Angel Chivilli

P New York Yankees

Age 25 RHP 6'2" / 185 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	22	MIX3 levels	55	0	60	3.43	3.81	27.9%	8.8%	0.5	K 24.2% · BB 9.7% · FIP 4.30
2025	23	MIX2 levels	53	0	68	7.05	5.10	16.9%	7.7%	-0.4	K 15.6% · BB 8.0% · FIP 5.09
2026	24	MIX2 levels	28	1	35	2.34	3.91	25.0%	7.9%	0.3	K 23.1% · BB 7.6% · FIP 4.01
2027PROJ	25	MLBNYY	53	0	56	4.82	4.56	23.8%	8.8%	-0.0
2028PROJ92% MLB	26	MLBNYY	39	0	41	4.63	4.51	24.3%	8.8%	0.0
2029PROJ93% MLB	27	MLBNYY	32	0	34	4.58	4.54	24.3%	8.9%	0.0

Last 3 seasons WAR 0.4 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo90

xwOBA vs53

K%48

CompsJosé Cisnero (age 24) · Will Vest (age 24) · Michael Feliz (age 25)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 120112vR 104

ERA4.82

FIP4.56

K%23.8%

BB%8.8%

K-BB%15.0%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL5050

CMD4040

K†5560

Statcast Percentiles

FB Velo

p9098.0

Whiff%

p9032.6%

p4821.9%

xwOBA vs

p530.309

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)
2019	17	ROK MLE	DSL Rockies	12	12	45	192	45	10	3	100%	3.8	15.9%	6.5%	9.4%	2.2%	4.00	3.78	—
2019	17	ROK RAW	DSL Rockies	12	12	45	192	45	10	3	100%	3.8	23.4%	5.2%	18.2%	1.6%	4.00	2.63	—
2021	19	ROK MLE	DSL Rockies	11	8	39	159	45	8	1	73%	3.5	19.2%	6.3%	13.0%	0.8%	3.49	2.72	—
2021	19	ROK RAW	DSL Rockies	11	8	39	159	45	8	1	73%	3.5	28.3%	5.0%	23.3%	0.6%	3.49	1.73	—
2022	20	MIX MLE	2 levels	32	0	41	167	51	10	1	0%	1.3	21.8%	7.2%	14.5%	0.8%	2.21	2.63	—
2022	20	MIX RAW	2 levels	32	0	41	167	51	10	1	0%	1.3	30.5%	6.0%	24.6%	0.6%	2.21	1.65	—
2023	21	MIX MLE	2 levels	53	0	61	271	68	21	9	0%	1.2	19.6%	9.0%	10.6%	4.2%	5.61	4.90	—
2023	21	MIX RAW	2 levels	53	0	61	271	68	21	9	0%	1.2	25.1%	7.7%	17.3%	3.3%	5.61	3.82	—
2024	22	MIX MLE	3 levels	55	0	60	251	70	22	9	0%	1.1	24.2%	9.7%	14.5%	3.7%	3.43	4.30	+0.2
2024	22	MIX MLE	3 levels	55	0	60	251	70	22	9	0%	1.1	24.2%	9.7%	14.5%	3.7%	3.43	4.30	+0.2
2024	22	MIX RAW	3 levels	55	0	60	251	70	22	9	0%	1.1	27.9%	8.8%	19.1%	3.6%	3.43	3.81	+0.5
2025	23	MIX MLE	2 levels	53	0	68	313	53	24	13	0%	1.3	15.6%	8.0%	7.6%	4.2%	7.05	5.09	-0.4
2025	23	MIX MLE	2 levels	53	0	68	313	53	24	13	0%	1.3	15.6%	8.0%	7.6%	4.2%	7.05	5.09	-0.4
2025	23	MIX RAW	2 levels	53	0	68	313	53	24	13	0%	1.3	16.9%	7.7%	9.3%	4.2%	7.05	5.10	-0.4
2026	24	MIX MLE	2 levels	28	1	35	140	35	11	5	4%	1.2	23.1%	7.6%	15.5%	3.5%	2.34	4.01	+0.2
2026	24	MIX MLE	2 levels	28	1	35	140	35	11	5	4%	1.2	23.1%	7.6%	15.5%	3.5%	2.34	4.01	+0.2
2026	24	MIX RAW	2 levels	28	1	35	140	35	11	5	4%	1.2	25.0%	7.9%	17.1%	3.6%	2.34	3.91	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			88	0	107	481	87	39	24	0%	1.2	18.1%	8.1%	10.0%	5.0%	5.80	5.48	-1.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	NYY	53	0	56	236	56	21	8	0%	1.1	23.8%	8.8%	15.0%	3.6%	4.82	4.56	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	NYY	42	0	44	188	46	16	7	0%	1.1	24.3%	8.8%	15.5%	3.6%	4.63	4.51	+0.0
2029	27	MLB MLE	NYY	34	0	36	152	37	13	6	0%	1.1	24.3%	8.9%	15.5%	3.6%	4.58	4.54	+0.0
2028	26	MLB CTX	NYY	39	0	41	173	42	15	6	0%	1.1	24.3%	8.8%	15.5%	3.6%	4.63	4.51	+0.0
2029	27	MLB CTX	NYY	32	0	34	144	35	13	5	0%	1.1	24.3%	8.9%	15.5%	3.6%	4.58	4.54	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		159	0	182	797	164	67	35	0%	1.1	20.6%	8.4%	12.2%	4.4%	5.31	4.87	-0.7
/ 200 IP	—	RAW		175	0	200	877	180	74	39	0%	1.1	20.6%	8.4%	12.2%	4.4%	5.31	4.87	-0.7
Career	—	MLE		244	21	348	1493	293	119	45	9%	1.4	19.6%	8.0%	11.6%	3.0%	4.34	4.13	-1.1
/ 200 IP	—	MLE		140	12	200	858	168	68	26	9%	1.4	19.6%	8.0%	11.6%	3.0%	4.34	4.13	-1.2

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.

2026 AAAScranton/Wilkes-Barre RailRiders · 18 IPFIP 2.28 → 2.62 (+0.34)K% 28.4% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.36%	—	×0.860	24.39%
BB% (unintentional) /BF	5.97%	—	×0.900	5.37%
HR / BF /BF	1.49%	÷1.000	×1.100	1.64%

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 2.28 → 2.62, 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 AAAAlbuquerque Isotopes · 9 IPFIP 1.54 → 1.79 (+0.24)K% 26.3% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.32%	—	×0.860	22.63%
BB% (unintentional) /BF	5.26%	—	×0.900	4.74%
HR / BF /BF	0.00%	÷1.017	×1.100	0.00%

Result: FIP 1.54 → 1.79, 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 AAHartford Yard Goats · 25 IPFIP 2.63 → 3.64 (+1.01)K% 34.6% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.58%	—	×0.810	28.01%
BB% (unintentional) /BF	11.21%	—	×1.100	12.34%
HR / BF /BF	1.87%	÷0.916	×1.200	2.45%

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 83).

Result: FIP 2.63 → 3.64, 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+Spokane Indians · 57 IPFIP 3.88 → 4.90 (+1.02)K% 25.5% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.49%	—	×0.770	19.63%
BB% (unintentional) /BF	7.84%	—	×1.150	9.02%
HR / BF /BF	3.53%	÷1.047	×1.250	4.22%

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 109).

Result: FIP 3.88 → 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 AFresno Grizzlies · 25 IPFIP 2.12 → 3.01 (+0.89)K% 25.9% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.93%	—	×0.740	19.19%
BB% (unintentional) /BF	5.56%	—	×1.180	6.56%
HR / BF /BF	0.93%	÷0.947	×1.300	1.27%

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 89).

Result: FIP 2.12 → 3.01, 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 ROKACL Rockies · 16 IPFIP 0.67 → 1.93 (+1.27)K% 39.0% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.98%	—	×0.680	26.51%
BB% (unintentional) /BF	6.78%	—	×1.250	8.47%
HR / BF /BF	0.00%	÷0.918	×1.400	0.00%

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 84).

Result: FIP 0.67 → 1.93, 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).

2021 ROKDSL Rockies · 39 IPFIP 1.69 → 2.72 (+1.03)K% 28.3% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.30%	—	×0.680	19.25%
BB% (unintentional) /BF	5.03%	—	×1.250	6.29%
HR / BF /BF	0.63%	÷1.078	×1.400	0.82%

Result: FIP 1.69 → 2.72, 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 ROKDSL Rockies · 45 IPFIP 2.64 → 3.78 (+1.14)K% 23.4% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.44%	—	×0.680	15.94%
BB% (unintentional) /BF	5.21%	—	×1.250	6.51%
HR / BF /BF	1.56%	÷1.000	×1.400	2.19%

Result: FIP 2.64 → 3.78, 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
Angel Chivilli (OGILVIE)	—	—	4.56	23.8%	8.8%	3.6%	—	4.52	24.3%	15.5%	80	-0.04	—	—	—
José Cisnero R 2013 · 3.86 FIP	24	SU	3.86	20.7%	8.6%	2.6%	.326	4.50	26.1%	14.4%	12	+0.64	2.26	322	78
Will Vest R 2019 · 3.71 FIP	24	SU	3.71	21.8%	8.5%	2.5%	.282	3.65	20.9%	11.9%	124	-0.06	2.56	448	77
Michael Feliz R 2018 · 3.94 FIP	25	SU	3.94	25.3%	10.6%	3.0%	.323	3.92	28.9%	19.8%	107	-0.02	2.77	442	76
Héctor Rondón R 2013 · 4.03 FIP	25	SU	4.03	18.2%	8.3%	2.6%	.267	2.63	25.9%	21.0%	184	-1.40	2.21	436	74
Grant Balfour R 2003 · 4.13 FIP	25	SU	4.13	26.1%	10.4%	3.5%	.275	3.79	24.4%	12.8%	39	-0.34	2.04	533	74
Hagen Danner R 2024 · 4.09 FIP	25	SU	4.09	20.0%	8.0%	3.0%	.295	4.34	18.6%	8.7%	96	+0.25	3.47	194	73
Nolan Clenney R 2021 · 3.73 FIP	25	SU	3.73	25.5%	8.4%	3.1%	.340	4.35	22.4%	13.7%	185	+0.62	3.73	223	73
Mitchell Stumpo R 2021 · 3.97 FIP	25	SU	3.97	25.6%	8.0%	3.7%	.299	5.27	22.4%	6.8%	121	+1.30	3.97	158	73
Emilio Pagán R 2016 · 4.08 FIP	25	SU	4.08	26.2%	11.5%	3.2%	.267	3.49	29.2%	23.8%	214	-0.59	2.67	724	73
Kaleb Bowman R 2023 · 3.88 FIP	26	SU	3.88	22.0%	7.5%	3.1%	.333	4.65	17.5%	6.2%	170	+0.77	3.88	203	72
Heath Hembree R 2015 · 3.95 FIP	26	SU	3.95	18.4%	7.5%	2.7%	.256	3.89	25.6%	17.6%	173	-0.06	2.52	382	72
Kyle Finnegan R 2017 · 5.04 FIP	25	SU	5.04	18.3%	9.8%	4.1%	.308	2.94	25.3%	15.9%	118	-2.10	2.57	753	72
Scott Dohmann R 2004 · 4.44 FIP	26	SU	4.44	24.7%	9.6%	4.0%	.270	4.80	20.6%	8.5%	112	+0.36	4.28	173	72
Matt Carasiti R 2016 · 3.68 FIP	25	SU	3.68	22.2%	7.6%	2.7%	.313	3.36	23.4%	12.8%	93	-0.32	2.80	312	72
Blake Goldsberry R 2022 · 3.43 FIP	25	SU	3.43	23.6%	8.3%	2.3%	.257	5.26	23.6%	12.0%	44	+1.83	3.43	117	72
Dovydas Neverauskas R 2018 · 4.63 FIP	25	SU	4.63	25.1%	12.3%	3.8%	.281	4.65	26.5%	16.4%	80	+0.02	2.74	353	72
Edgmer Escalona R 2012 · 4.56 FIP	25	SU	4.56	21.6%	6.2%	4.6%	.277	3.78	12.6%	6.9%	167	-0.78	3.26	316	72
Jon Leicester R 2004 · 4.69 FIP	25	SU	4.69	20.0%	8.6%	4.0%	.280	4.44	11.0%	2.0%	32	-0.25	3.76	113	71
Garrett Mock R 2008 · 3.57 FIP	25	SU	3.57	25.6%	11.1%	2.2%	.300	4.06	17.1%	7.4%	91	+0.49	3.57	132	71
Josh Zeid R 2013 · 4.00 FIP	26	SU	4.00	20.3%	9.3%	2.6%	.287	4.75	16.2%	4.8%	183	+0.75	4.00	313	71

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	1.2	50	21.5%	8.6%	1.63	5.17
Mike Mayers ('23)	1.3	53	23.0%	8.3%	1.61	5.21
Josh Osich ('21)	1.1	55	20.7%	9.0%	1.84	5.02
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Phil Hennigan ('69-'73, -0 WAR*)	1.4	70	20.9%*	10.4%*	1.50*	4.95*
Pete Ladd ('79-'86, 0 WAR*)	1.4	72	24.6%*	7.8%*	1.53*	4.42*