Carson Hobbs

P Tulsa Drillers

Age 25 RHP 6'1" / 197 lbs AA

Overview

AAPROSPECT

ETA2028MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	MIX3 levels	31	1	42	4.25	3.50	30.0%	11.1%	—	K 18.9% · BB 13.6% · FIP 5.63
2025	23	MIX2 levels	42	0	53	2.04	2.65	31.3%	10.4%	—	K 24.7% · BB 11.8% · FIP 3.54
2026	24	AALAD	49	1	65	3.31	3.54	24.5%	10.5%	—	K 19.9% · BB 11.5% · FIP 4.31
2027PROJ	25	MLBLAD	1	0	1	4.79	4.79	21.4%	12.3%	-0.0
2028PROJ44% MLB	26	MLBLAD	23	0	24	4.73	4.72	21.8%	12.0%	-0.0
2029PROJ63% MLB	27	MLBLAD	29	0	30	4.72	4.73	21.9%	11.8%	-0.1

Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.3 / P90 1.0, comp-based) · star 0% · didn't stick 96%

CompsNolan Riggs (age 25) · Ben Hecht (age 24) · Carlos Fisher (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 124116vR 108

ERA4.79

FIP4.79

K%21.4%

BB%12.3%

K-BB%9.0%

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)
2024	22	MIX MLE	3 levels	31	1	42	180	54	20	5	3%	1.4	18.9%	13.6%	5.3%	4.4%	4.25	5.63	—
2024	22	MIX MLE	3 levels	31	1	42	180	54	20	5	3%	1.4	18.9%	13.6%	5.3%	4.4%	4.25	5.63	—
2024	22	MIX RAW	3 levels	31	1	42	180	54	20	5	3%	1.4	30.0%	11.1%	18.9%	2.8%	4.25	3.50	—
2025	23	MIX MLE	2 levels	42	0	53	201	63	21	3	0%	1.3	24.7%	11.8%	12.9%	1.9%	2.04	3.54	—
2025	23	MIX MLE	2 levels	42	0	53	201	63	21	3	0%	1.3	24.7%	11.8%	12.9%	1.9%	2.04	3.54	—
2025	23	MIX RAW	2 levels	42	0	53	201	63	21	3	0%	1.3	31.3%	10.4%	20.9%	1.5%	2.04	2.65	—
2026	24	AA MLE	Tulsa Drillers	49	1	65	277	68	29	6	2%	1.3	19.9%	11.5%	8.4%	2.6%	3.31	4.31	—
2026	24	AA MLE	Tulsa Drillers	49	1	65	277	68	29	6	2%	1.3	19.9%	11.5%	8.4%	2.6%	3.31	4.31	—
2026	24	AA RAW	Tulsa Drillers	49	1	65	277	68	29	6	2%	1.3	24.5%	10.5%	14.1%	2.2%	3.31	3.54	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	LAD	1	0	1	4	1	1	0	0%	1.0	21.4%	12.3%	9.0%	2.8%	4.79	4.79	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	LAD	52	0	54	230	50	28	7	0%	1.0	21.8%	12.0%	9.8%	2.8%	4.73	4.72	-0.1
2029	27	MLB MLE	LAD	46	0	48	202	44	24	6	0%	1.0	21.9%	11.8%	10.0%	2.9%	4.72	4.73	-0.1
2030	28	MLB MLE	LAD	42	0	44	186	41	22	6	0%	1.1	21.8%	11.9%	10.0%	3.0%	4.76	4.79	-0.1
2031	29	MLB MLE	LAD	39	0	40	171	37	21	5	0%	1.0	21.6%	12.0%	9.6%	3.2%	4.85	4.91	-0.2
2028	26	MLB CTX	LAD	23	0	24	101	22	12	3	0%	1.0	21.8%	12.0%	9.8%	2.8%	4.73	4.72	-0.0
2029	27	MLB CTX	LAD	29	0	30	127	28	15	4	0%	1.0	21.9%	11.8%	10.0%	2.9%	4.72	4.73	-0.1
2030	28	MLB CTX	LAD	31	0	33	139	30	17	4	0%	1.1	21.8%	11.9%	10.0%	3.0%	4.76	4.79	-0.1
2031	29	MLB CTX	LAD	31	0	33	139	30	17	4	0%	1.1	21.6%	12.0%	9.6%	3.2%	4.85	4.91	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		115	0	121	509	111	61	15	0%	1.0	21.8%	11.9%	9.8%	3.0%	4.77	4.42	+0.2
/ 200 IP	—	RAW		190	0	200	844	184	101	25	0%	1.1	21.8%	11.9%	9.8%	3.0%	4.77	4.42	+0.3
Career	—	MLE		122	2	161	658	139	80	19	2%	1.3	21.1%	12.2%	8.9%	2.9%	3.14	4.44	-0.5
/ 200 IP	—	MLE		152	2	200	819	173	100	23	2%	1.3	21.1%	12.2%	8.9%	2.9%	3.14	4.44	-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 AATulsa Drillers · 65 IPFIP 3.54 → 4.31 (+0.76)K% 24.5% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.55%	—	×0.810	19.88%
BB% (unintentional) /BF	10.47%	—	×1.100	11.52%
HR / BF /BF	2.17%	÷1.000	×1.200	2.60%

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 3.54 → 4.31, 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 A+Great Lakes Loons · 30 IPFIP 2.84 → 3.94 (+1.10)K% 32.1% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.14%	—	×0.770	24.75%
BB% (unintentional) /BF	11.61%	—	×1.150	13.35%
HR / BF /BF	1.79%	÷0.992	×1.250	2.25%

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 2.84 → 3.94, 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 AATulsa Drillers · 23 IPFIP 2.29 → 3.05 (+0.76)K% 30.3% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.34%	—	×0.810	24.57%
BB% (unintentional) /BF	8.99%	—	×1.100	9.89%
HR / BF /BF	1.12%	÷0.957	×1.200	1.41%

Result: FIP 2.29 → 3.05, 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+Great Lakes Loons · 24 IPFIP 4.52 → 5.63 (+1.11)K% 24.5% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.55%	—	×0.770	18.90%
BB% (unintentional) /BF	11.82%	—	×1.150	13.59%
HR / BF /BF	3.64%	÷1.036	×1.250	4.39%

Result: FIP 4.52 → 5.63, 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 ARancho Cucamonga Quakes · 12 IPFIP 2.74 → 3.98 (+1.24)K% 34.0% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.04%	—	×0.740	25.19%
BB% (unintentional) /BF	10.64%	—	×1.180	12.55%
HR / BF /BF	2.13%	÷1.072	×1.300	2.58%

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 114).

Result: FIP 2.74 → 3.98, 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 ROKACL Dodgers · 6 IPFIP 0.16 → 1.73 (+1.57)K% 47.8% → 32.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.83%	—	×0.680	32.52%
BB% (unintentional) /BF	8.70%	—	×1.250	10.87%
HR / BF /BF	0.00%	÷0.942	×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 88).

Result: FIP 0.16 → 1.73, 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
Carson Hobbs (OGILVIE)	—	—	—	—	—	2.8%	—	4.74	21.8%	9.9%	146	-0.05	—	—	—
Nolan Riggs R 2018 · 4.49 FIP	25	SU	4.49	20.7%	14.0%	2.5%	.300	—	—	—	—	—	2.36	132	90
Ben Hecht R 2019 · 4.51 FIP	24	SU	4.51	22.7%	12.9%	3.1%	.293	7.98	14.1%	-11.4%	13	+3.47	4.39	155	90
Carlos Fisher R 2009 · 3.90 FIP	26	SU	3.90	21.2%	12.8%	1.8%	.317	3.80	18.2%	8.1%	46	-0.10	2.48	245	89
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	89
Dylan Hall R 2023 · 3.98 FIP	25	SU	3.98	21.0%	13.2%	1.8%	.305	7.24	15.1%	2.4%	58	+3.26	3.47	153	88
Nick Ernst R 2022 · 5.05 FIP	25	SU	5.05	21.9%	14.6%	3.5%	.275	—	—	—	—	—	3.56	117	88
Rhiner Cruz R 2012 · 4.80 FIP	25	SU	4.80	18.2%	11.5%	3.2%	.335	4.81	10.2%	-1.0%	21	+0.01	3.21	127	88
Cody Tucker R 2024 · 4.97 FIP	25	SU	4.97	22.0%	12.0%	4.0%	.272	5.36	15.8%	-1.9%	40	+0.39	4.97	105	88
Taylor Floyd R 2023 · 4.34 FIP	25	SU	4.34	21.7%	10.8%	3.1%	.331	4.61	18.4%	8.9%	192	+0.27	3.48	359	88
Vinnie Chulk R 2004 · 4.26 FIP	25	SU	4.26	17.7%	10.5%	2.4%	.308	3.95	16.9%	9.6%	171	-0.31	2.97	271	88
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	87
Esmerling Vasquez R 2009 · 3.86 FIP	25	SU	3.86	18.9%	11.3%	1.7%	.296	4.30	17.3%	4.7%	116	+0.44	3.70	204	87
Chase Plymell R 2023 · 4.23 FIP	25	SU	4.23	19.2%	13.0%	2.0%	.330	4.49	14.0%	6.3%	162	+0.26	3.81	291	87
Pat Light R 2016 · 4.10 FIP	25	SU	4.10	21.1%	13.1%	2.1%	.276	4.63	11.8%	-2.3%	55	+0.53	4.10	172	87
Austin Ross R 2019 · 4.41 FIP	24	SU	4.41	20.7%	9.6%	3.4%	.281	5.19	21.2%	5.7%	55	+0.78	4.41	121	87
Alec Barger R 2023 · 4.44 FIP	25	SU	4.44	21.5%	14.4%	2.4%	.326	4.67	18.6%	7.5%	79	+0.23	3.85	242	86
Kevin Kopps R 2022 · 4.56 FIP	25	SU	4.56	20.2%	15.1%	2.3%	.278	4.40	16.3%	4.0%	182	-0.16	3.45	237	86
Cameron Gann R 2017 · 4.22 FIP	24	SU	4.22	21.4%	12.4%	2.5%	.296	5.36	21.1%	6.8%	23	+1.14	3.58	146	86
Ryan Conroy R 2022 · 4.75 FIP	25	SU	4.75	19.3%	12.6%	3.1%	.361	—	—	—	—	—	4.01	106	86
Luis Ramirez R 2016 · 3.71 FIP	24	SU	3.71	24.0%	12.6%	1.9%	.286	—	—	—	—	—	3.71	104	86

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	1.3	51	21.7%	12.0%	1.14	4.77
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
David Aardsma ('15)	1.7	48	23.1%	12.4%	1.09	4.27
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*