Brian Keller

P Lehigh Valley IronPigs

Age 33 RHP 6'3" / 210 lbs AAA peak 0.1 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2021	27	AAAScranton/Wilk…	26	11	55	2.77	3.95	25.7%	18.2%	—	K 22.6% · BB 19.1% · FIP 4.23
2022	28	AAABOS	31	20	113	3.27	3.17	26.9%	11.1%	—	K 23.6% · BB 11.6% · FIP 3.67
2026	32	MIX3 levels	20	19	73	6.19	5.32	19.0%	9.2%	0.1	K 15.8% · BB 8.6% · FIP 5.62
2027PROJ	33	MLBPHI	5	5	28	5.25	5.25	16.6%	8.6%	0.0
2028PROJ62% MLB	34	MLBPHI	4	4	22	5.32	5.43	16.7%	9.2%	-0.0

Last 3 seasons WAR 0.1 · Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.1 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsMiguel Ruiz (age 31) · Rolando Valdez (age 33) · Sergio Valenzuela (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 117

ERA5.25

FIP5.25

K%16.6%

BB%8.6%

K-BB%7.9%

Proj IP42

Value2027 · WAR

Runs saved vs league avg · 42 IP

Grades · Contract

Scouting Grades

K†4040

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	22	ROK MLE	Pulaski Yankees	12	2	39	149	48	6	0	17%	3.2	21.9%	5.0%	16.9%	0.0%	0.92	1.89	—
2016	22	ROK RAW	Pulaski Yankees	12	2	39	149	48	6	0	17%	3.2	32.2%	4.0%	28.2%	0.0%	0.92	1.10	—
2017	23	MIX MLE	2 levels	24	24	144	586	157	28	6	100%	6.0	20.2%	5.6%	14.6%	1.4%	3.12	2.87	—
2017	23	MIX RAW	2 levels	24	24	144	586	157	28	6	100%	6.0	26.8%	4.8%	22.0%	1.0%	3.12	2.04	—
2018	24	AA MLE	Trenton Thunder	22	21	125	526	114	37	13	95%	5.7	17.6%	7.7%	9.8%	2.9%	3.74	4.17	—
2018	24	AA RAW	Trenton Thunder	22	21	125	526	114	37	13	95%	5.7	21.7%	7.0%	14.6%	2.5%	3.74	3.52	—
2019	25	MIX MLE	2 levels	12	12	70	290	58	19	4	100%	5.8	16.8%	7.1%	9.8%	1.5%	4.11	3.39	—
2019	25	MIX RAW	2 levels	12	12	70	290	58	19	4	100%	5.8	20.0%	6.6%	13.4%	1.4%	4.11	3.00	—
2021	27	AAA MLE	Scranton/Wilkes-Barre RailRiders	26	11	55	253	65	46	3	42%	2.1	22.6%	19.1%	3.5%	1.1%	2.77	4.23	—
2021	27	AAA RAW	Scranton/Wilkes-Barre RailRiders	26	11	55	253	65	46	3	42%	2.1	25.7%	18.2%	7.5%	1.2%	2.77	3.95	—
2022	28	AAA MLE	Worcester Red Sox	31	20	113	469	126	52	8	65%	3.6	23.6%	11.6%	12.0%	2.0%	3.27	3.67	—
2022	28	AAA RAW	Worcester Red Sox	31	20	113	469	126	52	8	65%	3.6	26.9%	11.1%	15.8%	1.7%	3.27	3.17	—
2026	32	MIX MLE	3 levels	20	19	73	327	62	30	15	95%	3.6	15.8%	8.6%	7.2%	5.0%	6.19	5.62	-0.2
2026	32	MIX MLE	3 levels	20	19	73	327	62	30	15	95%	3.6	15.8%	8.6%	7.2%	5.0%	6.19	5.62	-0.2
2026	32	MIX RAW	3 levels	20	19	73	327	62	30	15	95%	3.6	19.0%	9.2%	9.8%	4.6%	6.19	5.32	+0.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			1	0	3	11	3	0	1	0%	3.0	27.3%	0.0%	27.3%	9.1%	3.00	5.43	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	PHI	5	5	28	118	20	10	4	100%	5.6	16.6%	8.6%	7.9%	3.8%	5.25	5.25	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	PHI	6	6	36	151	25	14	6	100%	6.0	16.7%	9.2%	7.5%	4.0%	5.32	5.43	-0.0
2028	34	MLB CTX	PHI	4	4	22	93	16	9	4	100%	5.5	16.7%	9.2%	7.5%	4.0%	5.32	5.43	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	4	25	105	19	9	5	80%	5.0	17.8%	8.2%	9.6%	4.5%	5.04	5.13	+0.1
/ 200 IP	—	RAW		37	29	200	831	151	71	40	79%	5.4	17.8%	8.2%	9.6%	4.5%	5.04	5.13	+0.6
Career	—	MLE		147	109	619	2600	512	232	56	74%	4.2	19.7%	8.9%	10.7%	2.2%	3.58	3.76	-0.0
/ 200 IP	—	MLE		47	35	200	840	165	75	18	74%	4.2	19.7%	8.9%	10.7%	2.2%	3.58	3.76	-0.1

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 AAALehigh Valley IronPigs · 67 IPFIP 5.27 → 5.62 (+0.35)K% 18.4% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.36%	—	×0.860	15.79%
BB% (unintentional) /BF	9.51%	—	×0.900	8.56%
HR / BF /BF	4.59%	÷1.000	×1.100	5.05%

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 5.27 → 5.62, 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).

2022 AAAWorcester Red Sox · 113 IPFIP 3.17 → 3.67 (+0.50)K% 26.9% → 23.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.87%	—	×0.880	23.64%
BB% (unintentional) /BF	11.09%	—	×1.050	11.64%
HR / BF /BF	1.71%	÷0.939	×1.100	2.00%

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 88).

Result: FIP 3.17 → 3.67, 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).

2021 AAAScranton/Wilkes-Barre RailRiders · 55 IPFIP 3.88 → 4.23 (+0.35)K% 25.7% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.69%	—	×0.880	22.61%
BB% (unintentional) /BF	18.18%	—	×1.050	19.09%
HR / BF /BF	1.19%	÷1.149	×1.100	1.14%

Result: FIP 3.88 → 4.23, 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 AATrenton Thunder · 43 IPFIP 2.52 → 2.99 (+0.47)K% 19.8% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.76%	—	×0.810	16.01%
BB% (unintentional) /BF	5.99%	—	×1.100	6.59%
HR / BF /BF	0.60%	÷0.960	×1.200	0.75%

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 92).

Result: FIP 2.52 → 2.99, 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).

2019 AAAScranton/Wilkes-Barre RailRiders · 27 IPFIP 3.65 → 3.92 (+0.27)K% 20.3% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.33%	—	×0.880	17.89%
BB% (unintentional) /BF	7.32%	—	×1.050	7.68%
HR / BF /BF	2.44%	÷1.087	×1.100	2.47%

Result: FIP 3.65 → 3.92, 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 AATrenton Thunder · 125 IPFIP 3.52 → 4.17 (+0.66)K% 21.7% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.67%	—	×0.810	17.56%
BB% (unintentional) /BF	7.03%	—	×1.100	7.74%
HR / BF /BF	2.47%	÷1.034	×1.200	2.87%

Result: FIP 3.52 → 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).

2017 ACharleston RiverDogs · 82 IPFIP 2.13 → 3.08 (+0.95)K% 26.9% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.95%	—	×0.740	19.94%
BB% (unintentional) /BF	5.09%	—	×1.180	6.01%
HR / BF /BF	1.20%	÷0.945	×1.300	1.65%

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 89).

Result: FIP 2.13 → 3.08, 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 A+Tampa Yankees · 62 IPFIP 1.84 → 2.58 (+0.74)K% 26.6% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.59%	—	×0.770	20.47%
BB% (unintentional) /BF	4.37%	—	×1.150	5.02%
HR / BF /BF	0.79%	÷0.949	×1.250	1.05%

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 90).

Result: FIP 1.84 → 2.58, 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
Brian Keller (OGILVIE)	—	—	5.25	16.6%	8.6%	3.8%	—	5.43	16.7%	7.5%	36	+0.18	—	—	—
Miguel Ruiz R 2017 · 5.60 FIP	31	SP	5.60	10.6%	11.0%	3.6%	.279	—	—	—	—	—	5.60	117	70
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	69
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	66
Walter Silva R 2009 · 5.72 FIP	32	SP	5.72	9.1%	12.4%	3.3%	.330	—	—	—	—	—	3.67	453	66
Marco Quevedo R 2019 · 5.17 FIP	32	SP-	5.17	13.6%	11.4%	3.2%	.344	—	—	—	—	—	4.13	300	66
Elih Villanueva R 2017 · 5.48 FIP	31	SP	5.48	14.1%	6.0%	5.1%	.365	—	—	—	—	—	3.83	225	65
Diego Moreno R 2019 · 4.08 FIP	32	SP	4.08	12.4%	6.9%	2.1%	.376	4.75	18.6%	9.2%	30	+0.67	2.29	187	65
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	63
Deck McGuire R 2022 · 5.12 FIP	33	SP-	5.12	15.7%	13.1%	3.1%	.279	—	—	—	—	—	3.41	622	62
Osvaldo Fernandez R 2001 · 4.53 FIP	32	SP-	4.53	9.6%	8.2%	2.2%	.324	—	—	—	—	—	4.25	387	62
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	61
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	61
Thad Weber R 2017 · 5.25 FIP	32	SP-	5.25	13.2%	4.4%	4.9%	.398	—	—	—	—	—	4.40	378	59
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	57
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	57
Scott Carroll R 2017 · 5.71 FIP	32	SP	5.71	14.4%	8.6%	5.0%	.300	—	—	—	—	—	3.92	377	56
Cesar Carrillo R 2017 · 4.97 FIP	33	SP	4.97	12.0%	11.9%	2.5%	.320	6.22	11.0%	1.8%	66	+1.25	4.14	336	56
Jason Simontacchi R 2007 · 4.96 FIP	33	SP	4.96	13.0%	5.9%	4.0%	.331	—	—	—	—	—	4.79	356	55
Kodai Senga R 2024 · 4.69 FIP	31	SP	4.69	14.9%	13.8%	2.0%	.324	4.51	24.0%	11.5%	175	-0.18	3.40	352	54
Yohan Pino R 2017 · 5.33 FIP	33	SP-	5.33	15.2%	3.6%	5.6%	.296	—	—	—	—	—	3.84	193	54

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	0.4	40	17.0%	8.6%	1.57	5.20
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Ricky Stone ('07)	1.3	64	15.2%	8.0%	1.55	4.68
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*