Carson Whisenhunt

P Sacramento River Cats

Age 26 LHP 6'3" / 225 lbs AAA peak 0.5 · 2028 ILInjured 60-Day (D60)

Overview

AAASPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX2 levels	27	27	110	5.17	3.72	28.4%	11.3%	—	K 24.4% · BB 10.0% · FIP 4.07
2025	24	MIX2 levels	26	26	131	4.53	4.37	20.0%	8.5%	1.6	K 17.6% · BB 7.8% · FIP 4.75
2026	25	MIX2 levels	25	24	117	4.85	3.60	22.1%	11.0%	2.5	K 19.7% · BB 10.3% · FIP 3.77
2027PROJ	26	MLBSF	4	4	21	4.83	4.75	19.5%	9.7%	0.2
2028PROJ85% MLB	27	MLBSF	9	9	54	4.75	4.74	19.7%	9.5%	0.4
2029PROJ89% MLB	28	MLBSF	10	10	58	4.75	4.78	19.8%	9.6%	0.4

Last 3 seasons WAR 4.1 · Next 3 projected WAR 1.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo26

K%10

xwOBA vs10

Form8.05 ERA (proj 4.83) · K 13.4% (proj 19.5%) · BB 13.4% (proj 9.7%) ▼▼ last 90d · 19 IP through Oct 27

CompsJames Paxton (age 26) · Hunter Barco (age 23) · David Purcey (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114122vR 130

ERA4.83

FIP4.75

K%19.5%

BB%9.7%

K-BB%9.8%

Proj IP27

Value2027 · WAR

Runs saved vs league avg · 27 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2692.8

Whiff%

p6928.2%

p1015.9%

xwOBA vs

p100.368

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)
2022	21	MIX MLE	2 levels	4	3	8	30	14	1	0	75%	1.9	46.7%	3.3%	43.3%	0.0%	0.00	-0.42	—
2022	21	MIX RAW	2 levels	4	3	8	30	14	1	0	75%	1.9	46.7%	3.3%	43.3%	0.0%	0.00	-0.16	—
2023	22	MIX MLE	3 levels	16	16	59	235	83	23	3	100%	3.7	27.4%	11.1%	16.3%	1.7%	2.45	3.11	—
2023	22	MIX RAW	3 levels	16	16	59	235	83	23	3	100%	3.7	35.3%	9.8%	25.5%	1.3%	2.45	2.11	—
2024	23	MIX MLE	2 levels	27	27	110	496	141	56	14	100%	4.1	24.4%	10.0%	14.4%	3.2%	5.17	4.07	—
2024	23	MIX MLE	2 levels	27	27	110	496	141	56	14	100%	4.1	24.4%	10.0%	14.4%	3.2%	5.17	4.07	—
2024	23	MIX RAW	2 levels	27	27	110	496	141	56	14	100%	4.1	28.4%	11.3%	17.1%	2.8%	5.17	3.72	—
2025	24	MIX MLE	2 levels	26	26	131	556	111	47	19	100%	5.0	17.6%	7.8%	9.7%	3.9%	4.53	4.75	+1.0
2025	24	MIX MLE	2 levels	26	26	131	556	111	47	19	100%	5.0	17.6%	7.8%	9.7%	3.9%	4.53	4.75	+1.0
2025	24	MIX RAW	2 levels	26	26	131	556	111	47	19	100%	5.0	20.0%	8.5%	11.5%	3.4%	4.53	4.37	+1.6
2026	25	MIX MLE	2 levels	25	24	117	526	116	58	9	96%	4.7	19.7%	10.3%	9.3%	1.9%	4.85	3.77	+2.3
2026	25	MIX MLE	2 levels	25	24	117	526	116	58	9	96%	4.7	19.7%	10.3%	9.3%	1.9%	4.85	3.77	+2.3
2026	25	MIX RAW	2 levels	25	24	117	526	116	58	9	96%	4.7	22.1%	11.0%	11.0%	1.7%	4.85	3.60	+2.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			13	13	58	266	42	33	11	100%	4.5	15.8%	12.4%	3.4%	4.1%	5.90	5.82	-0.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	SF	4	4	21	89	17	9	3	100%	5.2	19.5%	9.7%	9.8%	3.1%	4.83	4.75	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	SF	11	11	64	269	53	26	8	100%	5.8	19.7%	9.5%	10.2%	3.1%	4.75	4.74	+0.5
2029	28	MLB MLE	SF	11	11	65	275	54	26	9	100%	5.9	19.8%	9.6%	10.2%	3.2%	4.75	4.78	+0.5
2030	29	MLB MLE	SF	10	10	58	243	47	24	8	100%	5.8	19.3%	9.7%	9.6%	3.3%	4.84	4.92	+0.3
2031	30	MLB MLE	SF	8	8	47	197	37	20	7	100%	5.8	18.6%	9.9%	8.7%	3.5%	4.99	5.11	+0.2
2028	27	MLB CTX	SF	9	9	54	228	45	22	7	100%	6.0	19.7%	9.5%	10.2%	3.1%	4.75	4.74	+0.4
2029	28	MLB CTX	SF	10	10	58	245	48	23	8	100%	5.8	19.8%	9.6%	10.2%	3.2%	4.75	4.78	+0.4
2030	29	MLB CTX	SF	9	9	52	220	42	21	7	100%	5.8	19.3%	9.7%	9.6%	3.3%	4.84	4.92	+0.3
2031	30	MLB CTX	SF	7	7	43	182	34	18	6	100%	6.1	18.6%	9.9%	8.7%	3.5%	4.99	5.11	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		48	48	265	1142	212	118	40	100%	5.5	18.6%	10.3%	8.3%	3.5%	5.06	4.75	+2.0
/ 200 IP	—	RAW		36	36	200	860	160	89	30	100%	5.6	18.6%	10.3%	8.3%	3.5%	5.06	4.75	+1.5
Career	—	MLE		98	96	424	1843	400	175	51	98%	4.3	21.7%	9.5%	12.3%	2.8%	4.42	3.99	+1.1
/ 200 IP	—	MLE		46	45	200	869	189	82	24	98%	4.3	21.7%	9.5%	12.3%	2.8%	4.42	3.99	+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.

2026 AAASacramento River Cats · 82 IPFIP 2.90 → 3.13 (+0.23)K% 24.9% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.86%	—	×0.860	21.38%
BB% (unintentional) /BF	10.22%	—	×0.900	9.20%
HR / BF /BF	1.10%	÷1.000	×1.100	1.22%

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 2.90 → 3.13, 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 · 108 IPFIP 3.88 → 4.30 (+0.42)K% 20.9% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.93%	—	×0.860	18.00%
BB% (unintentional) /BF	7.71%	—	×0.900	6.94%
HR / BF /BF	2.86%	÷0.938	×1.100	3.36%

Result: FIP 3.88 → 4.30, 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 AAASacramento River Cats · 105 IPFIP 3.73 → 4.07 (+0.34)K% 28.4% → 24.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.36%	—	×0.860	24.39%
BB% (unintentional) /BF	11.13%	—	×0.900	10.02%
HR / BF /BF	2.94%	÷1.010	×1.100	3.20%

Result: FIP 3.73 → 4.07, 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 ASan Jose Giants · 5 IPFIP 2.47 → 3.47 (+1.00)K% 30.0% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.740	22.20%
BB% (unintentional) /BF	15.00%	—	×1.180	17.70%
HR / BF /BF	0.00%	÷0.959	×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 92).

Result: FIP 2.47 → 3.47, 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+Eugene Emeralds · 25 IPFIP 1.53 → 2.53 (+1.00)K% 38.3% → 29.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.30%	—	×0.770	29.49%
BB% (unintentional) /BF	8.51%	—	×1.150	9.79%
HR / BF /BF	1.06%	÷1.076	×1.250	1.24%

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 115).

Result: FIP 1.53 → 2.53, 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 · 20 IPFIP 2.70 → 3.59 (+0.89)K% 32.1% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.14%	—	×0.810	26.04%
BB% (unintentional) /BF	13.10%	—	×1.100	14.40%
HR / BF /BF	1.19%	÷0.906	×1.200	1.58%

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 81).

Result: FIP 2.70 → 3.59, 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 ASan Jose Giants · 14 IPFIP 1.99 → 3.36 (+1.37)K% 35.1% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.09%	—	×0.740	25.96%
BB% (unintentional) /BF	7.02%	—	×1.180	8.28%
HR / BF /BF	1.75%	÷0.890	×1.300	2.56%

Result: FIP 1.99 → 3.36, 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 ASan Jose Giants · 5 IPFIP 0.78 → 1.66 (+0.88)K% 35.0% → 25.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.00%	—	×0.740	25.90%
BB% (unintentional) /BF	5.00%	—	×1.180	5.90%
HR / BF /BF	0.00%	÷1.063	×1.300	0.00%

Result: FIP 0.78 → 1.66, 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).

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
Carson Whisenhunt (OGILVIE)	—	—	—	—	—	3.1%	—	4.81	19.6%	10.0%	186	+0.06	—	—	—
James Paxton L 2015 · 4.22 FIP	26	SP	4.22	18.9%	9.4%	2.8%	.288	2.95	27.7%	21.7%	468	-1.27	2.46	1,022	79
Hunter Barco L 2024 · 3.61 FIP	23	SP	3.61	23.4%	10.0%	2.2%	.275	3.72	21.1%	10.0%	195	+0.11	3.29	257	75
David Purcey L 2008 · 4.39 FIP	26	SP	4.39	20.1%	10.0%	3.1%	.301	4.39	17.9%	5.0%	116	-0.00	3.60	206	73
Brad Mills L 2011 · 5.37 FIP	26	SP-	5.37	19.8%	12.1%	4.4%	.328	5.61	18.8%	7.9%	21	+0.24	4.22	243	72
Miguel Cienfuegos L 2023 · 5.12 FIP	26	SP	5.12	13.6%	10.5%	3.4%	.257	4.54	14.3%	5.8%	242	-0.58	2.95	313	69
Christian Friedrich L 2012 · 4.26 FIP	25	SP	4.26	19.6%	8.0%	3.3%	.340	3.59	19.0%	10.6%	83	-0.67	3.39	297	68
Chris Rusin L 2013 · 4.58 FIP	26	SP	4.58	12.8%	7.4%	2.9%	.267	3.89	15.5%	9.3%	263	-0.69	2.89	596	66
Hung-Chih Kuo L 2007 · 3.91 FIP	26	SP-	3.91	19.3%	10.0%	2.1%	.333	2.04	29.8%	22.7%	170	-1.87	1.63	287	65
Matt Portland L 2018 · 4.64 FIP	24	SP-	4.64	17.4%	11.0%	2.9%	.364	—	—	—	—	—	3.61	143	65
Jordan Fowler L 2023 · 4.08 FIP	24	SP	4.08	13.2%	7.9%	2.0%	.318	—	—	—	—	—	4.08	124	65
Miguel Pena L 2017 · 3.97 FIP	26	SP	3.97	16.8%	8.2%	2.3%	.288	5.08	16.0%	9.0%	68	+1.11	2.98	282	65
Jonathan Dziedzic L 2017 · 5.29 FIP	26	SP	5.29	17.3%	8.2%	4.8%	.280	4.68	13.5%	4.4%	198	-0.61	3.88	522	65
Hayden Mullins L 2024 · 4.39 FIP	23	SP-	4.39	23.4%	12.4%	3.1%	.288	3.69	25.5%	11.8%	194	-0.70	3.54	283	64
Scott Downs L 2000 · 4.63 FIP	24	SP	4.63	14.3%	8.8%	2.9%	.333	—	—	—	—	—	2.68	748	64
Christian MacLeod L 2024 · 4.77 FIP	24	SP	4.77	21.5%	13.6%	3.2%	.269	4.50	18.0%	3.0%	128	-0.27	3.88	280	64
Erik Rivera L 2024 · 5.71 FIP	23	SP-	5.71	19.0%	14.6%	4.3%	.255	4.74	23.9%	6.3%	106	-0.97	4.42	141	64
Grant Watson L 2017 · 4.70 FIP	24	SP-	4.70	16.4%	10.3%	3.0%	.344	—	—	—	—	—	2.59	180	64
Taylor Varnell L 2021 · 4.48 FIP	26	SP	4.48	20.1%	10.3%	3.2%	.278	—	—	—	—	—	2.89	248	64
David Huff L 2011 · 4.11 FIP	26	SP	4.11	15.9%	7.0%	2.6%	.290	4.20	17.1%	10.7%	123	+0.09	3.40	540	63
Pedro Hernandez L 2016 · 4.09 FIP	27	SP	4.09	13.1%	8.9%	1.8%	.270	—	—	—	—	—	4.09	124	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	1.6	46	18.7%	10.2%	1.33	5.02
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Will Cunnane ('04)	1.4	46	18.9%	10.4%	1.25	5.26
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*