Jake Garland

P Las Vegas Aviators

Age 26 RHP 6'5" / 260 lbs AAA

Overview

AAAPROSPECT

ETA2028MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX3 levels	27	16	108	3.82	4.18	15.2%	8.2%	—	K 11.3% · BB 9.0% · FIP 4.78
2025	24	A+OAK	20	12	77	4.19	3.71	17.0%	6.8%	—	K 13.1% · BB 7.8% · FIP 4.60
2026	25	MIX3 levels	41	2	77	3.62	3.96	16.1%	8.4%	—	K 13.3% · BB 8.2% · FIP 4.27
2027PROJ	26	MLBOAK	7	0	7	5.28	5.28	10.9%	9.3%	-0.1
2028PROJ43% MLB	27	MLBOAK	20	0	21	5.21	5.23	12.1%	9.4%	-0.2
2029PROJ63% MLB	28	MLBOAK	25	0	26	5.20	5.24	12.9%	9.5%	-0.2

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff30Control55Command35

Career WAR0.0 WAR median (P10 -0.1 / P90 0.1, comp-based) · star 0% · didn't stick 96%

CompsDennis O'Grady (age 26) · Joel De La Cruz (age 26) · Josh Roeder (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 133125vR 117

ERA5.28

FIP5.28

K%10.9%

BB%9.3%

K-BB%1.6%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF3030

CTRL5555

CMD3535

K†3030

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)
2022	21	ROK MLE	ACL Athletics	3	1	3	17	4	1	0	33%	1.0	23.5%	5.9%	17.6%	0.0%	12.00	1.86	—
2022	21	ROK RAW	ACL Athletics	3	1	3	17	4	1	0	33%	1.0	23.5%	5.9%	17.6%	0.0%	12.00	1.43	—
2023	22	MIX MLE	2 levels	24	19	117	517	90	35	6	79%	4.9	13.2%	7.8%	5.4%	1.2%	5.40	3.63	—
2023	22	MIX RAW	2 levels	24	19	117	517	90	35	6	79%	4.9	17.4%	6.8%	10.6%	1.2%	5.40	3.13	—
2024	23	MIX MLE	3 levels	27	16	108	462	70	38	11	59%	4.0	11.3%	9.0%	2.3%	2.7%	3.82	4.78	—
2024	23	MIX MLE	3 levels	27	16	108	462	70	38	11	59%	4.0	11.3%	9.0%	2.3%	2.7%	3.82	4.78	—
2024	23	MIX RAW	3 levels	27	16	108	462	70	38	11	59%	4.0	15.2%	8.2%	6.9%	2.4%	3.82	4.18	—
2025	24	A+ MLE	Lansing Lugnuts	20	12	77	324	55	22	7	60%	3.9	13.1%	7.8%	5.3%	2.9%	4.19	4.60	—
2025	24	A+ MLE	Lansing Lugnuts	20	12	77	324	55	22	7	60%	3.9	13.1%	7.8%	5.3%	2.9%	4.19	4.60	—
2025	24	A+ RAW	Lansing Lugnuts	20	12	77	324	55	22	7	60%	3.9	17.0%	6.8%	10.2%	2.2%	4.19	3.71	—
2026	25	MIX MLE	3 levels	41	2	77	347	56	29	7	5%	1.9	13.3%	8.2%	5.1%	2.3%	3.62	4.27	—
2026	25	MIX MLE	3 levels	41	2	77	347	56	29	7	5%	1.9	13.3%	8.2%	5.1%	2.3%	3.62	4.27	—
2026	25	MIX RAW	3 levels	41	2	77	347	56	29	7	5%	1.9	16.1%	8.4%	7.8%	2.0%	3.62	3.96	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	OAK	7	0	7	30	3	3	1	0%	1.0	10.9%	9.3%	1.6%	2.8%	5.28	5.28	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	OAK	47	0	49	209	25	20	6	0%	1.1	12.1%	9.4%	2.8%	2.9%	5.21	5.23	-0.4
2029	28	MLB MLE	OAK	40	0	42	176	23	17	5	0%	1.0	12.9%	9.5%	3.4%	3.0%	5.20	5.24	-0.3
2030	29	MLB MLE	OAK	36	0	37	157	21	15	5	0%	1.0	13.2%	9.7%	3.4%	3.1%	5.26	5.33	-0.3
2028	27	MLB CTX	OAK	20	0	21	89	11	8	3	0%	1.1	12.1%	9.4%	2.8%	2.9%	5.21	5.23	-0.2
2029	28	MLB CTX	OAK	25	0	26	110	14	10	3	0%	1.0	12.9%	9.5%	3.4%	3.0%	5.20	5.24	-0.2
2030	29	MLB CTX	OAK	26	0	27	114	15	11	4	0%	1.0	13.2%	9.7%	3.4%	3.1%	5.26	5.33	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		71	0	74	313	40	30	9	0%	1.0	12.8%	9.5%	3.2%	3.0%	5.22	4.89	-0.3
/ 200 IP	—	RAW		190	0	200	844	108	81	24	0%	1.1	12.8%	9.5%	3.2%	3.0%	5.22	4.89	-0.8
Career	—	MLE		115	50	382	1667	213	137	36	43%	3.3	12.8%	8.2%	4.6%	2.2%	4.40	4.25	-1.0
/ 200 IP	—	MLE		60	26	200	872	112	72	19	43%	3.3	12.8%	8.2%	4.6%	2.2%	4.40	4.25	-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.

2026 AAALas Vegas Aviators · 37 IPFIP 4.75 → 4.94 (+0.19)K% 14.1% → 12.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.12%	—	×0.860	12.15%
BB% (unintentional) /BF	10.17%	—	×0.900	9.15%
HR / BF /BF	2.82%	÷1.000	×1.100	3.11%

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 4.75 → 4.94, 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).

2026 AAMidland RockHounds · 29 IPFIP 2.57 → 3.03 (+0.46)K% 19.2% → 15.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.17%	—	×0.810	15.53%
BB% (unintentional) /BF	5.00%	—	×1.100	5.50%
HR / BF /BF	0.83%	÷1.000	×1.200	1.00%

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 100).

Result: FIP 2.57 → 3.03, 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).

2026 A+Lansing Lugnuts · 11 IPFIP 4.11 → 4.89 (+0.78)K% 16.0% → 12.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.770	12.32%
BB% (unintentional) /BF	10.00%	—	×1.150	11.50%
HR / BF /BF	2.00%	÷1.000	×1.250	2.50%

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 100).

Result: FIP 4.11 → 4.89, 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).

2025 A+Lansing Lugnuts · 77 IPFIP 3.71 → 4.60 (+0.88)K% 17.0% → 13.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.98%	—	×0.770	13.07%
BB% (unintentional) /BF	6.79%	—	×1.150	7.81%
HR / BF /BF	2.16%	÷0.921	×1.250	2.93%

Result: FIP 3.71 → 4.60, 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).

2024 A+Lansing Lugnuts · 98 IPFIP 3.89 → 4.78 (+0.89)K% 14.7% → 11.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.69%	—	×0.770	11.31%
BB% (unintentional) /BF	7.82%	—	×1.150	8.99%
HR / BF /BF	1.90%	÷0.867	×1.250	2.73%

Result: FIP 3.89 → 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).

2024 AAMidland RockHounds · 6 IPFIP 6.77 → 7.67 (+0.89)K% 4.3% → 3.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	4.35%	—	×0.810	3.52%
BB% (unintentional) /BF	13.04%	—	×1.100	14.35%
HR / BF /BF	4.35%	÷0.940	×1.200	5.55%

Result: FIP 6.77 → 7.67, 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).

2023 A+Lansing Lugnuts · 84 IPFIP 3.56 → 4.02 (+0.47)K% 15.5% → 12.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.53%	—	×0.770	11.96%
BB% (unintentional) /BF	7.11%	—	×1.150	8.17%
HR / BF /BF	1.58%	÷1.209	×1.250	1.63%

Result: FIP 3.56 → 4.02, 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 AStockton Ports · 32 IPFIP 1.93 → 2.56 (+0.63)K% 22.6% → 16.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.63%	—	×0.740	16.74%
BB% (unintentional) /BF	5.84%	—	×1.180	6.89%
HR / BF /BF	0.00%	÷0.945	×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 89).

Result: FIP 1.93 → 2.56, 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).

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
Jake Garland (OGILVIE)	—	—	5.28	10.9%	9.3%	2.8%	—	5.26	12.7%	3.2%	128	-0.02	—	—	—
Dennis O'Grady R 2015 · 4.95 FIP	26	SW	4.95	13.5%	11.0%	2.9%	.339	—	—	—	—	—	3.62	157	87
Joel De La Cruz R 2015 · 4.19 FIP	26	SW	4.19	10.3%	6.7%	2.0%	.276	4.61	14.4%	5.8%	120	+0.42	4.19	205	84
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	83
Cooper Adams R 2024 · 5.42 FIP	24	SW	5.42	13.0%	12.2%	3.4%	.275	4.32	21.7%	10.4%	141	-1.10	3.05	221	83
Brad Allen R 2015 · 4.25 FIP	26	SW	4.25	14.0%	12.6%	1.3%	.315	5.82	14.7%	1.5%	87	+1.57	4.25	149	82
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	82
Sugar Ray Marimon R 2015 · 4.12 FIP	26	SW	4.12	12.4%	9.1%	1.7%	.283	—	—	—	—	—	4.12	107	82
Tyler Yates R 2004 · 4.47 FIP	26	SW	4.47	15.4%	9.6%	2.6%	.333	3.64	22.5%	13.5%	116	-0.83	3.23	248	81
Alfonso Sanchez R 2015 · 4.96 FIP	27	SP-	4.96	12.5%	9.1%	3.2%	.346	4.85	14.0%	5.3%	138	-0.11	4.51	224	81
Dakota Hawkins R 2024 · 4.31 FIP	24	SW	4.31	16.3%	8.9%	2.7%	.277	4.32	19.4%	10.4%	102	+0.01	3.50	186	80
Jake McCasland R 2018 · 4.34 FIP	26	SW	4.34	12.8%	9.5%	2.0%	.313	—	—	—	—	—	3.07	367	80
Donovan Hand R 2013 · 4.72 FIP	27	SW	4.72	12.9%	7.0%	3.3%	.279	4.30	11.1%	6.8%	97	-0.42	4.30	305	80
Drasen Johnson R 2016 · 4.70 FIP	24	SW	4.70	9.6%	5.7%	3.1%	.325	—	—	—	—	—	4.70	110	79
Jorge Reyes R 2015 · 4.58 FIP	27	SW	4.58	15.9%	8.5%	3.2%	.307	3.49	14.2%	6.2%	129	-1.09	3.39	227	79
Kelvis Valerio R 2017 · 4.14 FIP	25	SW	4.14	11.7%	7.1%	2.1%	.269	—	—	—	—	—	4.14	266	79
Aaron Northcraft R 2016 · 4.19 FIP	26	SW	4.19	16.1%	8.3%	2.5%	.309	3.32	24.1%	13.4%	34	-0.87	3.32	252	79
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	79
Cullen Kafka R 2023 · 4.95 FIP	24	SW	4.95	14.2%	12.1%	2.8%	.330	—	—	—	—	—	3.64	148	78
Paulshawn Pasqualotto R 2024 · 4.84 FIP	23	SW	4.84	15.6%	9.5%	3.4%	.354	3.77	20.2%	10.8%	111	-1.07	3.73	186	78
Brooks Hall R 2016 · 4.30 FIP	26	SW	4.30	14.2%	6.7%	2.8%	.284	3.45	13.6%	6.2%	55	-0.85	3.45	274	78

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	1.0	50	12.0%	9.4%	1.14	5.24
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
Matt Whiteside ('05)	2.0	58	14.5%	8.8%	1.15	5.23
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*
Dave Leiper ('84-'96, 0 WAR*)	1.4	46	15.6%*	9.1%*	0.94*	4.28*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*