Andrew Nardi

P Miami Marlins

Age 28 LHP 6'3" / 215 lbs MLB peak 0.1 · 2027 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	24	MIX2 levels	66	59	2.90	3.18	30.8%	8.9%	1.0	K 30.8% · BB 8.0% · FIP 3.22
2024	25	MLBMIA	59	50	5.07	3.14	33.3%	8.1%	0.8
2026	27	MLBMIA	25	23	5.16	4.47	27.3%	11.1%	0.0
2027PROJ	28	MLBMIA	33	35	4.05	4.15	26.9%	8.7%	0.2
2028PROJ95% MLB	29	MLBMIA	47	49	4.21	4.31	26.3%	9.0%	0.1
2029PROJ95% MLB	30	MLBMIA	41	43	4.40	4.52	25.6%	9.3%	0.0

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.

Skills · percentileStatcast 2026

K%78

FB Velo51

xwOBA vs20

CompsYuki Matsui (age 28) · Darin Downs (age 28) · Josh Smoker (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 96104vR 112

ERA4.05

FIP4.15

K%26.9%

BB%8.7%

K-BB%18.1%

Proj IP35

Value2027 · WAR

Runs saved vs league avg · 35 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL5050

CMD7070

K†6060

Statcast Percentiles

FB Velo

p5194.6

Whiff%

p8330.4%

p7827.3%

xwOBA vs

p200.348

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	20	ROK MLE	GCL Marlins	13	0	18	82	30	12	0	0%	1.4	24.9%	18.3%	6.6%	0.0%	0.98	3.32	—
2019	20	ROK RAW	GCL Marlins	13	0	18	82	30	12	0	0%	1.4	36.6%	14.6%	22.0%	0.0%	0.98	1.79	—
2021	22	MIX MLE	3 levels	29	0	52	216	69	16	6	0%	1.8	24.6%	8.4%	16.3%	3.2%	3.61	3.86	—
2021	22	MIX RAW	3 levels	29	0	52	216	69	16	6	0%	1.8	31.9%	7.4%	24.5%	2.8%	3.61	2.87	—
2022	23	MIX MLE	3 levels	50	0	66	282	100	32	9	0%	1.3	31.5%	11.7%	19.7%	3.4%	3.97	3.80	+0.6
2022	23	MIX RAW	3 levels	50	0	66	282	100	32	9	0%	1.3	35.5%	11.3%	24.1%	3.2%	3.97	3.30	+1.0
2023	24	MIX MLE	2 levels	66	0	59	247	76	22	7	0%	0.9	30.8%	8.0%	22.8%	3.1%	2.90	3.22	+0.9
2023	24	MIX RAW	2 levels	66	0	59	247	76	22	7	0%	0.9	30.8%	8.9%	21.9%	2.8%	2.90	3.18	+1.0
2024	25	MLB MLE	Miami Marlins	59	0	50	210	70	17	7	0%	0.8	33.3%	8.1%	25.2%	3.5%	5.07	3.24	+0.8
2024	25	MLB MLE	Miami Marlins	59	0	50	210	70	17	7	0%	0.8	33.3%	8.1%	25.2%	3.5%	5.07	3.24	+0.8
2024	25	MLB RAW	Miami Marlins	59	0	50	210	70	17	7	0%	0.8	33.3%	8.1%	25.2%	3.3%	5.07	3.14	+0.8
2026	27	MLB MLE	Miami Marlins	25	0	23	99	27	11	4	0%	0.9	27.3%	11.1%	16.2%	4.3%	5.16	4.54	+0.0
2026	27	MLB MLE	Miami Marlins	25	0	23	99	27	11	4	0%	0.9	27.3%	11.1%	16.2%	4.3%	5.16	4.54	+0.0
2026	27	MLB RAW	Miami Marlins	25	0	23	99	27	11	4	0%	0.9	27.3%	11.1%	16.2%	4.0%	5.16	4.47	+0.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			160	0	144	629	194	61	23	0%	0.9	30.8%	9.7%	21.1%	3.7%	4.61	3.75	+1.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	MIA	33	0	35	148	40	13	5	0%	1.1	26.9%	8.7%	18.1%	3.3%	4.05	4.15	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	MIA	49	0	51	216	57	19	8	0%	1.0	26.3%	9.0%	17.3%	3.5%	4.21	4.31	+0.1
2029	30	MLB MLE	MIA	43	0	45	189	48	18	7	0%	1.0	25.6%	9.3%	16.3%	3.7%	4.40	4.52	+0.0
2028	29	MLB CTX	MIA	47	0	49	207	54	19	7	0%	1.0	26.3%	9.0%	17.3%	3.5%	4.21	4.31	+0.1
2029	30	MLB CTX	MIA	41	0	43	182	46	17	7	0%	1.0	25.6%	9.3%	16.3%	3.7%	4.40	4.52	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		247	0	235	1014	294	96	37	0%	1.0	29.0%	9.5%	19.5%	3.6%	4.49	3.84	+2.0
/ 200 IP	—	RAW		210	0	200	861	250	82	31	0%	1.0	29.0%	9.5%	19.5%	3.6%	4.49	3.84	+1.7
Career	—	MLE		242	0	268	1136	335	114	36	0%	1.1	29.5%	10.0%	19.5%	3.2%	3.77	3.61	+1.5
/ 200 IP	—	MLE		181	0	200	849	251	85	27	0%	1.1	29.5%	10.0%	19.5%	3.2%	3.77	3.61	+1.3

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.

2022 AAAJacksonville Jumbo Shrimp · 32 IPFIP 2.79 → 3.32 (+0.53)K% 36.3% → 31.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.29%	—	×0.880	31.94%
BB% (unintentional) /BF	11.29%	—	×1.050	11.85%
HR / BF /BF	2.42%	÷1.032	×1.100	2.58%

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 106).

Result: FIP 2.79 → 3.32, 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 AAPensacola Blue Wahoos · 19 IPFIP 1.02 → 1.85 (+0.84)K% 41.3% → 33.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	41.33%	—	×0.810	33.48%
BB% (unintentional) /BF	5.33%	—	×1.100	5.87%
HR / BF /BF	1.33%	÷1.048	×1.200	1.53%

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 110).

Result: FIP 1.02 → 1.85, 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 · 19 IPFIP 3.61 → 4.76 (+1.15)K% 32.9% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.93%	—	×0.770	25.35%
BB% (unintentional) /BF	4.88%	—	×1.150	5.61%
HR / BF /BF	4.88%	÷1.082	×1.250	5.63%

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 3.61 → 4.76, 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 · 17 IPFIP 3.98 → 4.85 (+0.87)K% 26.4% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.39%	—	×0.810	21.38%
BB% (unintentional) /BF	12.50%	—	×1.100	13.75%
HR / BF /BF	2.78%	÷1.011	×1.200	3.30%

Result: FIP 3.98 → 4.85, 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 AJupiter Hammerheads · 16 IPFIP 0.58 → 1.51 (+0.92)K% 37.1% → 27.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.10%	—	×0.740	27.45%
BB% (unintentional) /BF	4.84%	—	×1.180	5.71%
HR / BF /BF	0.00%	÷0.891	×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 78).

Result: FIP 0.58 → 1.51, 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 ROKGCL Marlins · 18 IPFIP 1.86 → 3.32 (+1.45)K% 36.6% → 24.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.59%	—	×0.680	24.88%
BB% (unintentional) /BF	14.63%	—	×1.250	18.29%
HR / BF /BF	0.00%	÷1.000	×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 100).

Result: FIP 1.86 → 3.32, 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
Andrew Nardi (OGILVIE)	—	—	4.15	26.9%	8.7%	3.3%	—	4.41	25.9%	16.8%	96	+0.26	—	—	—
Yuki Matsui L 2024 · 3.63 FIP	28	SU	3.63	26.8%	8.9%	3.0%	.242	4.25	23.9%	12.6%	140	+0.62	3.63	203	80
Darin Downs L 2013 · 3.30 FIP	28	SU	3.30	24.5%	6.0%	2.8%	.317	3.87	16.5%	7.3%	51	+0.57	2.83	107	80
Josh Smoker L 2017 · 4.20 FIP	28	SU	4.20	25.5%	9.4%	3.8%	.329	4.35	20.2%	11.3%	59	+0.15	2.71	230	79
Daniel Stumpf L 2019 · 3.56 FIP	28	SU	3.56	25.2%	8.8%	2.7%	.314	—	—	—	—	—	1.84	238	79
Hunter Cervenka L 2018 · 3.08 FIP	28	SU	3.08	24.6%	6.6%	2.2%	.268	3.11	26.6%	13.5%	55	+0.03	3.08	194	78
Adam Liberatore L 2015 · 3.64 FIP	28	SU	3.64	21.1%	7.3%	2.5%	.267	3.17	23.3%	15.2%	73	-0.47	2.38	124	77
Justin King L 2024 · 3.26 FIP	26	SU	3.26	29.5%	11.8%	2.1%	.346	4.16	22.4%	3.6%	65	+0.90	3.26	133	76
Zac Rosscup L 2015 · 4.84 FIP	27	SU	4.84	24.6%	11.0%	4.4%	.296	2.85	29.5%	21.7%	40	-1.99	2.56	173	76
David Purcey L 2010 · 3.60 FIP	28	SU	3.60	22.4%	9.8%	2.1%	.245	4.29	16.7%	2.7%	59	+0.69	3.60	206	76
George Sherrill L 2005 · 3.43 FIP	28	SU	3.43	31.2%	6.5%	3.9%	.222	3.20	26.4%	15.4%	139	-0.23	2.74	323	75
Wesley Wright L 2013 · 3.73 FIP	28	SU	3.73	23.7%	7.3%	3.1%	.307	3.54	15.8%	6.9%	104	-0.19	3.03	375	75
Mike Holtz L 2001 · 3.66 FIP	28	SU	3.66	22.8%	6.6%	3.0%	.310	5.33	14.6%	-0.6%	35	+1.67	2.61	238	74
Ashur Tolliver L 2016 · 4.19 FIP	28	SU	4.19	21.3%	9.8%	3.0%	.308	5.03	13.8%	-5.1%	35	+0.84	3.49	134	74
Kevin Chapman L 2016 · 3.35 FIP	28	SU	3.35	23.2%	9.5%	1.8%	.348	4.08	19.2%	8.0%	39	+0.73	3.01	194	74
Tony Sipp L 2011 · 4.43 FIP	28	SU	4.43	22.7%	8.4%	4.0%	.215	3.89	26.0%	16.7%	143	-0.54	2.22	504	73
Armando Almanza L 2001 · 5.21 FIP	28	SU	5.21	25.3%	14.0%	4.5%	.260	4.73	25.3%	14.7%	108	-0.48	2.90	211	73
Dario Alvarez L 2017 · 3.68 FIP	28	SU	3.68	24.7%	12.4%	2.0%	.336	3.47	20.7%	8.3%	27	-0.21	3.47	160	73
Luis Perez L 2012 · 3.32 FIP	27	SU	3.32	22.3%	9.1%	1.7%	.299	4.00	15.2%	2.6%	66	+0.68	3.32	173	72
Jake Diekman L 2015 · 3.38 FIP	28	SU	3.38	26.5%	11.9%	1.8%	.310	3.25	27.0%	15.3%	106	-0.13	2.27	592	72
Brian Fuentes L 2004 · 3.27 FIP	28	SU	3.27	23.9%	6.5%	2.5%	.304	3.33	25.8%	17.0%	201	+0.06	2.08	602	72

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	1.4	47	28.6%	9.6%	1.39	4.43
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
Noé Ramirez ('22)	1.5	59	24.8%	9.4%	1.42	4.21
Trevor May ('23)	2.3	50	26.8%	8.5%	1.20	4.24
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*