Vinny Nittoli

P Norfolk Tides

Age 36 RHP 6'0" / 204 lbs AAA peak 0.2 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	32	MIX2 levels	38	2	46	4.47	5.26	24.8%	9.4%	-0.4	K 21.6% · BB 9.1% · FIP 5.97
2024	33	MIX2 levels	35	0	42	3.00	3.53	29.5%	8.1%	0.5	K 29.1% · BB 8.5% · FIP 3.96
2025	34	AAABAL	37	1	39	4.58	3.89	25.8%	8.4%	—	K 22.2% · BB 7.6% · FIP 4.34
2026	35	No MLB games played
2027PROJ	36	MLBBAL	2	0	2	4.17	4.17	24.7%	8.2%	0.0
2028PROJMLE	37	MLBBAL	—	—	0	4.41	4.56	23.8%	8.9%	—

Last 3 seasons WAR 0.1 · Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsRafael Martín (age 35) · Peter Moylan (age 36) · Keiichi Yabu (age 36)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 112104vR 96

ERA4.17

FIP4.17

K%24.7%

BB%8.2%

K-BB%16.5%

Proj IP19

Value2027 · WAR

Runs saved vs league avg · 19 IP

Grades · Contract

Scouting Grades

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)
2015	24	ROK MLE	AZL Mariners	7	0	10	38	7	2	1	0%	1.4	18.4%	5.3%	13.2%	2.6%	3.60	3.66	—
2015	24	ROK RAW	AZL Mariners	7	0	10	38	7	2	1	0%	1.4	18.4%	5.3%	13.2%	2.6%	3.60	3.60	—
2016	25	MIX MLE	2 levels	40	0	65	273	74	23	8	0%	1.6	20.8%	9.7%	11.0%	3.8%	3.88	4.66	—
2016	25	MIX RAW	2 levels	40	0	65	273	74	23	8	0%	1.6	27.1%	8.4%	18.7%	2.9%	3.88	3.48	—
2019	28	MIX MLE	2 levels	34	4	61	263	60	17	7	12%	1.8	19.0%	6.9%	12.1%	3.3%	5.49	4.18	—
2019	28	MIX RAW	2 levels	34	4	61	263	60	17	7	12%	1.8	22.8%	6.5%	16.3%	2.7%	5.49	3.46	—
2021	30	MIX MLE	2 levels	31	6	42	175	52	11	9	19%	1.4	26.6%	5.6%	21.0%	4.6%	5.36	4.12	+0.2
2021	30	MIX RAW	2 levels	31	6	42	175	52	11	9	19%	1.4	29.7%	6.3%	23.4%	5.1%	5.36	4.20	+0.2
2022	31	MIX MLE	2 levels	39	4	54	216	65	15	7	10%	1.4	27.1%	7.1%	20.0%	3.6%	3.67	3.66	+0.6
2022	31	MIX RAW	2 levels	39	4	54	216	65	15	7	10%	1.4	30.1%	6.9%	23.1%	3.2%	3.67	3.21	+0.9
2023	32	MIX MLE	2 levels	38	2	46	202	50	19	11	5%	1.2	21.6%	9.1%	12.5%	6.5%	4.47	5.97	-0.8
2023	32	MIX RAW	2 levels	38	2	46	202	50	19	11	5%	1.2	24.8%	9.4%	15.3%	5.4%	4.47	5.26	-0.4
2024	33	MIX MLE	2 levels	35	0	42	173	51	14	6	0%	1.2	29.1%	8.5%	20.6%	4.1%	3.00	3.96	+0.3
2024	33	MIX MLE	2 levels	35	0	42	173	51	14	6	0%	1.2	29.1%	8.5%	20.6%	4.1%	3.00	3.96	+0.3
2024	33	MIX RAW	2 levels	35	0	42	173	51	14	6	0%	1.2	29.5%	8.1%	21.4%	3.5%	3.00	3.53	+0.5
2025	34	AAA MLE	Norfolk Tides	37	1	39	178	46	15	6	3%	1.1	22.2%	7.6%	14.6%	3.9%	4.58	4.34	—
2025	34	AAA MLE	Norfolk Tides	37	1	39	178	46	15	6	3%	1.1	22.2%	7.6%	14.6%	3.9%	4.58	4.34	—
2025	34	AAA RAW	Norfolk Tides	37	1	39	178	46	15	6	3%	1.1	25.8%	8.4%	17.4%	3.4%	4.58	3.89	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			15	0	19	75	13	5	2	0%	1.2	17.3%	6.7%	10.7%	2.7%	2.41	3.90	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	BAL	2	0	2	8	2	1	0	0%	1.0	24.7%	8.2%	16.5%	3.2%	4.17	4.17	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	BAL	17	0	18	74	18	7	3	0%	1.0	23.8%	8.9%	14.9%	3.6%	4.41	4.56	-0.0
2028	37	MLB CTX	BAL	—	—	0	—	—	—	—	—	—	23.8%	8.9%	14.9%	3.6%	4.41	4.56	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		15	0	19	76	13	5	2	0%	1.3	17.4%	6.7%	10.7%	2.7%	2.43	3.95	+0.1
/ 200 IP	—	RAW		161	0	200	804	138	53	21	0%	1.2	17.4%	6.7%	10.7%	2.7%	2.43	3.95	+1.4
Career	—	MLE		261	17	359	1518	352	119	63	7%	1.4	23.2%	7.8%	15.4%	4.1%	4.33	4.40	+0.1
/ 200 IP	—	MLE		145	9	200	845	196	66	35	7%	1.4	23.2%	7.8%	15.4%	4.1%	4.33	4.40	+0.8

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.

2025 AAANorfolk Tides · 39 IPFIP 3.84 → 4.34 (+0.50)K% 25.8% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.84%	—	×0.860	22.22%
BB% (unintentional) /BF	8.43%	—	×0.900	7.58%
HR / BF /BF	3.37%	÷0.945	×1.100	3.92%

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 89).

Result: FIP 3.84 → 4.34, 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 AAASyracuse Mets · 30 IPFIP 3.60 → 3.96 (+0.36)K% 33.9% → 29.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.86%	—	×0.860	29.12%
BB% (unintentional) /BF	9.45%	—	×0.900	8.50%
HR / BF /BF	3.94%	÷1.059	×1.100	4.09%

Result: FIP 3.60 → 3.96, 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 AAASyracuse Mets · 43 IPFIP 5.49 → 5.97 (+0.48)K% 25.1% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.13%	—	×0.860	21.61%
BB% (unintentional) /BF	10.16%	—	×0.900	9.14%
HR / BF /BF	5.88%	÷1.003	×1.100	6.45%

Result: FIP 5.49 → 5.97, 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).

2022 AAALehigh Valley IronPigs · 52 IPFIP 3.20 → 3.66 (+0.46)K% 30.8% → 27.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.77%	—	×0.880	27.08%
BB% (unintentional) /BF	6.73%	—	×1.050	7.07%
HR / BF /BF	3.37%	÷1.039	×1.100	3.56%

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 108).

Result: FIP 3.20 → 3.66, 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 AAASt. Paul Saints · 41 IPFIP 3.82 → 4.12 (+0.29)K% 30.2% → 26.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.18%	—	×0.880	26.56%
BB% (unintentional) /BF	5.33%	—	×1.050	5.59%
HR / BF /BF	4.73%	÷1.121	×1.100	4.64%

Result: FIP 3.82 → 4.12, 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).

2019 AANew Hampshire Fisher Cats · 43 IPFIP 3.00 → 3.92 (+0.91)K% 22.7% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.73%	—	×0.810	18.41%
BB% (unintentional) /BF	4.55%	—	×1.100	5.00%
HR / BF /BF	2.27%	÷0.860	×1.200	3.17%

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 72).

Result: FIP 3.00 → 3.92, 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 AAAReno Aces · 18 IPFIP 4.36 → 4.70 (+0.34)K% 23.0% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.99%	—	×0.880	20.23%
BB% (unintentional) /BF	10.34%	—	×1.050	10.86%
HR / BF /BF	3.45%	÷1.077	×1.100	3.52%

Result: FIP 4.36 → 4.70, 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).

2016 A+Bakersfield Blaze · 52 IPFIP 3.52 → 4.74 (+1.22)K% 28.6% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.64%	—	×0.770	22.05%
BB% (unintentional) /BF	8.64%	—	×1.150	9.93%
HR / BF /BF	3.18%	÷0.973	×1.250	4.09%

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 95).

Result: FIP 3.52 → 4.74, 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
Vinny Nittoli (OGILVIE)	—	—	4.17	24.7%	8.2%	3.2%	—	4.56	23.8%	14.9%	18	+0.39	—	—	—
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	71
Peter Moylan R 2015 · 3.11 FIP	36	SU	3.11	18.4%	8.2%	0.9%	.259	3.84	18.2%	9.1%	145	+0.73	2.54	431	65
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	64
Jay Jackson R 2024 · 5.31 FIP	36	SU	5.31	25.4%	7.9%	6.1%	.304	—	—	—	—	—	2.36	261	64
Juan Sandoval R 2017 · 3.42 FIP	36	SU	3.42	16.7%	7.2%	1.5%	.298	5.41	15.9%	8.7%	57	+1.99	3.24	225	63
Rudy Gonzalez R 2017 · 4.72 FIP	36	SU	4.72	15.8%	7.1%	3.8%	.354	—	—	—	—	—	3.31	119	61
Chris Nichting R 2002 · 4.67 FIP	36	SU	4.67	16.6%	3.3%	4.6%	.289	—	—	—	—	—	4.11	103	60
Kazuhiro Sasaki R 2003 · 3.30 FIP	35	SU	3.30	19.3%	8.7%	1.3%	.274	—	—	—	—	—	2.76	223	58
Salvador Valdez R 2019 · 4.30 FIP	36	SW	4.30	17.1%	8.2%	2.9%	.405	—	—	—	—	—	3.60	326	58
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	57
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	57
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	55
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	55
Daniel Bard R 2021 · 3.62 FIP	36	SU	3.62	26.3%	11.5%	2.3%	.337	3.64	24.6%	10.3%	110	+0.02	2.56	456	53
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	52
Jesus Adrian Castillo R 2019 · 5.13 FIP	35	SU	5.13	13.1%	7.8%	3.9%	.319	—	—	—	—	—	2.23	173	52
Erubiel Gonzalez R 2015 · 3.43 FIP	36	SU	3.43	12.4%	6.0%	1.1%	.328	3.26	14.8%	10.4%	69	-0.17	2.99	119	52
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	50
Brian Sweeney R 2010 · 4.63 FIP	36	SU	4.63	9.5%	3.4%	3.5%	.226	—	—	—	—	—	3.03	108	45
Tony Pena Jr. R 2017 · 3.43 FIP	36	SU	3.43	10.9%	4.3%	1.3%	.312	—	—	—	—	—	2.80	128	45

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	0.3	27	22.0%	7.9%	1.21	3.65
Shawn Tolleson ('16)	1.1	54	23.1%	8.3%	1.28	3.92
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Matt Bush ('23)	1.1	53	25.2%	8.0%	1.41	3.75
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*