Nick Zwack

P Sacramento River Cats

Age 28 LHP 6'4" / 243 lbs AAA peak 0.2 · 2027

Overview

AAAPROSPECT

MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	24	AASF	24	16	81	6.56	4.29	24.9%	8.8%	—	K 20.2% · BB 9.6% · FIP 5.41
2025	26	MIX4 levels	21	21	74	4.26	4.60	21.9%	8.4%	—	K 15.6% · BB 9.5% · FIP 6.15
2026	27	AAASF	42	0	44	5.77	3.86	27.8%	13.1%	—	K 23.9% · BB 11.8% · FIP 4.10
2027PROJ	28	MLBSF	3	0	3	4.86	4.86	21.3%	10.7%	-0.0
2028PROJ37% MLB	29	MLBSF	10	0	10	4.88	4.94	21.2%	10.7%	-0.0

Next 2 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 -0.1 / P90 0.4, comp-based) · star 0% · didn't stick 96%

CompsJohn Rheinecker (age 28) · Matt Whitehouse (age 28) · Chad Bell (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 109117vR 125

ERA4.86

FIP4.86

K%21.3%

BB%10.7%

K-BB%10.6%

Proj IP29

Value2027 · WAR

Runs saved vs league avg · 29 IP

Grades · Contract

Scouting Grades

K†5050

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	ROK MLE	FCL Mets	5	0	7	26	13	2	0	0%	1.4	50.0%	7.7%	42.3%	0.0%	0.00	-0.15	—
2021	22	ROK RAW	FCL Mets	5	0	7	26	13	2	0	0%	1.4	50.0%	7.7%	42.3%	0.0%	0.00	0.24	—
2022	23	MIX MLE	2 levels	24	21	106	423	132	34	6	88%	4.4	23.9%	9.3%	14.6%	1.6%	2.81	3.16	—
2022	23	MIX RAW	2 levels	24	21	106	423	132	34	6	88%	4.4	31.2%	8.0%	23.2%	1.4%	2.81	2.31	—
2023	24	AA MLE	Richmond Flying Squirrels	24	16	81	365	91	32	14	67%	3.4	20.2%	9.6%	10.6%	5.1%	6.56	5.41	—
2023	24	AA RAW	Richmond Flying Squirrels	24	16	81	365	91	32	14	67%	3.4	24.9%	8.8%	16.2%	3.8%	6.56	4.29	—
2025	26	MIX MLE	4 levels	21	21	74	311	68	26	13	100%	3.5	15.6%	9.5%	6.1%	5.8%	4.26	6.15	—
2025	26	MIX MLE	4 levels	21	21	74	311	68	26	13	100%	3.5	15.6%	9.5%	6.1%	5.8%	4.26	6.15	—
2025	26	MIX RAW	4 levels	21	21	74	311	68	26	13	100%	3.5	21.9%	8.4%	13.5%	4.2%	4.26	4.60	—
2026	27	AAA MLE	Sacramento River Cats	42	0	44	198	55	26	5	0%	1.0	23.9%	11.8%	12.1%	2.8%	5.77	4.10	—
2026	27	AAA MLE	Sacramento River Cats	42	0	44	198	55	26	5	0%	1.0	23.9%	11.8%	12.1%	2.8%	5.77	4.10	—
2026	27	AAA RAW	Sacramento River Cats	42	0	44	198	55	26	5	0%	1.0	27.8%	13.1%	14.6%	2.5%	5.77	3.86	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	SF	3	0	3	13	3	1	0	0%	1.0	21.3%	10.7%	10.6%	3.3%	4.86	4.86	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	SF	27	0	28	118	25	13	4	0%	1.0	21.2%	10.7%	10.5%	3.4%	4.88	4.94	-0.1
2028	29	MLB CTX	SF	10	0	10	42	9	5	1	0%	1.0	21.2%	10.7%	10.5%	3.4%	4.88	4.94	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		10	0	10	43	9	5	1	0%	1.0	21.2%	10.7%	10.5%	3.4%	4.88	4.56	-0.0
/ 200 IP	—	RAW		190	0	200	844	175	97	19	0%	1.1	21.2%	10.7%	10.5%	3.4%	4.88	4.56	-0.0
Career	—	MLE		116	58	311	1323	283	129	49	50%	2.7	21.4%	9.8%	11.7%	3.7%	4.48	4.56	+0.1
/ 200 IP	—	MLE		75	37	200	850	182	83	31	50%	2.7	21.4%	9.8%	11.7%	3.7%	4.48	4.56	+1.1

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 AAASacramento River Cats · 44 IPFIP 3.80 → 4.10 (+0.30)K% 27.8% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.78%	—	×0.860	23.89%
BB% (unintentional) /BF	13.13%	—	×0.900	11.82%
HR / BF /BF	2.53%	÷1.000	×1.100	2.78%

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 3.80 → 4.10, 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 AARichmond Flying Squirrels · 32 IPFIP 2.31 → 2.81 (+0.49)K% 24.8% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.81%	—	×0.810	20.09%
BB% (unintentional) /BF	6.98%	—	×1.100	7.67%
HR / BF /BF	0.78%	÷1.183	×1.200	0.79%

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 137).

Result: FIP 2.31 → 2.81, 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 AAASacramento River Cats · 14 IPFIP 9.35 → 10.19 (+0.85)K% 11.0% → 9.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.96%	—	×0.860	9.42%
BB% (unintentional) /BF	15.07%	—	×0.900	13.56%
HR / BF /BF	9.59%	÷0.938	×1.100	11.25%

Result: FIP 9.35 → 10.19, 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 A+Eugene Emeralds · 16 IPFIP 6.58 → 8.17 (+1.59)K% 17.6% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.65%	—	×0.770	13.59%
BB% (unintentional) /BF	7.35%	—	×1.150	8.46%
HR / BF /BF	7.35%	÷0.980	×1.250	9.37%

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 96).

Result: FIP 6.58 → 8.17, 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).

2025 ROKACL Giants · 12 IPFIP 0.11 → 1.25 (+1.13)K% 39.0% → 26.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.02%	—	×0.680	26.54%
BB% (unintentional) /BF	2.44%	—	×1.250	3.05%
HR / BF /BF	0.00%	÷1.128	×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 126).

Result: FIP 0.11 → 1.25, 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 AARichmond Flying Squirrels · 81 IPFIP 4.21 → 5.41 (+1.19)K% 24.9% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.93%	—	×0.810	20.19%
BB% (unintentional) /BF	8.77%	—	×1.100	9.64%
HR / BF /BF	3.84%	÷0.906	×1.200	5.08%

Result: FIP 4.21 → 5.41, 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).

2022 A+Eugene Emeralds · 93 IPFIP 2.47 → 3.29 (+0.82)K% 29.1% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.11%	—	×0.770	22.42%
BB% (unintentional) /BF	8.63%	—	×1.150	9.92%
HR / BF /BF	1.35%	÷1.120	×1.250	1.50%

Result: FIP 2.47 → 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).

2022 ASt. Lucie Mets · 13 IPFIP 0.75 → 2.24 (+1.49)K% 46.2% → 34.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	46.15%	—	×0.740	34.15%
BB% (unintentional) /BF	3.85%	—	×1.180	4.54%
HR / BF /BF	1.92%	÷0.949	×1.300	2.63%

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 90).

Result: FIP 0.75 → 2.24, 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
Nick Zwack (OGILVIE)	—	—	4.86	21.3%	10.7%	3.3%	—	4.94	21.2%	10.5%	28	+0.08	—	—	—
John Rheinecker L 2007 · 5.13 FIP	28	SW	5.13	16.7%	10.9%	3.8%	.317	—	—	—	—	—	4.14	121	76
Matt Whitehouse L 2019 · 4.07 FIP	28	SW	4.07	20.1%	10.9%	2.3%	.339	—	—	—	—	—	3.37	353	75
Chad Bell L 2017 · 4.57 FIP	28	SW	4.57	19.4%	8.9%	3.6%	.341	4.38	18.8%	11.4%	57	-0.19	3.39	393	72
Randy Keisler L 2005 · 5.07 FIP	29	SW	5.07	16.4%	9.9%	3.8%	.295	5.51	6.5%	0.0%	17	+0.44	5.07	135	72
Brendan Nail L 2023 · 4.36 FIP	27	SU	4.36	19.3%	10.5%	2.8%	.262	—	—	—	—	—	3.45	165	68
Austin Warner L 2022 · 4.78 FIP	28	SW	4.78	16.9%	9.0%	3.6%	.319	—	—	—	—	—	3.81	491	68
Brian Holmes L 2017 · 5.91 FIP	26	SW	5.91	15.5%	11.7%	4.8%	.354	—	—	—	—	—	3.60	205	67
Juan Grullon L 2016 · 4.64 FIP	26	SU	4.64	19.8%	10.9%	3.3%	.305	—	—	—	—	—	4.64	134	67
Jimmy Reyes L 2017 · 4.92 FIP	28	SU	4.92	13.8%	8.0%	3.6%	.294	—	—	—	—	—	3.02	200	67
Jake McSteen L 2024 · 4.64 FIP	28	SU	4.64	19.7%	6.4%	4.4%	.348	2.22	18.9%	13.2%	18	-2.42	2.22	286	67
Kyle Hunter L 2017 · 4.50 FIP	28	SU	4.50	14.0%	6.1%	3.3%	.335	—	—	—	—	—	4.32	188	66
Colton Johnson L 2024 · 3.92 FIP	26	SU	3.92	20.8%	11.0%	2.1%	.309	4.53	12.2%	-0.4%	48	+0.61	3.92	106	65
Everett Teaford L 2012 · 5.47 FIP	28	SW	5.47	13.3%	8.0%	4.5%	.291	4.42	13.9%	6.3%	103	-1.05	4.42	208	65
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	64
Reid Love L 2018 · 3.98 FIP	26	SW	3.98	19.6%	7.2%	3.0%	.373	—	—	—	—	—	3.66	280	64
Miguel Pena L 2019 · 5.08 FIP	28	SW	5.08	16.0%	7.0%	4.4%	.369	—	—	—	—	—	2.98	282	64
Mitchell Tyranski L 2024 · 4.90 FIP	26	SU	4.90	21.0%	12.3%	3.7%	.234	3.46	20.5%	4.0%	57	-1.44	3.46	145	64
Carson Teel L 2022 · 4.26 FIP	26	SU	4.26	17.7%	7.1%	3.2%	.355	—	—	—	—	—	3.43	248	64
Chris Reed L 2016 · 4.67 FIP	26	SW	4.67	16.4%	9.8%	3.1%	.238	—	—	—	—	—	4.67	137	64
Will Lamb L 2017 · 5.78 FIP	26	SU	5.78	20.0%	14.0%	4.7%	.322	—	—	—	—	—	3.64	178	63

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	29	21.3%	10.7%	1.31	4.87
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*