Max Scherzer

PosP

B/TR/R

Born1984-07-27

Age (2027)43

No MLB projection yet. Career stats below are historical.

Overview

MLBSP40-MAN

Pitching

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	40	MIX2 levels	13	13	58	3.86	3.77	27.7%	5.5%	1.1	K 26.2% · BB 5.4% · FIP 3.93
2025	41	MIX2 levels	19	19	94	4.90	4.67	24.0%	6.4%	0.8	K 22.9% · BB 6.4% · FIP 4.89
2026	42	MIX3 levels	23	23	103	5.49	4.62	21.0%	9.1%	0.9	K 20.3% · BB 8.9% · FIP 4.74
2027PROJ	43	MLBTOR	8	8	46	4.83	5.00	20.7%	8.3%	0.2
2028PROJ	44	MLBTOR	4	4	26	5.19	5.43	19.6%	9.0%	-0.0

Last 3 seasons WAR 2.9 · Next 2 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Hitting

Year	Age	Lvl / Team	PA	AVG/OBP/SLG	HR	SB	wRC+	WAR
2018	34	MLBWSH	78	.243/.274/.271	0	1	45	-0.3
2019	35	MLBWSH	61	.182/.182/.182	0	2	-13	-0.7
2021	37	MLBLAD	63	.000/.000/.000	0	0	-114	-1.5
2022	38	No MLB games played
2023	39	No MLB games played
2024	40	No MLB games played
2025	41	No MLB games played
2026	42	No MLB games played

Last 3 seasons WAR -2.5

Contract

No contract data on file.

Form3.89 ERA (proj 4.83) · K 23.0% (proj 20.7%) · BB 7.2% (proj 8.3%) ▲ last 60d · 35 IP through Oct 27

CompsFrancisco Campos (age 43) · Juan Antonio Pena (age 41)

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)
2008	24	MLB MLE	Arizona Diamondbacks	16	7	56	237	66	20	5	44%	3.5	27.8%	8.4%	19.4%	2.1%	3.05	2.98	+1.1
2008	24	MLB RAW	Arizona Diamondbacks	16	7	56	237	66	20	5	44%	3.5	27.8%	8.4%	19.4%	2.1%	3.05	2.98	+1.1
2009	25	MLB MLE	Arizona Diamondbacks	30	30	170	741	174	62	20	100%	5.7	23.5%	8.4%	15.1%	2.7%	4.12	3.66	+3.6
2009	25	MLB RAW	Arizona Diamondbacks	30	30	170	741	174	62	20	100%	5.7	23.5%	8.4%	15.1%	2.7%	4.12	3.68	+3.6
2010	26	MLB MLE	Detroit Tigers	31	31	196	800	184	69	20	100%	6.3	23.0%	8.6%	14.4%	2.6%	3.50	3.68	+4.1
2010	26	MLB RAW	Detroit Tigers	31	31	196	800	184	69	20	100%	6.3	23.0%	8.6%	14.4%	2.5%	3.50	3.61	+4.3
2011	27	MLB MLE	Detroit Tigers	33	33	195	833	174	55	29	100%	5.9	20.9%	6.6%	14.3%	3.6%	4.43	4.17	+2.8
2011	27	MLB RAW	Detroit Tigers	33	33	195	833	174	55	29	100%	5.9	20.9%	6.6%	14.3%	3.5%	4.43	4.09	+3.0
2012	28	MLB MLE	Detroit Tigers	32	32	188	787	231	58	23	100%	5.9	29.4%	7.4%	22.0%	3.1%	3.74	3.23	+5.1
2012	28	MLB RAW	Detroit Tigers	32	32	188	787	231	58	23	100%	5.9	29.4%	7.4%	22.0%	2.9%	3.74	3.16	+5.2
2013	29	MLB MLE	Detroit Tigers	32	32	214	836	240	56	18	100%	6.7	28.7%	6.7%	22.0%	2.2%	2.90	2.76	+7.3
2013	29	MLB RAW	Detroit Tigers	32	32	214	836	240	56	18	100%	6.7	28.7%	6.7%	22.0%	2.2%	2.90	2.74	+7.4
2014	30	MLB MLE	Detroit Tigers	33	33	220	904	252	62	18	100%	6.7	27.9%	6.9%	21.0%	2.1%	3.15	2.76	+7.5
2014	30	MLB RAW	Detroit Tigers	33	33	220	904	252	62	18	100%	6.7	27.9%	6.9%	21.0%	2.0%	3.15	2.72	+7.6
2015	31	MLB MLE	Washington Nationals	33	33	229	899	276	32	27	100%	6.9	30.7%	3.6%	27.1%	3.0%	2.79	2.61	+8.3
2015	31	MLB RAW	Washington Nationals	33	33	229	899	276	32	27	100%	6.9	30.7%	3.6%	27.1%	3.0%	2.79	2.64	+8.2
2016	32	MLB MLE	Washington Nationals	34	34	228	902	284	54	31	100%	6.7	31.5%	6.0%	25.5%	3.4%	2.96	3.09	+6.7
2016	32	MLB RAW	Washington Nationals	34	34	228	902	284	54	31	100%	6.7	31.5%	6.0%	25.5%	3.4%	2.96	3.09	+6.7
2017	33	MLB MLE	Washington Nationals	31	31	201	780	268	53	22	100%	6.5	34.4%	6.8%	27.6%	2.8%	2.51	2.61	+7.3
2017	33	MLB RAW	Washington Nationals	31	31	201	780	268	53	22	100%	6.5	34.4%	6.8%	27.6%	2.8%	2.51	2.65	+7.2
2018	34	MLB MLE	Washington Nationals	33	33	221	866	300	47	23	100%	6.7	34.6%	5.4%	29.2%	2.7%	2.53	2.32	+9.0
2018	34	MLB RAW	Washington Nationals	33	33	221	866	300	47	23	100%	6.7	34.6%	5.4%	29.2%	2.7%	2.53	2.37	+8.8
2019	35	MLB MLE	Washington Nationals	27	27	172	693	243	31	18	100%	6.4	35.1%	4.5%	30.6%	2.6%	2.92	2.13	+7.5
2019	35	MLB RAW	Washington Nationals	27	27	172	693	243	31	18	100%	6.4	35.1%	4.5%	30.6%	2.6%	2.92	2.18	+7.4
2020	36	MLB MLE	Washington Nationals	12	12	67	295	92	22	10	100%	5.6	31.2%	7.5%	23.7%	3.4%	3.74	3.27	+1.8
2020	36	MLB RAW	Washington Nationals	12	12	67	295	92	22	10	100%	5.6	31.2%	7.5%	23.7%	3.4%	3.74	3.28	+1.8
2021	37	MLB MLE	Los Angeles Dodgers	30	30	179	693	236	36	23	100%	6.0	34.1%	5.2%	28.9%	3.2%	2.46	2.63	+6.4
2021	37	MLB RAW	Los Angeles Dodgers	30	30	179	693	236	36	23	100%	6.0	34.1%	5.2%	28.9%	3.3%	2.46	2.74	+6.1
2022	38	MIX MLE	3 levels	26	26	157	614	194	27	15	100%	6.0	30.6%	4.2%	26.4%	2.3%	2.41	2.32	+6.3
2022	38	MIX RAW	3 levels	26	26	157	614	194	27	15	100%	6.0	31.6%	4.4%	27.2%	2.4%	2.41	2.39	+6.2
2023	39	MLB MLE	Texas Rangers	27	27	153	621	174	45	28	100%	5.7	28.0%	7.2%	20.8%	4.2%	3.77	3.95	+2.6
2023	39	MLB RAW	Texas Rangers	27	27	153	621	174	45	28	100%	5.7	28.0%	7.2%	20.8%	4.5%	3.77	4.09	+2.4
2024	40	MIX MLE	2 levels	13	13	58	235	65	13	10	100%	4.5	26.2%	5.4%	20.8%	4.3%	3.86	3.93	+1.0
2024	40	MIX MLE	2 levels	13	13	58	235	65	13	10	100%	4.5	26.2%	5.4%	20.8%	4.3%	3.86	3.93	+1.0
2024	40	MIX RAW	2 levels	13	13	58	235	65	13	10	100%	4.5	27.7%	5.5%	22.1%	4.3%	3.86	3.77	+1.1
2025	41	MIX MLE	2 levels	19	19	94	392	94	25	20	100%	4.9	22.9%	6.4%	16.5%	5.3%	4.90	4.89	+0.5
2025	41	MIX MLE	2 levels	19	19	94	392	94	25	20	100%	4.9	22.9%	6.4%	16.5%	5.3%	4.90	4.89	+0.5
2025	41	MIX RAW	2 levels	19	19	94	392	94	25	20	100%	4.9	24.0%	6.4%	17.6%	5.1%	4.90	4.67	+0.8
2026	42	MIX MLE	3 levels	23	23	103	438	92	40	17	100%	4.5	20.3%	8.9%	11.4%	4.1%	5.49	4.74	+0.8
2026	42	MIX MLE	3 levels	23	23	103	438	92	40	17	100%	4.5	20.3%	8.9%	11.4%	4.1%	5.49	4.74	+0.8
2026	42	MIX RAW	3 levels	23	23	103	438	92	40	17	100%	4.5	21.0%	9.1%	11.9%	3.9%	5.49	4.62	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			501	492	3048	12351	3557	794	369	98%	6.1	28.8%	6.4%	22.4%	3.0%	3.29	3.12	+87.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	43	MLB	TOR	8	8	46	194	40	16	8	100%	5.8	20.7%	8.3%	12.4%	4.0%	4.83	5.00	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	44	MLB MLE	TOR	4	4	26	112	22	10	5	100%	6.6	19.6%	9.0%	10.6%	4.5%	5.19	5.43	-0.0
2028	44	MLB CTX	TOR	4	4	26	110	21	10	5	100%	6.5	19.6%	9.0%	10.6%	4.5%	5.19	5.43	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		505	496	3074	12463	3579	804	374	98%	6.1	28.7%	6.5%	22.3%	3.0%	3.30	3.14	+86.9
/ 200 IP	—	RAW		33	32	200	811	233	52	24	98%	6.1	28.7%	6.5%	22.3%	3.0%	3.30	3.14	+5.7
Career	—	MLE		515	506	3102	12566	3622	805	380	98%	6.0	28.8%	6.4%	22.4%	3.0%	3.29	3.14	+86.8
/ 200 IP	—	MLE		33	33	200	810	234	52	24	98%	6.0	28.8%	6.4%	22.4%	3.0%	3.29	3.14	+5.6

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 AAABuffalo Bisons · 16 IPFIP 2.61 → 3.14 (+0.53)K% 35.0% → 30.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.00%	—	×0.860	30.10%
BB% (unintentional) /BF	5.00%	—	×0.900	4.50%
HR / BF /BF	3.33%	÷1.000	×1.100	3.67%

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 2.61 → 3.14, 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 AAABuffalo Bisons · 9 IPFIP 2.48 → 3.30 (+0.83)K% 35.3% → 30.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.29%	—	×0.860	30.35%
BB% (unintentional) /BF	5.88%	—	×0.900	5.29%
HR / BF /BF	2.94%	÷0.847	×1.100	3.82%

Result: FIP 2.48 → 3.30, 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 AAARound Rock Express · 15 IPFIP 2.95 → 3.93 (+0.97)K% 43.1% → 37.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.10%	—	×0.860	37.07%
BB% (unintentional) /BF	5.17%	—	×0.900	4.66%
HR / BF /BF	5.17%	÷0.928	×1.100	6.13%

Result: FIP 2.95 → 3.93, 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 AABinghamton Rumble Ponies · 8 IPFIP 1.98 → 3.27 (+1.29)K% 41.2% → 33.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.18%	—	×0.810	33.35%
BB% (unintentional) /BF	5.88%	—	×1.100	6.47%
HR / BF /BF	2.94%	÷0.895	×1.200	3.95%

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 79).

Result: FIP 1.98 → 3.27, 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).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	15.6	149	28.6%	6.6%	1.17	3.33
Curt Schilling ('07)	16.2	180	23.6%	5.3%	0.95	3.42
Yu Darvish ('25)	8.9	137	28.4%	7.7%	1.17	3.65
Johan Santana ('12)	10.1	169	24.1%	6.9%	0.98	3.20
Luis Tiant ('64-'82, 62 WAR*)	17.4	183	23.8%*	7.6%*	1.31*	3.72*
Jose Rijo ('84-'02, 33 WAR*)	9.4	145	25.9%*	8.4%*	0.93*	3.56*
David Cone ('86-'03, 56 WAR*)	14.5	181	27.6%*	8.9%*	0.97*	3.54*

Max Scherzer

Career Stats + Projections

How the minor-league lines were translated

Career Path Comps

Career Comps

			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 Scherzer (OGILVIE)	—	—	—	—	—	4.0%	—	5.43	19.6%	10.6%	26	+0.43	—	—	—
Francisco Campos R 2016 · 4.10 FIP	43	SP	4.10	12.4%	4.8%	2.6%	.272	4.74	11.2%	4.3%	115	+0.64	4.06	332	57
Juan Antonio Pena L 2019 · 4.56 FIP	41	SW	4.56	13.7%	14.1%	1.5%	.313	—	—	—	—	—	4.20	149	0