Tommy Mace

P Columbus Clippers

Age 28 RHP 6'6" / 230 lbs AAA

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	AACLE	28	27	146	3.71	4.14	16.8%	7.4%	—	K 13.6% · BB 8.2% · FIP 4.86
2025	26	MIX2 levels	30	20	116	3.73	4.57	17.7%	15.5%	—	K 14.5% · BB 16.7% · FIP 5.24
2026	27	AAACLE	25	0	40	5.80	6.47	15.4%	17.9%	—	K 13.2% · BB 16.2% · FIP 6.20
2027PROJ	28	MLBCLE	1	1	6	6.41	6.41	12.4%	17.9%	-0.1
2028PROJ37% MLB	29	MLBCLE	3	3	16	6.28	6.33	13.3%	17.2%	-0.2
2029PROJ55% MLB	30	MLBCLE	3	3	20	6.26	6.36	13.7%	16.9%	-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

Stuff35Control25Command25

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsNoah Song (age 26) · Alex Caldera (age 29) · Clay Condrey (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 155147vR 139

ERA6.41

FIP6.41

K%12.4%

BB%17.9%

K-BB%-5.5%

Proj IP59

Value2027 · WAR

Runs saved vs league avg · 59 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL2525

CMD2525

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)
2022	23	A+ MLE	Lake County Captains	22	21	85	360	75	38	13	95%	3.9	16.0%	12.1%	3.9%	4.0%	4.55	5.47	—
2022	23	A+ RAW	Lake County Captains	22	21	85	360	75	38	13	95%	3.9	20.8%	10.6%	10.3%	3.6%	4.55	4.66	—
2023	24	MIX MLE	2 levels	24	17	115	503	103	54	13	71%	4.8	16.2%	12.0%	4.2%	3.3%	4.63	5.06	—
2023	24	MIX RAW	2 levels	24	17	115	503	103	54	13	71%	4.8	20.5%	10.7%	9.7%	2.6%	4.63	4.19	—
2024	25	AA MLE	Akron RubberDucks	28	27	146	618	104	46	17	96%	5.2	13.6%	8.2%	5.4%	3.4%	3.71	4.86	—
2024	25	AA MLE	Akron RubberDucks	28	27	146	618	104	46	17	96%	5.2	13.6%	8.2%	5.4%	3.4%	3.71	4.86	—
2024	25	AA RAW	Akron RubberDucks	28	27	146	618	104	46	17	96%	5.2	16.8%	7.4%	9.4%	2.8%	3.71	4.14	—
2025	26	MIX MLE	2 levels	30	20	116	485	86	75	9	67%	3.9	14.5%	16.7%	-2.2%	2.3%	3.73	5.24	—
2025	26	MIX MLE	2 levels	30	20	116	485	86	75	9	67%	3.9	14.5%	16.7%	-2.2%	2.3%	3.73	5.24	—
2025	26	MIX RAW	2 levels	30	20	116	485	86	75	9	67%	3.9	17.7%	15.5%	2.3%	1.9%	3.73	4.57	—
2026	27	AAA MLE	Columbus Clippers	25	0	40	195	30	35	7	0%	1.6	13.2%	16.2%	-2.9%	3.9%	5.80	6.20	—
2026	27	AAA MLE	Columbus Clippers	25	0	40	195	30	35	7	0%	1.6	13.2%	16.2%	-2.9%	3.9%	5.80	6.20	—
2026	27	AAA RAW	Columbus Clippers	25	0	40	195	30	35	7	0%	1.6	15.4%	17.9%	-2.6%	3.6%	5.80	6.47	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CLE	1	1	6	25	3	5	1	100%	6.0	12.4%	17.9%	-5.5%	3.1%	6.41	6.41	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CLE	7	7	44	186	25	32	6	100%	6.3	13.3%	17.2%	-4.0%	3.3%	6.28	6.33	-0.4
2029	30	MLB MLE	CLE	6	6	37	155	21	26	5	100%	6.1	13.7%	16.9%	-3.3%	3.4%	6.26	6.36	-0.4
2028	29	MLB CTX	CLE	3	3	16	68	9	12	2	100%	5.3	13.3%	17.2%	-4.0%	3.3%	6.28	6.33	-0.2
2029	30	MLB CTX	CLE	3	3	20	84	12	14	3	100%	6.7	13.7%	16.9%	-3.3%	3.4%	6.26	6.36	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		6	6	36	154	21	26	5	100%	6.1	13.5%	17.1%	-3.6%	3.4%	6.27	5.96	-0.2
/ 200 IP	—	RAW		32	32	200	844	115	143	27	100%	6.3	13.5%	17.1%	-3.6%	3.4%	6.27	5.96	-1.2
Career	—	MLE		129	85	501	2161	319	267	71	66%	3.9	14.8%	12.4%	2.4%	3.3%	4.24	5.22	-0.8
/ 200 IP	—	MLE		51	34	200	862	127	107	28	66%	3.9	14.8%	12.4%	2.4%	3.3%	4.24	5.22	-2.1

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 AAAColumbus Clippers · 40 IPFIP 6.04 → 6.20 (+0.15)K% 15.4% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.38%	—	×0.860	13.23%
BB% (unintentional) /BF	17.95%	—	×0.900	16.15%
HR / BF /BF	3.59%	÷1.000	×1.100	3.95%

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 6.04 → 6.20, 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).

2025 AAAkron RubberDucks · 102 IPFIP 4.54 → 5.28 (+0.74)K% 17.1% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.06%	—	×0.810	13.82%
BB% (unintentional) /BF	15.65%	—	×1.100	17.22%
HR / BF /BF	1.64%	÷0.926	×1.200	2.12%

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 85).

Result: FIP 4.54 → 5.28, 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).

2025 AAAColumbus Clippers · 13 IPFIP 4.88 → 4.98 (+0.11)K% 22.8% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.81%	—	×0.860	19.61%
BB% (unintentional) /BF	14.04%	—	×0.900	12.63%
HR / BF /BF	3.51%	÷1.093	×1.100	3.53%

Result: FIP 4.88 → 4.98, 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 AAAkron RubberDucks · 146 IPFIP 4.13 → 4.86 (+0.73)K% 16.8% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.83%	—	×0.810	13.63%
BB% (unintentional) /BF	7.44%	—	×1.100	8.19%
HR / BF /BF	2.75%	÷0.966	×1.200	3.42%

Result: FIP 4.13 → 4.86, 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 AAAkron RubberDucks · 61 IPFIP 4.96 → 5.99 (+1.02)K% 18.3% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.28%	—	×0.810	14.81%
BB% (unintentional) /BF	12.90%	—	×1.100	14.19%
HR / BF /BF	3.23%	÷0.909	×1.200	4.26%

Result: FIP 4.96 → 5.99, 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+Lake County Captains · 54 IPFIP 3.14 → 3.92 (+0.78)K% 23.2% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.21%	—	×0.770	17.88%
BB% (unintentional) /BF	8.04%	—	×1.150	9.24%
HR / BF /BF	1.79%	÷1.060	×1.250	2.11%

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 112).

Result: FIP 3.14 → 3.92, 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+Lake County Captains · 85 IPFIP 4.66 → 5.47 (+0.81)K% 20.8% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.83%	—	×0.770	16.04%
BB% (unintentional) /BF	10.56%	—	×1.150	12.14%
HR / BF /BF	3.61%	÷1.134	×1.250	3.98%

Result: FIP 4.66 → 5.47, 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 Mace (OGILVIE)	—	—	6.41	12.4%	17.9%	3.1%	—	6.34	13.4%	-3.6%	81	-0.07	—	—	—
Noah Song R 2023 · 6.06 FIP	26	SP	6.06	12.0%	13.2%	4.2%	.239	3.80	19.8%	8.3%	116	-2.26	3.68	138	68
Alex Caldera R 2015 · 5.57 FIP	29	SW	5.57	10.4%	13.1%	3.1%	.333	4.54	11.9%	0.8%	84	-1.03	4.54	120	66
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	65
Daniel Bard R 2012 · 5.69 FIP	27	SP-	5.69	13.7%	15.2%	3.3%	.271	—	—	—	—	—	2.56	456	65
Chris Jensen R 2018 · 5.31 FIP	27	SW	5.31	12.0%	10.6%	3.4%	.347	—	—	—	—	—	4.47	488	64
Bryan Garcia R 2023 · 5.84 FIP	28	SP-	5.84	13.1%	15.8%	3.4%	.321	—	—	—	—	—	2.59	319	64
Jake Walters R 2023 · 5.85 FIP	27	SW	5.85	15.2%	13.9%	4.2%	.254	—	—	—	—	—	3.51	261	63
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	62
Brad Allen R 2016 · 5.82 FIP	27	SW	5.82	14.7%	13.2%	4.2%	.272	—	—	—	—	—	4.25	149	61
Luke Hudson R 2005 · 5.54 FIP	28	SP	5.54	13.9%	12.6%	3.7%	.260	3.81	14.5%	6.1%	102	-1.73	3.81	235	61
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	60
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	60
Victor Mateo R 2016 · 5.45 FIP	27	SW	5.45	10.2%	12.2%	3.0%	.370	—	—	—	—	—	4.32	199	60
Matt Palmer R 2008 · 5.81 FIP	29	SP	5.81	4.5%	17.9%	1.5%	.314	4.33	12.8%	2.4%	171	-1.48	2.98	183	59
Rafael Pineda R 2017 · 5.26 FIP	26	SP-	5.26	6.5%	9.9%	2.6%	.299	—	—	—	—	—	4.25	101	59
David Holman R 2018 · 5.28 FIP	28	SW	5.28	10.0%	8.3%	3.6%	.284	5.80	8.9%	-1.8%	35	+0.52	5.28	129	58
Tim Brennan R 2024 · 6.63 FIP	27	SP-	6.63	8.7%	12.8%	4.8%	.305	—	—	—	—	—	3.08	266	57
Eddie Bonine R 2009 · 5.60 FIP	28	SW	5.60	13.1%	7.6%	4.8%	.306	4.54	8.6%	2.0%	68	-1.06	4.40	129	57
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	57
Alex Blackford R 2017 · 5.59 FIP	26	SP	5.59	14.9%	12.5%	4.0%	.289	—	—	—	—	—	3.48	229	56

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	47	13.0%	17.4%	1.25	6.33
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Matt Anderson ('05)	1.3	51	19.3%	13.5%	1.05	5.19
Lloyd Allen ('69-'75, -5 WAR*)	1.5	59	19.8%*	13.9%*	0.79*	5.99*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*