Mike Mayers

P Buffalo Bisons

Age 35 RHP 6'2" / 220 lbs AAA peak 0.1 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	30	MIX2 levels	32	11	84	5.92	5.88	21.3%	9.4%	-1.3	K 20.2% · BB 9.7% · FIP 5.96
2023	31	MIX2 levels	34	15	101	6.13	5.02	17.1%	9.5%	-0.6	K 15.2% · BB 8.8% · FIP 4.92
2024	32	AAATOR	31	3	41	6.10	3.66	23.7%	10.8%	—	K 20.4% · BB 9.7% · FIP 3.87
2025	33	No MLB games played
2026	34	No MLB games played
2027PROJ	35	MLBTOR	22	0	23	4.35	4.37	23.3%	9.4%	0.0
2028PROJ5% MLB	36	MLBTOR	6	0	6	4.58	4.73	22.3%	10.0%	-0.0
2029PROJMLE	37	MLBTOR	—	—	0	4.91	5.14	21.2%	10.6%	—

Last 3 seasons WAR -1.8 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2023

FB Velo27

xwOBA vs27

K%10

CompsJean Machi (age 35) · Tiago Da Silva (age 34) · Keiichi Yabu (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 116108vR 100

ERA4.35

FIP4.37

K%23.3%

BB%9.4%

K-BB%14.0%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2792.9

Whiff%

p1019.5%

p1014.3%

xwOBA vs

p270.339

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)
2015	23	MIX MLE	2 levels	12	12	54	236	43	21	8	100%	4.5	13.8%	10.9%	2.9%	4.0%	5.87	5.51	—
2015	23	MIX RAW	2 levels	12	12	54	236	43	21	8	100%	4.5	18.2%	8.9%	9.3%	3.4%	5.87	4.61	—
2016	24	MIX MLE	3 levels	29	26	149	638	129	49	15	90%	5.1	18.0%	8.2%	9.9%	2.3%	4.04	3.85	+2.8
2016	24	MIX RAW	3 levels	29	26	149	638	129	49	15	90%	5.1	20.2%	7.7%	12.5%	2.4%	4.04	3.66	+3.1
2017	25	MIX MLE	2 levels	34	15	114	502	100	34	14	44%	3.4	17.9%	6.8%	11.1%	2.8%	3.62	4.00	+0.7
2017	25	MIX RAW	2 levels	34	15	114	502	100	34	14	44%	3.4	19.9%	6.8%	13.1%	2.8%	3.62	3.83	+1.0
2018	26	MIX MLE	2 levels	55	0	59	259	57	18	7	0%	1.1	21.7%	6.2%	15.5%	3.3%	4.10	3.88	+0.5
2018	26	MIX RAW	2 levels	55	0	59	259	57	18	7	0%	1.1	22.0%	6.9%	15.1%	2.7%	4.10	3.62	+0.7
2019	27	MIX MLE	2 levels	36	1	39	174	40	16	7	3%	1.1	21.3%	9.4%	11.9%	4.4%	4.85	4.92	-0.2
2019	27	MIX RAW	2 levels	36	1	39	174	40	16	7	3%	1.1	23.0%	9.2%	13.8%	4.0%	4.85	4.61	-0.0
2020	28	MLB MLE	Los Angeles Angels	29	0	30	121	43	9	2	0%	1.0	35.5%	7.4%	28.1%	1.6%	2.10	1.93	+0.9
2020	28	MLB RAW	Los Angeles Angels	29	0	30	121	43	9	2	0%	1.0	35.5%	7.4%	28.1%	1.7%	2.10	2.00	+0.9
2021	29	MLB MLE	Los Angeles Angels	72	2	75	315	90	26	11	3%	1.0	28.6%	8.3%	20.3%	3.4%	3.84	3.61	+0.8
2021	29	MLB RAW	Los Angeles Angels	72	2	75	315	90	26	11	3%	1.0	28.6%	8.3%	20.3%	3.5%	3.84	3.65	+0.8
2022	30	MIX MLE	2 levels	32	11	84	371	79	35	22	34%	2.6	20.2%	9.7%	10.5%	6.1%	5.92	5.96	-1.3
2022	30	MIX RAW	2 levels	32	11	84	371	79	35	22	34%	2.6	21.3%	9.4%	11.9%	5.9%	5.92	5.88	-1.3
2023	31	MIX MLE	2 levels	34	15	101	462	79	44	17	44%	3.0	15.2%	8.8%	6.4%	3.6%	6.13	4.92	-0.4
2023	31	MIX RAW	2 levels	34	15	101	462	79	44	17	44%	3.0	17.1%	9.5%	7.6%	3.7%	6.13	5.02	-0.6
2024	32	AAA MLE	Buffalo Bisons	31	3	41	194	46	21	4	10%	1.3	20.4%	9.7%	10.6%	2.3%	6.10	3.87	—
2024	32	AAA MLE	Buffalo Bisons	31	3	41	194	46	21	4	10%	1.3	20.4%	9.7%	10.6%	2.3%	6.10	3.87	—
2024	32	AAA RAW	Buffalo Bisons	31	3	41	194	46	21	4	10%	1.3	23.7%	10.8%	12.9%	2.1%	6.10	3.66	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			204	8	263	1152	265	92	47	4%	1.3	23.0%	8.0%	15.0%	4.1%	5.21	4.46	+0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	TOR	22	0	23	97	23	9	3	0%	1.0	23.3%	9.4%	14.0%	3.0%	4.35	4.37	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	TOR	111	0	116	492	110	49	17	0%	1.0	22.3%	10.0%	12.3%	3.4%	4.58	4.73	-0.2
2029	37	MLB MLE	TOR	82	0	86	362	77	38	14	0%	1.0	21.2%	10.6%	10.6%	3.8%	4.91	5.14	-0.6
2028	36	MLB CTX	TOR	6	0	6	25	6	3	1	0%	1.0	22.3%	10.0%	12.3%	3.4%	4.58	4.73	-0.0
2029	37	MLB CTX	TOR	—	—	0	—	—	—	—	—	—	21.2%	10.6%	10.6%	3.8%	4.91	5.14	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		210	8	268	1177	270	94	48	4%	1.3	23.0%	8.0%	15.0%	4.1%	5.19	4.41	+0.5
/ 200 IP	—	RAW		156	6	200	876	201	70	36	4%	1.3	23.0%	8.0%	15.0%	4.1%	5.19	4.41	+0.3
Career	—	MLE		364	85	747	3272	649	275	111	23%	2.1	19.8%	8.4%	11.4%	3.4%	4.66	4.35	-0.6
/ 200 IP	—	MLE		97	23	200	876	174	74	30	23%	2.1	19.8%	8.4%	11.4%	3.4%	4.66	4.35	-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.

2024 AAABuffalo Bisons · 41 IPFIP 3.60 → 3.87 (+0.27)K% 23.7% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.71%	—	×0.860	20.39%
BB% (unintentional) /BF	10.82%	—	×0.900	9.74%
HR / BF /BF	2.06%	÷0.990	×1.100	2.29%

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 98).

Result: FIP 3.60 → 3.87, 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 AAACharlotte Knights · 75 IPFIP 4.91 → 4.90 (−0.01)K% 18.1% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.08%	—	×0.860	15.55%
BB% (unintentional) /BF	9.91%	—	×0.900	8.92%
HR / BF /BF	3.79%	÷1.152	×1.100	3.62%

Result: FIP 4.91 → 4.90, 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 AAASalt Lake Bees · 33 IPFIP 5.21 → 5.84 (+0.63)K% 23.0% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.97%	—	×0.880	20.22%
BB% (unintentional) /BF	11.49%	—	×1.050	12.06%
HR / BF /BF	4.73%	÷0.978	×1.100	5.32%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 96).

Result: FIP 5.21 → 5.84, 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).

2019 AAAMemphis Redbirds · 20 IPFIP 4.33 → 4.97 (+0.64)K% 27.9% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.91%	—	×0.880	24.56%
BB% (unintentional) /BF	8.14%	—	×1.050	8.55%
HR / BF /BF	4.65%	÷0.982	×1.100	5.21%

Result: FIP 4.33 → 4.97, 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).

2018 AAAMemphis Redbirds · 8 IPFIP 2.59 → 2.91 (+0.32)K% 24.2% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.880	21.33%
BB% (unintentional) /BF	12.12%	—	×1.050	12.73%
HR / BF /BF	0.00%	÷0.909	×1.100	0.00%

Result: FIP 2.59 → 2.91, 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).

2017 AAAMemphis Redbirds · 110 IPFIP 3.59 → 4.00 (+0.42)K% 20.3% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.34%	—	×0.880	17.90%
BB% (unintentional) /BF	6.50%	—	×1.050	6.82%
HR / BF /BF	2.52%	÷0.980	×1.100	2.82%

Result: FIP 3.59 → 4.00, 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).

2016 AAAMemphis Redbirds · 89 IPFIP 3.36 → 3.84 (+0.48)K% 22.2% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.16%	—	×0.880	19.50%
BB% (unintentional) /BF	7.65%	—	×1.050	8.03%
HR / BF /BF	2.11%	÷0.931	×1.100	2.49%

Result: FIP 3.36 → 3.84, 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).

2016 AASpringfield Cardinals · 55 IPFIP 3.42 → 3.86 (+0.44)K% 19.2% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.20%	—	×0.810	15.55%
BB% (unintentional) /BF	7.59%	—	×1.100	8.35%
HR / BF /BF	1.79%	÷1.155	×1.200	1.86%

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 131).

Result: FIP 3.42 → 3.86, 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).

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
Mike Mayers (OGILVIE)	—	—	—	—	—	3.0%	—	4.90	21.8%	11.6%	202	+0.53	—	—	—
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	55
Tiago Da Silva R 2019 · 3.95 FIP	34	SW	3.95	15.0%	7.2%	2.2%	.365	—	—	—	—	—	2.21	287	54
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	50
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	50
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	49
Spencer Patton R 2023 · 4.33 FIP	35	SU	4.33	18.9%	9.7%	2.9%	.295	—	—	—	—	—	2.79	239	48
Juan Sandoval R 2016 · 3.24 FIP	35	SU	3.24	18.2%	10.2%	0.7%	.288	4.40	16.3%	9.1%	116	+1.16	3.24	225	46
Brian Schlitter R 2021 · 4.70 FIP	35	SU	4.70	14.9%	9.1%	3.1%	.318	—	—	—	—	—	3.27	300	45
Francisco Del Rosario R 2017 · 4.15 FIP	36	SU	4.15	16.4%	10.0%	2.1%	.267	6.35	11.9%	-0.6%	77	+2.20	3.93	194	44
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	44
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	44
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	42
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	41
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	40
Fernando Rodriguez Jr. R 2019 · 5.11 FIP	35	SW	5.11	25.0%	11.2%	4.9%	.312	—	—	—	—	—	3.34	335	40
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	40
Jay Jackson R 2023 · 4.61 FIP	35	SU	4.61	26.5%	5.1%	5.6%	.247	5.31	25.4%	17.5%	26	+0.70	2.36	261	39
Seunghwan Oh R 2017 · 3.90 FIP	35	SU	3.90	20.5%	2.3%	4.1%	.299	3.45	26.6%	20.5%	87	-0.45	1.87	226	39
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	39
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	38

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	3.1	79	22.7%	9.2%	1.41	4.83
John Boozer ('62-'69, -2 WAR*)	2.0	66	21.1%*	9.0%*	1.46*	5.15*
Brad Havens ('81-'89, 2 WAR*)	3.0	84	21.0%*	9.5%*	1.43*	4.96*
Daniel Norris ('23)	2.9	73	21.5%	8.9%	1.39	4.73
Vicente Palacios ('87-'00, 1 WAR*)	1.9	62	21.0%*	10.0%*	1.41*	4.86*
Brian Matusz ('16)	2.6	76	19.8%	8.7%	1.34	4.92
Jorge López ('25)	2.8	70	19.8%	8.8%	1.36	5.31