Ryan Gusto

P Miami Marlins

Age 28 RHP 6'4" / 232 lbs MLB Svc 1.0 · Ctrl thru 2031 peak 0.8 · 2027

Overview

MLBSP40-MANPre-ArbFA 2032

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	AAAHOU	29	26	148	3.70	3.50	22.6%	8.5%	—	K 19.5% · BB 7.7% · FIP 3.93
2025	26	MIX2 levels	29	19	106	5.86	4.39	20.7%	7.9%	1.3	K 21.4% · BB 7.9% · FIP 4.47
2026	27	MIX2 levels	33	25	133	4.00	3.69	21.7%	7.7%	2.7	K 20.4% · BB 7.5% · FIP 3.83
2027PROJ	28	MLBMIA	12	12	71	4.60	4.52	20.1%	7.8%	0.7
2028PROJ95% MLB	29	MLBMIA	10	10	60	4.56	4.59	19.5%	8.1%	0.5
2029PROJ95% MLB	30	MLBMIA	8	8	49	4.69	4.79	18.8%	8.4%	0.3

Last 3 seasons WAR 4.0 · Next 3 projected WAR 1.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2031Service1.669First FA2032

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Arb-1$0.6M2030Arb-2$2M2031Arb-3$2M

Skills · percentileStatcast 2026

FB Velo52

K%27

xwOBA vs25

Form4.38 ERA (proj 4.60) · K 18.8% (proj 20.1%) · BB 8.9% (proj 7.8%) · last 60d · 25 IP through Oct 27

CompsFabio Castillo (age 28) · Raynel Espinal (age 27) · Erik Hiljus (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 105

ERA4.60

FIP4.52

K%20.1%

BB%7.8%

K-BB%12.3%

Proj IP71

Value2027 · WAR

Runs saved vs league avg · 71 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit+$7M ctrl surplus

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL5050

CMD4545

K†5050

Statcast Percentiles

FB Velo

p5294.7

Whiff%

p1720.7%

p2718.9%

xwOBA vs

p250.341

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status Pre-Arb

MLB Debut 2025

Service 1.669 yrs.days

Team Control Through 2031

First FA Year 2032

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.7	$3M	+$2M
2028	Pre-Arb	$0.8M	+0.5	$2M	+$1M
2029	Arb-1	$0.6M	+0.3	$1M	+$0.5M
2030	Arb-2	$2M	—	—	—
2031	Arb-3	$2M	—	—	—
Totals		$2M		$4M	+$4M

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)
2019	20	ROK MLE	GCL Astros	2	1	4	17	6	3	0	50%	1.8	35.3%	17.6%	17.6%	0.0%	2.45	2.35	—
2019	20	ROK RAW	GCL Astros	2	1	4	17	6	3	0	50%	1.8	35.3%	17.6%	17.6%	0.0%	2.45	2.28	—
2022	23	MIX MLE	2 levels	23	13	90	395	96	36	14	57%	3.9	18.5%	10.5%	8.0%	4.6%	5.50	5.38	—
2022	23	MIX RAW	2 levels	23	13	90	395	96	36	14	57%	3.9	24.3%	9.1%	15.2%	3.5%	5.50	4.19	—
2023	24	MIX MLE	2 levels	26	14	110	468	115	46	13	54%	4.2	19.5%	11.0%	8.4%	2.8%	4.50	4.39	—
2023	24	MIX RAW	2 levels	26	14	110	468	115	46	13	54%	4.2	24.6%	9.8%	14.7%	2.8%	4.50	3.80	—
2024	25	AAA MLE	Sugar Land Space Cowboys	29	26	148	623	141	53	14	90%	5.1	19.5%	7.7%	11.8%	2.7%	3.70	3.93	—
2024	25	AAA MLE	Sugar Land Space Cowboys	29	26	148	623	141	53	14	90%	5.1	19.5%	7.7%	11.8%	2.7%	3.70	3.93	—
2024	25	AAA RAW	Sugar Land Space Cowboys	29	26	148	623	141	53	14	90%	5.1	22.6%	8.5%	14.1%	2.2%	3.70	3.50	—
2025	26	MIX MLE	2 levels	29	19	106	478	99	38	17	66%	3.7	21.4%	7.9%	13.5%	4.0%	5.86	4.47	+1.2
2025	26	MIX MLE	2 levels	29	19	106	478	99	38	17	66%	3.7	21.4%	7.9%	13.5%	4.0%	5.86	4.47	+1.2
2025	26	MIX RAW	2 levels	29	19	106	478	99	38	17	66%	3.7	20.7%	7.9%	12.8%	3.6%	5.86	4.39	+1.3
2026	27	MIX MLE	2 levels	33	25	133	581	126	45	15	76%	4.0	20.4%	7.5%	13.0%	2.8%	4.00	3.83	+2.5
2026	27	MIX MLE	2 levels	33	25	133	581	126	45	15	76%	4.0	20.4%	7.5%	13.0%	2.8%	4.00	3.83	+2.5
2026	27	MIX RAW	2 levels	33	25	133	581	126	45	15	76%	4.0	21.7%	7.7%	13.9%	2.6%	4.00	3.69	+2.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			50	35	190	845	171	64	28	70%	3.8	20.2%	7.6%	12.7%	3.3%	4.93	4.23	+2.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	MIA	12	12	71	300	60	24	10	100%	5.9	20.1%	7.8%	12.3%	3.2%	4.60	4.52	+0.7
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	MIA	10	10	63	265	52	21	9	100%	6.3	19.5%	8.1%	11.5%	3.3%	4.65	4.68	+0.5
2029	30	MLB MLE	MIA	9	9	51	216	41	18	8	100%	5.7	18.8%	8.4%	10.5%	3.5%	4.79	4.89	+0.3
2028	29	MLB CTX	MIA	10	10	60	253	49	20	8	100%	6.0	19.5%	8.1%	11.5%	3.2%	4.56	4.59	+0.5
2029	30	MLB CTX	MIA	8	8	49	207	39	17	7	100%	6.1	18.8%	8.4%	10.5%	3.4%	4.69	4.79	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		68	53	298	1302	259	101	43	78%	4.4	19.9%	7.8%	12.1%	3.3%	4.82	4.22	+4.2
/ 200 IP	—	RAW		46	36	200	874	174	68	29	78%	4.4	19.9%	7.8%	12.1%	3.3%	4.82	4.22	+2.8
Career	—	MLE		142	98	591	2562	513	225	83	69%	4.2	20.0%	8.8%	11.2%	3.2%	4.57	4.30	+3.4
/ 200 IP	—	MLE		48	33	200	867	174	76	28	69%	4.2	20.0%	8.8%	11.2%	3.2%	4.57	4.30	+2.3

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 AAAJacksonville Jumbo Shrimp · 45 IPFIP 3.08 → 3.41 (+0.33)K% 27.5% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.51%	—	×0.860	23.66%
BB% (unintentional) /BF	8.99%	—	×0.900	8.10%
HR / BF /BF	2.12%	÷1.000	×1.100	2.33%

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 3.08 → 3.41, 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 AAAJacksonville Jumbo Shrimp · 4 IPFIP 3.44 → 3.43 (−0.01)K% 8.0% → 6.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	8.00%	—	×0.860	6.88%
BB% (unintentional) /BF	8.00%	—	×0.900	7.20%
HR / BF /BF	0.00%	÷0.903	×1.100	0.00%

Result: FIP 3.44 → 3.43, 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 AAASugar Land Space Cowboys · 148 IPFIP 3.50 → 3.93 (+0.43)K% 22.6% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.63%	—	×0.860	19.46%
BB% (unintentional) /BF	8.51%	—	×0.900	7.66%
HR / BF /BF	2.25%	÷0.903	×1.100	2.74%

Result: FIP 3.50 → 3.93, 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 AACorpus Christi Hooks · 61 IPFIP 2.71 → 3.20 (+0.49)K% 24.9% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.90%	—	×0.810	20.17%
BB% (unintentional) /BF	10.04%	—	×1.100	11.04%
HR / BF /BF	0.80%	÷1.322	×1.200	0.73%

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 164).

Result: FIP 2.71 → 3.20, 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+Asheville Tourists · 49 IPFIP 5.03 → 5.75 (+0.73)K% 24.2% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.20%	—	×0.770	18.63%
BB% (unintentional) /BF	9.59%	—	×1.150	11.03%
HR / BF /BF	5.02%	÷1.218	×1.250	5.16%

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 144).

Result: FIP 5.03 → 5.75, 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).

2022 A+Asheville Tourists · 66 IPFIP 4.65 → 6.00 (+1.34)K% 24.3% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.32%	—	×0.770	18.73%
BB% (unintentional) /BF	9.46%	—	×1.150	10.88%
HR / BF /BF	4.39%	÷0.972	×1.250	5.65%

Result: FIP 4.65 → 6.00, 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 AFayetteville Woodpeckers · 24 IPFIP 2.63 → 3.55 (+0.92)K% 24.2% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.740	17.94%
BB% (unintentional) /BF	8.08%	—	×1.180	9.54%
HR / BF /BF	1.01%	÷0.949	×1.300	1.38%

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 90).

Result: FIP 2.63 → 3.55, 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).

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 Gusto (OGILVIE)	—	—	4.52	20.1%	7.8%	3.2%	—	4.77	19.2%	11.0%	114	+0.25	—	—	—
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	73
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	71
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	71
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	70
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	70
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	70
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	69
Dustin Nippert R 2009 · 4.09 FIP	28	SP-	4.09	18.0%	9.7%	2.3%	.271	4.49	17.9%	6.1%	57	+0.40	3.83	268	68
Shawn Haviland R 2015 · 3.95 FIP	29	SP-	3.95	14.6%	6.0%	2.4%	.303	4.67	16.1%	8.8%	169	+0.72	3.69	283	68
David Phelps R 2015 · 3.94 FIP	28	SP	3.94	16.0%	6.8%	2.4%	.299	2.82	29.9%	20.6%	142	-1.12	2.50	672	68
Gary Glover R 2005 · 4.20 FIP	28	SP-	4.20	20.4%	7.0%	3.5%	.327	4.50	15.2%	8.3%	132	+0.30	4.02	516	67
Taylor Jungmann R 2017 · 3.88 FIP	27	SP-	3.88	18.8%	11.1%	1.8%	.279	—	—	—	—	—	3.59	435	67
Kyle Snyder R 2006 · 4.47 FIP	28	SP-	4.47	19.9%	5.9%	4.2%	.373	4.83	16.9%	4.5%	54	+0.36	3.80	236	67
Nate Karns R 2016 · 3.88 FIP	28	SP-	3.88	24.2%	10.6%	2.7%	.322	4.46	27.1%	20.7%	45	+0.58	3.88	299	67
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	66
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	66
Drew VerHagen R 2019 · 4.11 FIP	28	SW	4.11	19.5%	7.3%	3.2%	.344	6.00	17.0%	4.7%	22	+1.89	2.80	487	66
Hector Noesí R 2015 · 4.37 FIP	28	SP-	4.37	17.6%	8.1%	3.2%	.261	—	—	—	—	—	3.73	613	65
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	65
Colin Rea R 2018 · 5.61 FIP	28	SP	5.61	17.6%	11.3%	4.7%	.344	4.14	17.7%	9.8%	198	-1.47	2.57	1,116	64

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	1.9	75	19.9%	7.8%	1.29	4.80
Tom Gorman ('81-'87, 0 WAR*)	1.1	71	21.5%*	7.2%*	1.19*	5.12*
Steve Wilson ('88-'93, 0 WAR*)	1.7	69	21.6%*	8.8%*	1.25*	4.84*
Rich Folkers ('70-'77, -0 WAR*)	2.1	85	19.1%*	8.8%*	1.35*	4.91*
Travis Harper ('06)	2.1	69	15.0%	7.5%	1.33	4.94
Jorge López ('25)	2.8	70	19.8%	8.8%	1.36	5.31
Joe Biagini ('21)	1.7	83	19.0%	7.9%	1.28	5.03