Max Lazar

P Lehigh Valley IronPigs

Age 28 RHP 6'1" / 200 lbs AAA

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX3 levels	48	0	57	2.53	2.14	29.3%	5.4%	1.7	K 22.2% · BB 5.9% · FIP 2.84
2025	26	MIX2 levels	54	0	63	4.31	4.47	19.1%	7.0%	0.1	K 17.8% · BB 6.8% · FIP 4.59
2026	27	MIX4 levels	43	1	52	4.50	4.23	23.5%	9.1%	0.2	K 21.8% · BB 9.2% · FIP 4.25
2027PROJ	28	MLBPHI	48	0	50	4.75	4.75	18.6%	8.3%	-0.1
2028PROJ85% MLB	29	MLBPHI	30	0	31	4.80	4.86	18.5%	8.6%	-0.1
2029PROJ88% MLB	30	MLBPHI	19	0	20	4.92	5.03	18.2%	8.9%	-0.1

Last 3 seasons WAR 1.9 · Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control60Command40FB velo50

CompsCarlos Fisher (age 28) · Neil Wagner (age 29) · Chris Hatcher (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.75

FIP4.75

K%18.6%

BB%8.3%

K-BB%10.4%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL6060

CMD4040

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)
2017	18	ROK MLE	AZL Brewers	7	1	14	56	14	1	2	14%	2.0	17.0%	2.2%	14.8%	5.0%	5.93	4.69	—
2017	18	ROK RAW	AZL Brewers	7	1	14	56	14	1	2	14%	2.0	25.0%	1.8%	23.2%	3.6%	5.93	3.17	—
2018	19	ROK MLE	Helena Brewers	14	14	68	295	55	15	7	100%	4.9	12.7%	6.4%	6.3%	3.3%	4.37	4.66	—
2018	19	ROK RAW	Helena Brewers	14	14	68	295	55	15	7	100%	4.9	18.6%	5.1%	13.6%	2.4%	4.37	3.48	—
2019	20	MIX MLE	2 levels	22	13	85	338	119	15	5	59%	3.9	25.4%	5.6%	19.9%	2.0%	2.33	2.76	—
2019	20	MIX RAW	2 levels	22	13	85	338	119	15	5	59%	3.9	35.2%	4.4%	30.8%	1.5%	2.33	1.59	—
2022	23	MIX MLE	3 levels	15	9	40	170	26	12	6	60%	2.7	10.5%	9.1%	1.4%	5.1%	3.83	6.15	—
2022	23	MIX RAW	3 levels	15	9	40	170	26	12	6	60%	2.7	15.3%	7.1%	8.2%	3.5%	3.83	4.65	—
2023	24	MIX MLE	2 levels	33	1	69	288	73	19	5	3%	2.1	19.9%	7.4%	12.5%	2.0%	3.26	3.47	—
2023	24	MIX RAW	2 levels	33	1	69	288	73	19	5	3%	2.1	25.3%	6.6%	18.8%	1.7%	3.26	2.75	—
2024	25	MIX MLE	3 levels	48	0	57	222	65	12	3	0%	1.2	22.2%	5.9%	16.3%	1.6%	2.53	2.84	+1.2
2024	25	MIX MLE	3 levels	48	0	57	222	65	12	3	0%	1.2	22.2%	5.9%	16.3%	1.6%	2.53	2.84	+1.2
2024	25	MIX RAW	3 levels	48	0	57	222	65	12	3	0%	1.2	29.3%	5.4%	23.9%	1.4%	2.53	2.14	+1.7
2025	26	MIX MLE	2 levels	54	0	63	257	49	18	10	0%	1.2	17.8%	6.8%	11.0%	3.9%	4.31	4.59	-0.0
2025	26	MIX MLE	2 levels	54	0	63	257	49	18	10	0%	1.2	17.8%	6.8%	11.0%	3.9%	4.31	4.59	-0.0
2025	26	MIX RAW	2 levels	54	0	63	257	49	18	10	0%	1.2	19.1%	7.0%	12.1%	3.9%	4.31	4.47	+0.1
2026	27	MIX MLE	4 levels	43	1	52	230	54	21	8	2%	1.2	21.8%	9.2%	12.5%	3.3%	4.50	4.25	+0.2
2026	27	MIX MLE	4 levels	43	1	52	230	54	21	8	2%	1.2	21.8%	9.2%	12.5%	3.3%	4.50	4.25	+0.2
2026	27	MIX RAW	4 levels	43	1	52	230	54	21	8	2%	1.2	23.5%	9.1%	14.3%	3.5%	4.50	4.23	+0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			55	0	65	269	43	17	12	0%	1.2	16.0%	6.3%	9.7%	4.5%	4.98	4.96	-0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	PHI	48	0	50	211	39	17	7	0%	1.0	18.6%	8.3%	10.4%	3.3%	4.75	4.75	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	PHI	34	0	36	151	28	13	5	0%	1.1	18.5%	8.6%	9.9%	3.4%	4.80	4.86	-0.1
2029	30	MLB MLE	PHI	22	0	23	98	18	9	3	0%	1.1	18.2%	8.9%	9.2%	3.6%	4.92	5.03	-0.1
2028	29	MLB CTX	PHI	30	0	31	131	24	11	4	0%	1.0	18.5%	8.6%	9.9%	3.4%	4.80	4.86	-0.1
2029	30	MLB CTX	PHI	19	0	20	84	15	8	3	0%	1.1	18.2%	8.9%	9.2%	3.6%	4.92	5.03	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		103	0	116	484	83	36	19	0%	1.1	17.0%	7.4%	9.7%	4.0%	4.92	4.80	-0.3
/ 200 IP	—	RAW		179	0	200	835	143	62	33	0%	1.1	17.0%	7.4%	9.7%	4.0%	4.92	4.80	-0.6
Career	—	MLE		236	39	447	1856	353	127	55	17%	1.9	19.0%	6.9%	12.2%	3.0%	3.58	3.99	-0.6
/ 200 IP	—	MLE		106	17	200	830	158	57	25	17%	1.9	19.0%	6.9%	12.2%	3.0%	3.58	3.99	-0.9

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 AAALehigh Valley IronPigs · 38 IPFIP 3.91 → 4.25 (+0.33)K% 25.3% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.30%	—	×0.860	21.76%
BB% (unintentional) /BF	10.24%	—	×0.900	9.22%
HR / BF /BF	3.01%	÷1.000	×1.100	3.31%

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 3.91 → 4.25, 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 AAALehigh Valley IronPigs · 21 IPFIP 3.63 → 4.16 (+0.53)K% 26.4% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.44%	—	×0.860	22.74%
BB% (unintentional) /BF	6.90%	—	×0.900	6.21%
HR / BF /BF	3.45%	÷0.947	×1.100	4.00%

Result: FIP 3.63 → 4.16, 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 AAALehigh Valley IronPigs · 33 IPFIP 2.06 → 2.35 (+0.29)K% 28.4% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.36%	—	×0.860	24.39%
BB% (unintentional) /BF	7.46%	—	×0.900	6.72%
HR / BF /BF	0.75%	÷0.989	×1.100	0.83%

Result: FIP 2.06 → 2.35, 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 AAReading Fightin Phils · 10 IPFIP -1.37 → -0.52 (+0.85)K% 52.9% → 42.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	52.94%	—	×0.810	42.88%
BB% (unintentional) /BF	0.00%	—	×1.100	0.00%
HR / BF /BF	0.00%	÷1.137	×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 127).

Result: FIP -1.37 → -0.52, 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+Wisconsin Timber Rattlers · 43 IPFIP 2.31 → 3.01 (+0.70)K% 24.3% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.29%	—	×0.770	18.71%
BB% (unintentional) /BF	5.08%	—	×1.150	5.85%
HR / BF /BF	1.13%	÷1.033	×1.250	1.37%

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 107).

Result: FIP 2.31 → 3.01, 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).

2023 AABiloxi Shuckers · 26 IPFIP 3.44 → 4.19 (+0.75)K% 27.0% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.03%	—	×0.810	21.89%
BB% (unintentional) /BF	9.01%	—	×1.100	9.91%
HR / BF /BF	2.70%	÷1.055	×1.200	3.07%

Result: FIP 3.44 → 4.19, 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+Wisconsin Timber Rattlers · 32 IPFIP 4.92 → 6.15 (+1.23)K% 13.7% → 10.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.67%	—	×0.770	10.53%
BB% (unintentional) /BF	7.91%	—	×1.150	9.10%
HR / BF /BF	3.60%	÷0.885	×1.250	5.08%

Result: FIP 4.92 → 6.15, 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 ACarolina Mudcats · 7 IPFIP 3.73 → 4.59 (+0.87)K% 22.2% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.740	16.44%
BB% (unintentional) /BF	3.70%	—	×1.180	4.37%
HR / BF /BF	3.70%	÷1.136	×1.300	4.24%

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 127).

Result: FIP 3.73 → 4.59, 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
Max Lazar (OGILVIE)	—	—	4.75	18.6%	8.3%	3.3%	—	4.93	18.4%	9.7%	59	+0.18	—	—	—
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	79
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	78
Chris Hatcher R 2012 · 5.60 FIP	27	SU	5.60	15.2%	9.1%	4.8%	.298	2.68	26.4%	20.9%	95	-2.92	2.51	246	76
Evan Scribner R 2013 · 4.06 FIP	28	SU	4.06	16.7%	6.1%	2.9%	.271	4.59	26.9%	25.2%	60	+0.53	3.23	136	76
Rob Scahill R 2015 · 3.91 FIP	28	SU	3.91	16.9%	7.7%	2.3%	.288	3.34	17.9%	10.1%	171	-0.57	3.06	250	76
Santiago Casilla R 2008 · 3.71 FIP	28	SU	3.71	18.8%	7.9%	2.2%	.337	3.37	20.6%	10.4%	155	-0.34	2.76	647	76
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	75
Francisco Del Rosario R 2007 · 3.93 FIP	26	SU	3.93	19.7%	9.4%	2.4%	.356	—	—	—	—	—	3.93	194	75
Tyler Walker R 2004 · 4.28 FIP	28	SU	4.28	17.5%	8.4%	2.9%	.311	3.77	18.5%	10.4%	101	-0.51	2.38	289	75
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	75
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	75
Jhan Mariñez R 2017 · 3.97 FIP	28	SU	3.97	17.2%	8.8%	2.2%	.309	4.09	21.2%	13.3%	48	+0.12	3.16	253	75
Jeff Fulchino R 2008 · 4.62 FIP	28	SU	4.62	16.7%	11.1%	2.8%	.380	3.86	21.0%	12.4%	164	-0.76	3.36	178	75
J.J. Putz R 2005 · 4.36 FIP	28	SU	4.36	17.4%	8.1%	3.1%	.270	2.24	31.4%	25.1%	196	-2.12	1.43	563	75
Brandon Cunniff R 2017 · 4.79 FIP	28	SU	4.79	20.1%	11.6%	3.5%	.275	6.80	13.9%	-1.9%	30	+2.01	3.89	180	74
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	74
Chad Paronto R 2002 · 3.73 FIP	27	SU	3.73	14.9%	6.5%	1.9%	.263	—	—	—	—	—	3.65	160	74
Theo Denlinger R 2024 · 4.23 FIP	28	SU	4.23	15.3%	5.4%	3.2%	.324	—	—	—	—	—	2.92	140	74
Gus Schlosser R 2016 · 3.92 FIP	27	SU	3.92	18.7%	5.6%	3.1%	.364	—	—	—	—	—	3.92	107	74
Ryan Doolittle R 2016 · 4.38 FIP	28	SU	4.38	13.9%	7.1%	2.8%	.269	—	—	—	—	—	4.03	101	74

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	0.9	46	17.6%	7.8%	1.45	4.86
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*