Luke Murphy

P Rocket City Trash Pandas

Age 27 RHP 6'5" / 190 lbs AA peak 0.2 · 2027

Overview

AARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX2 levels	43	0	53	3.54	2.65	29.3%	6.6%	—	K 23.2% · BB 7.3% · FIP 3.54
2025	25	MIX2 levels	37	2	45	9.33	5.00	21.8%	10.0%	—	K 18.3% · BB 9.4% · FIP 5.17
2026	26	MIX2 levels	56	0	58	2.79	2.50	28.4%	8.5%	1.4	K 24.6% · BB 8.9% · FIP 2.88
2027PROJ	27	MLBLAA	26	0	27	4.28	4.32	22.1%	9.2%	0.1
2028PROJ80% MLB	28	MLBLAA	24	0	25	4.36	4.40	22.1%	9.3%	0.0

Last 3 seasons WAR 1.4 · Next 2 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo67

K%52

xwOBA vs43

Form6.75 ERA (proj 4.28) · K 22.5% (proj 22.1%) · BB 12.4% (proj 9.2%) ▼ last 90d · 20 IP through Oct 27

Career WAR0.0 WAR median (P10 -0.2 / P90 0.8, comp-based) · star 0% · didn't stick 94%

CompsC.C. Lee (age 27) · Tom Wilhelmsen (age 27) · Neil Wagner (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.28

FIP4.32

K%22.1%

BB%9.2%

K-BB%13.0%

Proj IP38

Value2027 · WAR

Runs saved vs league avg · 38 IP

Grades · Statcast · Contract

Scouting Grades

K†5555

Statcast Percentiles

FB Velo

p6795.7

Whiff%

p2722.0%

p5222.5%

xwOBA vs

p430.320

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)
2021	21	A+ MLE	Tri-City Dust Devils	7	0	9	35	15	1	0	0%	1.3	42.9%	2.9%	40.0%	0.0%	3.00	-0.16	—
2021	21	A+ RAW	Tri-City Dust Devils	7	0	9	35	15	1	0	0%	1.3	42.9%	2.9%	40.0%	0.0%	3.00	0.10	—
2022	22	AA MLE	Rocket City Trash Pandas	37	0	45	181	52	26	0	0%	1.2	23.3%	15.8%	7.5%	0.0%	2.62	3.14	—
2022	22	AA RAW	Rocket City Trash Pandas	37	0	45	181	52	26	0	0%	1.2	28.7%	14.4%	14.4%	0.0%	2.62	2.52	—
2023	23	AA MLE	Rocket City Trash Pandas	44	1	49	223	62	27	4	2%	1.1	22.5%	13.3%	9.2%	2.2%	4.96	4.10	—
2023	23	AA RAW	Rocket City Trash Pandas	44	1	49	223	62	27	4	2%	1.1	27.8%	12.1%	15.7%	1.8%	4.96	3.28	—
2024	24	MIX MLE	2 levels	43	0	53	229	67	15	5	0%	1.2	23.2%	7.3%	15.9%	2.7%	3.54	3.54	—
2024	24	MIX MLE	2 levels	43	0	53	229	67	15	5	0%	1.2	23.2%	7.3%	15.9%	2.7%	3.54	3.54	—
2024	24	MIX RAW	2 levels	43	0	53	229	67	15	5	0%	1.2	29.3%	6.6%	22.7%	2.2%	3.54	2.65	—
2025	25	MIX MLE	2 levels	37	2	45	229	50	23	9	5%	1.2	18.3%	9.4%	9.0%	4.4%	9.33	5.17	—
2025	25	MIX MLE	2 levels	37	2	45	229	50	23	9	5%	1.2	18.3%	9.4%	9.0%	4.4%	9.33	5.17	—
2025	25	MIX RAW	2 levels	37	2	45	229	50	23	9	5%	1.2	21.8%	10.0%	11.8%	3.9%	9.33	5.00	—
2026	26	MIX MLE	2 levels	56	0	58	236	67	20	3	0%	1.0	24.6%	8.9%	15.8%	1.3%	2.79	2.88	+1.2
2026	26	MIX MLE	2 levels	56	0	58	236	67	20	3	0%	1.0	24.6%	8.9%	15.8%	1.3%	2.79	2.88	+1.2
2026	26	MIX RAW	2 levels	56	0	58	236	67	20	3	0%	1.0	28.4%	8.5%	19.9%	1.3%	2.79	2.50	+1.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			22	0	20	89	20	11	2	0%	0.9	22.5%	12.4%	10.1%	2.2%	6.75	4.05	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	LAA	26	0	27	114	25	10	3	0%	1.0	22.1%	9.2%	13.0%	2.8%	4.28	4.32	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	LAA	30	0	31	132	29	12	4	0%	1.0	22.1%	9.3%	12.8%	2.9%	4.36	4.40	+0.1
2028	28	MLB CTX	LAA	24	0	25	106	23	10	3	0%	1.0	22.1%	9.3%	12.8%	2.9%	4.36	4.40	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		46	0	45	195	43	21	5	0%	1.0	22.3%	10.7%	11.6%	2.6%	5.42	4.01	+0.3
/ 200 IP	—	RAW		204	0	200	865	191	93	22	0%	1.0	22.3%	10.7%	11.6%	2.6%	5.42	4.01	+1.3
Career	—	MLE		224	3	259	1133	260	118	24	1%	1.2	23.0%	10.5%	12.5%	2.2%	4.48	3.66	+0.2
/ 200 IP	—	MLE		173	2	200	874	201	91	19	1%	1.2	23.0%	10.5%	12.5%	2.2%	4.48	3.66	+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 · 38 IPFIP 1.55 → 2.21 (+0.67)K% 32.0% → 25.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.97%	—	×0.810	25.90%
BB% (unintentional) /BF	6.12%	—	×1.100	6.73%
HR / BF /BF	0.68%	÷1.000	×1.200	0.82%

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 1.55 → 2.21, 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 AAASalt Lake Bees · 29 IPFIP 5.45 → 5.80 (+0.34)K% 19.0% → 16.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.99%	—	×0.860	16.33%
BB% (unintentional) /BF	12.03%	—	×0.900	10.82%
HR / BF /BF	4.43%	÷0.989	×1.100	4.93%

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 98).

Result: FIP 5.45 → 5.80, 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 · 17 IPFIP 2.98 → 3.76 (+0.78)K% 28.2% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.17%	—	×0.810	22.82%
BB% (unintentional) /BF	5.63%	—	×1.100	6.20%
HR / BF /BF	2.82%	÷1.028	×1.200	3.29%

Result: FIP 2.98 → 3.76, 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 AARocket City Trash Pandas · 32 IPFIP 3.69 → 4.59 (+0.90)K% 24.7% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.67%	—	×0.810	19.98%
BB% (unintentional) /BF	6.67%	—	×1.100	7.33%
HR / BF /BF	3.33%	÷0.976	×1.200	4.10%

Result: FIP 3.69 → 4.59, 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+Tri-City Dust Devils · 21 IPFIP 0.69 → 1.55 (+0.86)K% 38.0% → 29.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.97%	—	×0.770	29.24%
BB% (unintentional) /BF	6.33%	—	×1.150	7.28%
HR / BF /BF	0.00%	÷0.916	×1.250	0.00%

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 83).

Result: FIP 0.69 → 1.55, 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 · 49 IPFIP 3.27 → 4.10 (+0.83)K% 27.8% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.80%	—	×0.810	22.52%
BB% (unintentional) /BF	12.11%	—	×1.100	13.32%
HR / BF /BF	1.79%	÷0.970	×1.200	2.22%

Result: FIP 3.27 → 4.10, 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).

2022 AARocket City Trash Pandas · 45 IPFIP 2.49 → 3.14 (+0.64)K% 28.7% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.73%	—	×0.810	23.27%
BB% (unintentional) /BF	14.36%	—	×1.100	15.80%
HR / BF /BF	0.00%	÷1.131	×1.200	0.00%

Result: FIP 2.49 → 3.14, 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).

2021 A+Tri-City Dust Devils · 9 IPFIP -0.16 → 0.73 (+0.89)K% 42.9% → 33.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.86%	—	×0.770	33.00%
BB% (unintentional) /BF	2.86%	—	×1.150	3.29%
HR / BF /BF	0.00%	÷0.923	×1.250	0.00%

Result: FIP -0.16 → 0.73, 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
Luke Murphy (OGILVIE)	—	—	4.32	22.1%	9.2%	2.8%	—	4.40	22.1%	12.8%	31	+0.08	—	—	—
C.C. Lee R 2014 · 3.77 FIP	27	SU	3.77	20.5%	8.7%	2.4%	.310	2.80	25.7%	17.6%	96	-0.97	2.59	149	89
Tom Wilhelmsen R 2011 · 3.28 FIP	27	SU	3.28	22.1%	9.6%	1.5%	.253	3.18	22.9%	13.4%	218	-0.10	2.72	398	88
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	85
Taylor Williams R 2018 · 3.52 FIP	27	SU	3.52	24.2%	8.9%	2.4%	.309	4.35	22.5%	12.7%	108	+0.83	2.51	309	85
Matt Ramsey R 2017 · 3.25 FIP	27	SU	3.25	24.2%	9.6%	1.8%	.330	3.21	23.6%	14.6%	81	-0.04	2.42	125	85
Fernando Rodriguez Jr. R 2011 · 3.85 FIP	27	SU	3.85	24.7%	10.8%	2.7%	.315	3.90	25.2%	16.5%	70	+0.05	3.34	335	85
Marcos Mateo R 2011 · 3.40 FIP	27	SU	3.40	25.5%	10.2%	2.1%	.361	—	—	—	—	—	3.12	104	85
Josh Lueke R 2011 · 3.24 FIP	26	SU	3.24	20.4%	8.5%	1.4%	.323	4.75	18.7%	12.4%	52	+1.51	2.29	191	84
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	84
Jason Motte R 2009 · 4.62 FIP	27	SU	4.62	22.1%	9.0%	4.1%	.297	2.84	26.9%	21.0%	192	-1.78	2.22	387	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
Francisco Del Rosario R 2007 · 3.93 FIP	26	SU	3.93	19.7%	9.4%	2.4%	.356	—	—	—	—	—	3.93	194	83
Michael Dimock R 2017 · 4.12 FIP	27	SU	4.12	18.9%	7.8%	2.9%	.339	3.37	23.5%	12.8%	29	-0.75	3.08	166	83
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	83
José A. Váldez R 2017 · 4.39 FIP	27	SU	4.39	21.6%	8.3%	3.8%	.325	4.15	18.8%	6.4%	153	-0.24	4.02	328	83
Jason Adam R 2019 · 3.39 FIP	27	SU	3.39	24.2%	9.0%	2.2%	.237	2.64	33.1%	24.9%	88	-0.75	2.42	396	83
Blake Smith R 2015 · 3.17 FIP	27	SU	3.17	23.3%	10.5%	1.3%	.290	3.59	22.4%	13.8%	71	+0.42	3.17	124	82
Jack Hartman R 2024 · 4.34 FIP	26	SU	4.34	20.9%	8.8%	3.4%	.310	4.29	17.6%	5.6%	46	-0.05	3.46	161	81
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	81
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	81

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	0.4	30	22.2%	10.0%	1.06	4.86
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Jacob Barnes ('25)	1.7	48	22.0%	9.2%	1.15	4.79
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*