Mac Heuer

P Tampa Tarpons

Age 23 RHP A peak 0.1 · 2028

Overview

APROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2026	22	ANYY	6	5	21	3.43	4.39	29.0%	15.1%	—	K 21.5% · BB 17.8% · FIP 5.84
2027PROJ	23	MLBNYY	2	2	12	5.14	5.14	22.6%	14.9%	-0.0
2028PROJ43% MLB	24	MLBNYY	2	2	9	4.92	4.83	23.2%	13.0%	0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0 WAR median (P10 0 / P90 3, comp-based) · star 2% · didn't stick 88%

CompsRyan Atkinson (age 23) · Dane Acker (age 23) · Ray Gaither (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 131123vR 115

ERA5.14

FIP5.14

K%22.6%

BB%14.9%

K-BB%7.7%

Proj IP12

Value2027 · WAR

Runs saved vs league avg · 12 IP

Grades · Contract

Scouting Grades

K†5555

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)
2026	22	A MLE	Tampa Tarpons	6	5	21	93	27	14	3	83%	3.5	21.5%	17.8%	3.7%	4.2%	3.43	5.84	—
2026	22	A MLE	Tampa Tarpons	6	5	21	93	27	14	3	83%	3.5	21.5%	17.8%	3.7%	4.2%	3.43	5.84	—
2026	22	A RAW	Tampa Tarpons	6	5	21	93	27	14	3	83%	3.5	29.0%	15.1%	14.0%	3.2%	3.43	4.39	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	23	MLB	NYY	2	2	12	51	11	8	2	100%	6.0	22.6%	14.9%	7.7%	3.1%	5.14	5.14	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	24	MLB MLE	NYY	4	4	20	84	20	11	3	100%	5.0	23.2%	13.0%	10.2%	3.0%	4.92	4.83	+0.0
2028	24	MLB CTX	NYY	2	2	9	38	9	5	1	100%	4.5	23.2%	13.0%	10.2%	3.0%	4.92	4.83	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		2	2	9	36	8	5	1	100%	4.3	23.2%	13.0%	10.2%	3.0%	4.92	4.45	+0.0
/ 200 IP	—	RAW		36	36	200	844	187	117	23	100%	5.6	23.2%	13.0%	10.2%	3.0%	4.92	4.45	+1.0
Career	—	MLE		6	5	21	93	20	17	4	83%	3.5	21.5%	17.8%	3.7%	4.2%	3.43	5.84	+0.0
/ 200 IP	—	MLE		57	48	200	886	190	157	37	83%	3.5	21.5%	17.8%	3.7%	4.2%	3.43	5.84	+0.2

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
Mac Heuer (OGILVIE)	—	—	5.14	22.6%	14.9%	3.1%	—	4.83	23.2%	10.2%	20	-0.31	—	—	—
Ryan Atkinson R 2016 · 4.58 FIP	23	SP-	4.58	18.4%	11.3%	2.9%	.315	4.48	21.6%	9.0%	305	-0.10	4.14	338	82
Dane Acker R 2022 · 5.60 FIP	23	SP	5.60	19.3%	15.2%	4.0%	.284	4.39	20.2%	8.6%	215	-1.21	4.29	257	81
Ray Gaither R 2022 · 4.85 FIP	24	SP-	4.85	21.9%	13.2%	3.5%	.314	4.34	18.3%	5.8%	123	-0.51	3.84	164	80
Noah Denoyer R 2021 · 4.51 FIP	23	SP-	4.51	21.5%	12.1%	3.1%	.275	4.10	25.7%	15.7%	121	-0.41	3.26	181	80
James Proctor R 2021 · 3.99 FIP	23	SP	3.99	22.0%	15.2%	1.5%	.277	4.39	14.0%	1.5%	48	+0.40	3.99	109	80
TJ Shook R 2021 · 4.90 FIP	23	SP	4.90	21.7%	13.8%	3.4%	.311	4.98	20.7%	10.3%	296	+0.08	3.35	452	79
Angel Guzman R 2006 · 4.73 FIP	24	SP-	4.73	22.1%	13.2%	3.3%	.353	3.88	19.6%	12.0%	91	-0.85	3.13	147	78
Shawn Hill R 2004 · 4.26 FIP	23	SP	4.26	19.6%	13.7%	2.0%	.450	3.70	14.5%	8.6%	134	-0.56	2.96	239	77
Michael Knorr R 2023 · 4.30 FIP	23	SP-	4.30	23.6%	11.1%	3.3%	.312	5.15	22.0%	9.5%	123	+0.85	4.30	181	76
Will Bednar R 2022 · 5.71 FIP	22	SP	5.71	20.5%	14.1%	4.7%	.173	4.78	26.6%	6.3%	95	-0.93	3.38	202	76
Daniel Corcino R 2014 · 4.37 FIP	23	SP-	4.37	18.8%	12.5%	2.3%	.208	4.14	19.6%	10.0%	76	-0.23	3.84	318	76
Blake Whitney R 2018 · 4.11 FIP	22	SP	4.11	19.1%	16.1%	1.1%	.338	6.22	25.6%	13.5%	33	+2.11	3.46	268	76
Rafael Montero R 2014 · 5.04 FIP	23	SP-	5.04	21.6%	11.9%	4.1%	.298	4.32	19.3%	8.2%	296	-0.72	2.43	714	75
Brandon White R 2023 · 4.93 FIP	23	SP	4.93	16.7%	10.3%	3.5%	.264	4.05	17.5%	10.6%	280	-0.88	3.90	299	75
Lisalverto Bonilla R 2014 · 4.32 FIP	24	SP-	4.32	20.5%	13.3%	2.3%	.208	3.88	19.8%	10.2%	210	-0.44	3.22	242	75
Alfredo Figaro R 2009 · 4.98 FIP	25	SP-	4.98	19.3%	12.0%	3.6%	.370	4.42	7.2%	-1.5%	15	-0.56	3.75	143	75
Tanner Hall R 2024 · 4.67 FIP	22	SP-	4.67	18.8%	11.2%	3.2%	.295	5.33	10.1%	-4.6%	72	+0.66	4.67	137	75
Rubén Menes R 2024 · 5.62 FIP	22	SP-	5.62	15.8%	15.2%	3.5%	.235	4.77	15.6%	2.4%	81	-0.85	3.39	112	75
Alonzo Tredwell R 2024 · 4.43 FIP	22	SP-	4.43	19.3%	17.4%	1.4%	.336	4.19	22.0%	9.9%	100	-0.24	4.19	166	75
Blair Henley R 2021 · 5.02 FIP	24	SP-	5.02	20.8%	12.2%	3.9%	.450	4.51	17.7%	5.4%	170	-0.51	3.97	187	75