Gavin Stone

P Oklahoma City Comets

Age 28 RHP 6'1" / 175 lbs AAA peak 1.5 · 2028 ILInjured 60-Day (D60)

Overview

AAASPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	24	MIX2 levels	29	23	132	5.74	4.26	24.4%	10.1%	1.8	K 21.5% · BB 9.3% · FIP 4.43
2024	25	MLBLAD	25	25	140	3.53	3.91	20.0%	6.4%	2.5
2026	27	AAALAD	6	6	15	5.28	2.84	34.4%	6.6%	—	K 29.6% · BB 5.9% · FIP 3.33
2027PROJ	28	MLBLAD	6	6	38	4.04	4.12	23.3%	7.3%	0.6
2028PROJ61% MLB	29	MLBLAD	12	12	72	4.19	4.29	22.7%	7.6%	0.9
2029PROJ72% MLB	30	MLBLAD	12	12	75	4.37	4.49	22.0%	7.9%	0.8

Last 3 seasons WAR 4.3 · Next 3 projected WAR 2.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

FB Velo55

xwOBA vs50

K%35

CompsBrian Edgington (age 25) · Omar Bencomo (age 28) · Erik Hiljus (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109101vR 93

ERA4.04

FIP4.12

K%23.3%

BB%7.3%

K-BB%15.9%

Proj IP84

Value2027 · WAR

Runs saved vs league avg · 84 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL6060

CMD5050

K†5555

Statcast Percentiles

FB Velo

p5594.9

Whiff%

p4624.7%

p3520.0%

xwOBA vs

p500.312

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	22	MIX MLE	2 levels	23	22	91	378	138	25	7	96%	4.0	27.3%	7.8%	19.5%	2.5%	3.76	3.15	—
2021	22	MIX RAW	2 levels	23	22	91	378	138	25	7	96%	4.0	36.5%	6.6%	29.9%	1.9%	3.76	1.89	—
2022	23	MIX MLE	3 levels	26	25	122	496	168	44	3	96%	4.7	27.7%	9.7%	17.9%	0.7%	1.48	2.39	—
2022	23	MIX RAW	3 levels	26	25	122	496	168	44	3	96%	4.7	33.9%	8.9%	25.0%	0.6%	1.48	1.74	—
2023	24	MIX MLE	2 levels	29	23	132	583	142	59	20	79%	4.5	21.5%	9.3%	12.1%	3.6%	5.74	4.43	+1.5
2023	24	MIX RAW	2 levels	29	23	132	583	142	59	20	79%	4.5	24.4%	10.1%	14.2%	3.4%	5.74	4.26	+1.8
2024	25	MLB MLE	Los Angeles Dodgers	25	25	140	580	116	37	18	100%	5.6	20.0%	6.4%	13.6%	3.0%	3.53	3.85	+2.6
2024	25	MLB MLE	Los Angeles Dodgers	25	25	140	580	116	37	18	100%	5.6	20.0%	6.4%	13.6%	3.0%	3.53	3.85	+2.6
2024	25	MLB RAW	Los Angeles Dodgers	25	25	140	580	116	37	18	100%	5.6	20.0%	6.4%	13.6%	3.1%	3.53	3.91	+2.5
2026	27	AAA MLE	Oklahoma City Comets	6	6	15	61	21	4	2	100%	2.6	29.6%	5.9%	23.7%	3.6%	5.28	3.33	—
2026	27	AAA MLE	Oklahoma City Comets	6	6	15	61	21	4	2	100%	2.6	29.6%	5.9%	23.7%	3.6%	5.28	3.33	—
2026	27	AAA RAW	Oklahoma City Comets	6	6	15	61	21	4	2	100%	2.6	34.4%	6.6%	27.9%	3.3%	5.28	2.84	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			33	29	171	732	138	50	26	88%	5.2	18.9%	6.8%	12.0%	3.6%	4.52	4.34	+2.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	LAD	6	6	38	160	37	12	5	100%	6.3	23.3%	7.3%	15.9%	3.1%	4.04	4.12	+0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	LAD	20	20	119	503	114	38	16	100%	6.0	22.7%	7.6%	15.1%	3.2%	4.19	4.29	+1.6
2029	30	MLB MLE	LAD	17	17	105	443	97	35	15	100%	6.2	22.0%	7.9%	14.1%	3.4%	4.37	4.49	+1.1
2030	31	MLB MLE	LAD	15	15	93	391	83	32	14	100%	6.2	21.2%	8.2%	13.0%	3.6%	4.58	4.72	+0.7
2031	32	MLB MLE	LAD	13	13	81	340	69	29	13	100%	6.2	20.4%	8.6%	11.8%	3.9%	4.82	4.98	+0.4
2032	33	MLB MLE	LAD	11	11	68	289	57	26	12	100%	6.2	19.6%	9.1%	10.5%	4.2%	5.08	5.26	+0.1
2028	29	MLB CTX	LAD	12	12	72	304	69	23	10	100%	6.0	22.7%	7.6%	15.1%	3.2%	4.19	4.29	+0.9
2029	30	MLB CTX	LAD	12	12	75	317	70	25	11	100%	6.2	22.0%	7.9%	14.1%	3.4%	4.37	4.49	+0.8
2030	31	MLB CTX	LAD	12	12	73	308	65	25	11	100%	6.1	21.2%	8.2%	13.0%	3.6%	4.58	4.72	+0.6
2031	32	MLB CTX	LAD	11	11	68	287	59	25	11	100%	6.2	20.4%	8.6%	11.8%	3.9%	4.82	4.98	+0.3
2032	33	MLB CTX	LAD	10	10	60	253	50	23	11	100%	6.0	19.6%	9.1%	10.5%	4.2%	5.08	5.26	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		91	87	520	2202	450	171	79	96%	5.7	20.4%	7.8%	12.7%	3.6%	4.56	4.34	+6.5
/ 200 IP	—	RAW		35	34	200	848	173	66	30	96%	5.7	20.4%	7.8%	12.7%	3.6%	4.56	4.34	+2.5
Career	—	MLE		109	101	500	2098	500	173	53	93%	4.6	23.8%	8.2%	15.6%	2.5%	3.71	3.52	+6.0
/ 200 IP	—	MLE		44	40	200	839	200	69	21	93%	4.6	23.8%	8.2%	15.6%	2.5%	3.71	3.52	+1.9

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 AAAOklahoma City Comets · 15 IPFIP 2.82 → 3.33 (+0.50)K% 34.4% → 29.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.43%	—	×0.860	29.61%
BB% (unintentional) /BF	6.56%	—	×0.900	5.90%
HR / BF /BF	3.28%	÷1.000	×1.100	3.61%

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 2.82 → 3.33, 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 AAAOklahoma City Dodgers · 101 IPFIP 3.63 → 3.97 (+0.34)K% 27.8% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.84%	—	×0.860	23.94%
BB% (unintentional) /BF	10.67%	—	×0.900	9.61%
HR / BF /BF	2.78%	÷1.006	×1.100	3.04%

Result: FIP 3.63 → 3.97, 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 AATulsa Drillers · 73 IPFIP 1.55 → 2.28 (+0.73)K% 35.3% → 28.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.31%	—	×0.810	28.60%
BB% (unintentional) /BF	9.90%	—	×1.100	10.89%
HR / BF /BF	0.33%	÷0.993	×1.200	0.40%

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 99).

Result: FIP 1.55 → 2.28, 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 A+Great Lakes Loons · 25 IPFIP 2.04 → 2.83 (+0.79)K% 28.0% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.00%	—	×0.770	21.56%
BB% (unintentional) /BF	6.00%	—	×1.150	6.90%
HR / BF /BF	1.00%	÷1.013	×1.250	1.23%

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 2.04 → 2.83, 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 AAAOklahoma City Dodgers · 23 IPFIP 1.78 → 2.26 (+0.48)K% 35.5% → 31.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.48%	—	×0.880	31.23%
BB% (unintentional) /BF	8.60%	—	×1.050	9.03%
HR / BF /BF	1.08%	÷0.997	×1.100	1.19%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 99).

Result: FIP 1.78 → 2.26, 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 ARancho Cucamonga Quakes · 70 IPFIP 2.00 → 3.23 (+1.23)K% 34.2% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.24%	—	×0.740	25.34%
BB% (unintentional) /BF	6.78%	—	×1.180	8.00%
HR / BF /BF	1.69%	÷0.965	×1.300	2.28%

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 93).

Result: FIP 2.00 → 3.23, 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+Great Lakes Loons · 21 IPFIP 1.42 → 2.86 (+1.44)K% 44.6% → 34.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.58%	—	×0.770	34.33%
BB% (unintentional) /BF	6.02%	—	×1.150	6.93%
HR / BF /BF	2.41%	÷0.930	×1.250	3.24%

Result: FIP 1.42 → 2.86, 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
Gavin Stone (OGILVIE)	—	—	4.12	23.3%	7.3%	3.1%	—	4.48	22.0%	14.2%	317	+0.36	—	—	—
Brian Edgington R 2024 · 3.99 FIP	25	SP	3.99	19.5%	6.5%	3.1%	.321	5.28	19.3%	7.0%	58	+1.29	3.99	171	75
Omar Bencomo R 2017 · 4.50 FIP	28	SP-	4.50	18.9%	6.3%	4.0%	.333	4.48	14.9%	10.1%	186	-0.02	3.70	381	75
Erik Hiljus R 2001 · 3.35 FIP	28	SP-	3.35	23.1%	6.9%	2.4%	.321	6.07	14.1%	4.4%	46	+2.72	3.35	112	75
Yariel Rodríguez R 2024 · 3.76 FIP	27	SP	3.76	24.9%	11.4%	2.4%	.275	3.72	24.1%	12.7%	89	-0.04	2.32	196	73
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	73
Todd Redmond R 2013 · 4.14 FIP	28	SP-	4.14	23.5%	6.5%	4.0%	.266	3.57	17.0%	10.1%	170	-0.57	3.21	247	71
Joe Ross R 2021 · 3.95 FIP	28	SP	3.95	23.7%	6.5%	3.7%	.266	3.90	19.6%	10.7%	86	-0.05	3.19	812	69
Ryan Watson R 2024 · 4.15 FIP	25	SP-	4.15	18.6%	4.9%	3.7%	.342	5.48	13.1%	5.4%	98	+1.33	4.15	165	69
Raynel Espinal R 2019 · 3.90 FIP	27	SP-	3.90	22.4%	7.1%	3.2%	.313	4.01	22.3%	12.4%	224	+0.11	2.48	507	69
Matt Shoemaker R 2015 · 4.38 FIP	28	SP	4.38	20.4%	5.8%	4.1%	.280	3.74	21.8%	15.9%	269	-0.64	3.12	728	69
Hector Velázquez R 2017 · 3.65 FIP	28	SP-	3.65	18.0%	6.6%	2.2%	.251	4.28	16.7%	7.4%	158	+0.63	2.75	536	69
Braydon Tucker R 2024 · 3.25 FIP	25	SP-	3.25	18.3%	7.1%	1.5%	.291	4.70	15.3%	6.3%	208	+1.45	3.25	314	69
Brad Peacock R 2016 · 3.97 FIP	28	SP-	3.97	20.9%	8.7%	2.8%	.302	3.45	29.4%	20.4%	289	-0.52	2.97	748	69
Jonathan Pintaro R 2024 · 3.42 FIP	26	SP	3.42	18.9%	9.4%	1.3%	.264	4.07	23.9%	12.1%	153	+0.65	3.42	223	68
Patrick Johnson R 2016 · 3.82 FIP	27	SP-	3.82	17.3%	6.9%	2.4%	.286	4.14	15.7%	6.4%	120	+0.32	3.82	248	67
Chase Anderson R 2016 · 4.83 FIP	28	SP	4.83	18.5%	8.2%	4.1%	.285	4.25	21.3%	13.3%	438	-0.58	3.30	1,260	67
Antonio Guzman R 2016 · 3.72 FIP	28	SP	3.72	21.3%	8.7%	2.4%	.292	3.83	19.5%	7.8%	118	+0.11	3.15	254	67
Austin Bergner R 2024 · 4.84 FIP	27	SP	4.84	22.2%	12.5%	3.7%	.325	4.42	18.7%	7.3%	107	-0.42	4.06	464	67
Ariel Peña R 2017 · 3.99 FIP	28	SP	3.99	22.5%	12.0%	2.3%	.304	6.07	19.9%	-5.7%	21	+2.08	3.74	223	67
Jason Forjet R 2016 · 4.48 FIP	26	SP	4.48	15.9%	5.5%	3.7%	.260	—	—	—	—	—	3.36	197	67

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	3.7	91	21.0%	7.8%	1.36	4.48
Mark Leiter ('90-'01, 5 WAR*)	5.9	118	20.7%*	7.8%*	1.36*	4.61*
Chase Anderson ('24)	5.5	101	19.7%	8.1%	1.48	4.41
Rubby De La Rosa ('17)	2.1	105	19.6%	8.6%	1.32	4.49
Marco Estrada ('19)	6.3	139	21.0%	7.6%	1.43	4.29
Bob Stoddard ('81-'87, 3 WAR*)	2.2	72	17.9%*	8.7%*	1.46*	4.11*
Larry McWilliams ('78-'90, 10 WAR*)	7.8	130	19.0%*	8.1%*	1.24*	4.56*