Doug Nikhazy

P Iowa Cubs

Age 27 LHP 6'0" / 210 lbs AAA peak 0.1 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX2 levels	25	24	124	2.98	3.64	25.4%	10.8%	—	K 21.3% · BB 10.5% · FIP 4.12
2025	25	MIX2 levels	23	20	90	5.40	4.86	22.4%	12.0%	0.6	K 19.3% · BB 10.0% · FIP 4.88
2026	26	MIX2 levels	19	9	51	9.77	6.08	21.7%	15.5%	-0.9	K 19.0% · BB 13.7% · FIP 5.90
2027PROJ	27	MLBCWS	16	16	97	5.38	5.38	20.1%	12.8%	0.0
2028PROJ75% MLB	28	MLBCWS	14	14	86	5.32	5.35	20.2%	12.4%	0.0
2029PROJ79% MLB	29	MLBCWS	13	13	78	5.33	5.40	20.1%	12.3%	0.0

Last 3 seasons WAR -0.3 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.3 / P90 0.1, comp-based) · star 0% · didn't stick 99%

CompsBrad Mills (age 26) · Matt Lujan (age 27) · Ben Holmes (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119127vR 135

ERA5.38

FIP5.38

K%20.1%

BB%12.8%

K-BB%7.4%

Proj IP144

Value2027 · WAR

Runs saved vs league avg · 144 IP

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)
2022	22	MIX MLE	2 levels	24	24	102	453	128	79	9	100%	4.3	21.8%	19.9%	1.9%	2.2%	3.96	4.99	—
2022	22	MIX RAW	2 levels	24	24	102	453	128	79	9	100%	4.3	28.3%	17.4%	10.8%	2.0%	3.96	4.06	—
2023	23	AA MLE	Akron RubberDucks	26	22	102	474	128	73	13	85%	3.9	21.9%	16.9%	4.9%	3.6%	4.94	5.39	—
2023	23	AA RAW	Akron RubberDucks	26	22	102	474	128	73	13	85%	3.9	27.0%	15.4%	11.6%	2.7%	4.94	4.39	—
2024	24	MIX MLE	2 levels	25	24	124	489	124	53	12	96%	4.9	21.3%	10.5%	10.8%	2.7%	2.98	4.12	—
2024	24	MIX MLE	2 levels	25	24	124	489	124	53	12	96%	4.9	21.3%	10.5%	10.8%	2.7%	2.98	4.12	—
2024	24	MIX RAW	2 levels	25	24	124	489	124	53	12	96%	4.9	25.4%	10.8%	14.5%	2.5%	2.98	3.64	—
2025	25	MIX MLE	2 levels	23	20	90	410	92	49	15	87%	3.9	19.3%	10.0%	9.3%	3.9%	5.40	4.88	+0.5
2025	25	MIX MLE	2 levels	23	20	90	410	92	49	15	87%	3.9	19.3%	10.0%	9.3%	3.9%	5.40	4.88	+0.5
2025	25	MIX RAW	2 levels	23	20	90	410	92	49	15	87%	3.9	22.4%	12.0%	10.5%	3.7%	5.40	4.86	+0.6
2026	26	MIX MLE	2 levels	19	9	51	258	56	40	11	47%	2.7	19.0%	13.7%	5.3%	4.9%	9.77	5.90	-0.8
2026	26	MIX MLE	2 levels	19	9	51	258	56	40	11	47%	2.7	19.0%	13.7%	5.3%	4.9%	9.77	5.90	-0.8
2026	26	MIX RAW	2 levels	19	9	51	258	56	40	11	47%	2.7	21.7%	15.5%	6.2%	4.3%	9.77	6.08	-0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			3	1	6	32	6	8	0	33%	2.0	18.8%	25.0%	-6.2%	0.0%	10.50	5.10	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	CWS	16	16	97	410	82	52	15	100%	6.1	20.1%	12.8%	7.4%	3.6%	5.38	5.38	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	CWS	19	19	115	486	98	60	18	100%	6.1	20.2%	12.4%	7.8%	3.6%	5.32	5.35	+0.1
2029	29	MLB MLE	CWS	16	16	99	417	84	51	16	100%	6.2	20.1%	12.3%	7.8%	3.8%	5.33	5.40	0.0
2030	30	MLB MLE	CWS	15	15	87	369	73	46	14	100%	5.8	19.8%	12.3%	7.5%	3.9%	5.42	5.52	-0.1
2028	28	MLB CTX	CWS	14	14	86	363	73	45	13	100%	6.1	20.2%	12.4%	7.8%	3.6%	5.32	5.35	+0.0
2029	29	MLB CTX	CWS	13	13	78	329	66	40	12	100%	6.0	20.1%	12.3%	7.8%	3.8%	5.33	5.40	0.0
2030	30	MLB CTX	CWS	12	12	72	304	60	38	12	100%	6.0	19.8%	12.3%	7.5%	3.9%	5.42	5.52	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		42	40	243	1032	206	131	38	95%	5.8	20.0%	12.7%	7.3%	3.6%	5.48	5.03	+1.0
/ 200 IP	—	RAW		35	33	200	850	170	108	31	95%	5.7	20.0%	12.7%	7.3%	3.6%	5.48	5.03	+0.8
Career	—	MLE		117	99	469	2084	435	299	69	85%	4.0	20.9%	14.3%	6.6%	3.3%	4.82	4.97	-0.0
/ 200 IP	—	MLE		50	42	200	889	186	127	29	85%	4.0	20.9%	14.3%	6.6%	3.3%	4.82	4.97	-0.0

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 AAAIowa Cubs · 49 IPFIP 5.59 → 5.90 (+0.31)K% 22.1% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.09%	—	×0.860	19.00%
BB% (unintentional) /BF	15.26%	—	×0.900	13.73%
HR / BF /BF	4.42%	÷1.000	×1.100	4.86%

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 5.59 → 5.90, 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).

2025 AAAColumbus Clippers · 86 IPFIP 4.74 → 4.88 (+0.14)K% 22.5% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.48%	—	×0.860	19.33%
BB% (unintentional) /BF	11.11%	—	×0.900	10.00%
HR / BF /BF	3.88%	÷1.093	×1.100	3.90%

Result: FIP 4.74 → 4.88, 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 AAAColumbus Clippers · 75 IPFIP 3.89 → 4.09 (+0.21)K% 25.0% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.860	21.50%
BB% (unintentional) /BF	11.33%	—	×0.900	10.20%
HR / BF /BF	2.67%	÷1.060	×1.100	2.77%

Result: FIP 3.89 → 4.09, 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 AAAkron RubberDucks · 48 IPFIP 3.35 → 4.17 (+0.83)K% 25.9% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.93%	—	×0.810	21.00%
BB% (unintentional) /BF	10.05%	—	×1.100	11.06%
HR / BF /BF	2.12%	÷0.966	×1.200	2.63%

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 93).

Result: FIP 3.35 → 4.17, 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 AAAkron RubberDucks · 102 IPFIP 4.28 → 5.39 (+1.11)K% 27.0% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.00%	—	×0.810	21.87%
BB% (unintentional) /BF	15.40%	—	×1.100	16.94%
HR / BF /BF	2.74%	÷0.909	×1.200	3.62%

Result: FIP 4.28 → 5.39, 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+Lake County Captains · 93 IPFIP 3.86 → 4.86 (+1.00)K% 29.4% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.35%	—	×0.770	22.60%
BB% (unintentional) /BF	16.92%	—	×1.150	19.45%
HR / BF /BF	1.99%	÷1.134	×1.250	2.19%

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 127).

Result: FIP 3.86 → 4.86, 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).

2022 AAAkron RubberDucks · 9 IPFIP 5.25 → 6.04 (+0.79)K% 19.6% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.61%	—	×0.810	15.88%
BB% (unintentional) /BF	21.57%	—	×1.100	23.73%
HR / BF /BF	1.96%	÷1.014	×1.200	2.32%

Result: FIP 5.25 → 6.04, 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
Doug Nikhazy (OGILVIE)	—	—	—	—	—	3.6%	—	5.42	20.0%	7.7%	301	+0.04	—	—	—
Brad Mills L 2011 · 5.37 FIP	26	SP-	5.37	19.8%	12.1%	4.4%	.328	5.61	18.8%	7.9%	21	+0.24	4.22	243	85
Matt Lujan L 2016 · 5.05 FIP	27	SP	5.05	18.5%	11.3%	3.8%	.319	4.69	14.3%	7.9%	70	-0.36	4.06	227	70
Ben Holmes L 2019 · 5.57 FIP	27	SP	5.57	19.7%	11.1%	5.0%	.331	—	—	—	—	—	3.09	451	67
Hayden Wynja L 2024 · 4.79 FIP	25	SP-	4.79	18.0%	10.5%	3.4%	.274	—	—	—	—	—	4.74	154	66
Marlon Arias L 2015 · 4.32 FIP	30	SP	4.32	16.8%	12.2%	2.0%	.330	3.73	17.2%	9.5%	22	-0.59	3.73	154	65
Matt Walker L 2023 · 4.73 FIP	25	SP-	4.73	12.7%	10.0%	2.6%	.333	—	—	—	—	—	4.21	156	64
Jack Snodgrass L 2015 · 4.66 FIP	27	SP-	4.66	12.6%	10.7%	2.3%	.278	5.01	15.7%	5.6%	45	+0.35	4.66	118	64
Luis Ysla L 2019 · 5.78 FIP	27	SP-	5.78	18.0%	14.4%	4.3%	.337	—	—	—	—	—	3.75	378	63
David Purcey L 2009 · 4.75 FIP	27	SP	4.75	17.5%	13.0%	2.7%	.322	4.13	18.2%	5.4%	68	-0.62	3.60	206	63
Houston Harding L 2024 · 4.54 FIP	26	SP-	4.54	16.5%	11.2%	2.6%	.268	5.19	12.0%	0.5%	61	+0.65	3.41	239	63
Aaron Rozek L 2023 · 4.87 FIP	27	SP-	4.87	17.4%	8.8%	3.9%	.311	4.34	16.7%	9.5%	356	-0.53	3.68	579	61
Taylor Varnell L 2021 · 4.48 FIP	26	SP	4.48	20.1%	10.3%	3.2%	.278	—	—	—	—	—	2.89	248	61
Jake Miednik L 2022 · 6.12 FIP	26	SP-	6.12	10.5%	14.6%	3.8%	.348	—	—	—	—	—	1.55	126	58
Luis Lugo L 2021 · 5.21 FIP	27	SP-	5.21	19.5%	13.2%	3.8%	.292	—	—	—	—	—	4.29	622	58
Greg Smith L 2010 · 5.33 FIP	26	SP	5.33	17.0%	12.1%	3.9%	.339	—	—	—	—	—	3.37	349	58
Justin Marks L 2015 · 4.60 FIP	27	SP-	4.60	15.4%	10.5%	2.7%	.323	3.88	19.0%	9.1%	216	-0.72	3.83	324	58
Brandon Williamson L 2024 · 5.90 FIP	26	SP-	5.90	20.3%	8.5%	6.3%	.158	5.14	15.1%	2.5%	67	-0.76	3.62	454	58
Juan Pablo Oramas L 2017 · 4.56 FIP	27	SP	4.56	15.4%	12.3%	2.2%	.363	3.60	21.2%	13.2%	140	-0.96	3.46	440	57
Alex Troop L 2023 · 5.03 FIP	27	SP-	5.03	17.8%	10.9%	3.7%	.275	5.10	17.3%	10.5%	43	+0.07	2.93	379	57
Tyler Alexander L 2019 · 5.56 FIP	27	SP-	5.56	21.7%	9.8%	5.6%	.289	5.27	15.7%	5.0%	26	-0.29	5.27	128	57

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	2.3	113	20.0%	12.7%	1.41	5.43
Jeff Robinson ('87-'92, 0 WAR*)	3.5	118	18.3%*	10.9%*	1.38*	5.14*
Jason Bere ('03)	5.6	123	18.4%	12.6%	1.17	5.14
Kazuhisa Ishii ('02-'05, 1 WAR*)	2.8	141	19.8%*	13.6%*	1.14*	4.72*
Tim Lollar ('80-'86, 3 WAR*)	4.5	129	21.2%*	12.2%*	1.35*	4.94*
Matt Beech ('98)	1.5	98	20.2%	10.0%	1.59	5.37
Rich Hand ('70-'73, 1 WAR*)	2.4	122	17.8%*	11.3%*	1.34*	4.83*