Everhett Hazelwood

P Winston-Salem Dash

Age 28 RHP 6'2" / 210 lbs A+

Overview

A+PROSPECT

MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	23	MIX2 levels	34	0	53	5.91	4.34	18.2%	10.5%	—	K 13.8% · BB 12.2% · FIP 5.23
2023	24	A+CWS	33	0	49	7.66	4.76	24.7%	13.4%	—	K 19.0% · BB 15.4% · FIP 5.70
2024	25	MIX2 levels	10	0	16	10.12	7.85	22.6%	14.3%	—	K 17.5% · BB 16.9% · FIP 9.36
2025	26	No MLB games played
2026	27	No MLB games played
2027PROJ	28	MLBCWS	—	—	0	4.63	4.63	22.6%	10.8%	—
2028PROJ30% MLB	29	MLBCWS	5	0	5	4.67	4.73	22.5%	10.9%	-0.0

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

Contract

No contract data on file.

CompsJosh Lueke (age 28) · Jason Bulger (age 29) · Matt Ramsey (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 105

ERA4.63

FIP4.63

K%22.6%

BB%10.8%

K-BB%11.8%

Proj IP8

Value2027 · WAR

Runs saved vs league avg · 8 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 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)
2021	22	MIX MLE	2 levels	10	0	14	55	13	3	1	0%	1.4	23.6%	5.5%	18.2%	1.8%	2.63	2.79	—
2021	22	MIX RAW	2 levels	10	0	14	55	13	3	1	0%	1.4	23.6%	5.5%	18.2%	1.8%	2.63	2.81	—
2022	23	MIX MLE	2 levels	34	0	53	247	45	26	6	0%	1.6	13.8%	12.2%	1.5%	3.2%	5.91	5.23	—
2022	23	MIX RAW	2 levels	34	0	53	247	45	26	6	0%	1.6	18.2%	10.5%	7.7%	2.4%	5.91	4.34	—
2023	24	A+ MLE	Winston-Salem Dash	33	0	49	239	59	32	8	0%	1.5	19.0%	15.4%	3.6%	4.1%	7.66	5.70	—
2023	24	A+ RAW	Winston-Salem Dash	33	0	49	239	59	32	8	0%	1.5	24.7%	13.4%	11.3%	3.3%	7.66	4.76	—
2024	25	MIX MLE	2 levels	10	0	16	84	19	12	6	0%	1.6	17.5%	16.9%	0.6%	10.2%	10.12	9.36	—
2024	25	MIX MLE	2 levels	10	0	16	84	19	12	6	0%	1.6	17.5%	16.9%	0.6%	10.2%	10.12	9.36	—
2024	25	MIX RAW	2 levels	10	0	16	84	19	12	6	0%	1.6	22.6%	14.3%	8.3%	7.1%	10.12	7.85	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CWS	—	—	0	—	—	—	—	—	—	22.6%	10.8%	11.8%	3.1%	4.63	4.63	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CWS	17	0	18	74	17	8	2	0%	1.0	22.5%	10.9%	11.6%	3.2%	4.67	4.73	-0.0
2028	29	MLB CTX	CWS	5	0	5	21	5	2	1	0%	1.0	22.5%	10.9%	11.6%	3.2%	4.67	4.73	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	0	5	22	5	2	1	0%	1.1	22.5%	10.9%	11.6%	3.2%	4.67	4.35	+0.0
/ 200 IP	—	RAW		190	0	200	844	188	75	38	0%	1.1	22.5%	10.9%	11.6%	3.2%	4.67	4.35	+0.5
Career	—	MLE		87	0	132	625	107	84	27	0%	1.5	17.1%	13.5%	3.7%	4.4%	6.73	5.75	-0.0
/ 200 IP	—	MLE		131	0	200	945	162	127	41	0%	1.5	17.1%	13.5%	3.7%	4.4%	6.73	5.75	-0.4

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 A+Winston-Salem Dash · 14 IPFIP 6.70 → 9.36 (+2.66)K% 22.7% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.67%	—	×0.770	17.45%
BB% (unintentional) /BF	14.67%	—	×1.150	16.87%
HR / BF /BF	6.67%	÷0.817	×1.250	10.20%

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 63).

Result: FIP 6.70 → 9.36, 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+Winston-Salem Dash · 49 IPFIP 4.55 → 5.70 (+1.15)K% 24.7% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.69%	—	×0.770	19.01%
BB% (unintentional) /BF	13.39%	—	×1.150	15.40%
HR / BF /BF	3.35%	÷1.017	×1.250	4.11%

Result: FIP 4.55 → 5.70, 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+Winston-Salem Dash · 33 IPFIP 5.01 → 6.12 (+1.11)K% 15.5% → 12.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.53%	—	×0.770	11.96%
BB% (unintentional) /BF	9.32%	—	×1.150	10.71%
HR / BF /BF	3.73%	÷0.955	×1.250	4.88%

Result: FIP 5.01 → 6.12, 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 AKannapolis Cannon Ballers · 20 IPFIP 2.76 → 3.56 (+0.80)K% 23.3% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.26%	—	×0.740	17.21%
BB% (unintentional) /BF	12.79%	—	×1.180	15.09%
HR / BF /BF	0.00%	÷1.172	×1.300	0.00%

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 134).

Result: FIP 2.76 → 3.56, 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).

2021 ROKACL White Sox · 9 IPFIP 3.53 → 4.91 (+1.38)K% 23.1% → 15.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.08%	—	×0.680	15.69%
BB% (unintentional) /BF	7.69%	—	×1.250	9.62%
HR / BF /BF	2.56%	÷1.027	×1.400	3.50%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 105).

Result: FIP 3.53 → 4.91, 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).

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
Everhett Hazelwood (OGILVIE)	—	—	4.63	22.6%	10.8%	3.1%	—	4.73	22.5%	11.6%	18	+0.10	—	—	—
Josh Lueke R 2013 · 4.09 FIP	28	SU	4.09	25.3%	11.1%	3.1%	.333	3.28	24.6%	20.9%	90	-0.81	2.29	191	83
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	83
Matt Ramsey R 2018 · 3.78 FIP	28	SU	3.78	24.9%	8.8%	3.0%	.276	2.42	21.7%	12.6%	34	-1.36	2.42	125	82
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	82
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	82
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	82
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	81
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	81
Spencer Bivens R 2022 · 4.86 FIP	28	SU	4.86	19.8%	13.5%	3.1%	.265	3.85	18.1%	10.3%	272	-1.01	3.52	391	81
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	80
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	80
Francisco Del Rosario R 2007 · 3.93 FIP	26	SU	3.93	19.7%	9.4%	2.4%	.356	—	—	—	—	—	3.93	194	80
Tyler Yates R 2006 · 4.17 FIP	28	SU	4.17	21.2%	10.6%	2.8%	.254	3.70	20.7%	11.1%	151	-0.47	3.23	248	79
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	79
Cole McDonald R 2024 · 5.01 FIP	27	SU	5.01	20.9%	12.7%	3.8%	.281	—	—	—	—	—	2.81	153	79
Jason Boyd R 2000 · 3.68 FIP	27	SU	3.68	19.9%	12.4%	1.2%	.346	4.86	13.9%	2.8%	81	+1.18	3.68	128	78
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	78
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	78
Ronald Peña R 2019 · 4.55 FIP	27	SU	4.55	20.5%	12.6%	2.9%	.355	4.49	16.5%	6.1%	39	-0.06	3.72	187	77
Greg Aquino R 2006 · 4.41 FIP	28	SU	4.41	23.2%	10.0%	3.6%	.331	4.39	17.4%	5.6%	30	-0.02	4.10	154	77