Landon Tomkins

P Altoona Curve

Age 27 RHP 6'3" / 200 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX2 levels	34	0	43	4.19	2.98	24.2%	8.4%	—	K 18.1% · BB 9.8% · FIP 3.86
2025	25	MIX2 levels	49	0	60	2.55	2.62	22.5%	9.5%	—	K 17.5% · BB 10.8% · FIP 3.25
2026	26	MIX2 levels	43	1	73	4.91	4.07	15.6%	12.3%	—	K 13.0% · BB 14.2% · FIP 4.72
2027PROJ	27	MLBPIT	67	0	70	5.32	5.32	14.1%	13.3%	-0.6
2028PROJ38% MLB	28	MLBPIT	25	0	26	5.27	5.30	14.9%	13.0%	-0.2
2029PROJ56% MLB	29	MLBPIT	34	0	36	5.30	5.36	15.3%	13.0%	-0.3

Next 3 projected WAR -1.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control45Command45

Career WAR0 WAR median (P10 0 / P90 0, comp-based) · star 0% · didn't stick 98%

CompsJulian Arballo (age 27) · Kevin Gryboski (age 28) · David Goforth (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 134126vR 118

ERA5.32

FIP5.32

K%14.1%

BB%13.3%

K-BB%0.8%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL4545

CMD4545

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 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 + 2027 so far)
2023	23	A MLE	Bradenton Marauders	11	0	16	72	6	8	1	0%	1.5	6.2%	13.1%	-6.9%	1.9%	4.50	5.26	—
2023	23	A RAW	Bradenton Marauders	11	0	16	72	6	8	1	0%	1.5	8.3%	11.1%	-2.8%	1.4%	4.50	4.66	—
2024	24	MIX MLE	2 levels	34	0	43	190	46	16	3	0%	1.3	18.1%	9.8%	8.3%	1.9%	4.19	3.86	—
2024	24	MIX MLE	2 levels	34	0	43	190	46	16	3	0%	1.3	18.1%	9.8%	8.3%	1.9%	4.19	3.86	—
2024	24	MIX RAW	2 levels	34	0	43	190	46	16	3	0%	1.3	24.2%	8.4%	15.8%	1.6%	4.19	2.98	—
2025	25	MIX MLE	2 levels	49	0	60	253	57	24	1	0%	1.2	17.5%	10.8%	6.7%	0.5%	2.55	3.25	—
2025	25	MIX MLE	2 levels	49	0	60	253	57	24	1	0%	1.2	17.5%	10.8%	6.7%	0.5%	2.55	3.25	—
2025	25	MIX RAW	2 levels	49	0	60	253	57	24	1	0%	1.2	22.5%	9.5%	13.0%	0.4%	2.55	2.62	—
2026	26	MIX MLE	2 levels	43	1	73	333	52	41	4	2%	1.7	13.0%	14.2%	-1.2%	1.7%	4.91	4.72	—
2026	26	MIX MLE	2 levels	43	1	73	333	52	41	4	2%	1.7	13.0%	14.2%	-1.2%	1.7%	4.91	4.72	—
2026	26	MIX RAW	2 levels	43	1	73	333	52	41	4	2%	1.7	15.6%	12.3%	3.3%	1.2%	4.91	4.07	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	PIT	67	0	70	296	42	39	7	0%	1.0	14.1%	13.3%	0.8%	2.5%	5.32	5.32	-0.6
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	PIT	65	0	68	287	43	37	7	0%	1.0	14.9%	13.0%	1.9%	2.6%	5.27	5.30	-0.6
2029	29	MLB MLE	PIT	62	0	65	274	42	35	8	0%	1.0	15.3%	13.0%	2.3%	2.8%	5.30	5.36	-0.6
2028	28	MLB CTX	PIT	25	0	26	110	16	14	3	0%	1.0	14.9%	13.0%	1.9%	2.6%	5.27	5.30	-0.2
2029	29	MLB CTX	PIT	34	0	36	152	23	20	4	0%	1.1	15.3%	13.0%	2.3%	2.8%	5.30	5.36	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		59	0	62	260	39	34	7	0%	1.0	15.1%	13.0%	2.1%	2.7%	5.29	4.96	-0.3
/ 200 IP	—	RAW		190	0	200	844	127	110	23	0%	1.1	15.1%	13.0%	2.1%	2.7%	5.29	4.96	-1.0
Career	—	MLE		137	1	192	848	126	103	12	1%	1.4	14.9%	12.1%	2.8%	1.4%	3.98	4.13	-1.2
/ 200 IP	—	MLE		142	1	200	882	131	107	12	1%	1.4	14.9%	12.1%	2.8%	1.4%	3.98	4.13	-1.8

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
Landon Tomkins (OGILVIE)	—	—	5.32	14.1%	13.3%	2.5%	—	5.33	15.1%	2.1%	133	+0.01	—	—	—
Julian Arballo R 2015 · 5.13 FIP	27	SU	5.13	15.1%	13.8%	2.8%	.335	4.46	12.6%	0.6%	116	-0.67	4.45	214	90
Kevin Gryboski R 2002 · 5.02 FIP	28	SU	5.02	13.9%	13.4%	2.5%	.263	3.83	12.0%	2.9%	126	-1.19	3.67	178	88
David Goforth R 2016 · 4.68 FIP	27	SU	4.68	14.5%	12.8%	2.1%	.333	4.52	13.9%	4.6%	122	-0.16	3.98	256	88
Kyle McMyne R 2017 · 4.84 FIP	27	SU	4.84	12.5%	12.8%	2.1%	.330	—	—	—	—	—	3.93	181	88
Armando Rivero R 2015 · 4.29 FIP	27	SU	4.29	18.7%	13.5%	1.9%	.256	2.70	32.9%	19.8%	68	-1.59	2.70	125	84
Roman Phansalkar R 2024 · 5.39 FIP	26	SU	5.39	15.8%	13.2%	3.6%	.294	4.33	18.2%	3.7%	31	-1.06	4.33	164	84
Trey Haley R 2016 · 4.98 FIP	26	SU	4.98	14.0%	16.5%	1.8%	.282	—	—	—	—	—	3.14	111	84
Francisco Rodriguez R 2010 · 4.33 FIP	27	SU	4.33	17.2%	11.0%	2.4%	.283	5.00	11.9%	3.4%	14	+0.67	3.16	334	84
Gregory Infante R 2015 · 4.54 FIP	28	SU	4.54	16.9%	15.7%	1.6%	.290	3.78	21.3%	12.7%	181	-0.76	2.97	230	83
Tucker Healy R 2017 · 4.33 FIP	27	SU	4.33	15.6%	11.5%	2.0%	.321	5.20	19.2%	8.7%	24	+0.87	2.82	174	83
Tyler Mizenko R 2016 · 5.15 FIP	26	SU	5.15	13.3%	10.2%	3.5%	.303	—	—	—	—	—	3.66	104	83
Brad Schreiber R 2017 · 4.23 FIP	26	SU	4.23	17.3%	12.7%	1.8%	.312	—	—	—	—	—	3.81	171	82
Justin Lehr R 2005 · 4.58 FIP	27	SU	4.58	14.9%	10.4%	2.6%	.252	4.23	16.0%	8.0%	16	-0.35	4.23	148	82
Nate Bump R 2003 · 4.74 FIP	27	SU	4.74	10.2%	12.0%	1.8%	.244	4.27	12.5%	5.5%	112	-0.47	4.06	148	82
Mark Peterson R 2017 · 4.78 FIP	26	SU	4.78	13.7%	11.9%	2.4%	.349	—	—	—	—	—	4.65	185	82
Connor Fenlong R 2024 · 4.16 FIP	24	SU	4.16	13.4%	11.8%	1.3%	.313	4.14	22.4%	14.4%	54	-0.02	4.14	102	82
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	82
Brian Bass R 2009 · 4.70 FIP	27	SU	4.70	13.5%	9.8%	2.8%	.321	—	—	—	—	—	4.70	176	82
Nelson Gonzalez R 2017 · 5.00 FIP	27	SU	5.00	15.3%	13.7%	2.6%	.239	5.79	17.4%	6.7%	96	+0.79	3.42	258	81
Daniel Webb R 2015 · 4.56 FIP	25	SU	4.56	15.7%	13.4%	2.0%	.321	—	—	—	—	—	4.12	126	81

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,474 reliever careers (754 from 1990-2025 + 720 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	1.0	68	14.7%	13.1%	1.01	5.30
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Luther Hackman ('03)	1.1	71	13.3%	10.9%	1.10	5.09
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*
Ron Willis ('66-'70, 0 WAR*)	1.2	60	15.6%*	12.1%*	0.86*	4.17*