Adam Mazur

P Jacksonville Jumbo Shrimp

Age 26 RHP 6'2" / 180 lbs AAA peak 0.6 · 2027 ILInjured 60-Day (D60)

Overview

AAASPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	22	MIX2 levels	24	18	96	2.81	2.43	22.8%	4.3%	—	K 18.0% · BB 4.9% · FIP 3.22
2024	23	MIX3 levels	27	27	127	5.46	4.07	21.1%	7.2%	2.0	K 18.4% · BB 7.1% · FIP 4.49
2025	24	MIX2 levels	28	25	137	4.46	4.65	20.2%	7.1%	1.2	K 17.8% · BB 6.6% · FIP 5.21
2026	25	No MLB games played
2027PROJ	26	MLBMIA	8	8	45	5.38	5.28	17.0%	9.8%	0.1
2028PROJ64% MLB	27	MLBMIA	10	10	63	5.24	5.22	17.5%	9.6%	0.1
2029PROJ76% MLB	28	MLBMIA	9	9	53	5.20	5.23	17.7%	9.6%	0.1

Last 3 seasons WAR 3.2 · Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo54

xwOBA vs21

K%10

CompsNestor Molina (age 27) · Andrew Quezada (age 26) · Jared Mortensen (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 117

ERA5.38

FIP5.28

K%17.0%

BB%9.8%

K-BB%7.3%

Proj IP101

Value2027 · WAR

Runs saved vs league avg · 101 IP

Grades · Statcast · Contract

Scouting Grades

STUF4040

CTRL3535

CMD2525

K†4040

Statcast Percentiles

FB Velo

p5494.8

Whiff%

p2521.8%

p1013.7%

xwOBA vs

p210.346

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)
2023	22	MIX MLE	2 levels	24	18	96	394	90	17	5	75%	4.0	18.0%	4.9%	13.2%	1.9%	2.81	3.22	—
2023	22	MIX RAW	2 levels	24	18	96	394	90	17	5	75%	4.0	22.8%	4.3%	18.5%	1.3%	2.81	2.43	—
2024	23	MIX MLE	3 levels	27	27	127	541	114	39	18	100%	4.7	18.4%	7.1%	11.3%	3.7%	5.46	4.49	+1.3
2024	23	MIX MLE	3 levels	27	27	127	541	114	39	18	100%	4.7	18.4%	7.1%	11.3%	3.7%	5.46	4.49	+1.3
2024	23	MIX RAW	3 levels	27	27	127	541	114	39	18	100%	4.7	21.1%	7.2%	13.9%	3.3%	5.46	4.07	+2.0
2025	24	MIX MLE	2 levels	28	25	137	589	119	42	25	89%	4.9	17.8%	6.6%	11.2%	5.1%	4.46	5.21	+0.3
2025	24	MIX MLE	2 levels	28	25	137	589	119	42	25	89%	4.9	17.8%	6.6%	11.2%	5.1%	4.46	5.21	+0.3
2025	24	MIX RAW	2 levels	28	25	137	589	119	42	25	89%	4.9	20.2%	7.1%	13.1%	4.2%	4.46	4.65	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			14	14	64	297	41	33	10	100%	4.5	13.8%	11.1%	2.7%	3.4%	6.22	5.41	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	MIA	8	8	45	190	32	19	7	100%	5.6	17.0%	9.8%	7.3%	3.7%	5.38	5.28	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	MIA	16	16	98	412	72	40	15	100%	6.1	17.5%	9.6%	7.9%	3.6%	5.24	5.22	+0.2
2029	28	MLB MLE	MIA	12	12	70	296	52	28	11	100%	5.8	17.7%	9.6%	8.1%	3.7%	5.20	5.23	+0.1
2030	29	MLB MLE	MIA	9	9	53	225	39	22	9	100%	5.9	17.3%	9.8%	7.6%	3.8%	5.27	5.34	+0.0
2031	30	MLB MLE	MIA	7	7	40	170	28	17	7	100%	5.7	16.8%	10.0%	6.8%	4.0%	5.41	5.52	-0.1
2028	27	MLB CTX	MIA	10	10	63	266	47	26	10	100%	6.3	17.5%	9.6%	7.9%	3.6%	5.24	5.22	+0.1
2029	28	MLB CTX	MIA	9	9	53	224	40	22	8	100%	5.9	17.7%	9.6%	8.1%	3.7%	5.20	5.23	+0.1
2030	29	MLB CTX	MIA	7	7	44	186	32	18	7	100%	6.3	17.3%	9.8%	7.6%	3.8%	5.27	5.34	+0.0
2031	30	MLB CTX	MIA	6	6	35	148	25	15	6	100%	5.8	16.8%	10.0%	6.8%	4.0%	5.41	5.52	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		46	46	258	1116	183	113	41	100%	5.6	16.4%	10.1%	6.3%	3.7%	5.50	4.99	+1.2
/ 200 IP	—	RAW		36	36	200	866	142	88	32	100%	5.6	16.4%	10.1%	6.3%	3.7%	5.50	4.99	+0.9
Career	—	MLE		79	70	360	1524	276	96	57	89%	4.6	18.1%	6.3%	11.8%	3.8%	4.37	4.44	+0.3
/ 200 IP	—	MLE		44	39	200	846	153	54	32	89%	4.6	18.1%	6.3%	11.8%	3.8%	4.37	4.44	+0.2

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.

2025 AAAJacksonville Jumbo Shrimp · 107 IPFIP 4.63 → 5.37 (+0.74)K% 22.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.860	19.11%
BB% (unintentional) /BF	6.67%	—	×0.900	6.00%
HR / BF /BF	4.67%	÷0.903	×1.100	5.69%

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 81).

Result: FIP 4.63 → 5.37, 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 AAAJacksonville Jumbo Shrimp · 61 IPFIP 4.10 → 4.74 (+0.64)K% 22.8% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.81%	—	×0.860	19.62%
BB% (unintentional) /BF	4.94%	—	×0.900	4.45%
HR / BF /BF	4.18%	÷0.925	×1.100	4.97%

Result: FIP 4.10 → 4.74, 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 AASan Antonio Missions · 32 IPFIP 1.83 → 2.43 (+0.60)K% 26.7% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.67%	—	×0.810	21.60%
BB% (unintentional) /BF	4.17%	—	×1.100	4.58%
HR / BF /BF	0.83%	÷0.953	×1.200	1.05%

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 91).

Result: FIP 1.83 → 2.43, 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+Fort Wayne TinCaps · 58 IPFIP 2.40 → 3.11 (+0.71)K% 20.4% → 15.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.43%	—	×0.770	15.73%
BB% (unintentional) /BF	4.35%	—	×1.150	5.00%
HR / BF /BF	0.87%	÷0.848	×1.250	1.28%

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 70).

Result: FIP 2.40 → 3.11, 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 AASan Antonio Missions · 38 IPFIP 2.43 → 3.37 (+0.94)K% 26.2% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.22%	—	×0.810	21.24%
BB% (unintentional) /BF	4.27%	—	×1.100	4.70%
HR / BF /BF	1.83%	÷0.820	×1.200	2.68%

Result: FIP 2.43 → 3.37, 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
Adam Mazur (OGILVIE)	—	—	5.28	17.0%	9.8%	3.7%	—	5.25	17.5%	7.9%	221	-0.03	—	—	—
Nestor Molina R 2016 · 4.83 FIP	27	SP	4.83	15.0%	8.0%	3.6%	.304	3.61	17.0%	10.2%	289	-1.22	3.01	401	85
Andrew Quezada R 2023 · 5.33 FIP	26	SP-	5.33	14.4%	9.5%	4.1%	.344	4.90	12.7%	5.3%	173	-0.43	4.40	412	81
Jared Mortensen R 2015 · 4.42 FIP	27	SP-	4.42	16.9%	7.8%	3.2%	.287	4.99	20.9%	2.1%	72	+0.57	4.42	200	81
Enrique Gonzalez R 2006 · 4.49 FIP	24	SP-	4.49	14.3%	7.4%	3.0%	.287	—	—	—	—	—	4.49	132	81
Forrest Snow R 2015 · 5.03 FIP	26	SP-	5.03	16.1%	8.2%	4.1%	.263	4.14	21.8%	14.2%	256	-0.89	3.02	406	80
Nolan McLean R 2024 · 4.40 FIP	23	SP	4.40	20.0%	10.1%	3.1%	.292	3.26	25.6%	16.0%	341	-1.14	3.17	451	80
M.D. Johnson R 2023 · 5.64 FIP	26	SP	5.64	16.4%	12.7%	4.2%	.254	3.52	14.6%	4.7%	67	-2.12	3.52	395	79
Nic Swanson R 2024 · 4.91 FIP	25	SP	4.91	19.3%	11.8%	3.5%	.286	5.43	19.9%	6.5%	132	+0.52	4.29	438	79
Chandler Champlain R 2024 · 4.72 FIP	25	SP	4.72	16.7%	8.1%	3.6%	.298	4.77	15.3%	8.7%	247	+0.05	4.56	628	78
Luke Irvine R 2016 · 4.31 FIP	27	SP-	4.31	13.4%	9.8%	2.0%	.302	—	—	—	—	—	4.31	104	78
Caleb Kilian R 2023 · 4.61 FIP	26	SP	4.61	16.0%	6.2%	3.8%	.290	3.54	21.7%	13.5%	105	-1.07	2.42	444	78
Jarrod Cande R 2024 · 5.42 FIP	24	SP	5.42	16.7%	11.0%	4.3%	.256	5.72	11.7%	-3.6%	23	+0.30	4.31	315	78
Brannon Easterling R 2017 · 4.40 FIP	26	SP-	4.40	12.7%	8.2%	2.4%	.322	—	—	—	—	—	3.50	334	77
Chris Stratton R 2017 · 4.19 FIP	26	SP	4.19	18.7%	8.4%	2.9%	.328	4.40	20.1%	11.2%	275	+0.21	3.17	991	77
Asher Wojciechowski R 2015 · 4.30 FIP	26	SP	4.30	15.7%	8.5%	2.6%	.323	4.61	20.4%	12.2%	287	+0.31	3.15	678	77
Mike Vasil R 2024 · 5.03 FIP	24	SP	5.03	15.4%	7.7%	4.1%	.310	3.89	19.4%	8.3%	101	-1.14	3.63	429	77
Gabriel Arias R 2015 · 4.42 FIP	25	SP	4.42	13.1%	7.2%	2.8%	.299	—	—	—	—	—	4.11	195	77
Jake Bockenstedt R 2024 · 6.05 FIP	24	SP	6.05	17.0%	13.1%	5.0%	.322	4.35	16.8%	5.4%	126	-1.70	3.74	218	77
Juan Carlos Sulbaran R 2016 · 4.65 FIP	26	SP	4.65	15.0%	8.9%	3.1%	.289	—	—	—	—	—	4.65	278	77
Kyle Haynes R 2016 · 4.58 FIP	25	SP	4.58	15.7%	9.9%	2.8%	.324	—	—	—	—	—	4.08	240	76

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	2.2	62	16.8%	9.9%	1.42	5.43
Lance Painter ('03)	2.2	56	16.7%	9.0%	1.32	5.24
Doug Linton ('03)	1.5	51	14.9%	9.0%	1.47	5.78
Steve Shields ('85-'89, -3 WAR*)	1.1	55	17.0%*	9.0%*	1.61*	5.49*
Mike Lincoln ('10)	1.9	54	14.1%	8.9%	1.32	5.33
Bob Priddy ('62-'71, -1 WAR*)	2.7	77	16.3%*	9.0%*	1.43*	4.80*
Mike Willis ('77-'81, 0 WAR*)	1.5	59	18.4%*	9.6%*	1.45*	4.77*