Seth Lonsway

P Sacramento River Cats

Age 28 LHP 6'0" / 206 lbs AAA peak 0.2 · 2027

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	19	17	96	3.01	2.76	20.4%	6.7%	—	K 16.0% · BB 7.6% · FIP 3.35
2025	26	MIX2 levels	28	28	134	3.76	3.65	21.1%	11.6%	—	K 17.4% · BB 11.9% · FIP 4.03
2026	27	MIX3 levels	27	20	98	5.16	5.09	14.1%	13.2%	0.4	K 12.1% · BB 12.5% · FIP 5.24
2027PROJ	28	MLBSF	8	8	49	5.45	5.45	13.1%	12.8%	-0.0
2028PROJ75% MLB	29	MLBSF	7	7	40	5.41	5.46	13.9%	12.6%	-0.0
2029PROJ82% MLB	30	MLBSF	6	6	36	5.46	5.55	14.2%	12.7%	-0.1

Last 3 seasons WAR 0.4 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control45Command40

Career WAR0.0 WAR median (P10 -0.2 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsMarco Tovar (age 28) · Jack Snodgrass (age 28) · Enrique Lechuga (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 120129vR 137

ERA5.45

FIP5.45

K%13.1%

BB%12.8%

K-BB%0.3%

Proj IP73

Value2027 · WAR

Runs saved vs league avg · 73 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL4545

CMD4040

K†3030

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	ROK MLE	ACL Giants Orange	4	4	5	20	10	0	1	100%	1.2	50.0%	0.0%	50.0%	5.0%	7.20	1.62	—
2021	22	ROK RAW	ACL Giants Orange	4	4	5	20	10	0	1	100%	1.2	50.0%	0.0%	50.0%	5.0%	7.20	1.70	—
2022	23	A MLE	San Jose Giants	26	9	95	419	120	51	8	35%	3.7	21.2%	14.4%	6.8%	2.3%	4.06	4.41	—
2022	23	A RAW	San Jose Giants	26	9	95	419	120	51	8	35%	3.7	28.6%	12.2%	16.5%	1.9%	4.06	3.28	—
2023	24	A+ MLE	Eugene Emeralds	28	17	89	435	78	58	9	61%	3.2	13.8%	15.3%	-1.5%	2.4%	5.87	5.20	—
2023	24	A+ RAW	Eugene Emeralds	28	17	89	435	78	58	9	61%	3.2	17.9%	13.3%	4.6%	2.1%	5.87	4.62	—
2024	25	MIX MLE	2 levels	19	17	96	406	83	27	4	89%	5.0	16.0%	7.6%	8.4%	1.2%	3.01	3.35	—
2024	25	MIX MLE	2 levels	19	17	96	406	83	27	4	89%	5.0	16.0%	7.6%	8.4%	1.2%	3.01	3.35	—
2024	25	MIX RAW	2 levels	19	17	96	406	83	27	4	89%	5.0	20.4%	6.7%	13.8%	1.0%	3.01	2.76	—
2025	26	MIX MLE	2 levels	28	28	134	579	122	67	9	100%	4.8	17.4%	11.9%	5.5%	1.6%	3.76	4.03	—
2025	26	MIX MLE	2 levels	28	28	134	579	122	67	9	100%	4.8	17.4%	11.9%	5.5%	1.6%	3.76	4.03	—
2025	26	MIX RAW	2 levels	28	28	134	579	122	67	9	100%	4.8	21.1%	11.6%	9.5%	1.6%	3.76	3.65	—
2026	27	MIX MLE	3 levels	27	20	98	447	63	59	11	74%	3.6	12.1%	12.5%	-0.3%	2.9%	5.16	5.24	+0.2
2026	27	MIX MLE	3 levels	27	20	98	447	63	59	11	74%	3.6	12.1%	12.5%	-0.3%	2.9%	5.16	5.24	+0.2
2026	27	MIX RAW	3 levels	27	20	98	447	63	59	11	74%	3.6	14.1%	13.2%	0.9%	2.5%	5.16	5.09	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			2	0	2	14	2	0	0	0%	1.2	14.3%	0.0%	14.3%	0.0%	7.71	1.39	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SF	8	8	49	207	27	26	5	100%	6.1	13.1%	12.8%	0.3%	2.6%	5.45	5.45	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SF	9	9	54	226	31	29	6	100%	5.9	13.9%	12.6%	1.2%	2.8%	5.41	5.46	-0.0
2029	30	MLB MLE	SF	7	7	44	187	27	24	6	100%	6.3	14.2%	12.7%	1.5%	3.0%	5.46	5.55	-0.1
2028	29	MLB CTX	SF	7	7	40	169	23	21	5	100%	5.7	13.9%	12.6%	1.2%	2.8%	5.41	5.46	-0.0
2029	30	MLB CTX	SF	6	6	36	152	22	19	5	100%	6.0	14.2%	12.7%	1.5%	3.0%	5.46	5.55	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		15	13	79	337	47	41	9	87%	5.3	14.0%	12.1%	1.9%	2.8%	5.50	4.99	+0.4
/ 200 IP	—	RAW		37	32	200	855	119	104	23	86%	5.3	14.0%	12.1%	1.9%	2.8%	5.50	4.99	+0.9
Career	—	MLE		132	95	517	2306	379	282	48	72%	3.9	16.4%	12.2%	4.2%	2.1%	4.34	4.41	-0.0
/ 200 IP	—	MLE		51	37	200	893	147	109	19	72%	3.9	16.4%	12.2%	4.2%	2.1%	4.34	4.41	-0.0

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 AAASacramento River Cats · 92 IPFIP 5.11 → 5.24 (+0.14)K% 14.1% → 12.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.08%	—	×0.860	12.11%
BB% (unintentional) /BF	13.84%	—	×0.900	12.46%
HR / BF /BF	2.63%	÷1.000	×1.100	2.89%

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 5.11 → 5.24, 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 AARichmond Flying Squirrels · 92 IPFIP 3.63 → 4.12 (+0.49)K% 21.3% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.32%	—	×0.810	17.27%
BB% (unintentional) /BF	10.66%	—	×1.100	11.73%
HR / BF /BF	1.78%	÷1.183	×1.200	1.80%

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 137).

Result: FIP 3.63 → 4.12, 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).

2025 AAASacramento River Cats · 42 IPFIP 3.67 → 3.84 (+0.17)K% 20.5% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.54%	—	×0.860	17.66%
BB% (unintentional) /BF	13.51%	—	×0.900	12.16%
HR / BF /BF	1.08%	÷0.938	×1.100	1.27%

Result: FIP 3.67 → 3.84, 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+Eugene Emeralds · 63 IPFIP 2.67 → 3.31 (+0.64)K% 20.8% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.80%	—	×0.770	16.02%
BB% (unintentional) /BF	7.30%	—	×1.150	8.39%
HR / BF /BF	0.73%	÷1.010	×1.250	0.90%

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 102).

Result: FIP 2.67 → 3.31, 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 AARichmond Flying Squirrels · 33 IPFIP 2.94 → 3.43 (+0.49)K% 19.7% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.70%	—	×0.810	15.95%
BB% (unintentional) /BF	5.30%	—	×1.100	5.83%
HR / BF /BF	1.52%	÷1.062	×1.200	1.71%

Result: FIP 2.94 → 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).

2023 A+Eugene Emeralds · 89 IPFIP 4.41 → 5.20 (+0.78)K% 17.9% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.93%	—	×0.770	13.81%
BB% (unintentional) /BF	13.33%	—	×1.150	15.33%
HR / BF /BF	2.07%	÷1.076	×1.250	2.40%

Result: FIP 4.41 → 5.20, 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).

2022 ASan Jose Giants · 95 IPFIP 3.27 → 4.41 (+1.14)K% 28.6% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.64%	—	×0.740	21.19%
BB% (unintentional) /BF	12.17%	—	×1.180	14.36%
HR / BF /BF	1.91%	÷1.063	×1.300	2.34%

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 3.27 → 4.41, 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).

2021 ROKACL Giants Orange · 5 IPFIP 1.62 → 3.84 (+2.21)K% 50.0% → 34.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	50.00%	—	×0.680	34.00%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	5.00%	÷1.065	×1.400	6.57%

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 113).

Result: FIP 1.62 → 3.84, 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
Seth Lonsway (OGILVIE)	—	—	5.45	13.1%	12.8%	2.6%	—	5.50	14.0%	1.4%	98	+0.05	—	—	—
Marco Tovar L 2017 · 5.04 FIP	28	SP-	5.04	16.1%	11.3%	3.4%	.317	4.78	12.6%	7.0%	82	-0.26	3.78	327	72
Jack Snodgrass L 2016 · 5.01 FIP	28	SP-	5.01	15.7%	10.1%	3.6%	.305	—	—	—	—	—	4.66	118	69
Enrique Lechuga L 2015 · 4.70 FIP	29	SP-	4.70	10.0%	10.5%	2.0%	.354	3.78	10.5%	4.4%	59	-0.92	3.78	137	67
Brad Mills L 2014 · 5.61 FIP	29	SP-	5.61	18.8%	10.9%	5.0%	.364	5.00	14.5%	4.0%	182	-0.61	4.22	243	66
Marlon Arias L 2015 · 4.32 FIP	30	SP	4.32	16.8%	12.2%	2.0%	.330	3.73	17.2%	9.5%	22	-0.59	3.73	154	66
Matt Tracy L 2017 · 4.82 FIP	28	SP-	4.82	16.1%	9.4%	3.5%	.325	3.24	13.9%	3.5%	49	-1.58	3.24	298	65
Darin Gorski L 2016 · 4.50 FIP	28	SP	4.50	15.0%	9.8%	2.6%	.299	—	—	—	—	—	4.50	206	63
Houston Harding L 2024 · 4.54 FIP	26	SP-	4.54	16.5%	11.2%	2.6%	.268	5.19	12.0%	0.5%	61	+0.65	3.41	239	63
Edgar Osuna L 2017 · 5.05 FIP	29	SP	5.05	10.6%	8.2%	3.3%	.345	5.09	10.0%	2.8%	83	+0.04	5.05	175	62
Amilcar Gaxiola L 2019 · 4.61 FIP	28	SP-	4.61	11.8%	10.0%	2.3%	.316	—	—	—	—	—	4.58	321	62
Alejandro Astorga L 2015 · 4.35 FIP	28	SP	4.35	11.5%	10.2%	1.7%	.283	3.87	14.7%	6.1%	220	-0.48	3.72	311	61
Eric DuBose L 2004 · 5.50 FIP	28	SP	5.50	14.2%	13.0%	3.5%	.274	5.45	12.6%	-1.5%	29	-0.05	3.92	178	60
Kason Gabbard L 2008 · 4.77 FIP	26	SP	4.77	12.5%	13.3%	1.9%	.311	—	—	—	—	—	3.78	163	59
Matt Lujan L 2017 · 4.69 FIP	28	SP-	4.69	14.3%	6.4%	3.6%	.348	—	—	—	—	—	4.06	227	59
John Parke L 2023 · 4.35 FIP	28	SP-	4.35	15.5%	10.1%	2.3%	.371	—	—	—	—	—	3.22	655	58
Juan Pablo Oramas L 2017 · 4.56 FIP	27	SP	4.56	15.4%	12.3%	2.2%	.363	3.60	21.2%	13.2%	140	-0.96	3.46	440	58
Daniel Camarena L 2021 · 4.47 FIP	28	SP	4.47	14.9%	8.3%	2.9%	.273	5.73	13.7%	5.9%	121	+1.26	3.76	674	57
Nick Additon L 2016 · 4.47 FIP	28	SP-	4.47	12.9%	6.8%	2.9%	.303	3.13	19.3%	10.2%	26	-1.34	3.13	217	56
Chris Reed L 2016 · 4.67 FIP	26	SW	4.67	16.4%	9.8%	3.1%	.238	—	—	—	—	—	4.67	137	56
Orlando Lara L 2015 · 4.29 FIP	30	SP	4.29	15.2%	10.3%	2.1%	.348	4.08	14.2%	7.2%	230	-0.21	3.85	426	55

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	0.9	58	13.6%	12.5%	1.07	5.47
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Luther Hackman ('03)	1.1	71	13.3%	10.9%	1.10	5.09
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*