Brandon Eisert

P Pittsburgh Pirates

Age 29 LHP 6'2" / 210 lbs MLB peak 0.2 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	45	4	60	3.88	3.60	26.9%	9.9%	0.7	K 25.0% · BB 8.3% · FIP 3.92
2025	27	MIX2 levels	74	3	72	4.40	3.97	24.5%	6.4%	0.5	K 24.2% · BB 6.2% · FIP 3.96
2026	28	MIX2 levels	63	7	71	4.94	3.04	26.4%	7.0%	1.3	K 25.0% · BB 6.8% · FIP 3.24
2027PROJ	29	MLBPIT	47	0	49	4.11	4.10	23.7%	6.9%	0.3
2028PROJ95% MLB	30	MLBPIT	38	0	40	4.23	4.31	23.0%	7.2%	0.1
2029PROJ95% MLB	31	MLBPIT	30	0	31	4.42	4.54	22.2%	7.6%	0.0

Last 3 seasons WAR 2.5 · Next 3 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%70

xwOBA vs63

FB Velo10

CompsYuki Matsui (age 28) · Ryan O'Rourke (age 28) · Matt Thornton (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 9098vR 106

ERA4.11

FIP4.10

K%23.7%

BB%6.9%

K-BB%16.8%

Proj IP52

Value2027 · WAR

Runs saved vs league avg · 52 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL5050

CMD5050

K†5555

Statcast Percentiles

FB Velo

p1090.0

Whiff%

p8430.6%

p7025.9%

xwOBA vs

p630.299

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	23	MIX MLE	3 levels	32	0	63	271	82	19	5	0%	2.0	23.2%	8.0%	15.3%	2.7%	3.55	3.61	—
2021	23	MIX RAW	3 levels	32	0	63	271	82	19	5	0%	2.0	30.3%	7.0%	23.2%	1.8%	3.55	2.44	—
2022	24	AAA MLE	Buffalo Bisons	45	5	61	248	77	15	8	11%	1.3	27.3%	6.4%	21.0%	3.7%	3.41	3.64	—
2022	24	AAA RAW	Buffalo Bisons	45	5	61	248	77	15	8	11%	1.3	31.0%	6.0%	25.0%	3.2%	3.41	3.02	—
2023	25	AAA MLE	Buffalo Bisons	59	1	69	290	76	25	9	2%	1.2	22.5%	7.8%	14.8%	3.7%	4.17	4.22	—
2023	25	AAA RAW	Buffalo Bisons	59	1	69	290	76	25	9	2%	1.2	26.2%	8.6%	17.6%	3.1%	4.17	3.68	—
2024	26	MIX MLE	2 levels	45	4	60	253	68	25	7	9%	1.3	25.0%	8.3%	16.7%	3.4%	3.88	3.92	+0.4
2024	26	MIX MLE	2 levels	45	4	60	253	68	25	7	9%	1.3	25.0%	8.3%	16.7%	3.4%	3.88	3.92	+0.4
2024	26	MIX RAW	2 levels	45	4	60	253	68	25	7	9%	1.3	26.9%	9.9%	17.0%	2.8%	3.88	3.60	+0.7
2025	27	MIX MLE	2 levels	74	3	72	314	77	20	12	4%	1.0	24.2%	6.2%	18.0%	3.9%	4.40	3.96	+0.5
2025	27	MIX MLE	2 levels	74	3	72	314	77	20	12	4%	1.0	24.2%	6.2%	18.0%	3.9%	4.40	3.96	+0.5
2025	27	MIX RAW	2 levels	74	3	72	314	77	20	12	4%	1.0	24.5%	6.4%	18.2%	3.8%	4.40	3.97	+0.5
2026	28	MIX MLE	2 levels	63	7	71	299	79	21	7	11%	1.1	25.0%	6.8%	18.2%	2.5%	4.94	3.24	+1.1
2026	28	MIX MLE	2 levels	63	7	71	299	79	21	7	11%	1.1	25.0%	6.8%	18.2%	2.5%	4.94	3.24	+1.1
2026	28	MIX RAW	2 levels	63	7	71	299	79	21	7	11%	1.1	26.4%	7.0%	19.4%	2.3%	4.94	3.04	+1.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			115	7	120	521	125	37	18	6%	1.0	24.0%	7.1%	16.9%	3.5%	4.79	3.89	+0.9
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	PIT	47	0	49	207	49	14	7	0%	1.0	23.7%	6.9%	16.8%	3.2%	4.11	4.10	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	PIT	40	0	42	176	41	13	6	0%	1.0	23.0%	7.2%	15.8%	3.4%	4.23	4.31	+0.1
2029	31	MLB MLE	PIT	31	0	33	138	31	10	5	0%	1.1	22.2%	7.6%	14.6%	3.6%	4.42	4.54	+0.0
2028	30	MLB CTX	PIT	38	0	40	169	39	12	6	0%	1.1	23.0%	7.2%	15.8%	3.4%	4.23	4.31	+0.1
2029	31	MLB CTX	PIT	30	0	31	131	29	10	5	0%	1.0	22.2%	7.6%	14.6%	3.6%	4.42	4.54	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		182	7	191	820	193	59	28	4%	1.1	23.5%	7.2%	16.3%	3.5%	4.61	3.93	+1.4
/ 200 IP	—	RAW		191	7	200	858	202	62	29	4%	1.0	23.5%	7.2%	16.3%	3.5%	4.61	3.93	+1.5
Career	—	MLE		318	20	396	1675	410	121	56	6%	1.2	24.5%	7.2%	17.3%	3.3%	4.09	3.77	+1.1
/ 200 IP	—	MLE		161	10	200	846	207	61	28	6%	1.2	24.5%	7.2%	17.3%	3.3%	4.09	3.77	+1.1

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 AAAIndianapolis Indians · 27 IPFIP 2.10 → 2.39 (+0.29)K% 27.3% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.860	23.45%
BB% (unintentional) /BF	6.36%	—	×0.900	5.73%
HR / BF /BF	0.91%	÷1.000	×1.100	1.00%

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 2.10 → 2.39, 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 AAABuffalo Bisons · 54 IPFIP 3.51 → 3.92 (+0.41)K% 29.1% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.07%	—	×0.860	25.00%
BB% (unintentional) /BF	9.25%	—	×0.900	8.33%
HR / BF /BF	3.08%	÷0.990	×1.100	3.43%

Result: FIP 3.51 → 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).

2023 AAABuffalo Bisons · 69 IPFIP 3.68 → 4.22 (+0.54)K% 26.2% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.21%	—	×0.860	22.54%
BB% (unintentional) /BF	8.62%	—	×0.900	7.76%
HR / BF /BF	3.10%	÷0.916	×1.100	3.73%

Result: FIP 3.68 → 4.22, 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).

2022 AAABuffalo Bisons · 61 IPFIP 3.01 → 3.64 (+0.63)K% 31.0% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.05%	—	×0.880	27.32%
BB% (unintentional) /BF	6.05%	—	×1.050	6.35%
HR / BF /BF	3.23%	÷0.951	×1.100	3.73%

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 90).

Result: FIP 3.01 → 3.64, 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+Vancouver Canadians · 47 IPFIP 2.95 → 4.19 (+1.23)K% 29.6% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.56%	—	×0.770	22.76%
BB% (unintentional) /BF	7.88%	—	×1.150	9.06%
HR / BF /BF	2.46%	÷0.909	×1.250	3.39%

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 82).

Result: FIP 2.95 → 4.19, 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 AANew Hampshire Fisher Cats · 14 IPFIP 0.95 → 1.49 (+0.54)K% 30.9% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.91%	—	×0.810	25.04%
BB% (unintentional) /BF	3.64%	—	×1.100	4.00%
HR / BF /BF	0.00%	÷0.973	×1.200	0.00%

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 95).

Result: FIP 0.95 → 1.49, 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
Brandon Eisert (OGILVIE)	—	—	4.10	23.7%	6.9%	3.2%	—	4.41	22.6%	15.3%	75	+0.31	—	—	—
Yuki Matsui L 2024 · 3.63 FIP	28	SU	3.63	26.8%	8.9%	3.0%	.242	4.25	23.9%	12.6%	140	+0.62	3.63	203	77
Ryan O'Rourke L 2016 · 3.05 FIP	28	SU	3.05	23.4%	6.7%	1.9%	.284	4.08	22.1%	7.8%	56	+1.03	3.05	145	76
Matt Thornton L 2006 · 3.43 FIP	29	SU	3.43	21.6%	7.5%	2.2%	.263	2.61	27.2%	20.5%	196	-0.82	1.71	663	76
Tony Sipp L 2012 · 4.57 FIP	29	SU	4.57	21.9%	9.4%	3.9%	.252	3.22	28.6%	20.4%	143	-1.35	2.22	504	75
Sammy Solís L 2018 · 4.39 FIP	29	SU	4.39	24.9%	9.6%	4.0%	.330	4.05	26.2%	17.3%	23	-0.34	2.51	190	74
Jerry Blevins L 2013 · 3.81 FIP	29	SU	3.81	21.2%	6.1%	3.1%	.234	2.51	28.2%	21.3%	99	-1.30	2.36	486	73
Craig Breslow L 2010 · 3.96 FIP	29	SU	3.96	23.4%	8.2%	3.2%	.221	3.44	18.2%	10.5%	182	-0.52	2.41	616	72
Tyler Webb L 2019 · 4.28 FIP	29	SU	4.28	21.7%	9.0%	3.4%	.178	4.75	22.1%	8.2%	60	+0.47	3.10	337	72
Hideki Okajima L 2007 · 3.05 FIP	31	SU	3.05	23.2%	5.5%	2.2%	.234	3.87	20.2%	12.6%	169	+0.82	3.05	238	71
Scott Alexander L 2018 · 3.30 FIP	29	SU	3.30	20.9%	9.3%	1.4%	.290	4.64	13.3%	5.0%	45	+1.34	2.90	427	70
Matt Grace L 2018 · 3.13 FIP	29	SU	3.13	19.4%	4.5%	2.0%	.273	5.21	17.0%	12.1%	47	+2.08	2.68	289	70
Nick Hagadone L 2015 · 3.65 FIP	29	SU	3.65	22.6%	8.9%	2.4%	.329	3.74	22.6%	13.3%	33	+0.09	2.97	141	70
Buddy Boshers L 2017 · 4.56 FIP	29	SU	4.56	18.9%	8.0%	3.7%	.300	3.47	24.1%	15.6%	112	-1.09	2.76	239	70
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	70
Josh Smoker L 2018 · 3.66 FIP	29	SU	3.66	22.1%	8.4%	2.5%	.318	6.58	14.2%	3.4%	14	+2.92	2.71	230	70
Clay Rapada L 2011 · 4.34 FIP	30	SU	4.34	26.1%	10.1%	3.9%	.268	3.00	24.5%	14.2%	38	-1.34	3.00	120	70
Sean Gilmartin L 2019 · 4.21 FIP	29	SU	4.21	24.1%	8.9%	3.7%	.279	—	—	—	—	—	2.33	386	69
Andrew Chafin L 2019 · 3.11 FIP	29	SU	3.11	30.2%	8.0%	2.8%	.346	2.88	25.7%	18.4%	126	-0.23	2.42	545	69
Damaso Marte L 2004 · 4.27 FIP	29	SU	4.27	22.4%	9.9%	3.3%	.236	3.28	25.9%	15.1%	149	-0.99	2.41	495	69
Tyler Olson L 2019 · 3.86 FIP	29	SU	3.86	20.0%	10.0%	2.1%	.326	3.96	21.6%	12.9%	31	+0.10	3.15	263	69

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	1.2	49	23.5%	7.7%	1.32	4.50
Chris Hatcher ('18)	1.3	53	22.9%	8.4%	1.32	4.65
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Ian Krol ('21)	1.0	42	21.2%	8.8%	1.25	4.49
Pete Ladd ('79-'86, 0 WAR*)	1.4	72	24.6%*	7.8%*	1.53*	4.42*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Tom Dukes ('67-'72, -2 WAR*)	1.1	43	22.7%*	8.7%*	1.16*	5.37*