Ryan Pepiot — OGILVIE

Ryan Pepiot P Tampa Bay Rays

Age 28 RHP 6'3" / 210 lbs MLB Svc 3.0 · Ctrl thru 2028 peak 1.8 · 2026 ILInjured 60-Day (D60)

2026 ROS PROJECTION0 act + 3 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 112104vR 96

ERA4.10

FIP4.39

K%25.2%

BB%8.8%

K-BB%16.5%

ROS IP3

Value2026 · WAR

Runs saved vs league avg · 3 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control-$5M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

STUF5555

CTRL4545

CMD5555

K†6060

Statcast Percentiles

FB Velo

p6095.2

Whiff%

p5526.0%

p6324.6%

xwOBA vs

p510.311

CH+4.8 (25%)

CT+3.5 (6%)

FB+1.0 (47%)

SI (2%)

CU (3%)

SL-4.0 (18%)

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

Status Arb-1

MLB Debut 2022

Service 3.029 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$0.2M	+0.1	$0.3M	+$0.0M
2027	Arb-2	$6M	+0.6	$2M	+$0.0M (cut)
2028	Arb-3	$6M	+0.2	$0.7M	+$0.0M (cut)
Totals		$0.2M		$3M	+$0.0M

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 industry-standard fWAR.

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 + 2026 so far)
2019	21	MIX MLE	2 levels	13	10	23	98	31	13	0	77%	1.8	20.4%	14.0%	6.5%	0.0%	1.93	3.14	—
2019	21	MIX RAW	2 levels	13	10	23	98	31	13	0	77%	1.8	31.6%	13.3%	18.4%	0.0%	1.93	2.11	—
2021	23	MIX MLE	2 levels	26	22	101	435	127	47	19	85%	3.9	24.4%	11.6%	12.7%	5.1%	4.62	5.29	—
2021	23	MIX RAW	2 levels	26	22	101	435	127	47	19	85%	3.9	29.2%	10.8%	18.4%	4.4%	4.62	4.42	—
2022	24	MIX MLE	2 levels	28	24	128	529	156	63	16	86%	4.6	26.9%	12.2%	14.7%	3.2%	2.82	4.12	+1.2
2022	24	MIX RAW	2 levels	28	24	128	529	156	63	16	86%	4.6	29.5%	11.9%	17.6%	3.0%	2.82	3.77	+1.7
2023	25	MIX MLE	2 levels	14	9	65	252	64	10	11	64%	4.6	23.6%	3.8%	19.9%	4.4%	2.78	4.00	+0.7
2023	25	MIX MLE	2 levels	14	9	65	252	64	10	11	64%	4.6	23.6%	3.8%	19.9%	4.4%	2.78	4.00	+0.7
2023	25	MIX RAW	2 levels	14	9	65	252	64	10	11	64%	4.6	25.4%	4.0%	21.4%	4.4%	2.78	3.80	+0.9
2024	26	MIX MLE	2 levels	27	27	133	552	149	50	17	100%	4.9	26.3%	8.9%	17.4%	3.2%	3.51	3.78	+1.8
2024	26	MIX MLE	2 levels	27	27	133	552	149	50	17	100%	4.9	26.3%	8.9%	17.4%	3.2%	3.51	3.78	+1.8
2024	26	MIX RAW	2 levels	27	27	133	552	149	50	17	100%	4.9	27.0%	9.1%	17.9%	3.1%	3.51	3.65	+2.0
2025	27	MLB MLE	Tampa Bay Rays	31	31	168	679	167	61	26	100%	5.4	24.6%	9.0%	15.6%	3.7%	3.86	4.20	+1.4
2025	27	MLB MLE	Tampa Bay Rays	31	31	168	679	167	61	26	100%	5.4	24.6%	9.0%	15.6%	3.7%	3.86	4.20	+1.4
2025	27	MLB RAW	Tampa Bay Rays	31	31	168	679	167	61	26	100%	5.4	24.6%	9.0%	15.6%	3.8%	3.86	4.22	+1.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			74	67	376	1537	389	141	56	91%	5.1	25.3%	9.2%	16.1%	3.6%	3.54	4.09	+3.6
▸ 2026 season — projected remainder (no 2026 stats recorded)
2026	28	MLB	TB	1	1	3	13	3	1	0	100%	3.0	25.2%	8.8%	16.5%	3.5%	4.10	4.39	+0.0
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	29	MLB MLE	TB	26	26	155	656	162	59	24	100%	6.0	24.6%	9.0%	15.7%	3.7%	4.37	4.55	+0.6
2028	30	MLB MLE	TB	24	24	146	617	148	57	24	100%	6.1	23.9%	9.3%	14.7%	3.9%	4.60	4.76	+0.2
2029	31	MLB MLE	TB	23	23	136	575	133	55	24	100%	5.9	23.2%	9.6%	13.6%	4.1%	4.83	4.99	-0.1
2030	32	MLB MLE	TB	21	21	126	532	119	53	23	100%	6.0	22.4%	10.0%	12.4%	4.3%	5.08	5.24	-0.5
2027	29	MLB CTX	TB	26	26	155	654	161	59	25	100%	6.0	24.6%	9.0%	15.7%	3.8%	4.43	4.61	+0.6
2028	30	MLB CTX	TB	24	24	146	616	148	57	25	100%	6.1	23.9%	9.3%	14.7%	4.0%	4.66	4.82	+0.2
2029	31	MLB CTX	TB	23	23	136	574	133	55	24	100%	5.9	23.2%	9.6%	13.6%	4.2%	4.90	5.06	-0.1
2030	32	MLB CTX	TB	21	21	126	532	119	53	24	100%	6.0	22.4%	10.0%	12.4%	4.5%	5.15	5.31	-0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		168	161	940	3917	951	366	154	96%	5.6	24.3%	9.3%	14.9%	3.9%	4.28	4.38	+5.7
/ 200 IP	—	RAW		36	34	200	834	202	78	33	96%	5.6	24.3%	9.3%	14.9%	3.9%	4.28	4.38	+1.2
Career	—	MLE		139	123	618	2545	640	249	93	88%	4.4	25.2%	9.8%	15.4%	3.7%	3.51	4.22	+3.8
/ 200 IP	—	MLE		45	40	200	824	207	81	30	88%	4.4	25.2%	9.8%	15.4%	3.7%	3.51	4.22	+0.8

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 Pepiot (OGILVIE)	—	—	4.39	25.2%	8.8%	3.5%	—	4.76	24.0%	14.7%	438	+0.37	—	—	—
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	1,146	68
Jake Odorizzi R 2018 · 3.91 FIP	28	SP	3.91	22.8%	9.4%	2.8%	.284	3.73	24.3%	16.6%	277	-0.18	3.16	1,048	68
Dan Straily R 2017 · 4.48 FIP	28	SP	4.48	22.1%	7.3%	4.2%	.283	5.36	18.7%	10.3%	237	+0.88	3.50	890	67
Chris Archer R 2017 · 3.31 FIP	28	SP	3.31	29.2%	7.0%	3.3%	.322	4.20	26.2%	17.7%	268	+0.89	2.85	1,018	67
Anthony DeSclafani R 2018 · 4.47 FIP	28	SP	4.47	22.3%	5.8%	4.6%	.290	3.95	22.6%	16.0%	368	-0.52	3.38	981	65
Jordan Lyles R 2019 · 4.34 FIP	28	SP	4.34	24.4%	8.8%	4.0%	.283	4.70	18.1%	10.8%	417	+0.36	3.44	1,080	65
Nathan Eovaldi R 2018 · 3.49 FIP	28	SP	3.49	22.2%	4.2%	3.2%	.283	3.44	25.1%	19.2%	298	-0.05	2.44	1,378	65
Chris Tillman R 2016 · 3.92 FIP	28	SP	3.92	19.6%	9.1%	2.4%	.277	5.96	12.2%	0.4%	144	+2.04	3.92	489	64
Zack Godley R 2018 · 3.56 FIP	28	SP	3.56	23.4%	10.0%	2.1%	.315	5.07	17.6%	6.5%	219	+1.51	3.21	953	63
Masahiro Tanaka R 2017 · 3.99 FIP	28	SP	3.99	25.8%	5.3%	4.4%	.300	3.90	22.1%	16.9%	386	-0.09	3.34	918	61
Sonny Gray R 2018 · 3.79 FIP	28	SP-	3.79	21.1%	9.8%	2.2%	.320	3.21	28.5%	19.1%	367	-0.58	2.55	1,792	60
Michael Wacha R 2019 · 5.42 FIP	28	SP	5.42	18.5%	9.1%	5.0%	.307	4.31	21.8%	16.0%	286	-1.11	3.57	1,638	60
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	533	59
Danny Salazar R 2017 · 3.34 FIP	27	SP	3.34	33.0%	10.0%	3.2%	.339	—	—	—	—	—	3.34	425	59
Taylor Jungmann R 2017 · 3.88 FIP	27	SP-	3.88	18.8%	11.1%	1.8%	.279	—	—	—	—	—	3.59	435	58
Ian Kennedy R 2015 · 4.22 FIP	30	SP	4.22	24.4%	6.7%	4.2%	.293	4.94	21.1%	13.0%	469	+0.72	2.88	864	57
Jacob deGrom R 2016 · 3.22 FIP	28	SP	3.22	23.7%	6.0%	2.5%	.310	2.46	31.0%	25.4%	622	-0.76	0.74	1,538	57
Julio Teheran R 2019 · 4.23 FIP	28	SP	4.23	21.5%	10.6%	2.9%	.257	7.66	13.4%	2.7%	31	+3.43	3.61	1,134	57
Rick Porcello R 2017 · 4.46 FIP	28	SP	4.46	20.5%	5.3%	4.4%	.320	3.98	21.1%	15.4%	425	-0.48	3.13	1,023	57
Frankie Montas R 2021 · 3.32 FIP	28	SP	3.32	26.6%	7.2%	2.8%	.291	3.94	23.0%	14.6%	295	+0.62	2.82	1,009	57

Career Comps

Retired MLB careers whose totals most resemble what we're projecting for this player. Pool: 133 completed pitcher careers (2015-2024).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	3.6	143	24.0%	9.3%	1.50	4.57
Mike Foltynewicz ('21)	4.0	134	21.4%	7.7%	1.46	4.45
Dan Straily ('19)	2.7	136	20.0%	8.9%	1.72	4.54
Julio Teheran ('23)	5.2	147	20.4%	8.8%	1.34	4.12
Triston McKenzie ('24)	2.1	105	26.0%	9.4%	1.52	3.94
Dylan Bundy ('22)	4.5	130	22.0%	7.3%	1.61	4.75
Kutter Crawford ('24)	2.0	130	23.9%	7.2%	1.45	4.47