Nate Peterson

P Chattanooga Lookouts

Age 27 LHP 5'9" / 180 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	AAMIL	27	15	93	4.08	5.05	23.8%	10.4%	—	K 19.2% · BB 11.4% · FIP 5.51
2025	25	MIX2 levels	31	8	74	4.00	3.76	18.1%	10.4%	—	K 14.3% · BB 11.5% · FIP 4.27
2026	26	MIX2 levels	26	13	88	5.34	4.83	20.1%	13.1%	—	K 17.5% · BB 13.1% · FIP 5.16
2027PROJ	27	MLBCIN	1	0	1	5.61	5.61	15.3%	13.8%	-0.0
2028PROJ38% MLB	28	MLBCIN	17	0	18	5.53	5.57	16.0%	13.5%	-0.2
2029PROJ56% MLB	29	MLBCIN	21	0	22	5.53	5.60	16.3%	13.4%	-0.3

Next 3 projected WAR -0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control45Command35

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 98%

CompsJack Snodgrass (age 27) · Justin Marks (age 27) · Enrique Lechuga (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123132vR 140

ERA5.61

FIP5.61

K%15.3%

BB%13.8%

K-BB%1.5%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL4545

CMD3535

K†3040

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)
2023	23	MIX MLE	2 levels	19	12	74	317	78	31	7	63%	3.9	18.4%	11.4%	7.0%	2.7%	3.75	4.46	—
2023	23	MIX RAW	2 levels	19	12	74	317	78	31	7	63%	3.9	24.6%	9.8%	14.8%	2.2%	3.75	3.48	—
2024	24	AA MLE	Biloxi Shuckers	27	15	93	404	96	42	19	56%	3.4	19.2%	11.4%	7.8%	4.7%	4.08	5.51	—
2024	24	AA MLE	Biloxi Shuckers	27	15	93	404	96	42	19	56%	3.4	19.2%	11.4%	7.8%	4.7%	4.08	5.51	—
2024	24	AA RAW	Biloxi Shuckers	27	15	93	404	96	42	19	56%	3.4	23.8%	10.4%	13.4%	4.7%	4.08	5.05	—
2025	25	MIX MLE	2 levels	31	8	74	326	59	34	5	26%	2.4	14.3%	11.5%	2.8%	1.7%	4.00	4.27	—
2025	25	MIX MLE	2 levels	31	8	74	326	59	34	5	26%	2.4	14.3%	11.5%	2.8%	1.7%	4.00	4.27	—
2025	25	MIX RAW	2 levels	31	8	74	326	59	34	5	26%	2.4	18.1%	10.4%	7.7%	1.5%	4.00	3.76	—
2026	26	MIX MLE	2 levels	26	13	88	398	80	52	12	50%	3.4	17.5%	13.1%	4.4%	3.4%	5.34	5.16	—
2026	26	MIX MLE	2 levels	26	13	88	398	80	52	12	50%	3.4	17.5%	13.1%	4.4%	3.4%	5.34	5.16	—
2026	26	MIX RAW	2 levels	26	13	88	398	80	52	12	50%	3.4	20.1%	13.1%	7.0%	3.0%	5.34	4.83	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	CIN	1	0	1	4	1	1	0	0%	1.0	15.3%	13.8%	1.5%	3.0%	5.61	5.61	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	CIN	47	0	49	207	33	28	6	0%	1.0	16.0%	13.5%	2.4%	3.1%	5.53	5.57	-0.5
2029	29	MLB MLE	CIN	38	0	40	170	28	23	6	0%	1.1	16.3%	13.4%	2.9%	3.3%	5.53	5.60	-0.5
2028	28	MLB CTX	CIN	17	0	18	76	12	10	2	0%	1.1	16.0%	13.5%	2.4%	3.1%	5.53	5.57	-0.2
2029	29	MLB CTX	CIN	21	0	22	93	15	12	3	0%	1.0	16.3%	13.4%	2.9%	3.3%	5.53	5.60	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		39	0	41	172	28	23	6	0%	1.0	16.1%	13.4%	2.7%	3.2%	5.53	5.21	-0.3
/ 200 IP	—	RAW		190	0	200	844	137	113	29	0%	1.1	16.1%	13.4%	2.7%	3.2%	5.53	5.21	-1.5
Career	—	MLE		103	48	329	1445	253	172	47	47%	3.2	17.5%	11.9%	5.6%	3.2%	4.32	4.90	-1.0
/ 200 IP	—	MLE		63	29	200	878	154	105	28	47%	3.2	17.5%	11.9%	5.6%	3.2%	4.32	4.90	-2.3

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.

2026 AAChattanooga Lookouts · 80 IPFIP 4.35 → 5.16 (+0.81)K% 21.6% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.59%	—	×0.810	17.49%
BB% (unintentional) /BF	11.93%	—	×1.100	13.12%
HR / BF /BF	2.84%	÷1.000	×1.200	3.41%

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 100).

Result: FIP 4.35 → 5.16, 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).

2026 AAALouisville Bats · 8 IPFIP 7.51 → 7.57 (+0.07)K% 8.7% → 7.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	8.70%	—	×0.860	7.48%
BB% (unintentional) /BF	21.74%	—	×0.900	19.57%
HR / BF /BF	4.35%	÷1.000	×1.100	4.78%

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 7.51 → 7.57, 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 AABiloxi Shuckers · 69 IPFIP 3.83 → 4.27 (+0.44)K% 17.7% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.70%	—	×0.810	14.34%
BB% (unintentional) /BF	10.49%	—	×1.100	11.54%
HR / BF /BF	1.64%	÷1.170	×1.200	1.68%

Result: FIP 3.83 → 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 AAANashville Sounds · 6 IPFIP 2.30 → 2.46 (+0.16)K% 23.8% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.860	20.48%
BB% (unintentional) /BF	9.52%	—	×0.900	8.57%
HR / BF /BF	0.00%	÷1.111	×1.100	0.00%

Result: FIP 2.30 → 2.46, 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 AABiloxi Shuckers · 93 IPFIP 4.99 → 5.51 (+0.52)K% 23.8% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.76%	—	×0.810	19.25%
BB% (unintentional) /BF	10.40%	—	×1.100	11.44%
HR / BF /BF	4.70%	÷1.198	×1.200	4.71%

Result: FIP 4.99 → 5.51, 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).

2023 ACarolina Mudcats · 43 IPFIP 2.10 → 3.06 (+0.96)K% 30.4% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.39%	—	×0.740	22.49%
BB% (unintentional) /BF	9.94%	—	×1.180	11.73%
HR / BF /BF	0.55%	÷1.072	×1.300	0.67%

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 114).

Result: FIP 2.10 → 3.06, 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+Wisconsin Timber Rattlers · 31 IPFIP 5.30 → 6.32 (+1.02)K% 16.9% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.91%	—	×0.770	13.02%
BB% (unintentional) /BF	9.56%	—	×1.150	10.99%
HR / BF /BF	4.41%	÷1.033	×1.250	5.34%

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 107).

Result: FIP 5.30 → 6.32, 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
Nate Peterson (OGILVIE)	—	—	5.61	15.3%	13.8%	3.0%	—	5.58	16.1%	2.6%	89	-0.03	—	—	—
Jack Snodgrass L 2015 · 4.66 FIP	27	SP-	4.66	12.6%	10.7%	2.3%	.278	5.01	15.7%	5.6%	45	+0.35	4.66	118	77
Justin Marks L 2015 · 4.60 FIP	27	SP-	4.60	15.4%	10.5%	2.7%	.323	3.88	19.0%	9.1%	216	-0.72	3.83	324	75
Enrique Lechuga L 2015 · 4.70 FIP	29	SP-	4.70	10.0%	10.5%	2.0%	.354	3.78	10.5%	4.4%	59	-0.92	3.78	137	75
Aaron Rozek L 2023 · 4.87 FIP	27	SP-	4.87	17.4%	8.8%	3.9%	.311	4.34	16.7%	9.5%	356	-0.53	3.68	579	75
Mark Manfredi Sr. L 2024 · 4.60 FIP	24	SW	4.60	22.0%	14.9%	2.7%	.289	3.22	25.4%	11.6%	128	-1.38	2.91	204	75
Matt Whitehouse L 2018 · 4.55 FIP	27	SW	4.55	17.0%	12.8%	2.3%	.308	4.07	20.1%	9.2%	81	-0.48	3.37	353	74
Dan Meyer L 2008 · 5.66 FIP	27	SW	5.66	15.2%	10.6%	4.5%	.315	3.73	23.1%	15.2%	58	-1.93	3.73	112	74
Brian Holmes L 2017 · 5.91 FIP	26	SW	5.91	15.5%	11.7%	4.8%	.354	—	—	—	—	—	3.60	205	73
Chris Reed L 2016 · 4.67 FIP	26	SW	4.67	16.4%	9.8%	3.1%	.238	—	—	—	—	—	4.67	137	72
Houston Harding L 2024 · 4.54 FIP	26	SP-	4.54	16.5%	11.2%	2.6%	.268	5.19	12.0%	0.5%	61	+0.65	3.41	239	72
Matt Walker L 2023 · 4.73 FIP	25	SP-	4.73	12.7%	10.0%	2.6%	.333	—	—	—	—	—	4.21	156	71
Jordan Carr L 2024 · 4.42 FIP	27	SW	4.42	13.1%	8.8%	2.4%	.295	6.61	11.8%	-1.7%	47	+2.19	3.49	269	69
Scott DeCecco L 2015 · 4.55 FIP	24	SP-	4.55	14.5%	11.5%	2.2%	.331	—	—	—	—	—	4.55	125	69
Luis Ysla L 2019 · 5.78 FIP	27	SP-	5.78	18.0%	14.4%	4.3%	.337	—	—	—	—	—	3.75	378	69
Luis Leroy Cruz L 2015 · 5.03 FIP	24	SP-	5.03	16.0%	10.1%	3.7%	.289	—	—	—	—	—	5.03	116	68
Eric Jokisch L 2016 · 4.64 FIP	27	SW	4.64	12.4%	9.6%	2.5%	.330	3.93	15.2%	7.6%	283	-0.71	3.78	427	68
Mitch Stallings L 2021 · 5.48 FIP	26	SW	5.48	16.8%	11.5%	4.3%	.328	—	—	—	—	—	2.18	108	68
Danny Wirchansky L 2024 · 4.47 FIP	27	SP-	4.47	16.2%	7.4%	3.3%	.246	5.88	13.0%	0.2%	68	+1.41	4.47	179	67
Matt Stalcup L 2016 · 6.20 FIP	26	SW	6.20	11.5%	12.7%	4.5%	.337	—	—	—	—	—	3.62	145	67
Cam Vieaux L 2021 · 5.10 FIP	27	SP-	5.10	18.0%	11.8%	3.7%	.288	4.45	20.0%	10.8%	122	-0.65	4.20	620	66

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	0.8	53	15.7%	13.6%	1.21	5.57
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Mike Mohler ('01)	2.1	60	15.0%	12.4%	0.97	4.99
Matt Anderson ('05)	1.3	51	19.3%	13.5%	1.05	5.19
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*