Bryce Osmond

P Rocket City Trash Pandas

Age 26 RHP 6'3" / 185 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	22	MIX2 levels	23	23	97	4.28	4.51	23.2%	10.9%	—	K 18.0% · BB 12.4% · FIP 5.56
2025	24	MIX2 levels	9	6	20	6.30	5.25	23.6%	12.4%	—	K 12.2% · BB 15.1% · FIP 7.49
2026	25	AALAA	31	8	64	8.20	6.27	22.0%	11.1%	—	K 17.8% · BB 12.3% · FIP 7.04
2027PROJ	26	MLBLAA	1	0	1	5.81	5.81	18.1%	12.2%	-0.0
2028PROJ38% MLB	27	MLBLAA	16	0	17	5.69	5.70	18.6%	11.9%	-0.2
2029PROJ60% MLB	28	MLBLAA	24	0	25	5.64	5.68	18.8%	11.9%	-0.3

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.3, comp-based) · star 0% · didn't stick 96%

CompsColby Morris (age 25) · Carlos Torres (age 26) · Alfonso Sanchez (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 143135vR 127

ERA5.81

FIP5.81

K%18.1%

BB%12.2%

K-BB%5.9%

Proj IP34

Value2027 · WAR

Runs saved vs league avg · 34 IP

Grades · Contract

Scouting Grades

K†4545

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	MIX MLE	2 levels	23	23	97	431	100	47	15	100%	4.2	18.0%	12.4%	5.6%	4.4%	4.28	5.56	—
2023	22	MIX RAW	2 levels	23	23	97	431	100	47	15	100%	4.2	23.2%	10.9%	12.3%	3.5%	4.28	4.51	—
2025	24	MIX MLE	2 levels	9	6	20	89	21	11	4	67%	2.2	12.2%	15.1%	-2.9%	6.4%	6.30	7.49	—
2025	24	MIX MLE	2 levels	9	6	20	89	21	11	4	67%	2.2	12.2%	15.1%	-2.9%	6.4%	6.30	7.49	—
2025	24	MIX RAW	2 levels	9	6	20	89	21	11	4	67%	2.2	23.6%	12.4%	11.2%	4.5%	6.30	5.25	—
2026	25	AA MLE	Rocket City Trash Pandas	31	8	64	305	67	34	18	26%	2.1	17.8%	12.3%	5.5%	7.1%	8.20	7.04	—
2026	25	AA MLE	Rocket City Trash Pandas	31	8	64	305	67	34	18	26%	2.1	17.8%	12.3%	5.5%	7.1%	8.20	7.04	—
2026	25	AA RAW	Rocket City Trash Pandas	31	8	64	305	67	34	18	26%	2.1	22.0%	11.1%	10.8%	5.9%	8.20	6.27	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	LAA	1	0	1	4	1	1	0	0%	1.0	18.1%	12.2%	5.9%	4.2%	5.81	5.81	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	LAA	44	0	46	194	36	23	8	0%	1.0	18.6%	11.9%	6.6%	4.2%	5.69	5.70	-0.6
2029	28	MLB MLE	LAA	40	0	42	175	33	21	7	0%	1.0	18.8%	11.9%	6.9%	4.2%	5.64	5.68	-0.5
2028	27	MLB CTX	LAA	16	0	17	72	13	9	3	0%	1.1	18.6%	11.9%	6.6%	4.2%	5.69	5.70	-0.2
2029	28	MLB CTX	LAA	24	0	25	106	20	13	4	0%	1.0	18.8%	11.9%	6.9%	4.2%	5.64	5.68	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		40	0	42	177	33	21	7	0%	1.0	18.7%	11.9%	6.8%	4.2%	5.66	5.31	-0.4
/ 200 IP	—	RAW		190	0	200	844	157	100	33	0%	1.1	18.7%	11.9%	6.8%	4.2%	5.66	5.31	-1.8
Career	—	MLE		63	37	180	825	143	104	46	59%	2.9	17.3%	12.6%	4.6%	5.6%	5.89	6.31	-0.3
/ 200 IP	—	MLE		70	41	200	915	158	116	51	59%	2.9	17.3%	12.6%	4.6%	5.6%	5.89	6.31	-0.7

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 AARocket City Trash Pandas · 64 IPFIP 5.90 → 7.04 (+1.14)K% 22.0% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.97%	—	×0.810	17.79%
BB% (unintentional) /BF	11.15%	—	×1.100	12.26%
HR / BF /BF	5.90%	÷1.000	×1.200	7.08%

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 5.90 → 7.04, 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 AARocket City Trash Pandas · 16 IPFIP 6.57 → 7.49 (+0.92)K% 15.1% → 12.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.07%	—	×0.810	12.21%
BB% (unintentional) /BF	13.70%	—	×1.100	15.07%
HR / BF /BF	5.48%	÷1.028	×1.200	6.40%

Result: FIP 6.57 → 7.49, 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 A+Tri-City Dust Devils · 84 IPFIP 3.99 → 5.08 (+1.09)K% 23.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.91%	—	×0.770	18.41%
BB% (unintentional) /BF	10.05%	—	×1.150	11.56%
HR / BF /BF	2.99%	÷0.990	×1.250	3.78%

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 98).

Result: FIP 3.99 → 5.08, 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 AARocket City Trash Pandas · 13 IPFIP 6.99 → 8.32 (+1.33)K% 19.0% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.05%	—	×0.810	15.43%
BB% (unintentional) /BF	15.87%	—	×1.100	17.46%
HR / BF /BF	6.35%	÷0.970	×1.200	7.85%

Result: FIP 6.99 → 8.32, 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
Bryce Osmond (OGILVIE)	—	—	5.81	18.1%	12.2%	4.2%	—	5.69	18.7%	6.8%	87	-0.12	—	—	—
Colby Morris R 2022 · 5.76 FIP	25	SW	5.76	16.2%	11.8%	4.6%	.268	—	—	—	—	—	4.11	105	87
Carlos Torres R 2009 · 5.24 FIP	26	SP-	5.24	16.9%	11.5%	3.9%	.284	3.59	18.2%	7.3%	67	-1.65	2.89	604	83
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	78
Cameron Foster R 2024 · 4.83 FIP	25	SW	4.83	17.4%	11.5%	3.2%	.321	3.09	25.5%	17.5%	60	-1.74	2.50	213	78
Victor Santos R 2003 · 5.99 FIP	26	SP-	5.99	12.8%	12.8%	4.3%	.293	4.38	15.4%	7.7%	411	-1.61	4.09	602	77
Taylor Grover R 2017 · 4.93 FIP	26	SW	4.93	20.0%	10.9%	3.9%	.320	4.89	16.2%	8.9%	14	-0.04	3.68	239	75
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	75
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	73
André Rienzo R 2014 · 5.13 FIP	26	SP-	5.13	16.3%	10.6%	3.8%	.324	4.13	17.5%	4.8%	171	-1.00	3.53	321	73
David Griffin R 2022 · 4.71 FIP	26	SP-	4.71	16.6%	9.8%	3.2%	.285	5.83	14.2%	5.0%	81	+1.12	4.43	239	73
Paulshawn Pasqualotto R 2024 · 4.84 FIP	23	SW	4.84	15.6%	9.5%	3.4%	.354	3.77	20.2%	10.8%	111	-1.07	3.73	186	73
Nick Hull R 2024 · 4.62 FIP	24	SW	4.62	19.0%	12.2%	2.9%	.296	5.00	16.8%	6.2%	111	+0.38	4.26	292	73
Michael Knorr R 2024 · 5.56 FIP	24	SP-	5.56	21.6%	12.5%	4.9%	.314	4.95	22.3%	9.7%	83	-0.61	4.30	181	72
Grant Judkins R 2024 · 5.13 FIP	26	SW	5.13	16.8%	9.1%	4.2%	.264	5.80	14.9%	5.8%	124	+0.67	5.13	322	72
Robbie Peto R 2023 · 5.75 FIP	25	SW	5.75	15.3%	13.4%	4.1%	.325	—	—	—	—	—	5.39	232	72
Kaleb Roper R 2022 · 5.67 FIP	26	SW	5.67	17.3%	11.8%	4.6%	.398	—	—	—	—	—	5.67	146	72
Denny Bautista R 2006 · 4.71 FIP	25	SP-	4.71	13.9%	10.8%	2.6%	.298	4.58	17.5%	3.3%	74	-0.13	3.38	238	71
Reid Morgan R 2023 · 6.83 FIP	26	SW	6.83	15.6%	7.1%	7.6%	.322	5.19	17.2%	8.0%	46	-1.64	5.19	154	71
Ranfi Casimiro R 2018 · 4.62 FIP	26	SW	4.62	16.4%	10.7%	2.8%	.285	4.93	8.4%	-0.2%	16	+0.31	3.81	420	71
Carlos Tavera R 2024 · 5.12 FIP	25	SW	5.12	18.3%	13.3%	3.4%	.299	5.43	21.9%	8.8%	29	+0.31	3.85	263	71

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	0.6	40	18.5%	12.0%	1.62	5.71
Dave Stevens ('00)	1.3	50	14.6%	11.3%	1.76	6.02
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*