Wes Parsons

P Columbus Clippers

Age 34 RHP 6'5" / 206 lbs AAA peak 0.1 · 2027

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2019	26	MIX2 levels	59	0	91	3.84	3.92	20.2%	12.1%	0.7	K 18.5% · BB 12.4% · FIP 4.01
2023	30	MIX3 levels	19	19	89	5.26	4.34	25.8%	12.3%	1.1	K 23.7% · BB 11.4% · FIP 4.58
2024	31	MIX2 levels	16	5	35	4.67	5.23	26.7%	14.3%	-0.3	K 25.2% · BB 15.4% · FIP 5.24
2025	32	No MLB games played
2026	33	No MLB games played
2027PROJ	34	MLBCLE	5	0	5	5.08	4.94	22.3%	13.2%	-0.0
2028PROJ6% MLB	35	MLBCLE	2	0	2	5.14	5.21	21.5%	13.3%	-0.0
2029PROJMLE	36	MLBCLE	—	—	0	5.34	5.51	20.6%	13.6%	—

Last 3 seasons WAR 1.5 · Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff44Control20Command20FB velo50

CompsNelson Figueroa (age 34) · Fernando Rodriguez Jr. (age 34) · Tim Adleman (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127119vR 111

ERA5.08

FIP4.94

K%22.3%

BB%13.2%

K-BB%9.2%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL2020

CMD2020

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)
2015	22	MIX MLE	3 levels	5	4	20	75	16	1	1	80%	3.9	21.3%	1.3%	20.0%	1.3%	2.75	2.20	—
2015	22	MIX RAW	3 levels	5	4	20	75	16	1	1	80%	3.9	21.3%	1.3%	20.0%	1.3%	2.75	2.29	—
2016	23	MIX MLE	3 levels	21	9	67	281	55	20	0	43%	3.2	14.1%	8.6%	5.5%	0.0%	3.51	3.00	—
2016	23	MIX RAW	3 levels	21	9	67	281	55	20	0	43%	3.2	19.6%	7.1%	12.5%	0.0%	3.51	2.35	—
2017	24	MIX MLE	2 levels	30	11	111	471	108	38	5	37%	3.7	18.7%	8.8%	9.9%	1.4%	3.15	3.39	—
2017	24	MIX RAW	2 levels	30	11	111	471	108	38	5	37%	3.7	22.9%	8.1%	14.9%	1.1%	3.15	2.77	—
2018	25	MIX MLE	3 levels	25	21	122	509	107	37	9	84%	4.9	18.4%	7.7%	10.8%	1.9%	2.94	3.56	+2.7
2018	25	MIX RAW	3 levels	25	21	122	509	107	37	9	84%	4.9	21.0%	7.3%	13.8%	1.8%	2.94	3.21	+3.3
2019	26	MIX MLE	2 levels	59	0	91	397	80	48	7	0%	1.5	18.5%	12.4%	6.2%	1.6%	3.84	4.01	+0.6
2019	26	MIX RAW	2 levels	59	0	91	397	80	48	7	0%	1.5	20.2%	12.1%	8.1%	1.8%	3.84	3.92	+0.7
2023	30	MIX MLE	3 levels	19	19	89	399	103	49	13	100%	4.7	23.7%	11.4%	12.3%	3.7%	5.26	4.58	+0.9
2023	30	MIX RAW	3 levels	19	19	89	399	103	49	13	100%	4.7	25.8%	12.3%	13.5%	3.3%	5.26	4.34	+1.1
2024	31	MIX MLE	2 levels	16	5	35	161	43	23	7	31%	2.2	25.2%	15.4%	9.8%	4.2%	4.67	5.24	-0.3
2024	31	MIX MLE	2 levels	16	5	35	161	43	23	7	31%	2.2	25.2%	15.4%	9.8%	4.2%	4.67	5.24	-0.3
2024	31	MIX RAW	2 levels	16	5	35	161	43	23	7	31%	2.2	26.7%	14.3%	12.4%	4.3%	4.67	5.23	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			38	1	53	244	39	34	11	3%	1.4	16.0%	13.9%	2.0%	4.5%	6.84	6.27	-1.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	CLE	5	0	5	21	5	3	1	0%	1.0	22.3%	13.2%	9.2%	3.1%	5.08	4.94	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	CLE	34	0	36	152	33	20	5	0%	1.1	21.5%	13.3%	8.2%	3.4%	5.14	5.21	-0.3
2029	36	MLB MLE	CLE	26	0	27	113	23	15	4	0%	1.0	20.6%	13.6%	7.0%	3.7%	5.34	5.51	-0.3
2028	35	MLB CTX	CLE	2	0	2	8	2	1	0	0%	1.0	21.5%	13.3%	8.2%	3.4%	5.14	5.21	-0.0
2029	36	MLB CTX	CLE	—	—	0	—	—	—	—	—	—	20.6%	13.6%	7.0%	3.7%	5.34	5.51	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		40	1	55	252	41	35	11	2%	1.4	16.2%	13.9%	2.3%	4.5%	6.77	5.95	-0.9
/ 200 IP	—	RAW		146	4	200	924	150	128	40	3%	1.4	16.2%	13.9%	2.3%	4.5%	6.77	5.95	-3.2
Career	—	MLE		175	69	535	2293	446	225	45	39%	3.1	19.4%	9.8%	9.6%	2.0%	3.70	3.78	-1.6
/ 200 IP	—	MLE		65	26	200	857	167	84	17	39%	3.1	19.4%	9.8%	9.6%	2.0%	3.70	3.78	-2.7

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.

2024 AAAColumbus Clippers · 26 IPFIP 5.02 → 5.24 (+0.21)K% 29.3% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.27%	—	×0.860	25.17%
BB% (unintentional) /BF	17.07%	—	×0.900	15.37%
HR / BF /BF	4.07%	÷1.060	×1.100	4.22%

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 112).

Result: FIP 5.02 → 5.24, 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).

2023 AAABuffalo Bisons · 82 IPFIP 4.07 → 4.58 (+0.51)K% 27.5% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.53%	—	×0.860	23.67%
BB% (unintentional) /BF	12.64%	—	×0.900	11.38%
HR / BF /BF	3.09%	÷0.916	×1.100	3.71%

Result: FIP 4.07 → 4.58, 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 AAAGwinnett Stripers · 57 IPFIP 2.54 → 2.87 (+0.33)K% 22.5% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.50%	—	×0.880	19.80%
BB% (unintentional) /BF	8.75%	—	×1.050	9.19%
HR / BF /BF	0.42%	÷0.899	×1.100	0.51%

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 80).

Result: FIP 2.54 → 2.87, 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).

2018 AAAGwinnett Stripers · 88 IPFIP 3.26 → 3.66 (+0.40)K% 20.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.94%	—	×0.880	18.42%
BB% (unintentional) /BF	6.89%	—	×1.050	7.23%
HR / BF /BF	1.93%	÷0.970	×1.100	2.19%

Result: FIP 3.26 → 3.66, 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).

2018 AAMississippi Braves · 29 IPFIP 2.65 → 3.27 (+0.62)K% 22.8% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.76%	—	×0.810	18.44%
BB% (unintentional) /BF	8.13%	—	×1.100	8.94%
HR / BF /BF	0.81%	÷0.897	×1.200	1.09%

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 79).

Result: FIP 2.65 → 3.27, 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).

2017 AAMississippi Braves · 103 IPFIP 2.75 → 3.41 (+0.66)K% 23.3% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.28%	—	×0.810	18.86%
BB% (unintentional) /BF	7.60%	—	×1.100	8.36%
HR / BF /BF	1.19%	÷0.925	×1.200	1.54%

Result: FIP 2.75 → 3.41, 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).

2017 AAAGwinnett Braves · 8 IPFIP 2.93 → 3.21 (+0.28)K% 20.0% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.880	17.60%
BB% (unintentional) /BF	12.00%	—	×1.050	12.60%
HR / BF /BF	0.00%	÷0.972	×1.100	0.00%

Result: FIP 2.93 → 3.21, 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).

2016 A+Carolina Mudcats · 56 IPFIP 2.50 → 3.00 (+0.50)K% 18.3% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.26%	—	×0.770	14.06%
BB% (unintentional) /BF	7.47%	—	×1.150	8.59%
HR / BF /BF	0.00%	÷1.362	×1.250	0.00%

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 172).

Result: FIP 2.50 → 3.00, 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 Parsons (OGILVIE)	—	—	4.94	22.3%	13.2%	3.1%	—	5.34	21.1%	7.7%	63	+0.40	—	—	—
Nelson Figueroa R 2008 · 3.94 FIP	34	SW	3.94	17.1%	11.8%	1.4%	.306	3.96	17.5%	9.9%	192	+0.02	3.71	499	71
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	66
Tim Adleman R 2022 · 5.69 FIP	34	SP-	5.69	17.5%	8.6%	5.4%	.275	—	—	—	—	—	3.63	605	65
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	63
Rudy Gonzalez R 2015 · 4.52 FIP	34	SW	4.52	13.5%	9.6%	2.4%	.347	3.84	14.0%	6.5%	79	-0.68	3.31	119	62
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	62
Marco Antonio Duarte R 2019 · 5.03 FIP	32	SW	5.03	12.2%	9.1%	3.3%	.420	—	—	—	—	—	4.07	203	61
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	60
Tiago Da Silva R 2019 · 3.95 FIP	34	SW	3.95	15.0%	7.2%	2.2%	.365	—	—	—	—	—	2.21	287	59
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	58
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	57
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	56
Austin Adams R 2019 · 5.80 FIP	32	SU	5.80	20.8%	10.6%	5.7%	.280	—	—	—	—	—	3.40	162	55
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	55
Scott McGough R 2024 · 4.56 FIP	34	SU	4.56	18.6%	12.2%	2.7%	.289	3.82	20.3%	13.1%	57	-0.74	3.55	429	53
Pete Walker R 2003 · 5.73 FIP	34	SW	5.73	12.0%	9.1%	4.5%	.267	4.70	14.0%	5.1%	114	-1.03	4.45	327	53
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	52
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	52
Paolo Espino R 2021 · 4.32 FIP	34	SP-	4.32	20.2%	5.1%	4.2%	.277	4.81	16.6%	10.9%	260	+0.49	3.42	933	52
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	52

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	42	19.8%	13.9%	1.44	5.68
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Matt Perisho ('05)	1.4	69	15.2%	12.2%	1.37	6.39
Dave Stevens ('00)	1.3	50	14.6%	11.3%	1.76	6.02
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*
Bill Laxton ('70-'77, -3 WAR*)	1.2	61	26.1%*	14.4%*	1.87*	5.39*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*