Brendon Little

P Buffalo Bisons

Age 30 LHP 6'2" / 195 lbs AAA peak 0.4 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	65	0	63	3.86	4.04	22.4%	11.0%	0.4	K 21.1% · BB 10.6% · FIP 4.06
2025	28	MLBTOR	79	0	68	3.03	2.62	30.8%	13.9%	1.6
2026	29	MIX2 levels	60	1	60	4.33	3.76	33.2%	15.9%	0.6	K 30.8% · BB 15.0% · FIP 3.85
2027PROJ	30	MLBTOR	50	0	52	3.93	3.97	32.5%	14.7%	0.4
2028PROJ95% MLB	31	MLBTOR	37	0	39	4.09	4.20	31.7%	15.0%	0.2
2029PROJ95% MLB	32	MLBTOR	29	0	30	4.31	4.46	30.9%	15.4%	0.0

Last 3 seasons WAR 2.5 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%90

xwOBA vs81

FB Velo71

Form2.04 ERA (proj 3.93) · K 39.0% (proj 32.5%) · BB 22.1% (proj 14.7%) · last 90d · 18 IP through Oct 27

CompsJustin Wilson (age 30) · Mike Dunn (age 30) · Anthony Gose (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 92101vR 109

ERA3.93

FIP3.97

K%32.5%

BB%14.7%

K-BB%17.8%

Proj IP53

Value2027 · WAR

Runs saved vs league avg · 53 IP

Grades · Statcast · Contract

Scouting Grades

STUF7575

CTRL3030

CMD4545

K†7070

Statcast Percentiles

FB Velo

p7196.0

Whiff%

p9041.6%

p9033.3%

xwOBA vs

p810.282

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)
2018	21	A MLE	South Bend Cubs	22	21	101	454	90	43	8	95%	4.6	14.7%	11.2%	3.5%	2.6%	5.15	4.70	—
2018	21	A RAW	South Bend Cubs	22	21	101	454	90	43	8	95%	4.6	19.8%	9.5%	10.4%	1.8%	5.15	3.62	—
2019	22	MIX MLE	3 levels	12	12	55	233	57	26	4	100%	4.6	17.7%	12.6%	5.2%	1.3%	3.58	3.90	—
2019	22	MIX RAW	3 levels	12	12	55	233	57	26	4	100%	4.6	24.5%	11.2%	13.3%	1.7%	3.58	3.39	—
2021	24	MIX MLE	2 levels	26	0	42	181	53	19	4	0%	1.6	24.7%	11.4%	13.4%	2.4%	3.24	3.76	—
2021	24	MIX RAW	2 levels	26	0	42	181	53	19	4	0%	1.6	29.3%	10.5%	18.8%	2.2%	3.24	3.17	—
2022	25	MIX MLE	2 levels	37	0	51	229	49	26	5	0%	1.4	19.3%	11.8%	7.6%	2.0%	4.76	4.05	+0.3
2022	25	MIX RAW	2 levels	37	0	51	229	49	26	5	0%	1.4	21.4%	11.4%	10.0%	2.2%	4.76	3.98	+0.3
2023	26	AAA MLE	Iowa Cubs	50	2	73	316	73	38	6	4%	1.5	19.9%	10.8%	9.0%	2.2%	4.05	3.98	—
2023	26	AAA RAW	Iowa Cubs	50	2	73	316	73	38	6	4%	1.5	23.1%	12.0%	11.1%	1.9%	4.05	3.73	—
2024	27	MIX MLE	2 levels	65	0	63	272	61	30	7	0%	1.0	21.1%	10.6%	10.6%	2.6%	3.86	4.06	+0.4
2024	27	MIX MLE	2 levels	65	0	63	272	61	30	7	0%	1.0	21.1%	10.6%	10.6%	2.6%	3.86	4.06	+0.4
2024	27	MIX RAW	2 levels	65	0	63	272	61	30	7	0%	1.0	22.4%	11.0%	11.4%	2.6%	3.86	4.04	+0.4
2025	28	MLB MLE	Toronto Blue Jays	79	0	68	295	91	41	2	0%	0.9	30.8%	13.9%	16.9%	0.7%	3.03	2.63	+1.6
2025	28	MLB MLE	Toronto Blue Jays	79	0	68	295	91	41	2	0%	0.9	30.8%	13.9%	16.9%	0.7%	3.03	2.63	+1.6
2025	28	MLB RAW	Toronto Blue Jays	79	0	68	295	91	41	2	0%	0.9	30.8%	13.9%	16.9%	0.7%	3.03	2.62	+1.6
2026	29	MIX MLE	2 levels	60	1	60	271	90	43	7	2%	1.0	30.8%	15.0%	15.9%	2.7%	4.33	3.85	+0.5
2026	29	MIX MLE	2 levels	60	1	60	271	90	43	7	2%	1.0	30.8%	15.0%	15.9%	2.7%	4.33	3.85	+0.5
2026	29	MIX RAW	2 levels	60	1	60	271	90	43	7	2%	1.0	33.2%	15.9%	17.3%	2.6%	4.33	3.76	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			159	0	143	626	171	78	15	0%	0.9	27.3%	12.5%	14.9%	2.4%	4.09	3.71	+1.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	TOR	50	0	52	220	71	32	5	0%	1.0	32.5%	14.7%	17.8%	2.5%	3.93	3.97	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	TOR	40	0	42	175	56	26	5	0%	1.0	31.7%	15.0%	16.7%	2.7%	4.09	4.20	+0.2
2029	32	MLB MLE	TOR	30	0	32	135	42	21	4	0%	1.1	30.9%	15.4%	15.5%	3.0%	4.31	4.46	+0.0
2030	33	MLB MLE	TOR	22	0	23	98	30	16	3	0%	1.1	30.1%	15.9%	14.2%	3.2%	4.57	4.74	-0.1
2028	31	MLB CTX	TOR	37	0	39	165	52	25	4	0%	1.1	31.7%	15.0%	16.7%	2.7%	4.09	4.20	+0.2
2029	32	MLB CTX	TOR	29	0	30	127	39	20	4	0%	1.0	30.9%	15.4%	15.5%	3.0%	4.31	4.46	+0.0
2030	33	MLB CTX	TOR	21	0	22	93	28	15	3	0%	1.0	30.1%	15.9%	14.2%	3.2%	4.57	4.74	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		246	0	235	1014	291	138	26	0%	1.0	28.7%	13.6%	15.2%	2.6%	4.16	3.82	+2.0
/ 200 IP	—	RAW		210	0	200	863	248	118	22	0%	1.0	28.7%	13.6%	15.2%	2.6%	4.16	3.82	+1.7
Career	—	MLE		351	36	514	2251	492	272	47	10%	1.5	21.8%	12.1%	9.8%	2.1%	4.09	3.92	+1.6
/ 200 IP	—	MLE		136	14	200	875	191	106	18	10%	1.5	21.8%	12.1%	9.8%	2.1%	4.09	3.92	+1.3

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.

2026 AAABuffalo Bisons · 32 IPFIP 3.28 → 3.53 (+0.25)K% 33.1% → 28.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.09%	—	×0.860	28.46%
BB% (unintentional) /BF	17.27%	—	×0.900	15.54%
HR / BF /BF	1.44%	÷1.000	×1.100	1.58%

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 3.28 → 3.53, 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 · 17 IPFIP 2.51 → 2.68 (+0.17)K% 31.6% → 27.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.65%	—	×0.860	27.22%
BB% (unintentional) /BF	16.46%	—	×0.900	14.81%
HR / BF /BF	0.00%	÷0.990	×1.100	0.00%

Result: FIP 2.51 → 2.68, 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 3.71 → 3.98 (+0.27)K% 23.1% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.10%	—	×0.860	19.87%
BB% (unintentional) /BF	12.03%	—	×0.900	10.82%
HR / BF /BF	1.90%	÷0.965	×1.100	2.16%

Result: FIP 3.71 → 3.98, 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 AAAIowa Cubs · 50 IPFIP 3.65 → 4.05 (+0.40)K% 22.0% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.97%	—	×0.880	19.34%
BB% (unintentional) /BF	11.21%	—	×1.050	11.77%
HR / BF /BF	1.79%	÷0.996	×1.100	1.98%

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 99).

Result: FIP 3.65 → 4.05, 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 AATennessee Smokies · 23 IPFIP 3.44 → 4.20 (+0.76)K% 27.6% → 22.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.55%	—	×0.810	22.32%
BB% (unintentional) /BF	12.24%	—	×1.100	13.47%
HR / BF /BF	2.04%	÷1.050	×1.200	2.33%

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 110).

Result: FIP 3.44 → 4.20, 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 AAAIowa Cubs · 18 IPFIP 2.85 → 3.24 (+0.39)K% 31.3% → 27.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.33%	—	×0.880	27.57%
BB% (unintentional) /BF	8.43%	—	×1.050	8.86%
HR / BF /BF	2.41%	÷1.081	×1.100	2.45%

Result: FIP 2.85 → 3.24, 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 ASouth Bend Cubs · 28 IPFIP 2.69 → 3.43 (+0.74)K% 21.9% → 16.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.93%	—	×0.740	16.23%
BB% (unintentional) /BF	11.40%	—	×1.180	13.46%
HR / BF /BF	0.00%	÷0.914	×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 83).

Result: FIP 2.69 → 3.43, 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 A+Myrtle Beach Pelicans · 20 IPFIP 3.43 → 4.49 (+1.06)K% 25.6% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.56%	—	×0.770	19.68%
BB% (unintentional) /BF	10.00%	—	×1.150	11.50%
HR / BF /BF	2.22%	÷0.956	×1.250	2.91%

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 91).

Result: FIP 3.43 → 4.49, 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
Brendon Little (OGILVIE)	—	—	3.97	32.5%	14.7%	2.5%	—	4.42	31.0%	15.7%	97	+0.45	—	—	—
Justin Wilson L 2018 · 3.56 FIP	30	SU	3.56	29.2%	13.6%	2.2%	.308	3.85	24.0%	13.5%	93	+0.29	2.49	554	73
Mike Dunn L 2015 · 3.75 FIP	30	SU	3.75	27.7%	11.9%	2.7%	.294	4.21	22.5%	10.9%	110	+0.46	2.82	432	69
Anthony Gose L 2021 · 4.69 FIP	30	SU	4.69	29.9%	19.7%	2.9%	.250	4.08	27.7%	15.5%	66	-0.61	3.78	233	69
George Sherrill L 2007 · 2.82 FIP	30	SU	2.82	30.8%	8.8%	2.2%	.226	3.61	20.7%	11.3%	159	+0.79	2.74	323	68
Scott Sauerbeck L 2002 · 2.79 FIP	30	SU	2.79	27.5%	9.0%	1.6%	.291	4.27	20.4%	8.0%	92	+1.48	2.79	386	68
Brian Moran L 2019 · 3.40 FIP	30	SU	3.40	26.9%	10.0%	2.4%	.269	2.99	25.5%	18.5%	99	-0.41	1.80	421	67
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	66
Kyle Regnault L 2018 · 3.82 FIP	29	SU	3.82	27.6%	9.7%	3.3%	.367	—	—	—	—	—	2.88	204	65
Sammy Solís L 2019 · 4.05 FIP	30	SU	4.05	26.2%	8.9%	3.7%	.291	—	—	—	—	—	2.51	190	64
Jason Christiansen L 2000 · 3.08 FIP	30	SU	3.08	25.2%	10.5%	1.4%	.288	4.28	20.1%	10.6%	62	+1.20	2.22	429	64
Doug Creek L 2000 · 4.57 FIP	31	SU	4.57	27.5%	13.6%	3.8%	.267	4.75	21.9%	7.8%	132	+0.18	4.48	277	64
Hung-Chih Kuo L 2011 · 4.46 FIP	30	SU	4.46	28.3%	16.5%	3.0%	.303	—	—	—	—	—	1.63	287	64
James Pazos L 2021 · 4.41 FIP	30	SU	4.41	26.0%	12.0%	3.6%	.350	—	—	—	—	—	2.55	261	63
Damaso Marte L 2005 · 3.97 FIP	30	SU	3.97	25.4%	13.6%	2.4%	.320	2.99	26.1%	16.8%	169	-0.98	2.41	495	63
Brian Fuentes L 2006 · 3.47 FIP	30	SU	3.47	26.6%	8.0%	2.9%	.246	3.22	24.6%	15.8%	179	-0.25	2.08	602	62
Cory Luebke L 2016 · 3.88 FIP	31	SU	3.88	26.4%	9.1%	3.4%	.354	—	—	—	—	—	2.80	216	62
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	62
Tony Sipp L 2013 · 4.38 FIP	30	SU	4.38	24.0%	11.4%	3.4%	.271	3.74	27.3%	19.7%	149	-0.64	2.22	504	61
Michael Gonzalez L 2008 · 3.78 FIP	30	SU	3.78	31.0%	7.7%	4.2%	.247	3.17	26.5%	18.0%	152	-0.61	1.45	454	61
Ryan Buchter L 2017 · 4.45 FIP	30	SU	4.45	24.3%	9.3%	4.0%	.202	4.19	25.3%	15.6%	85	-0.26	2.37	296	60

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	1.5	42	29.5%	14.8%	1.00	4.12
Kyle Barraclough ('23)	1.4	56	28.2%	13.9%	0.99	3.86
Rex Brothers ('21)	1.6	54	27.6%	13.5%	0.98	4.08
Matt Mantei ('05)	1.6	54	28.0%	14.1%	0.84	4.07
Rod Scurry ('80-'88, 5 WAR*)	2.3	58	29.6%*	13.6%*	0.91*	3.67*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*