Kyle Nicolas

P Rochester Red Wings

Age 28 RHP 6'3" / 216 lbs AAA peak 0.1 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	60	0	65	3.44	3.61	23.7%	13.6%	0.7	K 22.6% · BB 12.3% · FIP 3.73
2025	26	MIX2 levels	61	1	74	4.28	3.07	25.6%	11.6%	1.3	K 23.5% · BB 11.0% · FIP 3.25
2026	27	MIX2 levels	55	0	55	4.77	4.87	25.6%	22.4%	-0.2	K 23.4% · BB 18.8% · FIP 4.27
2027PROJ	28	MLBCIN	55	0	58	4.51	4.64	25.8%	15.9%	-0.1
2028PROJ91% MLB	29	MLBCIN	31	0	33	4.68	4.80	25.2%	16.1%	-0.1
2029PROJ93% MLB	30	MLBCIN	19	0	20	4.87	5.00	24.5%	16.4%	-0.1

Last 3 seasons WAR 1.8 · 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

Stuff55Control30Command40FB velo65

CompsJose De La Torre (age 27) · José A. Váldez (age 28) · Jeff Ames (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121113vR 105

ERA4.51

FIP4.64

K%25.8%

BB%15.9%

K-BB%9.9%

Proj IP65

Value2027 · WAR

Runs saved vs league avg · 65 IP

Grades · Contract

Scouting Grades

STUF5555

CTRL3030

CMD4040

K†6060

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	21	20	99	426	136	49	16	95%	4.7	25.1%	12.9%	12.1%	4.4%	4.18	5.02	—
2021	22	MIX RAW	2 levels	21	20	99	426	136	49	16	95%	4.7	31.9%	11.5%	20.4%	3.8%	4.18	3.94	—
2022	23	AA MLE	Altoona Curve	24	22	91	390	101	47	9	92%	3.8	21.0%	13.3%	7.7%	2.6%	3.97	4.41	—
2022	23	AA RAW	Altoona Curve	24	22	91	390	101	47	9	92%	3.8	25.9%	12.1%	13.8%	2.3%	3.97	3.72	—
2023	24	MIX MLE	3 levels	39	18	104	473	134	56	17	46%	2.7	23.7%	11.5%	12.2%	3.7%	5.54	4.61	-0.1
2023	24	MIX RAW	3 levels	39	18	104	473	134	56	17	46%	2.7	28.3%	11.8%	16.5%	3.6%	5.54	4.26	+0.4
2024	25	MIX MLE	2 levels	60	0	65	287	68	39	4	0%	1.1	22.6%	12.3%	10.3%	1.8%	3.44	3.73	+0.6
2024	25	MIX MLE	2 levels	60	0	65	287	68	39	4	0%	1.1	22.6%	12.3%	10.3%	1.8%	3.44	3.73	+0.6
2024	25	MIX RAW	2 levels	60	0	65	287	68	39	4	0%	1.1	23.7%	13.6%	10.1%	1.4%	3.44	3.61	+0.7
2025	26	MIX MLE	2 levels	61	1	74	328	84	38	4	2%	1.2	23.5%	11.0%	12.5%	1.4%	4.28	3.25	+1.1
2025	26	MIX MLE	2 levels	61	1	74	328	84	38	4	2%	1.2	23.5%	11.0%	12.5%	1.4%	4.28	3.25	+1.1
2025	26	MIX RAW	2 levels	61	1	74	328	84	38	4	2%	1.2	25.6%	11.6%	14.0%	1.2%	4.28	3.07	+1.3
2026	27	MIX MLE	2 levels	55	0	55	281	72	63	4	0%	1.0	23.4%	18.8%	4.6%	1.4%	4.77	4.27	+0.2
2026	27	MIX MLE	2 levels	55	0	55	281	72	63	4	0%	1.0	23.4%	18.8%	4.6%	1.4%	4.77	4.27	+0.2
2026	27	MIX RAW	2 levels	55	0	55	281	72	63	4	0%	1.0	25.6%	22.4%	3.2%	1.4%	4.77	4.87	-0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			93	0	105	478	103	65	9	0%	1.1	21.5%	13.6%	7.9%	1.9%	4.96	4.11	+0.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CIN	55	0	58	245	63	39	6	0%	1.1	25.8%	15.9%	9.9%	2.4%	4.51	4.64	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CIN	34	0	36	151	38	24	4	0%	1.1	25.2%	16.1%	9.1%	2.6%	4.68	4.80	-0.1
2029	30	MLB MLE	CIN	21	0	22	92	23	15	3	0%	1.0	24.5%	16.4%	8.1%	2.8%	4.87	5.00	-0.1
2028	29	MLB CTX	CIN	31	0	33	139	35	22	4	0%	1.1	25.2%	16.1%	9.1%	2.6%	4.68	4.80	-0.1
2029	30	MLB CTX	CIN	19	0	20	84	21	14	2	0%	1.1	24.5%	16.4%	8.1%	2.8%	4.87	5.00	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		143	0	158	702	159	101	15	0%	1.1	22.6%	14.4%	8.2%	2.1%	4.89	4.18	+0.7
/ 200 IP	—	RAW		181	0	200	886	201	128	19	0%	1.1	22.6%	14.4%	8.2%	2.1%	4.89	4.18	+0.9
Career	—	MLE		260	61	487	2185	508	286	60	23%	1.9	23.3%	13.1%	10.2%	2.7%	4.41	4.29	+0.3
/ 200 IP	—	MLE		107	25	200	897	209	117	24	23%	1.9	23.3%	13.1%	10.2%	2.7%	4.41	4.29	+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.

2026 AAARochester Red Wings · 47 IPFIP 4.14 → 4.27 (+0.13)K% 27.2% → 23.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.20%	—	×0.860	23.39%
BB% (unintentional) /BF	20.92%	—	×0.900	18.83%
HR / BF /BF	1.26%	÷1.000	×1.100	1.38%

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 4.14 → 4.27, 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).

2025 AAAIndianapolis Indians · 36 IPFIP 2.39 → 2.67 (+0.28)K% 31.1% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.06%	—	×0.860	26.71%
BB% (unintentional) /BF	12.42%	—	×0.900	11.18%
HR / BF /BF	0.62%	÷0.915	×1.100	0.75%

Result: FIP 2.39 → 2.67, 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 AAAIndianapolis Indians · 11 IPFIP 3.20 → 3.29 (+0.09)K% 29.5% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.55%	—	×0.860	25.41%
BB% (unintentional) /BF	20.45%	—	×0.900	18.41%
HR / BF /BF	0.00%	÷0.909	×1.100	0.00%

Result: FIP 3.20 → 3.29, 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 AAAltoona Curve · 54 IPFIP 3.93 → 4.63 (+0.70)K% 26.4% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.36%	—	×0.810	21.35%
BB% (unintentional) /BF	9.62%	—	×1.100	10.59%
HR / BF /BF	3.35%	÷1.106	×1.200	3.63%

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 121).

Result: FIP 3.93 → 4.63, 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 AAAIndianapolis Indians · 45 IPFIP 4.38 → 4.58 (+0.20)K% 30.8% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.77%	—	×0.860	26.46%
BB% (unintentional) /BF	13.94%	—	×0.900	12.55%
HR / BF /BF	3.85%	÷1.095	×1.100	3.86%

Result: FIP 4.38 → 4.58, 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 AAAltoona Curve · 91 IPFIP 3.71 → 4.41 (+0.70)K% 25.9% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.90%	—	×0.810	20.98%
BB% (unintentional) /BF	12.05%	—	×1.100	13.26%
HR / BF /BF	2.31%	÷1.084	×1.200	2.55%

Result: FIP 3.71 → 4.41, 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 A+Beloit Snappers · 60 IPFIP 4.22 → 5.47 (+1.25)K% 33.2% → 25.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.20%	—	×0.770	25.57%
BB% (unintentional) /BF	9.27%	—	×1.150	10.66%
HR / BF /BF	5.02%	÷1.082	×1.250	5.80%

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 116).

Result: FIP 4.22 → 5.47, 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 AAPensacola Blue Wahoos · 39 IPFIP 3.45 → 4.31 (+0.85)K% 29.9% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.94%	—	×0.810	24.25%
BB% (unintentional) /BF	14.97%	—	×1.100	16.47%
HR / BF /BF	1.80%	÷1.011	×1.200	2.13%

Result: FIP 3.45 → 4.31, 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
Kyle Nicolas (OGILVIE)	—	—	4.64	25.8%	15.9%	2.4%	—	4.88	24.9%	8.8%	58	+0.24	—	—	—
Jose De La Torre R 2013 · 5.22 FIP	27	SU	5.22	28.3%	18.9%	3.9%	.308	3.87	17.6%	6.6%	110	-1.35	2.64	141	73
José A. Váldez R 2018 · 4.02 FIP	28	SU	4.02	23.1%	16.2%	1.5%	.325	4.21	16.8%	6.2%	103	+0.19	4.02	328	72
Jeff Ames R 2019 · 4.45 FIP	28	SU	4.45	25.6%	16.8%	2.5%	.351	—	—	—	—	—	3.85	272	70
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	69
Joe Colón J R 2017 · 4.25 FIP	27	SU	4.25	20.4%	12.1%	2.4%	.315	—	—	—	—	—	3.27	113	68
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	68
Daniel Robert R 2023 · 3.45 FIP	28	SU	3.45	22.7%	10.7%	1.7%	.310	3.02	25.4%	17.1%	87	-0.43	2.32	186	68
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	67
Michael Ynoa R 2019 · 4.68 FIP	27	SU	4.68	23.1%	13.8%	3.3%	.281	—	—	—	—	—	3.30	142	67
Peyton Gray R 2021 · 4.27 FIP	26	SU	4.27	29.2%	14.1%	3.4%	.307	—	—	—	—	—	3.62	160	67
Jose Rafael De Paula R 2019 · 4.43 FIP	28	SU	4.43	23.3%	13.6%	2.9%	.313	—	—	—	—	—	2.64	315	66
Grant Balfour R 2007 · 4.01 FIP	29	SU	4.01	24.8%	16.5%	1.7%	.406	2.81	28.4%	18.8%	181	-1.20	2.04	533	66
Jeff Johnson R 2017 · 3.69 FIP	27	SU	3.69	23.6%	15.6%	1.1%	.297	—	—	—	—	—	2.49	160	66
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	66
Lucas Erceg R 2023 · 3.50 FIP	28	SU	3.50	25.7%	13.8%	1.5%	.330	3.25	21.4%	13.5%	171	-0.25	2.10	351	66
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	66
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	65
Mike Adams R 2005 · 4.83 FIP	27	SU	4.83	23.0%	14.8%	3.3%	.278	3.00	28.6%	22.0%	65	-1.83	1.36	405	65
Caleb Simpson R 2019 · 4.02 FIP	27	SU	4.02	24.7%	17.3%	1.5%	.189	4.23	22.4%	9.7%	54	+0.21	3.57	197	65
Zack Jones R 2018 · 5.00 FIP	27	SU	5.00	27.7%	24.1%	2.2%	.167	—	—	—	—	—	2.57	109	65

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	1.1	46	23.6%	15.0%	0.86	4.78
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
Matt Anderson ('05)	1.3	51	19.3%	13.5%	1.05	5.19
Charlie Kerfeld ('85-'90, -0 WAR*)	1.0	50	22.3%*	12.7%*	0.72*	4.84*
John Parrish ('10)	1.4	46	17.6%	14.8%	0.88	4.51
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*