Wes Benjamin

P El Paso Chihuahuas

Age 34 LHP 6'2" / 210 lbs AAA

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2021	28	MIX2 levels	28	12	69	8.44	5.41	17.5%	12.0%	-0.7	K 16.0% · BB 12.4% · FIP 5.28
2022	29	AAACWS	7	7	31	3.82	4.73	24.6%	9.2%	—	K 21.7% · BB 9.7% · FIP 4.46
2025	32	AAASD	28	22	108	6.42	4.76	17.6%	9.8%	—	K 15.1% · BB 8.8% · FIP 4.91
2026	33	No MLB games played
2027PROJ	34	MLBSD	1	1	7	5.34	5.31	14.1%	9.7%	0.0
2028PROJ6% MLB	35	MLBSD	1	1	2	5.42	5.54	14.1%	10.2%	-0.0
2029PROJMLE	36	MLBSD	—	—	0	5.62	5.82	13.7%	10.7%	—

Last 3 seasons WAR -0.7 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2021

K%14

FB Velo10

xwOBA vs10

CompsJuan Antonio Pena (age 37) · Chris Michalak (age 35) · Tomas Solis (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 118126vR 134

ERA5.34

FIP5.31

K%14.1%

BB%9.7%

K-BB%4.4%

Proj IP67

Value2027 · WAR

Runs saved vs league avg · 67 IP

Grades · Statcast · Contract

Scouting Grades

STUF4040

CTRL5050

CMD4040

K†3030

Statcast Percentiles

FB Velo

p1091.3

Whiff%

p1921.0%

p1417.0%

xwOBA vs

p100.365

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)
2015	22	ROK MLE	AZL Rangers	1	1	1	5	2	1	0	100%	1.0	40.0%	20.0%	20.0%	0.0%	0.00	2.26	—
2015	22	ROK RAW	AZL Rangers	1	1	1	5	2	1	0	100%	1.0	40.0%	20.0%	20.0%	0.0%	0.00	2.10	—
2016	23	A MLE	Hickory Crawdads	21	18	102	423	101	22	13	86%	4.9	17.7%	6.1%	11.5%	3.6%	3.79	4.38	—
2016	23	A RAW	Hickory Crawdads	21	18	102	423	101	22	13	86%	4.9	23.9%	5.2%	18.7%	3.1%	3.79	3.42	—
2017	24	A+ MLE	Down East Wood Ducks	22	22	119	506	101	34	8	100%	5.4	15.4%	7.7%	7.6%	2.0%	3.94	3.87	—
2017	24	A+ RAW	Down East Wood Ducks	22	22	119	506	101	34	8	100%	5.4	20.0%	6.7%	13.2%	1.6%	3.94	3.13	—
2018	25	MIX MLE	2 levels	18	18	87	353	81	24	9	100%	4.8	17.7%	7.7%	10.0%	3.0%	3.32	4.23	—
2018	25	MIX RAW	2 levels	18	18	87	353	81	24	9	100%	4.8	22.9%	6.8%	16.1%	2.5%	3.32	3.41	—
2019	26	AAA MLE	Nashville Sounds	27	25	135	605	114	53	24	93%	5.0	16.6%	9.2%	7.4%	4.4%	5.52	5.27	—
2019	26	AAA RAW	Nashville Sounds	27	25	135	605	114	53	24	93%	5.0	18.8%	8.8%	10.1%	4.0%	5.52	4.90	—
2020	27	MLB MLE	Texas Rangers	8	1	22	98	21	7	4	12%	2.8	21.4%	7.1%	14.3%	3.8%	4.84	4.28	+0.1
2020	27	MLB RAW	Texas Rangers	8	1	22	98	21	7	4	12%	2.8	21.4%	7.1%	14.3%	4.1%	4.84	4.49	+0.0
2021	28	MIX MLE	2 levels	28	12	69	349	61	42	12	43%	2.5	16.0%	12.4%	3.6%	3.6%	8.44	5.28	-0.6
2021	28	MIX RAW	2 levels	28	12	69	349	61	42	12	43%	2.5	17.5%	12.0%	5.4%	3.4%	8.44	5.41	-0.7
2022	29	AAA MLE	Charlotte Knights	7	7	31	130	32	12	6	100%	4.4	21.7%	9.7%	12.0%	3.6%	3.82	4.46	—
2022	29	AAA RAW	Charlotte Knights	7	7	31	130	32	12	6	100%	4.4	24.6%	9.2%	15.4%	4.6%	3.82	4.73	—
2025	32	AAA MLE	El Paso Chihuahuas	28	22	108	500	88	49	16	79%	3.9	15.1%	8.8%	6.3%	3.6%	6.42	4.91	—
2025	32	AAA MLE	El Paso Chihuahuas	28	22	108	500	88	49	16	79%	3.9	15.1%	8.8%	6.3%	3.6%	6.42	4.91	—
2025	32	AAA RAW	El Paso Chihuahuas	28	22	108	500	88	49	16	79%	3.9	17.6%	9.8%	7.8%	3.2%	6.42	4.76	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			21	3	45	210	40	24	10	14%	2.1	19.0%	11.4%	7.6%	4.8%	6.80	5.81	-0.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	SD	1	1	7	30	4	3	1	100%	7.0	14.1%	9.7%	4.4%	3.3%	5.34	5.31	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	SD	7	7	43	183	26	19	7	100%	6.2	14.1%	10.2%	3.9%	3.6%	5.42	5.54	-0.1
2029	36	MLB MLE	SD	5	5	32	135	19	14	5	100%	6.4	13.7%	10.7%	3.0%	3.9%	5.62	5.82	-0.1
2028	35	MLB CTX	SD	1	1	2	8	1	1	0	100%	2.0	14.1%	10.2%	3.9%	3.6%	5.42	5.54	-0.0
2029	36	MLB CTX	SD	—	—	0	—	—	—	—	—	—	13.7%	10.7%	3.0%	3.9%	5.62	5.82	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		21	3	47	220	41	25	10	14%	2.3	18.8%	11.4%	7.4%	4.7%	6.73	5.54	-0.5
/ 200 IP	—	RAW		90	14	200	929	173	106	42	16%	2.2	18.8%	11.4%	7.4%	4.7%	6.73	5.54	-2.3
Career	—	MLE		160	126	674	2969	498	256	101	79%	4.2	16.8%	8.6%	8.2%	3.4%	5.03	4.65	-0.4
/ 200 IP	—	MLE		47	37	200	881	148	76	30	79%	4.2	16.8%	8.6%	8.2%	3.4%	5.03	4.65	-0.7

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 AAAEl Paso Chihuahuas · 108 IPFIP 4.61 → 4.91 (+0.30)K% 17.6% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.60%	—	×0.860	15.14%
BB% (unintentional) /BF	9.80%	—	×0.900	8.82%
HR / BF /BF	3.20%	÷0.981	×1.100	3.59%

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 96).

Result: FIP 4.61 → 4.91, 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 AAACharlotte Knights · 31 IPFIP 4.72 → 4.46 (−0.26)K% 24.6% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.62%	—	×0.880	21.66%
BB% (unintentional) /BF	9.23%	—	×1.050	9.69%
HR / BF /BF	4.62%	÷1.421	×1.100	3.57%

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 184).

Result: FIP 4.72 → 4.46, 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).

2021 AAARound Rock Express · 47 IPFIP 4.33 → 4.78 (+0.45)K% 17.7% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.72%	—	×0.880	15.59%
BB% (unintentional) /BF	10.55%	—	×1.050	11.08%
HR / BF /BF	2.53%	÷0.958	×1.100	2.91%

Result: FIP 4.33 → 4.78, 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 AAANashville Sounds · 135 IPFIP 4.80 → 5.27 (+0.47)K% 18.8% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.84%	—	×0.880	16.58%
BB% (unintentional) /BF	8.76%	—	×1.050	9.20%
HR / BF /BF	3.97%	÷0.998	×1.100	4.37%

Result: FIP 4.80 → 5.27, 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).

2018 AAFrisco RoughRiders · 80 IPFIP 3.64 → 4.23 (+0.59)K% 21.8% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.82%	—	×0.810	17.67%
BB% (unintentional) /BF	6.97%	—	×1.100	7.67%
HR / BF /BF	2.73%	÷1.088	×1.200	3.01%

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 118).

Result: FIP 3.64 → 4.23, 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).

2018 ROKAZL Rangers · 7 IPFIP 0.35 → 1.54 (+1.20)K% 39.1% → 26.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.13%	—	×0.680	26.61%
BB% (unintentional) /BF	4.35%	—	×1.250	5.43%
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 0.35 → 1.54, 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).

2017 A+Down East Wood Ducks · 119 IPFIP 3.13 → 3.87 (+0.74)K% 20.0% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.96%	—	×0.770	15.37%
BB% (unintentional) /BF	6.72%	—	×1.150	7.73%
HR / BF /BF	1.58%	÷0.995	×1.250	1.99%

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 99).

Result: FIP 3.13 → 3.87, 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).

2016 AHickory Crawdads · 102 IPFIP 3.43 → 4.38 (+0.95)K% 23.9% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.88%	—	×0.740	17.67%
BB% (unintentional) /BF	5.20%	—	×1.180	6.14%
HR / BF /BF	3.07%	÷1.100	×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 120).

Result: FIP 3.43 → 4.38, 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
Wes Benjamin (OGILVIE)	—	—	5.31	14.1%	9.7%	3.3%	—	5.66	13.9%	3.5%	75	+0.35	—	—	—
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	79
Chris Michalak L 2006 · 5.71 FIP	35	SP-	5.71	6.2%	8.6%	3.7%	.273	—	—	—	—	—	4.71	186	73
Tomas Solis L 2017 · 5.48 FIP	34	SP	5.48	11.3%	7.9%	4.2%	.322	6.44	8.9%	1.4%	57	+0.96	4.20	327	71
Chris Narveson L 2016 · 4.59 FIP	34	SP-	4.59	16.2%	8.5%	3.2%	.253	4.59	12.2%	1.8%	103	+0.00	4.00	625	71
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	69
Arturo Lopez L 2017 · 4.34 FIP	34	SP	4.34	10.3%	5.4%	2.6%	.342	5.46	12.2%	5.4%	117	+1.12	4.34	445	68
Paul Oseguera L 2016 · 5.62 FIP	32	SP	5.62	5.6%	12.5%	2.6%	.320	—	—	—	—	—	3.83	162	64
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	63
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	62
Jorge Castillo L 2016 · 4.94 FIP	34	SP	4.94	13.0%	4.6%	4.3%	.246	4.93	16.8%	9.2%	179	-0.01	4.50	408	53
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	46
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	38
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	37
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	36
Walter Silva R 2009 · 5.72 FIP	32	SP	5.72	9.1%	12.4%	3.3%	.330	—	—	—	—	—	3.67	453	36
Juan Delgadillo R 2017 · 4.47 FIP	34	SP	4.47	10.9%	6.2%	2.7%	.311	—	—	—	—	—	4.47	143	36
Guillermo Moscoso R 2018 · 5.07 FIP	34	SP-	5.07	18.2%	8.4%	4.5%	.318	4.35	12.6%	5.9%	104	-0.72	3.56	486	35
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	35
Jarrett Grube R 2016 · 4.74 FIP	34	SP-	4.74	18.9%	7.2%	4.2%	.280	4.41	15.8%	7.7%	134	-0.33	3.75	393	34
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	34

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	0.9	37	15.3%	10.4%	1.48	5.76
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Dave Stevens ('00)	1.3	50	14.6%	11.3%	1.76	6.02
Mike Lincoln ('10)	1.9	54	14.1%	8.9%	1.32	5.33
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Dennis Powell ('85-'93, -2 WAR*)	1.7	49	17.6%*	10.1%*	1.18*	5.31*
Steve Shields ('85-'89, -3 WAR*)	1.1	55	17.0%*	9.0%*	1.61*	5.49*