Landen Roupp

P San Francisco Giants

Age 28 RHP 6'2" / 220 lbs MLB Svc 2.0 · Ctrl thru 2030 peak 1.5 · 2027

Overview

MLBSP40-MANPre-ArbFA 2031

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX3 levels	34	12	77	3.40	2.85	27.5%	12.3%	1.6	K 23.7% · BB 12.6% · FIP 3.27
2025	26	MIX2 levels	23	23	110	3.86	3.67	21.7%	9.0%	2.3	K 21.4% · BB 9.2% · FIP 3.83
2026	27	MLBSF	29	29	155	4.01	3.63	21.8%	11.4%	3.3
2027PROJ	28	MLBSF	18	18	110	4.09	4.30	21.4%	11.1%	1.4
2028PROJ95% MLB	29	MLBSF	13	13	76	4.21	4.36	20.8%	11.3%	0.8
2029PROJ95% MLB	30	MLBSF	9	9	56	4.42	4.56	20.1%	11.6%	0.5

Last 3 seasons WAR 7.2 · Next 3 projected WAR 2.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2030Service2.494First FA2031

2027Pre-Arb$0.8M2028Arb-1$2M2029Arb-2$2M2030Arb-3$2M

Skills · percentileStatcast 2026

xwOBA vs60

K%47

FB Velo27

Form1.76 ERA (proj 4.09) · K 16.1% (proj 21.4%) · BB 14.5% (proj 11.1%) ▼▼ last 60d · 15 IP through Oct 27

CompsTaylor Jungmann (age 27) · Chase Anderson (age 28) · Brad Peacock (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109101vR 93

ERA4.09

FIP4.30

K%21.4%

BB%11.1%

K-BB%10.3%

Proj IP110

Value2027 · WAR

Runs saved vs league avg · 110 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$17M ctrl surplus

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4040

CMD4545

K†5050

Statcast Percentiles

FB Velo

p2792.9

Whiff%

p4424.4%

p4721.8%

xwOBA vs

p600.302

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

Status Pre-Arb

MLB Debut 2024

Service 2.494 yrs.days

Team Control Through 2030

First FA Year 2031

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+1.4	$11M	+$10M
2028	Arb-1	$2M	+0.8	$3M	+$1M
2029	Arb-2	$2M	+0.5	$2M	+$0.2M
2030	Arb-3	$2M	+0.2	$0.6M	+$0.0M (cut)
Totals		$5M		$17M	+$12M

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	5	0	8	31	14	1	0	0%	1.6	45.2%	3.2%	41.9%	0.0%	2.25	-0.31	—
2021	22	MIX RAW	2 levels	5	0	8	31	14	1	0	0%	1.6	45.2%	3.2%	41.9%	0.0%	2.25	-0.02	—
2022	23	MIX MLE	3 levels	26	14	107	432	152	37	6	54%	4.1	26.9%	9.8%	17.1%	1.7%	2.60	3.02	—
2022	23	MIX RAW	3 levels	26	14	107	432	152	37	6	54%	4.1	35.2%	8.6%	26.6%	1.4%	2.60	2.03	—
2023	24	AA MLE	Richmond Flying Squirrels	10	10	31	120	42	9	1	100%	3.1	28.3%	8.2%	20.1%	1.1%	1.74	2.36	—
2023	24	AA RAW	Richmond Flying Squirrels	10	10	31	120	42	9	1	100%	3.1	35.0%	7.5%	27.5%	0.8%	1.74	1.68	—
2024	25	MIX MLE	3 levels	34	12	77	324	89	40	3	35%	2.3	23.7%	12.6%	11.1%	1.1%	3.40	3.27	+1.2
2024	25	MIX MLE	3 levels	34	12	77	324	89	40	3	35%	2.3	23.7%	12.6%	11.1%	1.1%	3.40	3.27	+1.2
2024	25	MIX RAW	3 levels	34	12	77	324	89	40	3	35%	2.3	27.5%	12.3%	15.1%	0.9%	3.40	2.85	+1.6
2025	26	MIX MLE	2 levels	23	23	110	488	106	44	11	100%	4.8	21.4%	9.2%	12.2%	2.5%	3.86	3.83	+2.1
2025	26	MIX MLE	2 levels	23	23	110	488	106	44	11	100%	4.8	21.4%	9.2%	12.2%	2.5%	3.86	3.83	+2.1
2025	26	MIX RAW	2 levels	23	23	110	488	106	44	11	100%	4.8	21.7%	9.0%	12.7%	2.3%	3.86	3.67	+2.3
2026	27	MLB MLE	San Francisco Giants	29	29	155	657	143	75	11	100%	5.3	21.8%	11.4%	10.4%	1.8%	4.01	3.70	+3.2
2026	27	MLB MLE	San Francisco Giants	29	29	155	657	143	75	11	100%	5.3	21.8%	11.4%	10.4%	1.8%	4.01	3.70	+3.2
2026	27	MLB RAW	San Francisco Giants	29	29	155	657	143	75	11	100%	5.3	21.8%	11.4%	10.4%	1.7%	4.01	3.63	+3.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			74	55	312	1350	292	145	24	74%	4.2	21.6%	10.7%	10.9%	1.8%	3.87	3.62	+6.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SF	18	18	110	464	99	51	10	100%	6.1	21.4%	11.1%	10.3%	2.2%	4.09	4.30	+1.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SF	13	13	80	337	70	38	8	100%	6.1	20.8%	11.3%	9.5%	2.4%	4.31	4.46	+0.9
2029	30	MLB MLE	SF	10	10	59	250	50	29	6	100%	5.9	20.1%	11.6%	8.5%	2.6%	4.53	4.67	+0.5
2030	31	MLB MLE	SF	7	7	44	185	36	22	5	100%	6.3	19.3%	11.9%	7.4%	2.8%	4.75	4.90	+0.2
2031	32	MLB MLE	SF	5	5	31	130	24	16	4	100%	6.2	18.5%	12.3%	6.2%	3.1%	4.99	5.16	+0.1
2028	29	MLB CTX	SF	13	13	76	321	67	36	7	100%	5.8	20.8%	11.3%	9.5%	2.2%	4.21	4.36	+0.8
2029	30	MLB CTX	SF	9	9	56	236	48	27	6	100%	6.2	20.1%	11.6%	8.5%	2.4%	4.42	4.56	+0.5
2030	31	MLB CTX	SF	7	7	42	177	34	21	5	100%	6.0	19.3%	11.9%	7.4%	2.6%	4.63	4.78	+0.2
2031	32	MLB CTX	SF	5	5	29	122	23	15	3	100%	5.8	18.5%	12.3%	6.2%	2.8%	4.86	5.03	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		108	89	515	2207	463	245	45	82%	4.8	21.0%	11.1%	9.9%	2.0%	4.10	3.85	+9.6
/ 200 IP	—	RAW		42	34	200	857	180	95	17	82%	4.8	21.0%	11.1%	9.9%	2.0%	4.10	3.85	+3.7
Career	—	MLE		127	88	488	2052	489	214	36	69%	3.8	23.8%	10.4%	13.4%	1.8%	3.40	3.38	+8.3
/ 200 IP	—	MLE		52	36	200	842	200	88	15	69%	3.8	23.8%	10.4%	13.4%	1.8%	3.40	3.38	+3.2

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.

2024 AAASacramento River Cats · 21 IPFIP 2.87 → 3.12 (+0.25)K% 33.3% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.860	28.67%
BB% (unintentional) /BF	15.56%	—	×0.900	14.00%
HR / BF /BF	1.11%	÷1.010	×1.100	1.21%

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 102).

Result: FIP 2.87 → 3.12, 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 AARichmond Flying Squirrels · 31 IPFIP 1.55 → 2.36 (+0.81)K% 35.0% → 28.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.00%	—	×0.810	28.35%
BB% (unintentional) /BF	7.50%	—	×1.100	8.25%
HR / BF /BF	0.83%	÷0.906	×1.200	1.10%

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 81).

Result: FIP 1.55 → 2.36, 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 ASan Jose Giants · 49 IPFIP 1.79 → 2.88 (+1.09)K% 35.0% → 25.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.03%	—	×0.740	25.92%
BB% (unintentional) /BF	8.63%	—	×1.180	10.18%
HR / BF /BF	1.02%	÷1.063	×1.300	1.24%

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 113).

Result: FIP 1.79 → 2.88, 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+Eugene Emeralds · 32 IPFIP 0.94 → 1.93 (+1.00)K% 41.6% → 32.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.60%	—	×0.770	32.03%
BB% (unintentional) /BF	7.20%	—	×1.150	8.28%
HR / BF /BF	0.80%	÷1.120	×1.250	0.89%

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 124).

Result: FIP 0.94 → 1.93, 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).

2022 AARichmond Flying Squirrels · 26 IPFIP 3.48 → 4.50 (+1.02)K% 28.2% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.18%	—	×0.810	22.83%
BB% (unintentional) /BF	10.00%	—	×1.100	11.00%
HR / BF /BF	2.73%	÷0.929	×1.200	3.52%

Result: FIP 3.48 → 4.50, 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 ROKACL Giants Black · 6 IPFIP -0.76 → 0.79 (+1.55)K% 52.2% → 35.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	52.17%	—	×0.680	35.48%
BB% (unintentional) /BF	4.35%	—	×1.250	5.43%
HR / BF /BF	0.00%	÷1.222	×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 144).

Result: FIP -0.76 → 0.79, 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
Landen Roupp (OGILVIE)	—	—	4.30	21.4%	11.1%	2.2%	—	4.63	20.2%	8.7%	183	+0.33	—	—	—
Taylor Jungmann R 2017 · 3.88 FIP	27	SP-	3.88	18.8%	11.1%	1.8%	.279	—	—	—	—	—	3.59	435	71
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	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	71
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	70
Rodrigo Lopez R 2004 · 4.21 FIP	28	SP-	4.21	16.9%	7.3%	2.9%	.275	4.57	14.2%	7.8%	478	+0.36	4.06	1,344	67
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	64
Victor Santos R 2005 · 4.67 FIP	28	SP	4.67	13.9%	8.1%	3.1%	.278	4.90	16.0%	7.8%	179	+0.23	4.09	602	63
Jesse Hahn R 2017 · 3.66 FIP	28	SP	3.66	16.6%	9.7%	1.3%	.327	2.19	29.2%	16.9%	17	-1.47	2.19	499	63
Hector Noesí R 2015 · 4.37 FIP	28	SP-	4.37	17.6%	8.1%	3.2%	.261	—	—	—	—	—	3.73	613	62
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	62
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	61
Paul Clemens R 2016 · 4.58 FIP	28	SP	4.58	17.6%	9.1%	3.3%	.271	4.72	14.9%	3.9%	53	+0.14	4.58	345	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	2,087	61
Lucas Harrell R 2013 · 5.12 FIP	28	SP-	5.12	12.6%	11.7%	2.9%	.299	4.18	15.5%	2.7%	121	-0.94	2.81	541	60
Bud Norris R 2013 · 3.68 FIP	28	SP	3.68	19.0%	8.7%	2.0%	.330	4.05	20.0%	11.9%	361	+0.37	3.51	1,221	59
Tyler Wilson R 2017 · 4.45 FIP	27	SP-	4.45	12.1%	7.0%	2.7%	.311	—	—	—	—	—	3.62	377	59
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	59
Jorge Sosa R 2005 · 4.23 FIP	28	SW	4.23	14.7%	9.7%	2.1%	.259	4.99	14.0%	6.8%	252	+0.76	4.06	773	58
Jason Hammel R 2011 · 4.52 FIP	28	SP	4.52	12.7%	8.8%	2.5%	.275	3.89	20.3%	13.2%	434	-0.63	3.10	1,810	58
Cha Seung Baek R 2008 · 4.29 FIP	28	SP-	4.29	15.3%	6.6%	3.0%	.283	—	—	—	—	—	3.35	280	58

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	3.2	79	21.0%	11.1%	0.83	4.14
Greg Cadaret ('87-'98, 4 WAR*)	3.6	80	22.3%*	12.1%*	0.88*	4.14*
George Frazier ('78-'87, 2 WAR*)	3.4	68	21.6%*	10.5%*	0.92*	4.42*
Horacio Pina ('68-'78, 2 WAR*)	2.2	62	20.7%*	11.2%*	0.84*	4.01*
Bryce Florie ('01)	2.5	82	18.1%	11.1%	0.84	4.47
John Gant ('21)	1.9	93	20.2%	12.5%	0.82	3.89
Darren Dreifort ('04)	4.4	97	21.2%	10.3%	0.93	4.36