /BF	8.33%	—	×1.100	9.17%
HR / BF /BF	1.52%	÷1.000	×1.200	1.82%

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 2.94 → 3.60, 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 AAFrisco RoughRiders · 67 IPFIP 2.79 → 3.59 (+0.80)K% 28.9% → 23.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.87%	—	×0.810	23.39%
BB% (unintentional) /BF	9.15%	—	×1.100	10.07%
HR / BF /BF	1.76%	÷0.976	×1.200	2.16%

Result: FIP 2.79 → 3.59, 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+Hickory Crawdads · 71 IPFIP 2.50 → 3.67 (+1.17)K% 35.1% → 27.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.11%	—	×0.770	27.03%
BB% (unintentional) /BF	6.38%	—	×1.150	7.34%
HR / BF /BF	2.84%	÷1.014	×1.250	3.50%

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 103).

Result: FIP 2.50 → 3.67, 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 ADown East Wood Ducks · 18 IPFIP 2.37 → 3.75 (+1.39)K% 36.2% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.23%	—	×0.740	26.81%
BB% (unintentional) /BF	5.80%	—	×1.180	6.84%
HR / BF /BF	2.90%	÷1.008	×1.300	3.74%

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 102).

Result: FIP 2.37 → 3.75, 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 AAFrisco RoughRiders · 6 IPFIP 1.81 → 2.78 (+0.96)K% 43.5% → 35.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.48%	—	×0.810	35.22%
BB% (unintentional) /BF	0.00%	—	×1.100	0.00%
HR / BF /BF	4.35%	÷1.080	×1.200	4.83%

Result: FIP 1.81 → 2.78, 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 ROKACL Rangers · 4 IPFIP 5.39 → 7.15 (+1.77)K% 25.0% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.680	17.00%
BB% (unintentional) /BF	16.67%	—	×1.250	20.83%
HR / BF /BF	4.17%	÷1.124	×1.400	5.19%

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 125).

Result: FIP 5.39 → 7.15, 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
Ryan Lobus (OGILVIE)	—	—	—	—	—	2.8%	—	4.33	22.7%	13.9%	157	+0.15	—	—	—
R.J. Alaniz R 2017 · 3.91 FIP	26	SU	3.91	20.7%	8.9%	2.6%	.318	3.28	23.8%	15.0%	96	-0.63	2.45	362	88
Colton Murray R 2016 · 3.97 FIP	26	SU	3.97	21.2%	9.4%	2.7%	.295	4.27	21.8%	13.1%	41	+0.30	3.34	187	86
Jhan Mariñez R 2015 · 3.50 FIP	26	SU	3.50	23.1%	9.3%	2.1%	.244	3.70	18.9%	11.1%	168	+0.20	3.16	253	86
Matt Pushard R 2024 · 3.87 FIP	26	SU	3.87	24.1%	8.9%	3.0%	.242	3.29	22.2%	14.0%	115	-0.58	2.84	220	85
Joe Navilhon R 2019 · 3.23 FIP	26	SU	3.23	20.5%	7.7%	1.6%	.322	4.28	23.4%	16.7%	99	+1.05	2.25	273	85
Simon Castro R 2015 · 3.28 FIP	27	SU	3.28	26.4%	8.5%	2.4%	.320	3.58	26.0%	17.6%	128	+0.30	3.01	185	85
Santiago Casilla R 2007 · 3.58 FIP	27	SU	3.58	23.7%	7.8%	2.7%	.257	3.60	19.8%	10.7%	154	+0.02	2.76	647	85
Joe Broussard R 2017 · 3.83 FIP	26	SU	3.83	23.5%	7.9%	3.1%	.316	3.72	21.1%	12.0%	95	-0.11	2.62	304	85
Shay Schanaman R 2024 · 4.34 FIP	24	SU	4.34	21.0%	7.6%	3.7%	.292	6.05	16.4%	2.8%	90	+1.71	4.34	148	85
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	85
Seth Simmons R 2015 · 3.07 FIP	27	SU	3.07	23.8%	9.7%	1.4%	.277	4.87	16.6%	7.6%	175	+1.80	3.07	251	84
Jose Veras R 2008 · 3.67 FIP	27	SU	3.67	24.9%	9.1%	2.8%	.281	4.10	23.8%	11.7%	169	+0.43	3.37	422	84
Madison Younginer IV R 2017 · 4.22 FIP	26	SU	4.22	23.0%	9.8%	3.3%	.370	4.73	14.0%	-5.3%	27	+0.51	3.08	219	84
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	84
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	84
Trent Harris R 2024 · 3.45 FIP	25	SU	3.45	26.9%	9.5%	2.6%	.258	3.36	24.7%	16.7%	121	-0.09	3.06	198	84
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	84
Shawn Armstrong R 2017 · 4.21 FIP	26	SU	4.21	22.1%	9.2%	3.3%	.282	3.18	26.9%	17.2%	144	-1.03	1.79	653	84
Fernery Ozuna R 2022 · 3.84 FIP	26	SU	3.84	22.4%	8.7%	2.8%	.324	5.65	19.0%	7.4%	49	+1.81	3.84	157	83
Stephen Perakslis R 2017 · 3.07 FIP	26	SW	3.07	21.3%	8.2%	1.3%	.313	5.15	11.8%	5.9%	42	+2.08	3.07	211	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	1.1	57	22.7%	8.6%	1.15	4.26
Shawn Tolleson ('16)	1.1	54	23.1%	8.3%	1.28	3.92
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*