Jordan Weems

P Oklahoma City Comets

Age 34 RHP 6'4" / 211 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MIX2 levels	53	55	6.09	4.82	19.5%	11.7%	-0.2	K 18.6% · BB 11.4% · FIP 4.71
2025	32	MIX2 levels	43	51	5.29	3.98	21.4%	11.4%	0.3	K 20.5% · BB 10.0% · FIP 4.17
2026	33	AAALAD	17	14	9.22	9.10	11.7%	20.8%	—	K 10.1% · BB 18.7% · FIP 7.76
2027PROJ	34	MLBLAD	2	2	4.98	5.24	18.5%	11.4%	-0.0
2028PROJ6% MLB	35	MLBLAD	1	1	5.43	5.66	17.5%	12.0%	-0.0

Last 3 seasons WAR 0.2 · Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsJose Manuel Lopez (age 34) · Joe Nelson (age 34) · Matt Miller (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 116

ERA4.98

FIP5.24

K%18.5%

BB%11.4%

K-BB%7.0%

Proj IP18

Value2027 · WAR

Runs saved vs league avg · 18 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)
2016	23	ROK MLE	GCL Red Sox	8	0	17	57	10	4	0	0%	2.1	11.9%	8.8%	3.2%	0.0%	1.06	3.20	—
2016	23	ROK RAW	GCL Red Sox	8	0	17	57	10	4	0	0%	2.1	17.5%	7.0%	10.5%	0.0%	1.06	2.63	—
2017	24	MIX MLE	3 levels	24	1	53	226	46	24	5	4%	2.2	15.1%	13.7%	1.3%	3.6%	4.10	5.52	—
2017	24	MIX RAW	3 levels	24	1	53	226	46	24	5	4%	2.2	20.4%	10.6%	9.7%	2.2%	4.10	3.95	—
2018	25	MIX MLE	3 levels	43	0	59	257	63	33	4	0%	1.4	19.0%	12.0%	7.0%	1.6%	3.36	3.90	—
2018	25	MIX RAW	3 levels	43	0	59	257	63	33	4	0%	1.4	24.5%	12.8%	11.7%	1.6%	3.36	3.52	—
2019	26	MIX MLE	2 levels	41	1	56	248	69	32	2	2%	1.4	22.9%	14.1%	8.9%	0.9%	4.37	3.46	—
2019	26	MIX RAW	2 levels	41	1	56	248	69	32	2	2%	1.4	27.8%	12.9%	14.9%	0.8%	4.37	2.81	—
2020	27	MLB MLE	Oakland Athletics	9	0	14	58	18	7	1	0%	1.6	31.0%	12.1%	19.0%	1.9%	3.21	3.05	+0.3
2020	27	MLB RAW	Oakland Athletics	9	0	14	58	18	7	1	0%	1.6	31.0%	12.1%	19.0%	1.7%	3.21	2.96	+0.3
2021	28	MIX MLE	2 levels	37	0	34	156	33	19	11	0%	0.9	18.2%	11.7%	6.5%	8.2%	8.74	7.55	-1.2
2021	28	MIX RAW	2 levels	37	0	34	156	33	19	11	0%	0.9	21.2%	12.2%	9.0%	7.1%	8.74	7.04	-1.0
2022	29	MIX MLE	2 levels	65	0	80	323	90	23	11	0%	1.2	26.0%	7.3%	18.7%	3.4%	3.95	3.71	+0.8
2022	29	MIX RAW	2 levels	65	0	80	323	90	23	11	0%	1.2	27.9%	7.1%	20.7%	3.4%	3.95	3.50	+1.0
2023	30	MIX MLE	2 levels	73	0	79	329	84	36	11	0%	1.1	24.5%	10.5%	14.0%	3.4%	3.66	4.21	+0.3
2023	30	MIX RAW	2 levels	73	0	79	329	84	36	11	0%	1.1	25.5%	10.9%	14.6%	3.3%	3.66	4.16	+0.4
2024	31	MIX MLE	2 levels	53	0	55	257	50	30	8	0%	1.0	18.6%	11.4%	7.2%	3.2%	6.09	4.71	-0.1
2024	31	MIX MLE	2 levels	53	0	55	257	50	30	8	0%	1.0	18.6%	11.4%	7.2%	3.2%	6.09	4.71	-0.1
2024	31	MIX RAW	2 levels	53	0	55	257	50	30	8	0%	1.0	19.5%	11.7%	7.8%	3.1%	6.09	4.82	-0.2
2025	32	MIX MLE	2 levels	43	0	51	229	49	26	5	0%	1.2	20.5%	10.0%	10.4%	2.8%	5.29	4.17	+0.2
2025	32	MIX MLE	2 levels	43	0	51	229	49	26	5	0%	1.2	20.5%	10.0%	10.4%	2.8%	5.29	4.17	+0.2
2025	32	MIX RAW	2 levels	43	0	51	229	49	26	5	0%	1.2	21.4%	11.4%	10.0%	2.2%	5.29	3.98	+0.3
2026	33	AAA MLE	Oklahoma City Comets	17	0	14	77	9	16	4	0%	0.8	10.1%	18.7%	-8.6%	5.7%	9.22	7.76	—
2026	33	AAA MLE	Oklahoma City Comets	17	0	14	77	9	16	4	0%	0.8	10.1%	18.7%	-8.6%	5.7%	9.22	7.76	—
2026	33	AAA RAW	Oklahoma City Comets	17	0	14	77	9	16	4	0%	0.8	11.7%	20.8%	-9.1%	5.2%	9.22	9.10	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			144	0	160	705	161	73	26	0%	1.1	22.8%	10.4%	12.5%	3.7%	5.51	4.57	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	LAD	2	0	2	8	2	1	0	0%	1.0	18.5%	11.4%	7.0%	3.4%	4.98	5.24	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	LAD	14	0	15	62	11	7	2	0%	1.1	17.5%	12.0%	5.5%	3.7%	5.34	5.57	-0.2
2028	35	MLB CTX	LAD	1	0	1	4	1	1	0	0%	1.0	17.5%	12.0%	5.5%	3.9%	5.43	5.66	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		145	0	161	708	162	73	26	0%	1.1	22.8%	10.4%	12.4%	3.7%	5.51	4.51	+0.1
/ 200 IP	—	RAW		180	0	200	881	201	91	32	0%	1.1	22.8%	10.4%	12.4%	3.7%	5.51	4.51	+0.1
Career	—	MLE		413	2	510	2217	460	252	69	0%	1.2	20.8%	11.4%	9.4%	3.1%	4.61	4.51	-0.2
/ 200 IP	—	MLE		162	1	200	869	180	99	27	0%	1.2	20.8%	11.4%	9.4%	3.1%	4.61	4.51	-0.2

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.

2026 AAAOklahoma City Comets · 14 IPFIP 7.60 → 7.76 (+0.16)K% 11.7% → 10.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.69%	—	×0.860	10.05%
BB% (unintentional) /BF	20.78%	—	×0.900	18.70%
HR / BF /BF	5.19%	÷1.000	×1.100	5.71%

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 100).

Result: FIP 7.60 → 7.76, 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).

2025 AAASugar Land Space Cowboys · 47 IPFIP 3.84 → 4.17 (+0.33)K% 23.8% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.79%	—	×0.860	20.46%
BB% (unintentional) /BF	11.17%	—	×0.900	10.05%
HR / BF /BF	2.43%	÷0.961	×1.100	2.78%

Result: FIP 3.84 → 4.17, 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 AAARochester Red Wings · 13 IPFIP 3.17 → 3.44 (+0.27)K% 24.6% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.59%	—	×0.860	21.15%
BB% (unintentional) /BF	9.84%	—	×0.900	8.85%
HR / BF /BF	1.64%	÷0.986	×1.100	1.83%

Result: FIP 3.17 → 3.44, 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 AAARochester Red Wings · 24 IPFIP 3.84 → 4.01 (+0.17)K% 24.7% → 21.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.74%	—	×0.860	21.28%
BB% (unintentional) /BF	13.40%	—	×0.900	12.06%
HR / BF /BF	2.06%	÷1.058	×1.100	2.14%

Result: FIP 3.84 → 4.01, 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 AAARochester Red Wings · 40 IPFIP 2.83 → 3.22 (+0.38)K% 31.2% → 27.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.21%	—	×0.880	27.46%
BB% (unintentional) /BF	7.64%	—	×1.050	8.03%
HR / BF /BF	2.55%	÷1.084	×1.100	2.58%

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 117).

Result: FIP 2.83 → 3.22, 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 AAAReno Aces · 28 IPFIP 6.69 → 7.55 (+0.86)K% 20.6% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.63%	—	×0.880	18.16%
BB% (unintentional) /BF	11.11%	—	×1.050	11.67%
HR / BF /BF	7.14%	÷0.958	×1.100	8.21%

Result: FIP 6.69 → 7.55, 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).

2019 AAPortland Sea Dogs · 44 IPFIP 2.69 → 3.38 (+0.69)K% 28.1% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.06%	—	×0.810	22.73%
BB% (unintentional) /BF	13.27%	—	×1.100	14.59%
HR / BF /BF	0.51%	÷0.953	×1.200	0.64%

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 91).

Result: FIP 2.69 → 3.38, 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).

2019 AAAPawtucket Red Sox · 12 IPFIP 3.34 → 3.75 (+0.41)K% 26.9% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.92%	—	×0.880	23.69%
BB% (unintentional) /BF	11.54%	—	×1.050	12.12%
HR / BF /BF	1.92%	÷1.038	×1.100	2.04%

Result: FIP 3.34 → 3.75, 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).

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
Jordan Weems (OGILVIE)	—	—	5.24	18.5%	11.4%	3.4%	—	5.57	17.5%	5.5%	15	+0.33	—	—	—
Jose Manuel Lopez R 2019 · 6.14 FIP	34	SU	6.14	17.9%	14.2%	5.0%	.299	—	—	—	—	—	3.50	170	81
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	80
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	77
Scott Proctor R 2011 · 6.33 FIP	34	SU	6.33	14.4%	12.9%	5.1%	.289	—	—	—	—	—	3.68	337	76
Diego Moreno R 2021 · 4.75 FIP	34	SU	4.75	18.6%	9.4%	3.7%	.232	—	—	—	—	—	2.29	187	74
Matt Bush R 2018 · 4.72 FIP	32	SU	4.72	17.6%	13.0%	2.7%	.278	—	—	—	—	—	2.87	249	73
Austin Adams R 2019 · 5.80 FIP	32	SU	5.80	20.8%	10.6%	5.7%	.280	—	—	—	—	—	3.40	162	72
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	72
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	71
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	70
Fernando Villalobos R 2017 · 4.70 FIP	32	SU	4.70	10.6%	8.0%	2.7%	.313	—	—	—	—	—	4.00	152	69
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	69
Raul Barron R 2019 · 5.92 FIP	33	SU	5.92	11.4%	8.9%	4.8%	.265	—	—	—	—	—	3.04	201	69
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	67
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	66
Giovanni Carrara R 2002 · 4.78 FIP	34	SU	4.78	14.5%	7.2%	3.6%	.239	3.83	17.1%	7.9%	158	-0.95	2.50	462	66
Denny Stark R 2009 · 6.38 FIP	34	SU	6.38	13.0%	18.5%	3.7%	.314	—	—	—	—	—	5.28	259	65
Jose Pina R 2019 · 5.28 FIP	33	SU	5.28	14.6%	6.8%	4.7%	.304	—	—	—	—	—	3.63	424	61
Marco Antonio Duarte R 2019 · 5.03 FIP	32	SW	5.03	12.2%	9.1%	3.3%	.420	—	—	—	—	—	4.07	203	59
Spencer Patton R 2022 · 6.26 FIP	34	SU	6.26	25.7%	13.0%	6.7%	.347	4.33	18.9%	9.2%	59	-1.93	2.79	239	59

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	1.0	38	22.0%	11.4%	1.42	5.45
Will Cunnane ('04)	1.4	46	18.9%	10.4%	1.25	5.26
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
José Ruiz ('25)	1.4	57	22.3%	10.4%	1.44	4.62
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Phil Hennigan ('69-'73, -0 WAR*)	1.4	70	20.9%*	10.4%*	1.50*	4.95*