Tommy Vail

P Winston-Salem Dash

Age 28 LHP 6'0" / 195 lbs A+

Overview

A+PROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	26	10	69	1.69	2.34	36.5%	13.1%	—	K 27.5% · BB 15.3% · FIP 3.65
2025	26	MIX3 levels	31	9	85	4.15	4.23	24.3%	15.5%	—	K 19.7% · BB 16.4% · FIP 4.85
2026	27	MIX4 levels	17	3	30	9.49	5.01	24.5%	14.8%	—	K 18.6% · BB 17.7% · FIP 6.78
2027PROJ	28	MLBCWS	—	—	0	5.78	5.78	19.5%	18.1%	—
2028PROJ30% MLB	29	MLBCWS	11	0	12	5.71	5.76	19.7%	17.4%	-0.2
2029PROJ51% MLB	30	MLBCWS	16	0	17	5.74	5.83	19.6%	17.1%	-0.2

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control30Command35

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

CompsStephen Randolph (age 29) · John Rheinecker (age 28) · Braulio Lara (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127135vR 143

ERA5.78

FIP5.78

K%19.5%

BB%18.1%

K-BB%1.4%

Proj IP59

Value2027 · WAR

Runs saved vs league avg · 59 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL3030

CMD3535

K†4545

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)
2024	25	MIX MLE	2 levels	26	10	69	274	100	36	3	38%	2.7	27.5%	15.3%	12.2%	1.7%	1.69	3.65	—
2024	25	MIX MLE	2 levels	26	10	69	274	100	36	3	38%	2.7	27.5%	15.3%	12.2%	1.7%	1.69	3.65	—
2024	25	MIX RAW	2 levels	26	10	69	274	100	36	3	38%	2.7	36.5%	13.1%	23.4%	1.1%	1.69	2.34	—
2025	26	MIX MLE	3 levels	31	9	85	375	91	58	8	29%	2.7	19.7%	16.4%	3.3%	2.4%	4.15	4.85	—
2025	26	MIX MLE	3 levels	31	9	85	375	91	58	8	29%	2.7	19.7%	16.4%	3.3%	2.4%	4.15	4.85	—
2025	26	MIX RAW	3 levels	31	9	85	375	91	58	8	29%	2.7	24.3%	15.5%	8.8%	2.1%	4.15	4.23	—
2026	27	MIX MLE	4 levels	17	3	30	155	38	23	5	18%	1.8	18.6%	17.7%	0.9%	5.5%	9.49	6.78	—
2026	27	MIX MLE	4 levels	17	3	30	155	38	23	5	18%	1.8	18.6%	17.7%	0.9%	5.5%	9.49	6.78	—
2026	27	MIX RAW	4 levels	17	3	30	155	38	23	5	18%	1.8	24.5%	14.8%	9.7%	3.2%	9.49	5.01	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CWS	—	—	0	—	—	—	—	—	—	19.5%	18.1%	1.4%	3.0%	5.78	5.78	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CWS	39	0	41	172	34	30	5	0%	1.0	19.7%	17.4%	2.3%	3.2%	5.71	5.76	-0.5
2029	30	MLB MLE	CWS	31	0	33	139	27	24	5	0%	1.1	19.6%	17.1%	2.5%	3.4%	5.74	5.83	-0.4
2028	29	MLB CTX	CWS	11	0	12	51	10	9	2	0%	1.1	19.7%	17.4%	2.3%	3.2%	5.71	5.76	-0.2
2029	30	MLB CTX	CWS	16	0	17	72	14	12	2	0%	1.1	19.6%	17.1%	2.5%	3.4%	5.74	5.83	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		28	0	29	123	24	21	4	0%	1.0	19.6%	17.2%	2.4%	3.3%	5.73	5.42	-0.3
/ 200 IP	—	RAW		190	0	200	844	165	145	28	0%	1.1	19.6%	17.2%	2.4%	3.3%	5.73	5.42	-2.0
Career	—	MLE		74	22	184	804	178	131	22	30%	2.5	22.1%	16.3%	5.9%	2.8%	4.10	4.81	-1.0
/ 200 IP	—	MLE		80	24	200	872	193	142	24	30%	2.5	22.1%	16.3%	5.9%	2.8%	4.10	4.81	-2.8

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 A+Winston-Salem Dash · 17 IPFIP 5.42 → 6.78 (+1.37)K% 24.2% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.18%	—	×0.770	18.62%
BB% (unintentional) /BF	15.38%	—	×1.150	17.69%
HR / BF /BF	4.40%	÷1.000	×1.250	5.49%

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 100).

Result: FIP 5.42 → 6.78, 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).

2026 AABirmingham Barons · 6 IPFIP 3.25 → 3.60 (+0.35)K% 13.8% → 11.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.79%	—	×0.810	11.17%
BB% (unintentional) /BF	10.34%	—	×1.100	11.38%
HR / BF /BF	0.00%	÷1.000	×1.200	0.00%

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 100).

Result: FIP 3.25 → 3.60, 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).

2026 ROKACL White Sox · 5 IPFIP 3.48 → 6.14 (+2.66)K% 45.5% → 30.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	45.45%	—	×0.680	30.91%
BB% (unintentional) /BF	13.64%	—	×1.250	17.05%
HR / BF /BF	4.55%	÷1.000	×1.400	6.36%

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 100).

Result: FIP 3.48 → 6.14, 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 AABirmingham Barons · 51 IPFIP 3.87 → 4.80 (+0.93)K% 22.1% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.12%	—	×0.810	17.92%
BB% (unintentional) /BF	15.04%	—	×1.100	16.55%
HR / BF /BF	1.33%	÷0.784	×1.200	2.03%

Result: FIP 3.87 → 4.80, 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 A+Winston-Salem Dash · 30 IPFIP 3.66 → 4.95 (+1.29)K% 29.5% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.46%	—	×0.770	22.68%
BB% (unintentional) /BF	13.95%	—	×1.150	16.05%
HR / BF /BF	2.33%	÷0.923	×1.250	3.15%

Result: FIP 3.66 → 4.95, 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 AAACharlotte Knights · 3 IPFIP 11.12 → 10.01 (−1.12)K% 15.0% → 12.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.00%	—	×0.860	12.90%
BB% (unintentional) /BF	30.00%	—	×0.900	27.00%
HR / BF /BF	10.00%	÷1.320	×1.100	8.34%

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 164).

Result: FIP 11.12 → 10.01, 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+Winston-Salem Dash · 36 IPFIP 3.04 → 4.28 (+1.24)K% 29.9% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.93%	—	×0.770	23.05%
BB% (unintentional) /BF	13.61%	—	×1.150	15.65%
HR / BF /BF	1.36%	÷0.817	×1.250	2.08%

Result: FIP 3.04 → 4.28, 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 AKannapolis Cannon Ballers · 33 IPFIP 1.40 → 2.91 (+1.51)K% 44.1% → 32.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.09%	—	×0.740	32.63%
BB% (unintentional) /BF	12.60%	—	×1.180	14.87%
HR / BF /BF	0.79%	÷0.820	×1.300	1.25%

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 64).

Result: FIP 1.40 → 2.91, 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
Tommy Vail (OGILVIE)	—	—	5.78	19.5%	18.1%	3.0%	—	5.79	19.7%	2.4%	74	+0.01	—	—	—
Stephen Randolph L 2003 · 4.83 FIP	29	SU	4.83	18.5%	14.8%	2.6%	.247	5.69	15.8%	-3.0%	82	+0.86	4.83	155	70
John Rheinecker L 2007 · 5.13 FIP	28	SW	5.13	16.7%	10.9%	3.8%	.317	—	—	—	—	—	4.14	121	69
Braulio Lara L 2017 · 5.80 FIP	28	SU	5.80	19.8%	17.8%	3.9%	.361	—	—	—	—	—	3.96	118	68
Will Lamb L 2017 · 5.78 FIP	26	SU	5.78	20.0%	14.0%	4.7%	.322	—	—	—	—	—	3.64	178	68
Brian Holmes L 2017 · 5.91 FIP	26	SW	5.91	15.5%	11.7%	4.8%	.354	—	—	—	—	—	3.60	205	66
Kit Scheetz L 2021 · 5.08 FIP	27	SU	5.08	16.2%	13.6%	2.9%	.278	—	—	—	—	—	2.34	195	66
Luke Westphal L 2016 · 4.69 FIP	27	SU	4.69	21.2%	19.7%	1.6%	.353	—	—	—	—	—	2.97	294	66
Trey Jeans L 2022 · 5.09 FIP	26	SU	5.09	22.3%	16.5%	3.3%	.291	—	—	—	—	—	2.74	111	66
Randy Keisler L 2005 · 5.07 FIP	29	SW	5.07	16.4%	9.9%	3.8%	.295	5.51	6.5%	0.0%	17	+0.44	5.07	135	65
Joey Marciano L 2023 · 4.90 FIP	28	SU	4.90	20.0%	17.3%	2.4%	.314	—	—	—	—	—	3.65	330	65
Andrew Mitchell L 2022 · 6.04 FIP	27	SU	6.04	18.2%	17.0%	4.2%	.317	—	—	—	—	—	2.51	119	65
Adam Scott L 2023 · 4.65 FIP	27	SW	4.65	16.1%	17.3%	1.3%	.301	—	—	—	—	—	4.17	315	65
Juan Grullon L 2016 · 4.64 FIP	26	SU	4.64	19.8%	10.9%	3.3%	.305	—	—	—	—	—	4.64	134	64
Heath Murray L 2001 · 5.40 FIP	28	SU	5.40	14.0%	11.6%	3.6%	.333	6.02	20.0%	7.3%	12	+0.62	4.69	159	63
Bryan Harper L 2018 · 4.63 FIP	28	SU	4.63	14.9%	13.9%	1.9%	.288	—	—	—	—	—	4.13	133	63
Mitchell Tyranski L 2024 · 4.90 FIP	26	SU	4.90	21.0%	12.3%	3.7%	.234	3.46	20.5%	4.0%	57	-1.44	3.46	145	63
Trey Cumbie L 2022 · 5.07 FIP	26	SU	5.07	23.3%	16.1%	3.4%	.215	—	—	—	—	—	3.44	152	63
Ron Mahay L 2000 · 6.03 FIP	29	SU	6.03	16.1%	12.1%	5.0%	.353	4.58	22.4%	12.1%	81	-1.45	3.14	568	63
Juan Pablo Perez L 2007 · 5.32 FIP	28	SU	5.32	17.5%	14.0%	3.5%	.324	—	—	—	—	—	1.75	104	62
Cam Booser L 2022 · 6.54 FIP	30	SU	6.54	20.8%	20.7%	4.7%	.350	4.49	24.8%	15.2%	157	-2.05	2.76	314	62

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	0.7	44	19.6%	17.6%	1.22	5.75
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*