Randy Wynne

P Louisville Bats

Age 34 RHP 6'1" / 180 lbs AAA peak 0.1 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	30	MIX2 levels	30	13	76	6.48	7.03	14.1%	5.7%	-2.1	K 12.5% · BB 5.1% · FIP 7.11
2024	31	AAACIN	27	18	93	4.16	5.68	15.8%	6.6%	—	K 13.6% · BB 6.0% · FIP 5.75
2025	32	MIX2 levels	17	13	63	5.43	5.81	13.0%	4.1%	-0.3	K 10.7% · BB 3.5% · FIP 6.55
2026	33	No MLB games played
2027PROJ	34	MLBCIN	1	1	6	5.48	5.48	10.0%	5.1%	-0.0
2028PROJ6% MLB	35	MLBCIN	1	1	2	5.54	5.67	10.8%	6.1%	-0.0
2029PROJMLE	36	MLBCIN	—	—	0	5.72	5.91	11.0%	6.9%	—

Last 3 seasons WAR -2.4 · 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

Stuff30Control70Command40

CompsSergio Valenzuela (age 32) · Juan Omar Espinoza (age 32) · Rolando Valdez (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 137129vR 121

ERA5.48

FIP5.48

K%10.0%

BB%5.1%

K-BB%4.9%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL7070

CMD4040

K†3030

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)
2019	26	MIX MLE	2 levels	4	1	14	58	15	0	2	25%	3.5	20.7%	0.0%	20.7%	5.5%	4.50	4.35	—
2019	26	MIX RAW	2 levels	4	1	14	58	15	0	2	25%	3.5	25.9%	0.0%	25.9%	3.4%	4.50	2.81	—
2021	28	AA MLE	Chattanooga Lookouts	25	14	89	388	67	11	13	56%	3.6	14.0%	3.1%	10.9%	4.2%	4.94	4.64	—
2021	28	AA RAW	Chattanooga Lookouts	25	14	89	388	67	11	13	56%	3.6	17.3%	2.8%	14.4%	3.4%	4.94	3.86	—
2022	29	AAA MLE	Louisville Bats	26	22	133	578	85	34	28	85%	5.1	12.9%	6.2%	6.8%	4.2%	4.75	5.07	—
2022	29	AAA RAW	Louisville Bats	26	22	133	578	85	34	28	85%	5.1	14.7%	5.9%	8.8%	4.8%	4.75	5.33	—
2023	30	MIX MLE	2 levels	30	13	76	348	49	20	26	43%	2.5	12.5%	5.1%	7.4%	8.1%	6.48	7.11	-2.2
2023	30	MIX RAW	2 levels	30	13	76	348	49	20	26	43%	2.5	14.1%	5.7%	8.3%	7.5%	6.48	7.03	-2.1
2024	31	AAA MLE	Louisville Bats	27	18	93	393	62	26	22	67%	3.4	13.6%	6.0%	7.6%	5.5%	4.16	5.75	—
2024	31	AAA MLE	Louisville Bats	27	18	93	393	62	26	22	67%	3.4	13.6%	6.0%	7.6%	5.5%	4.16	5.75	—
2024	31	AAA RAW	Louisville Bats	27	18	93	393	62	26	22	67%	3.4	15.8%	6.6%	9.2%	5.6%	4.16	5.68	—
2025	32	MIX MLE	2 levels	17	13	63	270	35	11	16	76%	3.7	10.7%	3.5%	7.2%	7.1%	5.43	6.55	-0.8
2025	32	MIX MLE	2 levels	17	13	63	270	35	11	16	76%	3.7	10.7%	3.5%	7.2%	7.1%	5.43	6.55	-0.8
2025	32	MIX RAW	2 levels	17	13	63	270	35	11	16	76%	3.7	13.0%	4.1%	8.9%	5.9%	5.43	5.81	-0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			2	0	5	24	3	2	1	0%	2.7	12.5%	8.3%	4.2%	4.2%	3.37	5.54	-0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	CIN	1	1	6	25	3	1	1	100%	6.0	10.0%	5.1%	4.9%	4.0%	5.48	5.48	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	CIN	7	7	44	188	20	11	8	100%	6.4	10.8%	6.1%	4.7%	4.2%	5.54	5.67	-0.1
2029	36	MLB MLE	CIN	6	6	34	142	16	10	6	100%	5.6	11.0%	6.9%	4.1%	4.5%	5.72	5.91	-0.2
2030	37	MLB MLE	CIN	4	4	26	111	12	9	5	100%	6.6	10.9%	7.7%	3.2%	4.9%	5.97	6.20	-0.2
2028	35	MLB CTX	CIN	1	1	2	8	1	1	0	100%	2.0	10.8%	6.1%	4.7%	4.2%	5.54	5.67	-0.0
2029	36	MLB CTX	CIN	—	—	0	—	—	—	—	—	—	11.0%	6.9%	4.1%	4.5%	5.72	5.91	—
2030	37	MLB CTX	CIN	—	—	0	—	—	—	—	—	—	10.9%	7.7%	3.2%	4.9%	5.97	6.20	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		2	0	8	34	4	3	1	0%	3.9	12.0%	7.7%	4.3%	4.2%	4.06	5.36	-0.1
/ 200 IP	—	RAW		62	10	200	883	103	77	26	17%	3.2	12.0%	7.7%	4.3%	4.2%	4.06	5.36	-1.8
Career	—	MLE		129	81	468	2035	267	98	113	63%	3.6	13.1%	4.8%	8.3%	5.5%	5.03	5.64	-0.6
/ 200 IP	—	MLE		55	35	200	869	114	42	48	63%	3.6	13.1%	4.8%	8.3%	5.5%	5.03	5.64	-1.0

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 AAALouisville Bats · 60 IPFIP 5.75 → 6.55 (+0.80)K% 12.5% → 10.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.45%	—	×0.860	10.71%
BB% (unintentional) /BF	3.89%	—	×0.900	3.50%
HR / BF /BF	5.84%	÷0.901	×1.100	7.12%

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 80).

Result: FIP 5.75 → 6.55, 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 AAALouisville Bats · 93 IPFIP 5.68 → 5.75 (+0.07)K% 15.8% → 13.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.78%	—	×0.860	13.57%
BB% (unintentional) /BF	6.62%	—	×0.900	5.95%
HR / BF /BF	5.60%	÷1.111	×1.100	5.54%

Result: FIP 5.68 → 5.75, 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 AAALouisville Bats · 74 IPFIP 6.82 → 7.11 (+0.29)K% 14.5% → 12.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.54%	—	×0.860	12.50%
BB% (unintentional) /BF	5.64%	—	×0.900	5.07%
HR / BF /BF	7.72%	÷1.054	×1.100	8.06%

Result: FIP 6.82 → 7.11, 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 AAALouisville Bats · 133 IPFIP 5.26 → 5.07 (−0.19)K% 14.7% → 12.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.71%	—	×0.880	12.94%
BB% (unintentional) /BF	5.88%	—	×1.050	6.18%
HR / BF /BF	4.84%	÷1.282	×1.100	4.16%

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 156).

Result: FIP 5.26 → 5.07, 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).

2021 AAChattanooga Lookouts · 89 IPFIP 3.84 → 4.64 (+0.80)K% 17.3% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.27%	—	×0.810	13.99%
BB% (unintentional) /BF	2.84%	—	×1.100	3.12%
HR / BF /BF	3.35%	÷0.950	×1.200	4.23%

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 90).

Result: FIP 3.84 → 4.64, 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 ADayton Dragons · 12 IPFIP 2.93 → 4.35 (+1.42)K% 28.0% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.00%	—	×0.740	20.72%
BB% (unintentional) /BF	0.00%	—	×1.180	0.00%
HR / BF /BF	4.00%	÷0.950	×1.300	5.47%

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 90).

Result: FIP 2.93 → 4.35, 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
Randy Wynne (OGILVIE)	—	—	5.48	10.0%	5.1%	4.0%	—	5.88	10.9%	4.1%	104	+0.40	—	—	—
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	74
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	73
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	70
Juan Delgadillo R 2017 · 4.47 FIP	34	SP	4.47	10.9%	6.2%	2.7%	.311	—	—	—	—	—	4.47	143	67
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	65
Tim Adleman R 2022 · 5.69 FIP	34	SP-	5.69	17.5%	8.6%	5.4%	.275	—	—	—	—	—	3.63	605	63
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	60
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	60
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	60
Yohan Pino R 2017 · 5.33 FIP	33	SP-	5.33	15.2%	3.6%	5.6%	.296	—	—	—	—	—	3.84	193	58
Jesse Estrada R 2017 · 5.39 FIP	33	SP	5.39	8.3%	5.6%	4.2%	.285	4.34	14.4%	7.8%	85	-1.05	3.80	257	58
Zach Neal R 2023 · 5.98 FIP	34	SW	5.98	15.6%	6.0%	6.3%	.291	—	—	—	—	—	4.24	732	57
Walter Silva R 2009 · 5.72 FIP	32	SP	5.72	9.1%	12.4%	3.3%	.330	—	—	—	—	—	3.67	453	57
Francisco Cordova R 2016 · 4.59 FIP	32	SP	4.59	7.1%	7.7%	2.0%	.300	—	—	—	—	—	4.59	115	56
Francisco Rodriguez R 2017 · 4.43 FIP	34	SP	4.43	11.4%	8.2%	2.3%	.305	5.18	10.7%	1.4%	83	+0.75	3.16	334	54
Jason Simontacchi R 2007 · 4.96 FIP	33	SP	4.96	13.0%	5.9%	4.0%	.331	—	—	—	—	—	4.79	356	51
Marco Carrillo R 2019 · 6.08 FIP	32	SP	6.08	9.9%	9.1%	4.9%	.334	—	—	—	—	—	5.33	194	51
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	51
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	49
Matt Buschmann R 2016 · 4.84 FIP	32	SP	4.84	12.8%	8.4%	3.2%	.325	—	—	—	—	—	4.03	277	48

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	43	10.6%	6.2%	1.66	5.55
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Ricky Stone ('07)	1.3	64	15.2%	8.0%	1.55	4.68
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Larry Casian ('90-'98, 0 WAR*)	1.2	40	14.7%*	6.8%*	1.25*	4.37*
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*