Jalen Beeks

P Texas Rangers

Age 34 LHP 5'11" / 215 lbs MLB ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MLBPIT	71	0	70	4.50	3.71	17.6%	8.0%	0.7
2025	32	MIX2 levels	62	2	58	3.70	3.80	20.1%	8.1%	0.5	K 20.3% · BB 7.8% · FIP 3.88
2026	33	MLBTEX	29	0	26	3.81	5.29	18.6%	6.2%	-0.2
2027PROJ	34	MLBTEX	27	0	28	4.39	4.54	19.7%	7.4%	0.0
2028PROJ	35	MLBTEX	24	0	25	4.68	4.88	18.8%	7.9%	-0.1

Last 3 seasons WAR 1.0 · Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo34

K%25

xwOBA vs10

CompsAlejandro Soto (age 33) · Pedro Borbón (age 34) · Hideki Okajima (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 103111vR 119

ERA4.39

FIP4.54

K%19.7%

BB%7.4%

K-BB%12.3%

Proj IP28

Value2027 · WAR

Runs saved vs league avg · 28 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3493.4

Whiff%

p3723.4%

p2518.6%

xwOBA vs

p100.363

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	A MLE	Greenville Drive	26	26	146	616	100	28	17	100%	5.6	12.0%	5.4%	6.6%	3.7%	4.32	4.78	—
2015	22	A RAW	Greenville Drive	26	26	146	616	100	28	17	100%	5.6	16.2%	4.5%	11.7%	2.8%	4.32	3.82	—
2016	23	MIX MLE	2 levels	26	26	133	581	111	52	15	100%	5.1	15.1%	10.1%	5.0%	3.4%	3.87	4.95	—
2016	23	MIX RAW	2 levels	26	26	133	581	111	52	15	100%	5.1	19.1%	9.0%	10.2%	2.6%	3.87	4.07	—
2017	24	MIX MLE	2 levels	26	26	145	605	155	55	13	100%	5.6	21.9%	9.7%	12.1%	2.2%	3.29	3.71	—
2017	24	MIX RAW	2 levels	26	26	145	605	155	55	13	100%	5.6	25.6%	9.1%	16.5%	2.1%	3.29	3.27	—
2018	25	MIX MLE	2 levels	30	17	138	578	159	49	16	57%	4.6	25.1%	8.7%	16.4%	2.5%	3.85	3.45	+3.3
2018	25	MIX RAW	2 levels	30	17	138	578	159	49	16	57%	4.6	27.5%	8.5%	19.0%	2.8%	3.85	3.37	+3.4
2019	26	MIX MLE	2 levels	36	6	115	506	99	43	14	17%	3.2	19.2%	8.4%	10.8%	2.7%	4.30	4.00	+0.7
2019	26	MIX RAW	2 levels	36	6	115	506	99	43	14	17%	3.2	19.6%	8.5%	11.1%	2.8%	4.30	4.08	+0.6
2020	27	MLB MLE	Tampa Bay Rays	12	0	19	81	26	4	1	0%	1.6	32.1%	4.9%	27.2%	1.3%	3.26	1.71	+0.7
2020	27	MLB RAW	Tampa Bay Rays	12	0	19	81	26	4	1	0%	1.6	32.1%	4.9%	27.2%	1.2%	3.26	1.70	+0.7
2022	29	MLB MLE	Tampa Bay Rays	42	7	61	250	70	22	7	17%	1.5	28.0%	8.8%	19.2%	2.9%	2.80	3.43	+0.8
2022	29	MLB RAW	Tampa Bay Rays	42	7	61	250	70	22	7	17%	1.5	28.0%	8.8%	19.2%	2.8%	2.80	3.38	+0.9
2023	30	MIX MLE	2 levels	50	9	68	302	74	29	7	18%	1.4	23.3%	9.3%	13.9%	2.3%	5.16	3.59	+0.8
2023	30	MIX RAW	2 levels	50	9	68	302	74	29	7	18%	1.4	24.5%	9.6%	14.9%	2.3%	5.16	3.54	+0.8
2024	31	MLB MLE	Pittsburgh Pirates	71	0	70	312	55	25	6	0%	1.0	17.6%	8.0%	9.6%	2.1%	4.50	3.77	+0.6
2024	31	MLB MLE	Pittsburgh Pirates	71	0	70	312	55	25	6	0%	1.0	17.6%	8.0%	9.6%	2.1%	4.50	3.77	+0.6
2024	31	MLB RAW	Pittsburgh Pirates	71	0	70	312	55	25	6	0%	1.0	17.6%	8.0%	9.6%	1.9%	4.50	3.71	+0.7
2025	32	MIX MLE	2 levels	62	2	58	234	47	19	6	3%	0.9	20.3%	7.8%	12.6%	2.7%	3.70	3.88	+0.5
2025	32	MIX MLE	2 levels	62	2	58	234	47	19	6	3%	0.9	20.3%	7.8%	12.6%	2.7%	3.70	3.88	+0.5
2025	32	MIX RAW	2 levels	62	2	58	234	47	19	6	3%	0.9	20.1%	8.1%	12.0%	2.6%	3.70	3.80	+0.5
2026	33	MLB MLE	Texas Rangers	29	0	26	113	21	7	6	0%	0.9	18.6%	6.2%	12.4%	4.9%	3.81	5.03	-0.1
2026	33	MLB MLE	Texas Rangers	29	0	26	113	21	7	6	0%	0.9	18.6%	6.2%	12.4%	4.9%	3.81	5.03	-0.1
2026	33	MLB RAW	Texas Rangers	29	0	26	113	21	7	6	0%	0.9	18.6%	6.2%	12.4%	5.3%	3.81	5.29	-0.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			292	21	431	1866	397	160	48	7%	1.5	21.3%	8.6%	12.7%	2.6%	4.28	3.82	+3.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	TEX	27	0	28	118	23	9	4	0%	1.0	19.7%	7.4%	12.3%	3.3%	4.39	4.54	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	TEX	24	0	25	106	20	8	4	0%	1.1	18.8%	7.9%	10.8%	3.6%	4.68	4.88	-0.1
2028	35	MLB CTX	TEX	24	0	25	106	20	8	4	0%	1.0	18.8%	7.9%	10.8%	3.6%	4.68	4.88	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		316	21	456	1972	417	168	52	7%	1.4	21.1%	8.5%	12.6%	2.6%	4.30	3.84	+3.8
/ 200 IP	—	RAW		139	9	200	865	183	74	23	7%	1.4	21.1%	8.5%	12.6%	2.6%	4.30	3.84	+1.7
Career	—	MLE		410	119	979	4178	826	348	117	29%	2.4	19.8%	8.3%	11.5%	2.8%	3.94	4.02	+3.6
/ 200 IP	—	MLE		84	24	200	854	169	71	24	29%	2.4	19.8%	8.3%	11.5%	2.8%	3.94	4.02	+1.6

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.

2023 AAADurham Bulls · 26 IPFIP 3.45 → 3.60 (+0.15)K% 24.5% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.55%	—	×0.860	21.11%
BB% (unintentional) /BF	7.27%	—	×0.900	6.55%
HR / BF /BF	2.73%	÷1.137	×1.100	2.64%

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 127).

Result: FIP 3.45 → 3.60, 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 AAADurham Bulls · 11 IPFIP 4.91 → 5.15 (+0.24)K% 23.8% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.880	20.95%
BB% (unintentional) /BF	9.52%	—	×1.050	10.00%
HR / BF /BF	4.76%	÷1.128	×1.100	4.64%

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 126).

Result: FIP 4.91 → 5.15, 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 AAAPawtucket Red Sox · 87 IPFIP 2.76 → 2.86 (+0.10)K% 33.0% → 29.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.96%	—	×0.880	29.00%
BB% (unintentional) /BF	7.04%	—	×1.050	7.39%
HR / BF /BF	2.82%	÷1.342	×1.100	2.31%

Result: FIP 2.76 → 2.86, 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 AAAPawtucket Red Sox · 96 IPFIP 3.47 → 3.76 (+0.29)K% 24.1% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.07%	—	×0.880	21.18%
BB% (unintentional) /BF	8.19%	—	×1.050	8.60%
HR / BF /BF	2.48%	÷1.106	×1.100	2.47%

Result: FIP 3.47 → 3.76, 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).

2017 AAPortland Sea Dogs · 49 IPFIP 2.87 → 3.61 (+0.74)K% 28.7% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.71%	—	×0.810	23.26%
BB% (unintentional) /BF	10.89%	—	×1.100	11.98%
HR / BF /BF	1.49%	÷1.020	×1.200	1.75%

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 104).

Result: FIP 2.87 → 3.61, 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 AAPortland Sea Dogs · 65 IPFIP 3.82 → 4.11 (+0.29)K% 19.2% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.18%	—	×0.810	15.53%
BB% (unintentional) /BF	9.59%	—	×1.100	10.55%
HR / BF /BF	2.05%	÷1.371	×1.200	1.80%

Result: FIP 3.82 → 4.11, 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).

2016 A+Salem Red Sox · 67 IPFIP 4.25 → 5.79 (+1.53)K% 19.0% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.03%	—	×0.770	14.65%
BB% (unintentional) /BF	8.30%	—	×1.150	9.55%
HR / BF /BF	3.11%	÷0.787	×1.250	4.95%

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 57).

Result: FIP 4.25 → 5.79, 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).

2015 AGreenville Drive · 146 IPFIP 3.82 → 4.78 (+0.96)K% 16.2% → 12.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.23%	—	×0.740	12.01%
BB% (unintentional) /BF	4.55%	—	×1.180	5.36%
HR / BF /BF	2.76%	÷0.979	×1.300	3.66%

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 96).

Result: FIP 3.82 → 4.78, 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).

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
Jalen Beeks (OGILVIE)	—	—	—	—	—	3.3%	—	4.88	18.8%	10.8%	25	+0.34	—	—	—
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	65
Pedro Borbón L 2002 · 4.57 FIP	34	SU	4.57	21.6%	7.3%	4.3%	.277	—	—	—	—	—	2.26	264	62
Hideki Okajima L 2010 · 4.27 FIP	34	SU	4.27	15.5%	7.0%	2.9%	.333	—	—	—	—	—	3.05	238	62
James Jones L 2023 · 4.67 FIP	34	SU	4.67	13.7%	11.5%	2.3%	.246	—	—	—	—	—	3.58	127	59
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	59
Juan Pablo Perez L 2013 · 3.68 FIP	34	SU	3.68	25.2%	11.5%	2.3%	.250	3.68	26.5%	11.2%	51	-0.00	1.75	104	59
Tom Martin L 2004 · 4.74 FIP	34	SU	4.74	14.7%	7.8%	3.4%	.278	3.96	14.7%	7.1%	86	-0.78	3.40	303	59
Clay Rapada L 2015 · 3.84 FIP	34	SU	3.84	14.3%	8.0%	1.7%	.299	—	—	—	—	—	3.00	120	58
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	57
Jamie Walker L 2005 · 3.81 FIP	34	SU	3.81	14.4%	4.8%	2.4%	.270	4.46	16.3%	12.2%	147	+0.65	3.48	442	56
Brandon Mann L 2018 · 3.59 FIP	34	SU	3.59	17.8%	11.4%	1.0%	.232	—	—	—	—	—	3.59	190	55
Heriberto Ruelas L 2016 · 3.75 FIP	34	SU	3.75	15.0%	8.9%	1.4%	.310	3.42	17.2%	10.5%	49	-0.33	2.95	117	55
Tim Byrdak L 2008 · 5.18 FIP	34	SU	5.18	19.8%	11.4%	4.2%	.229	4.30	22.4%	10.5%	138	-0.88	2.85	320	55
Joey Eischen L 2004 · 3.63 FIP	34	SU	3.63	21.2%	7.5%	2.5%	.255	3.37	19.0%	9.1%	51	-0.26	2.13	294	55
Carlos Pulido L 2004 · 4.41 FIP	32	SU	4.41	16.4%	5.5%	3.6%	.341	—	—	—	—	—	2.91	111	54
Ryan Buchter L 2021 · 5.24 FIP	34	SU	5.24	22.9%	13.2%	4.4%	.267	—	—	—	—	—	2.37	296	52
Dan Runzler L 2019 · 4.84 FIP	34	SU	4.84	16.0%	13.0%	2.6%	.284	—	—	—	—	—	2.84	187	51
Doug Creek L 2003 · 5.00 FIP	34	SU	5.00	15.9%	13.0%	2.9%	.255	6.28	17.8%	10.9%	22	+1.28	4.48	277	49
Vic Darensbourg L 2005 · 4.11 FIP	34	SU	4.11	9.4%	5.2%	2.1%	.275	—	—	—	—	—	2.94	287	49
Brady Feigl L 2024 · 4.12 FIP	33	SU	4.12	23.7%	4.7%	4.4%	.312	3.70	22.2%	14.9%	14	-0.42	2.69	212	45

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	2.4	54	21.0%	8.8%	1.03	4.31
Shane Greene ('23)	2.4	59	21.7%	8.6%	1.12	4.50
Ken Dayley ('82-'93, 4 WAR*)	2.9	64	21.8%*	9.1%*	0.97*	4.10*
Anthony Bass ('23)	2.6	52	18.9%	8.6%	0.98	3.91
Aaron Fultz ('07)	2.4	60	19.2%	9.1%	0.94	4.26
Ed Vande Berg ('82-'88, 3 WAR*)	2.6	74	19.6%*	8.8%*	1.07*	4.07*
Jerry Don Gleaton ('79-'92, 2 WAR*)	2.2	64	19.4%*	10.2%*	1.05*	4.44*