Wil Jensen

P Knoxville Smokies

Age 29 RHP 6'4" / 180 lbs AA peak 0.2 · 2027

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	AASF	34	4	89	2.53	3.85	24.9%	11.0%	—	K 20.2% · BB 12.1% · FIP 4.88
2024	26	MIX2 levels	35	6	89	3.74	2.85	27.8%	8.7%	—	K 22.7% · BB 8.4% · FIP 3.48
2025	27	AACHC	8	0	10	1.74	1.55	31.8%	9.1%	—	K 31.8% · BB 9.1% · FIP 1.56
2026	28	No MLB games played
2027PROJ	29	MLBCHC	1	0	1	4.26	4.26	23.1%	8.8%	0.0
2028PROJ31% MLB	30	MLBCHC	14	0	15	4.37	4.44	22.7%	9.1%	0.0
2029PROJ51% MLB	31	MLBCHC	19	0	20	4.53	4.64	22.4%	9.5%	-0.0

Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsTiago Da Silva (age 30) · Junior Guerra (age 30) · Elian Leyva (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114106vR 98

ERA4.26

FIP4.26

K%23.1%

BB%8.8%

K-BB%14.3%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Contract

Scouting Grades

K†5555

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	23	A MLE	San Jose Giants	23	19	103	426	109	25	12	83%	4.5	18.9%	6.9%	12.0%	3.6%	3.59	4.37	—
2021	23	A RAW	San Jose Giants	23	19	103	426	109	25	12	83%	4.5	25.6%	5.9%	19.7%	2.8%	3.59	3.23	—
2022	24	MIX MLE	2 levels	23	17	93	382	99	29	13	74%	4.0	20.2%	8.6%	11.6%	4.0%	3.50	4.69	—
2022	24	MIX RAW	2 levels	23	17	93	382	99	29	13	74%	4.0	25.9%	7.6%	18.3%	3.4%	3.50	3.73	—
2023	25	AA MLE	Richmond Flying Squirrels	34	4	89	373	93	41	10	12%	2.6	20.2%	12.1%	8.1%	3.6%	2.53	4.88	—
2023	25	AA RAW	Richmond Flying Squirrels	34	4	89	373	93	41	10	12%	2.6	24.9%	11.0%	13.9%	2.7%	2.53	3.85	—
2024	26	MIX MLE	2 levels	35	6	89	381	106	33	7	17%	2.5	22.7%	8.4%	14.3%	2.2%	3.74	3.48	—
2024	26	MIX MLE	2 levels	35	6	89	381	106	33	7	17%	2.5	22.7%	8.4%	14.3%	2.2%	3.74	3.48	—
2024	26	MIX RAW	2 levels	35	6	89	381	106	33	7	17%	2.5	27.8%	8.7%	19.2%	1.8%	3.74	2.85	—
2025	27	AA MLE	Knoxville Smokies	8	0	10	44	14	4	0	0%	1.3	31.8%	9.1%	22.7%	0.0%	1.74	1.56	—
2025	27	AA MLE	Knoxville Smokies	8	0	10	44	14	4	0	0%	1.3	31.8%	9.1%	22.7%	0.0%	1.74	1.56	—
2025	27	AA RAW	Knoxville Smokies	8	0	10	44	14	4	0	0%	1.3	31.8%	9.1%	22.7%	0.0%	1.74	1.55	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	CHC	1	0	1	4	1	0	0	0%	1.0	23.1%	8.8%	14.3%	2.9%	4.26	4.26	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	CHC	45	0	47	198	45	18	6	0%	1.0	22.7%	9.1%	13.6%	3.2%	4.37	4.44	+0.1
2029	31	MLB MLE	CHC	38	0	40	168	38	16	6	0%	1.0	22.4%	9.5%	12.9%	3.4%	4.53	4.64	-0.0
2028	30	MLB CTX	CHC	14	0	15	63	14	6	2	0%	1.1	22.7%	9.1%	13.6%	3.2%	4.37	4.44	+0.0
2029	31	MLB CTX	CHC	19	0	20	84	19	8	3	0%	1.1	22.4%	9.5%	12.9%	3.4%	4.53	4.64	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		33	0	35	148	33	14	5	0%	1.1	22.5%	9.3%	13.2%	3.3%	4.46	4.18	+0.2
/ 200 IP	—	RAW		190	0	200	844	188	80	29	0%	1.1	22.5%	9.3%	13.2%	3.3%	4.46	4.18	+0.9
Career	—	MLE		123	46	384	1606	334	143	53	37%	3.1	20.8%	8.9%	11.8%	3.3%	3.31	4.28	+0.0
/ 200 IP	—	MLE		64	24	200	837	174	75	27	37%	3.1	20.8%	8.9%	11.8%	3.3%	3.31	4.28	+0.0

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 AAKnoxville Smokies · 10 IPFIP 1.56 → 2.19 (+0.63)K% 31.8% → 25.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.82%	—	×0.810	25.77%
BB% (unintentional) /BF	9.09%	—	×1.100	10.00%
HR / BF /BF	0.00%	÷0.911	×1.200	0.00%

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 82).

Result: FIP 1.56 → 2.19, 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).

2024 AARichmond Flying Squirrels · 84 IPFIP 2.79 → 3.48 (+0.69)K% 28.0% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.05%	—	×0.810	22.72%
BB% (unintentional) /BF	7.65%	—	×1.100	8.41%
HR / BF /BF	1.98%	÷1.062	×1.200	2.24%

Result: FIP 2.79 → 3.48, 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 · 5 IPFIP 3.70 → 3.73 (+0.02)K% 25.0% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.860	21.50%
BB% (unintentional) /BF	21.43%	—	×0.900	19.29%
HR / BF /BF	0.00%	÷1.010	×1.100	0.00%

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 102).

Result: FIP 3.70 → 3.73, 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 · 89 IPFIP 3.86 → 4.88 (+1.02)K% 24.9% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.93%	—	×0.810	20.20%
BB% (unintentional) /BF	10.99%	—	×1.100	12.09%
HR / BF /BF	2.68%	÷0.906	×1.200	3.55%

Result: FIP 3.86 → 4.88, 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 · 63 IPFIP 3.07 → 3.96 (+0.90)K% 29.8% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.84%	—	×0.770	22.98%
BB% (unintentional) /BF	6.20%	—	×1.150	7.13%
HR / BF /BF	3.10%	÷1.120	×1.250	3.46%

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 124).

Result: FIP 3.07 → 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).

2022 AARichmond Flying Squirrels · 29 IPFIP 5.14 → 6.21 (+1.06)K% 17.7% → 14.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.74%	—	×0.810	14.37%
BB% (unintentional) /BF	10.48%	—	×1.100	11.53%
HR / BF /BF	4.03%	÷0.929	×1.200	5.21%

Result: FIP 5.14 → 6.21, 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 ASan Jose Giants · 103 IPFIP 3.23 → 4.37 (+1.14)K% 25.6% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.59%	—	×0.740	18.93%
BB% (unintentional) /BF	5.87%	—	×1.180	6.92%
HR / BF /BF	2.82%	÷1.008	×1.300	3.63%

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 102).

Result: FIP 3.23 → 4.37, 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
Wil Jensen (OGILVIE)	—	—	4.26	23.1%	8.8%	2.9%	—	4.53	22.6%	13.3%	87	+0.27	—	—	—
Tiago Da Silva R 2015 · 3.10 FIP	30	SW	3.10	19.6%	4.5%	2.0%	.278	2.38	21.4%	18.5%	98	-0.72	2.21	287	74
Junior Guerra R 2015 · 3.18 FIP	30	SW	3.18	26.8%	10.3%	1.9%	.269	4.15	20.8%	10.9%	390	+0.97	3.18	646	72
Elian Leyva R 2018 · 3.10 FIP	29	SU	3.10	17.7%	7.3%	1.0%	.308	4.30	17.0%	8.5%	71	+1.20	3.10	158	71
Phil Klein R 2016 · 3.10 FIP	27	SW	3.10	24.5%	6.6%	2.2%	.287	—	—	—	—	—	3.10	197	70
Yoanner Negrin R 2015 · 3.79 FIP	31	SW	3.79	15.1%	7.5%	1.9%	.256	3.29	15.0%	8.5%	270	-0.50	3.15	485	70
Jose Pina R 2015 · 4.90 FIP	29	SW	4.90	16.9%	9.2%	3.8%	.231	3.66	13.6%	6.9%	246	-1.24	3.63	424	70
Ramon Delgado R 2016 · 4.60 FIP	29	SW	4.60	13.8%	5.9%	3.5%	.332	4.31	11.2%	7.2%	74	-0.29	4.31	135	70
Kolton Mahoney R 2019 · 3.56 FIP	27	SW	3.56	19.4%	8.8%	1.8%	.293	—	—	—	—	—	3.56	302	69
Mike Wright Jr. R 2019 · 3.76 FIP	29	SW	3.76	19.9%	7.2%	2.6%	.347	4.19	17.6%	7.3%	169	+0.43	3.76	725	68
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	68
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	68
Edgar Alberto Garcia R 2017 · 4.01 FIP	29	SP-	4.01	17.3%	10.9%	1.8%	.305	—	—	—	—	—	4.01	272	66
Aldo Montes R 2019 · 4.69 FIP	29	SW	4.69	18.2%	10.6%	3.3%	.336	—	—	—	—	—	4.69	210	66
Felipe Arredondo R 2016 · 3.92 FIP	29	SW	3.92	17.2%	6.6%	2.6%	.281	4.71	15.4%	8.2%	139	+0.79	3.92	337	66
Steve Johnson R 2017 · 4.53 FIP	29	SW	4.53	20.3%	8.9%	3.7%	.321	—	—	—	—	—	2.22	206	66
Mayckol Guaipe R 2019 · 4.18 FIP	28	SW	4.18	26.0%	7.6%	4.2%	.432	—	—	—	—	—	1.88	136	65
Austin Pruitt R 2019 · 4.21 FIP	29	SW	4.21	20.5%	5.5%	3.9%	.327	4.13	18.3%	14.4%	95	-0.08	2.94	819	65
Seth Simmons R 2016 · 4.27 FIP	28	SW	4.27	18.1%	8.1%	3.0%	.262	6.20	13.3%	2.4%	54	+1.93	3.07	251	65
Rodolfo Aguirre R 2015 · 4.29 FIP	30	SW	4.29	12.4%	6.9%	2.5%	.288	4.81	11.4%	1.3%	125	+0.52	3.39	212	65
Mitch Neunborn R 2024 · 4.25 FIP	27	SP-	4.25	19.0%	12.0%	2.2%	.285	5.80	16.4%	6.5%	114	+1.55	3.65	248	64

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	0.7	48	22.8%	9.1%	1.21	4.37
Chris Hatcher ('18)	1.3	53	22.9%	8.4%	1.32	4.65
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Ian Krol ('21)	1.0	42	21.2%	8.8%	1.25	4.49
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*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*