Ben Brown

P Chicago Cubs

Age 27 RHP 6'6" / 210 lbs MLB Svc 2.0 · Ctrl thru 2030 peak 1.5 · 2028 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MANArb-1FA 2031

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MLBCHC	15	8	55	3.58	2.99	28.8%	8.6%	1.6
2025	25	MIX2 levels	28	17	117	5.45	3.88	25.2%	6.6%	2.1	K 25.6% · BB 6.8% · FIP 3.97
2026	26	MLBCHC	20	8	68	1.85	2.41	24.5%	7.2%	1.8
2027PROJ	27	MLBCHC	7	7	43	3.79	3.60	26.3%	6.7%	0.9
2028PROJ95% MLB	28	MLBCHC	12	12	72	3.67	3.62	26.1%	6.9%	1.5
2029PROJ95% MLB	29	MLBCHC	11	11	69	3.74	3.78	25.6%	7.1%	1.3

Last 3 seasons WAR 5.6 · Next 3 projected WAR 3.7Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2030Service2.983First FA2031Super-2

2027Arb-1$2M2028Arb-2$5M2029Arb-3$7M2030Arb-4$8M

Skills · percentileStatcast 2026

xwOBA vs84

FB Velo75

K%62

CompsJoaquín Benoit (age 27) · Erik Hiljus (age 28) · K.C. Hunt (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9587vR 79

ERA3.79

FIP3.60

K%26.3%

BB%6.7%

K-BB%19.6%

Proj IP43

Value2027 · WAR

Runs saved vs league avg · 43 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$16M ctrl surplus

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL5555

CMD6060

K†6060

Statcast Percentiles

FB Velo

p7596.3

Whiff%

p6327.3%

p6224.5%

xwOBA vs

p840.279

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status Pre-Arb SUPER-2

MLB Debut 2024

Service 2.983 yrs.days

Team Control Through 2030

First FA Year 2031

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-1	$2M	+0.9	$4M	+$1M
2028	Arb-2	$5M	+1.5	$11M	+$7M
2029	Arb-3	$7M	+1.3	$9M	+$3M
2030	Arb-4	$8M	+1.0	$6M	+$0.3M
Totals		$22M		$30M	+$12M

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)
2017	17	ROK MLE	GCL Phillies	10	0	14	59	10	6	0	0%	1.4	11.5%	12.7%	-1.2%	0.0%	2.57	3.74	—
2017	17	ROK RAW	GCL Phillies	10	0	14	59	10	6	0	0%	1.4	16.9%	10.2%	6.8%	0.0%	2.57	2.96	—
2018	18	ROK MLE	GCL Phillies West	10	8	49	204	62	15	2	80%	4.9	20.7%	9.2%	11.5%	1.4%	3.12	3.27	—
2018	18	ROK RAW	GCL Phillies West	10	8	49	204	62	15	2	80%	4.9	30.4%	7.4%	23.0%	1.0%	3.12	2.02	—
2019	19	A MLE	Lakewood BlueClaws	4	1	14	54	20	3	0	25%	3.4	27.4%	6.6%	20.9%	0.0%	0.00	1.62	—
2019	19	A RAW	Lakewood BlueClaws	4	1	14	54	20	3	0	25%	3.4	37.0%	5.6%	31.5%	0.0%	0.00	0.83	—
2021	21	MIX MLE	2 levels	7	4	16	70	17	8	2	57%	2.3	20.0%	14.9%	5.1%	4.6%	6.19	5.83	—
2021	21	MIX RAW	2 levels	7	4	16	70	17	8	2	57%	2.3	24.3%	11.4%	12.9%	2.9%	6.19	4.10	—
2022	22	MIX MLE	2 levels	23	22	104	434	149	36	10	96%	4.5	26.8%	9.4%	17.5%	3.1%	3.38	3.73	—
2022	22	MIX RAW	2 levels	23	22	104	434	149	36	10	96%	4.5	34.3%	8.3%	26.0%	2.3%	3.38	2.52	—
2023	23	MIX MLE	2 levels	26	19	93	399	130	56	10	73%	3.6	27.6%	12.9%	14.7%	2.8%	4.27	3.97	—
2023	23	MIX RAW	2 levels	26	19	93	399	130	56	10	73%	3.6	32.6%	14.0%	18.5%	2.5%	4.27	3.51	—
2024	24	MLB MLE	Chicago Cubs	15	8	55	222	64	19	5	53%	3.7	28.8%	8.6%	20.3%	2.3%	3.58	3.03	+1.6
2024	24	MLB MLE	Chicago Cubs	15	8	55	222	64	19	5	53%	3.7	28.8%	8.6%	20.3%	2.3%	3.58	3.03	+1.6
2024	24	MLB RAW	Chicago Cubs	15	8	55	222	64	19	5	53%	3.7	28.8%	8.6%	20.3%	2.3%	3.58	2.99	+1.6
2025	25	MIX MLE	2 levels	28	17	117	512	129	34	19	61%	4.2	25.6%	6.8%	18.9%	4.0%	5.45	3.97	+2.0
2025	25	MIX MLE	2 levels	28	17	117	512	129	34	19	61%	4.2	25.6%	6.8%	18.9%	4.0%	5.45	3.97	+2.0
2025	25	MIX RAW	2 levels	28	17	117	512	129	34	19	61%	4.2	25.2%	6.6%	18.6%	3.7%	5.45	3.88	+2.1
2026	26	MLB MLE	Chicago Cubs	20	8	68	265	65	19	2	40%	3.4	24.5%	7.2%	17.4%	0.8%	1.85	2.37	+1.9
2026	26	MLB MLE	Chicago Cubs	20	8	68	265	65	19	2	40%	3.4	24.5%	7.2%	17.4%	0.8%	1.85	2.37	+1.9
2026	26	MLB RAW	Chicago Cubs	20	8	68	265	65	19	2	40%	3.4	24.5%	7.2%	17.4%	0.8%	1.85	2.41	+1.8
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			60	31	230	959	250	70	25	52%	3.8	26.1%	7.3%	18.8%	2.6%	4.15	3.25	+6.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	CHC	7	7	43	182	48	12	5	100%	6.1	26.3%	6.7%	19.6%	2.7%	3.79	3.60	+0.9
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	CHC	12	12	76	320	84	22	9	100%	6.3	26.1%	6.9%	19.3%	2.8%	3.73	3.68	+1.6
2029	29	MLB MLE	CHC	12	12	72	306	78	22	9	100%	6.0	25.6%	7.1%	18.5%	3.0%	3.80	3.84	+1.4
2030	30	MLB MLE	CHC	11	11	68	288	71	21	9	100%	6.2	24.9%	7.4%	17.5%	3.2%	3.95	4.05	+1.1
2031	31	MLB MLE	CHC	10	10	61	258	62	20	9	100%	6.1	24.1%	7.7%	16.4%	3.4%	4.15	4.28	+0.8
2028	28	MLB CTX	CHC	12	12	72	304	79	21	8	100%	6.0	26.1%	6.9%	19.3%	2.7%	3.67	3.62	+1.5
2029	29	MLB CTX	CHC	11	11	69	291	74	21	8	100%	6.3	25.6%	7.1%	18.5%	2.8%	3.74	3.78	+1.3
2030	30	MLB CTX	CHC	10	10	65	274	68	20	8	100%	6.5	24.9%	7.4%	17.5%	3.0%	3.88	3.98	+1.0
2031	31	MLB CTX	CHC	9	9	58	245	59	19	8	100%	6.4	24.1%	7.7%	16.4%	3.3%	4.08	4.21	+0.8
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		102	73	493	2072	531	151	58	72%	4.8	25.6%	7.3%	18.3%	2.8%	3.98	3.39	+12.1
/ 200 IP	—	RAW		41	30	200	840	215	61	24	72%	4.8	25.6%	7.3%	18.3%	2.8%	3.98	3.39	+4.9
Career	—	MLE		143	87	530	2219	565	205	58	61%	3.7	25.5%	9.3%	16.2%	2.6%	3.77	3.57	+10.8
/ 200 IP	—	MLE		54	33	200	837	213	77	22	61%	3.7	25.5%	9.3%	16.2%	2.6%	3.77	3.57	+4.3

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 AAAIowa Cubs · 11 IPFIP 3.42 → 3.56 (+0.14)K% 20.0% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.860	17.20%
BB% (unintentional) /BF	5.00%	—	×0.900	4.50%
HR / BF /BF	2.50%	÷1.125	×1.100	2.44%

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 3.42 → 3.56, 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 AAAIowa Cubs · 73 IPFIP 3.98 → 4.36 (+0.38)K% 31.1% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.06%	—	×0.860	26.71%
BB% (unintentional) /BF	15.53%	—	×0.900	13.98%
HR / BF /BF	2.80%	÷0.965	×1.100	3.18%

Result: FIP 3.98 → 4.36, 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 AATennessee Smokies · 20 IPFIP 1.51 → 2.31 (+0.80)K% 39.0% → 31.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.96%	—	×0.810	31.56%
BB% (unintentional) /BF	7.79%	—	×1.100	8.57%
HR / BF /BF	1.30%	÷1.082	×1.200	1.44%

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 116).

Result: FIP 1.51 → 2.31, 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+Jersey Shore BlueClaws · 73 IPFIP 2.39 → 3.77 (+1.38)K% 35.4% → 27.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.35%	—	×0.770	27.22%
BB% (unintentional) /BF	7.74%	—	×1.150	8.91%
HR / BF /BF	2.36%	÷0.881	×1.250	3.34%

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 76).

Result: FIP 2.39 → 3.77, 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 AATennessee Smokies · 31 IPFIP 2.79 → 3.65 (+0.86)K% 32.1% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.12%	—	×0.810	26.01%
BB% (unintentional) /BF	9.49%	—	×1.100	10.44%
HR / BF /BF	2.19%	÷1.010	×1.200	2.60%

Result: FIP 2.79 → 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).

2021 A+Jersey Shore BlueClaws · 12 IPFIP 4.59 → 5.83 (+1.25)K% 25.9% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.93%	—	×0.770	19.96%
BB% (unintentional) /BF	12.96%	—	×1.150	14.91%
HR / BF /BF	3.70%	÷1.004	×1.250	4.61%

Result: FIP 4.59 → 5.83, 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 ALakewood BlueClaws · 14 IPFIP 0.68 → 1.62 (+0.94)K% 37.0% → 27.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.04%	—	×0.740	27.41%
BB% (unintentional) /BF	5.56%	—	×1.180	6.56%
HR / BF /BF	0.00%	÷0.809	×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 62).

Result: FIP 0.68 → 1.62, 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 ROKGCL Phillies West · 49 IPFIP 2.00 → 3.27 (+1.27)K% 30.4% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.39%	—	×0.680	20.67%
BB% (unintentional) /BF	7.35%	—	×1.250	9.19%
HR / BF /BF	0.98%	÷1.000	×1.400	1.37%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. 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 2.00 → 3.27, 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
Ben Brown (OGILVIE)	—	—	3.60	26.3%	6.7%	2.7%	—	3.85	25.5%	18.4%	216	+0.25	—	—	—
Joaquín Benoit R 2004 · 4.49 FIP	27	SP-	4.49	20.8%	6.8%	4.2%	.302	3.31	23.7%	14.5%	249	-1.18	1.99	1,064	68
Erik Hiljus R 2001 · 3.35 FIP	28	SP-	3.35	23.1%	6.9%	2.4%	.321	6.07	14.1%	4.4%	46	+2.72	3.35	112	64
K.C. Hunt R 2024 · 2.69 FIP	24	SP-	2.69	26.8%	7.1%	1.8%	.277	4.94	17.5%	6.4%	186	+2.25	2.69	288	62
Tylor Megill R 2022 · 3.70 FIP	27	SP-	3.70	25.5%	6.5%	3.5%	.302	3.88	22.8%	12.8%	359	+0.18	3.02	603	61
Junior Guerra R 2015 · 3.18 FIP	30	SW	3.18	26.8%	10.3%	1.9%	.269	4.15	20.8%	10.9%	390	+0.97	3.18	646	59
Garrett Whitlock R 2023 · 3.78 FIP	27	SP-	3.78	23.7%	4.0%	3.9%	.343	2.05	29.5%	22.9%	143	-1.73	1.81	576	58
Rubby De La Rosa R 2016 · 4.09 FIP	27	SP-	4.09	24.3%	8.6%	3.6%	.248	4.13	27.6%	18.3%	42	+0.04	3.75	455	58
Phil Klein R 2016 · 3.10 FIP	27	SW	3.10	24.5%	6.6%	2.2%	.287	—	—	—	—	—	3.10	197	58
Ricky Castro R 2024 · 3.99 FIP	24	SP-	3.99	20.4%	8.6%	2.8%	.287	5.11	19.0%	10.6%	178	+1.12	3.99	241	57
Louis Varland R 2024 · 4.42 FIP	26	SP-	4.42	21.7%	7.2%	4.1%	.329	2.31	28.6%	21.4%	151	-2.11	1.70	689	57
Tiago Da Silva R 2015 · 3.10 FIP	30	SW	3.10	19.6%	4.5%	2.0%	.278	2.38	21.4%	18.5%	98	-0.72	2.21	287	57
David Phelps R 2014 · 4.00 FIP	27	SP-	4.00	18.5%	8.9%	2.5%	.293	3.31	23.8%	15.6%	254	-0.69	2.50	672	57
Chase Whitley R 2016 · 4.10 FIP	27	SP-	4.10	19.5%	7.0%	3.2%	.217	3.22	18.0%	11.8%	81	-0.88	3.09	235	55
TJ Shook R 2024 · 4.15 FIP	26	SW	4.15	23.7%	8.7%	3.5%	.317	3.92	20.0%	11.1%	107	-0.23	3.35	452	55
Heath Holder R 2019 · 3.26 FIP	26	SW	3.26	21.9%	7.5%	1.9%	.263	5.51	19.8%	4.9%	85	+2.25	2.94	367	55
Raynel Espinal R 2019 · 3.90 FIP	27	SP-	3.90	22.4%	7.1%	3.2%	.313	4.01	22.3%	12.4%	224	+0.11	2.48	507	55
Kutter Crawford R 2023 · 3.62 FIP	27	SP-	3.62	25.6%	6.8%	3.3%	.265	4.53	23.1%	16.4%	184	+0.91	3.30	741	54
Felipe Paulino R 2011 · 3.63 FIP	27	SP-	3.63	22.2%	8.8%	2.4%	.333	4.36	21.3%	11.3%	56	+0.73	3.24	554	53
Yoshinobu Yamamoto R 2024 · 2.45 FIP	25	SP	2.45	28.5%	6.0%	1.8%	.303	2.98	27.5%	20.3%	359	+0.53	2.45	449	53
Matt Shoemaker R 2014 · 3.12 FIP	27	SP-	3.12	22.8%	4.4%	2.5%	.283	4.02	21.0%	15.3%	373	+0.90	3.12	728	53

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	2.8	69	25.7%	7.2%	1.10	3.99
Joe Sambito ('76-'87, 8 WAR*)	3.1	70	26.8%*	7.5%*	1.06*	3.65*
Bob James ('78-'87, 4 WAR*)	2.0	68	26.3%*	8.8%*	1.07*	4.04*
Joe Beckwith ('79-'86, 3 WAR*)	2.1	70	24.9%*	8.2%*	1.13*	3.96*
Eric Gagne ('08)	3.2	80	27.0%	8.5%	1.06	3.47
Daniel Hudson ('24)	4.3	71	22.8%	7.7%	1.01	3.74
Addison Reed ('18)	2.3	66	24.5%	6.2%	1.04	3.53