Jaime Arias

P Akron RubberDucks

Age 28 LHP 6'0" / 210 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	23	MIX3 levels	29	15	81	5.98	4.26	20.2%	9.0%	—	K 15.6% · BB 9.9% · FIP 5.00
2023	24	MIX3 levels	12	6	39	6.05	5.56	21.0%	9.6%	—	K 17.5% · BB 13.9% · FIP 5.99
2024	25	MIX2 levels	15	7	54	4.70	4.96	18.3%	9.8%	—	K 15.1% · BB 9.7% · FIP 5.33
2025	26	No MLB games played
2026	27	No MLB games played
2027PROJ	28	MLBCLE	1	0	1	4.76	4.76	19.1%	9.4%	-0.0
2028PROJ31% MLB	29	MLBCLE	9	0	9	4.80	4.85	19.3%	9.6%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsChad Bell (age 28) · Yohan Flande (age 28) · Matt Whitehouse (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 107115vR 124

ERA4.76

FIP4.76

K%19.1%

BB%9.4%

K-BB%9.7%

Proj IP37

Value2027 · WAR

Runs saved vs league avg · 37 IP

Grades · Contract

Scouting Grades

K†4545

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	22	A MLE	Lynchburg Hillcats	23	9	87	338	111	15	12	39%	3.8	24.3%	5.2%	19.1%	4.9%	3.81	4.38	—
2021	22	A RAW	Lynchburg Hillcats	23	9	87	338	111	15	12	39%	3.8	32.8%	4.4%	28.4%	3.6%	3.81	2.86	—
2022	23	MIX MLE	3 levels	29	15	81	367	74	33	11	52%	2.8	15.6%	9.9%	5.8%	3.6%	5.98	5.00	—
2022	23	MIX RAW	3 levels	29	15	81	367	74	33	11	52%	2.8	20.2%	9.0%	11.2%	3.0%	5.98	4.26	—
2023	24	MIX MLE	3 levels	12	6	39	167	35	16	9	50%	3.2	17.5%	13.9%	3.6%	4.8%	6.05	5.99	—
2023	24	MIX RAW	3 levels	12	6	39	167	35	16	9	50%	3.2	21.0%	9.6%	11.4%	5.4%	6.05	5.56	—
2024	25	MIX MLE	2 levels	15	7	54	235	43	23	9	47%	3.6	15.1%	9.7%	5.4%	4.1%	4.70	5.33	—
2024	25	MIX MLE	2 levels	15	7	54	235	43	23	9	47%	3.6	15.1%	9.7%	5.4%	4.1%	4.70	5.33	—
2024	25	MIX RAW	2 levels	15	7	54	235	43	23	9	47%	3.6	18.3%	9.8%	8.5%	3.8%	4.70	4.96	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CLE	1	0	1	4	1	0	0	0%	1.0	19.1%	9.4%	9.7%	3.1%	4.76	4.76	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CLE	28	0	29	122	24	12	4	0%	1.0	19.3%	9.6%	9.7%	3.2%	4.80	4.85	-0.1
2028	29	MLB CTX	CLE	9	0	9	38	7	4	1	0%	1.0	19.3%	9.6%	9.7%	3.2%	4.80	4.85	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	9	38	7	4	1	0%	1.0	19.3%	9.6%	9.7%	3.2%	4.80	4.47	+0.0
/ 200 IP	—	RAW		190	0	200	844	155	88	22	0%	1.1	19.3%	9.6%	9.7%	3.2%	4.80	4.47	+0.2
Career	—	MLE		79	37	261	1107	204	100	47	47%	3.3	18.5%	9.0%	9.4%	4.3%	5.00	5.03	-0.1
/ 200 IP	—	MLE		61	28	200	848	157	76	36	47%	3.3	18.5%	9.0%	9.4%	4.3%	5.00	5.03	-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.

2024 AAAkron RubberDucks · 32 IPFIP 2.97 → 3.65 (+0.68)K% 23.3% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.26%	—	×0.810	18.84%
BB% (unintentional) /BF	7.75%	—	×1.100	8.53%
HR / BF /BF	1.55%	÷0.966	×1.200	1.93%

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 93).

Result: FIP 2.97 → 3.65, 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 AAAColumbus Clippers · 22 IPFIP 7.24 → 7.37 (+0.13)K% 12.3% → 10.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.26%	—	×0.860	10.55%
BB% (unintentional) /BF	12.26%	—	×0.900	11.04%
HR / BF /BF	6.60%	÷1.060	×1.100	6.85%

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 7.24 → 7.37, 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).

2023 AAAkron RubberDucks · 24 IPFIP 4.85 → 5.99 (+1.14)K% 21.6% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.62%	—	×0.810	17.51%
BB% (unintentional) /BF	12.61%	—	×1.100	13.87%
HR / BF /BF	3.60%	÷0.909	×1.200	4.76%

Result: FIP 4.85 → 5.99, 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 A+Lake County Captains · 8 IPFIP 6.89 → 8.51 (+1.62)K% 27.6% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.59%	—	×0.770	21.24%
BB% (unintentional) /BF	3.45%	—	×1.150	3.97%
HR / BF /BF	10.34%	÷1.060	×1.250	12.20%

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 112).

Result: FIP 6.89 → 8.51, 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 AAAColumbus Clippers · 7 IPFIP 6.70 → 7.03 (+0.33)K% 11.1% → 9.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.11%	—	×0.860	9.56%
BB% (unintentional) /BF	3.70%	—	×0.900	3.33%
HR / BF /BF	7.41%	÷1.037	×1.100	7.86%

Result: FIP 6.70 → 7.03, 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 AAAkron RubberDucks · 44 IPFIP 4.60 → 5.31 (+0.70)K% 16.1% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.10%	—	×0.810	13.04%
BB% (unintentional) /BF	7.80%	—	×1.100	8.59%
HR / BF /BF	3.41%	÷1.014	×1.200	4.04%

Result: FIP 4.60 → 5.31, 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+Lake County Captains · 34 IPFIP 3.76 → 4.59 (+0.83)K% 25.0% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.770	19.25%
BB% (unintentional) /BF	10.14%	—	×1.150	11.66%
HR / BF /BF	2.70%	÷1.134	×1.250	2.98%

Result: FIP 3.76 → 4.59, 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 ALynchburg Hillcats · 87 IPFIP 2.84 → 4.38 (+1.54)K% 32.8% → 24.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.84%	—	×0.740	24.30%
BB% (unintentional) /BF	4.44%	—	×1.180	5.24%
HR / BF /BF	3.55%	÷0.950	×1.300	4.86%

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 2.84 → 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
Jaime Arias (OGILVIE)	—	—	4.76	19.1%	9.4%	3.1%	—	4.85	19.3%	9.7%	29	+0.09	—	—	—
Chad Bell L 2017 · 4.57 FIP	28	SW	4.57	19.4%	8.9%	3.6%	.341	4.38	18.8%	11.4%	57	-0.19	3.39	393	74
Yohan Flande L 2014 · 3.65 FIP	28	SP-	3.65	14.1%	5.8%	1.8%	.266	3.90	14.1%	7.9%	312	+0.25	3.18	394	74
Matt Whitehouse L 2019 · 4.07 FIP	28	SW	4.07	20.1%	10.9%	2.3%	.339	—	—	—	—	—	3.37	353	72
John Rheinecker L 2007 · 5.13 FIP	28	SW	5.13	16.7%	10.9%	3.8%	.317	—	—	—	—	—	4.14	121	72
Everett Teaford L 2012 · 5.47 FIP	28	SW	5.47	13.3%	8.0%	4.5%	.291	4.42	13.9%	6.3%	103	-1.05	4.42	208	72
Chris Reed L 2016 · 4.67 FIP	26	SW	4.67	16.4%	9.8%	3.1%	.238	—	—	—	—	—	4.67	137	71
Roy Merritt L 2016 · 3.93 FIP	30	SP-	3.93	13.3%	5.9%	2.2%	.293	3.95	16.2%	10.4%	116	+0.02	3.93	129	70
Brad Mills L 2014 · 5.61 FIP	29	SP-	5.61	18.8%	10.9%	5.0%	.364	5.00	14.5%	4.0%	182	-0.61	4.22	243	70
T.J. Sikkema L 2024 · 3.57 FIP	26	SP-	3.57	18.5%	6.0%	2.3%	.282	4.10	16.1%	7.2%	87	+0.53	3.57	300	70
Austin Warner L 2022 · 4.78 FIP	28	SW	4.78	16.9%	9.0%	3.6%	.319	—	—	—	—	—	3.81	491	69
Onelki Garcia L 2017 · 4.02 FIP	27	SP-	4.02	16.5%	9.3%	2.1%	.328	—	—	—	—	—	2.99	164	69
Danny Wirchansky L 2024 · 4.47 FIP	27	SP-	4.47	16.2%	7.4%	3.3%	.246	5.88	13.0%	0.2%	68	+1.41	4.47	179	69
Carlos Teller L 2015 · 3.75 FIP	28	SP-	3.75	13.8%	10.9%	0.8%	.329	4.75	13.3%	3.1%	187	+1.00	3.75	333	68
Brian Holmes L 2017 · 5.91 FIP	26	SW	5.91	15.5%	11.7%	4.8%	.354	—	—	—	—	—	3.60	205	68
Tyler Alexander L 2019 · 5.56 FIP	27	SP-	5.56	21.7%	9.8%	5.6%	.289	5.27	15.7%	5.0%	26	-0.29	5.27	128	68
Randy Keisler L 2005 · 5.07 FIP	29	SW	5.07	16.4%	9.9%	3.8%	.295	5.51	6.5%	0.0%	17	+0.44	5.07	135	68
Houston Harding L 2024 · 4.54 FIP	26	SP-	4.54	16.5%	11.2%	2.6%	.268	5.19	12.0%	0.5%	61	+0.65	3.41	239	67
Edgar Olmos L 2017 · 3.64 FIP	27	SW	3.64	18.9%	9.7%	1.7%	.252	—	—	—	—	—	3.19	203	67
Matt Tracy L 2017 · 4.82 FIP	28	SP-	4.82	16.1%	9.4%	3.5%	.325	3.24	13.9%	3.5%	49	-1.58	3.24	298	67
Miguel Pena L 2019 · 5.08 FIP	28	SW	5.08	16.0%	7.0%	4.4%	.369	—	—	—	—	—	2.98	282	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	0.3	33	19.2%	9.5%	1.22	4.78
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Randy Flores ('10)	1.2	42	17.7%	9.3%	1.04	4.61
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*