Erich Uelmen

P Reno Aces

Age 31 RHP 6'3" / 195 lbs AAA

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	26	MIX2 levels	53	0	69	3.52	3.32	24.3%	10.6%	1.0	K 22.2% · BB 11.0% · FIP 3.59
2023	27	MIX4 levels	17	0	19	5.79	3.58	19.8%	11.6%	0.2	K 17.0% · BB 10.1% · FIP 3.78
2024	28	MIX2 levels	25	3	31	5.58	4.63	19.0%	11.6%	—	K 15.7% · BB 10.5% · FIP 4.67
2025	29	No MLB games played
2026	30	No MLB games played
2027PROJ	31	MLBARI	6	0	6	4.72	4.74	21.6%	10.9%	-0.0
2028PROJ37% MLB	32	MLBARI	14	0	15	4.84	4.95	20.9%	11.1%	-0.1
2029PROJ55% MLB	33	MLBARI	17	0	18	5.03	5.19	20.3%	11.4%	-0.1

Last 3 seasons WAR 1.2 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2022

xwOBA vs49

FB Velo38

K%16

CompsYoanner Negrin (age 31) · Dustin Molleken (age 31) · Felipe Arredondo (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.72

FIP4.74

K%21.6%

BB%10.9%

K-BB%10.7%

Proj IP55

Value2027 · WAR

Runs saved vs league avg · 55 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL4545

CMD3535

K†5050

Statcast Percentiles

FB Velo

p3893.7

Whiff%

p6327.3%

p1617.2%

xwOBA vs

p490.313

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)
2018	22	MIX MLE	2 levels	21	20	89	379	82	30	3	95%	4.3	16.2%	9.2%	7.0%	1.1%	3.83	3.48	—
2018	22	MIX RAW	2 levels	21	20	89	379	82	30	3	95%	4.3	21.6%	7.9%	13.7%	0.8%	3.83	2.71	—
2019	23	MIX MLE	2 levels	17	17	91	390	76	37	9	100%	5.4	15.3%	10.7%	4.6%	2.7%	4.55	4.64	—
2019	23	MIX RAW	2 levels	17	17	91	390	76	37	9	100%	5.4	19.5%	9.5%	10.0%	2.3%	4.55	3.94	—
2021	25	MIX MLE	2 levels	31	11	90	407	88	41	16	35%	2.9	17.9%	11.0%	7.0%	4.3%	5.78	5.32	—
2021	25	MIX RAW	2 levels	31	11	90	407	88	41	16	35%	2.9	21.6%	10.1%	11.5%	3.9%	5.78	4.82	—
2022	26	MIX MLE	2 levels	53	0	69	301	73	32	5	0%	1.3	22.2%	11.0%	11.2%	1.8%	3.52	3.59	+0.8
2022	26	MIX RAW	2 levels	53	0	69	301	73	32	5	0%	1.3	24.3%	10.6%	13.6%	1.7%	3.52	3.32	+1.0
2023	27	MIX MLE	4 levels	17	0	19	86	17	10	1	0%	1.1	17.0%	10.1%	6.8%	1.5%	5.79	3.78	+0.2
2023	27	MIX RAW	4 levels	17	0	19	86	17	10	1	0%	1.1	19.8%	11.6%	8.1%	1.2%	5.79	3.58	+0.2
2024	28	MIX MLE	2 levels	25	3	31	147	28	17	4	12%	1.2	15.7%	10.5%	5.2%	2.9%	5.58	4.67	—
2024	28	MIX MLE	2 levels	25	3	31	147	28	17	4	12%	1.2	15.7%	10.5%	5.2%	2.9%	5.58	4.67	—
2024	28	MIX RAW	2 levels	25	3	31	147	28	17	4	12%	1.2	19.0%	11.6%	7.5%	2.7%	5.58	4.63	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			26	0	28	130	22	13	3	0%	1.1	16.9%	10.0%	6.9%	2.3%	5.79	4.31	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	ARI	6	0	6	25	5	3	1	0%	1.0	21.6%	10.9%	10.7%	3.1%	4.72	4.74	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	ARI	39	0	41	175	37	19	6	0%	1.1	20.9%	11.1%	9.8%	3.3%	4.84	4.95	-0.2
2029	33	MLB MLE	ARI	31	0	33	139	28	16	5	0%	1.1	20.3%	11.4%	8.9%	3.6%	5.03	5.19	-0.2
2030	34	MLB MLE	ARI	26	0	27	114	22	13	4	0%	1.0	19.5%	11.8%	7.7%	3.9%	5.26	5.45	-0.3
2028	32	MLB CTX	ARI	14	0	15	63	13	7	2	0%	1.1	20.9%	11.1%	9.8%	3.3%	4.84	4.95	-0.1
2029	33	MLB CTX	ARI	17	0	18	76	15	9	3	0%	1.1	20.3%	11.4%	8.9%	3.6%	5.03	5.19	-0.1
2030	34	MLB CTX	ARI	13	0	14	59	12	7	2	0%	1.1	19.5%	11.8%	7.7%	3.9%	5.26	5.45	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		71	0	75	329	62	36	10	0%	1.1	19.0%	10.9%	8.1%	3.1%	5.32	4.57	-0.0
/ 200 IP	—	RAW		189	0	200	876	165	96	27	0%	1.1	19.0%	10.9%	8.1%	3.1%	5.32	4.57	-0.0
Career	—	MLE		164	51	389	1710	298	178	43	31%	2.4	17.4%	10.4%	7.0%	2.5%	4.63	4.32	-0.6
/ 200 IP	—	MLE		84	26	200	879	153	92	22	31%	2.4	17.4%	10.4%	7.0%	2.5%	4.63	4.32	-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.

2024 AAAReno Aces · 28 IPFIP 4.64 → 4.67 (+0.03)K% 18.2% → 15.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.25%	—	×0.860	15.69%
BB% (unintentional) /BF	11.68%	—	×0.900	10.51%
HR / BF /BF	2.92%	÷1.124	×1.100	2.86%

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 125).

Result: FIP 4.64 → 4.67, 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 AAALehigh Valley IronPigs · 16 IPFIP 3.64 → 3.78 (+0.14)K% 19.7% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.72%	—	×0.860	16.96%
BB% (unintentional) /BF	11.27%	—	×0.900	10.14%
HR / BF /BF	1.41%	÷1.028	×1.100	1.51%

Result: FIP 3.64 → 3.78, 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).

2022 AAAIowa Cubs · 42 IPFIP 2.75 → 3.18 (+0.43)K% 29.1% → 25.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.05%	—	×0.880	25.56%
BB% (unintentional) /BF	11.73%	—	×1.050	12.32%
HR / BF /BF	1.12%	÷0.996	×1.100	1.23%

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 99).

Result: FIP 2.75 → 3.18, 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 AATennessee Smokies · 70 IPFIP 4.22 → 4.90 (+0.69)K% 20.6% → 16.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.65%	—	×0.810	16.72%
BB% (unintentional) /BF	10.00%	—	×1.100	11.00%
HR / BF /BF	2.90%	÷1.050	×1.200	3.32%

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 110).

Result: FIP 4.22 → 4.90, 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 AAAIowa Cubs · 21 IPFIP 6.28 → 6.66 (+0.39)K% 24.7% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.74%	—	×0.880	21.77%
BB% (unintentional) /BF	10.31%	—	×1.050	10.82%
HR / BF /BF	7.22%	÷1.081	×1.100	7.35%

Result: FIP 6.28 → 6.66, 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).

2019 A+Myrtle Beach Pelicans · 62 IPFIP 3.20 → 4.00 (+0.80)K% 20.2% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.16%	—	×0.770	15.52%
BB% (unintentional) /BF	7.26%	—	×1.150	8.35%
HR / BF /BF	1.61%	÷0.956	×1.250	2.11%

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 91).

Result: FIP 3.20 → 4.00, 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).

2019 AATennessee Smokies · 29 IPFIP 5.18 → 5.74 (+0.56)K% 18.3% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.31%	—	×0.810	14.83%
BB% (unintentional) /BF	13.38%	—	×1.100	14.72%
HR / BF /BF	3.52%	÷1.142	×1.200	3.70%

Result: FIP 5.18 → 5.74, 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 ASouth Bend Cubs · 56 IPFIP 1.81 → 2.50 (+0.70)K% 25.0% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.740	18.50%
BB% (unintentional) /BF	6.47%	—	×1.180	7.63%
HR / BF /BF	0.00%	÷0.881	×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 76).

Result: FIP 1.81 → 2.50, 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
Erich Uelmen (OGILVIE)	—	—	4.74	21.6%	10.9%	3.1%	—	5.16	20.4%	9.0%	101	+0.42	—	—	—
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	76
Dustin Molleken R 2016 · 4.04 FIP	31	SU	4.04	19.6%	12.1%	1.9%	.276	3.38	24.3%	11.9%	16	-0.66	3.38	129	76
Felipe Arredondo R 2017 · 4.76 FIP	30	SW	4.76	14.8%	7.3%	3.6%	.311	4.65	16.2%	9.1%	64	-0.11	3.92	337	72
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	72
Angel Sánchez R 2023 · 4.90 FIP	33	SW	4.90	19.0%	10.5%	3.8%	.333	3.77	11.8%	6.8%	27	-1.13	3.77	284	72
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	71
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	70
Robert Stock R 2021 · 4.18 FIP	31	SW	4.18	23.0%	8.5%	3.5%	.301	7.20	14.3%	0.1%	23	+3.02	2.74	378	70
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	69
Murphy Smith R 2018 · 4.57 FIP	30	SW	4.57	13.6%	9.3%	2.6%	.273	—	—	—	—	—	3.16	300	69
Cody Satterwhite R 2017 · 4.22 FIP	30	SU	4.22	17.0%	7.1%	3.0%	.310	—	—	—	—	—	3.69	147	69
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	68
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	68
Clay Hensley R 2011 · 4.78 FIP	31	SW	4.78	15.5%	9.8%	3.2%	.249	4.37	17.9%	5.9%	51	-0.41	2.58	517	67
Neil Wagner R 2016 · 4.05 FIP	32	SU	4.05	19.8%	12.3%	1.9%	.360	3.11	20.7%	12.1%	54	-0.94	3.11	135	66
Jason Urquidez R 2015 · 3.59 FIP	32	SU	3.59	15.6%	9.3%	1.1%	.386	1.81	25.5%	20.7%	90	-1.78	1.25	123	66
Tim Dillard R 2015 · 3.58 FIP	32	SW	3.58	15.9%	7.7%	1.5%	.330	3.85	16.7%	8.1%	144	+0.27	2.92	432	66
Spencer Bivens R 2024 · 4.07 FIP	30	SU	4.07	18.0%	5.8%	3.2%	.265	3.88	18.2%	10.9%	157	-0.19	3.52	391	66
Marco Antonio Duarte R 2019 · 5.03 FIP	32	SW	5.03	12.2%	9.1%	3.3%	.420	—	—	—	—	—	4.07	203	66
Chris Jakubauskas R 2009 · 4.97 FIP	30	SW	4.97	12.1%	6.2%	3.9%	.250	4.42	15.7%	7.8%	72	-0.55	4.42	165	66

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	20.2%	11.1%	1.25	5.04
Pedro Borbón ('03)	1.4	45	18.5%	11.1%	1.10	4.68
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Josias Manzanillo ('04)	1.7	57	20.0%	10.2%	1.21	4.71
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*