Jack Jasiak

P Akron RubberDucks

Age 26 RHP 6'0" / 210 lbs AA peak 0.3 · 2028

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	ALynchburg Hil…	32	2	67	4.57	3.40	20.6%	7.3%	—	K 15.2% · BB 8.6% · FIP 4.59
2025	24	MIX2 levels	40	0	69	3.38	2.45	25.5%	6.3%	—	K 19.9% · BB 7.1% · FIP 3.24
2026	25	MIX2 levels	39	0	65	4.59	3.56	28.7%	7.2%	—	K 25.2% · BB 7.4% · FIP 3.57
2027PROJ	26	MLBCLE	1	0	1	4.05	4.05	22.4%	6.9%	0.0
2028PROJ38% MLB	27	MLBCLE	21	0	22	4.10	4.11	22.5%	7.2%	0.1
2029PROJ60% MLB	28	MLBCLE	30	0	32	4.17	4.21	22.4%	7.5%	0.1

Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control55Command55

Career WAR0.0 WAR median (P10 -0.2 / P90 1.8, comp-based) · star 0% · didn't stick 90%

CompsSimon Castro (age 27) · Joe Broussard (age 26) · Santiago Casilla (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 110102vR 94

ERA4.05

FIP4.05

K%22.4%

BB%6.9%

K-BB%15.5%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL5555

CMD5555

K†5555

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)
2023	22	A MLE	Lynchburg Hillcats	32	0	69	307	50	37	5	0%	2.1	12.1%	14.2%	-2.2%	2.1%	4.46	5.03	—
2023	22	A RAW	Lynchburg Hillcats	32	0	69	307	50	37	5	0%	2.1	16.3%	12.1%	4.2%	1.6%	4.46	4.21	—
2024	23	A MLE	Lynchburg Hillcats	32	2	67	301	62	22	6	6%	2.1	15.2%	8.6%	6.6%	3.1%	4.57	4.59	—
2024	23	A MLE	Lynchburg Hillcats	32	2	67	301	62	22	6	6%	2.1	15.2%	8.6%	6.6%	3.1%	4.57	4.59	—
2024	23	A RAW	Lynchburg Hillcats	32	2	67	301	62	22	6	6%	2.1	20.6%	7.3%	13.3%	2.0%	4.57	3.40	—
2025	24	MIX MLE	2 levels	40	0	69	302	77	19	4	0%	1.7	19.9%	7.1%	12.7%	1.7%	3.38	3.24	—
2025	24	MIX MLE	2 levels	40	0	69	302	77	19	4	0%	1.7	19.9%	7.1%	12.7%	1.7%	3.38	3.24	—
2025	24	MIX RAW	2 levels	40	0	69	302	77	19	4	0%	1.7	25.5%	6.3%	19.2%	1.3%	3.38	2.45	—
2026	25	MIX MLE	2 levels	39	0	65	279	80	20	10	0%	1.7	25.2%	7.4%	17.8%	3.0%	4.59	3.57	—
2026	25	MIX MLE	2 levels	39	0	65	279	80	20	10	0%	1.7	25.2%	7.4%	17.8%	3.0%	4.59	3.57	—
2026	25	MIX RAW	2 levels	39	0	65	279	80	20	10	0%	1.7	28.7%	7.2%	21.5%	3.6%	4.59	3.56	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	CLE	1	0	1	4	1	0	0	0%	1.0	22.4%	6.9%	15.5%	2.9%	4.05	4.05	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	CLE	56	0	59	250	56	18	7	0%	1.1	22.5%	7.2%	15.2%	2.9%	4.10	4.11	+0.3
2029	28	MLB MLE	CLE	51	0	53	224	50	17	7	0%	1.0	22.4%	7.5%	14.9%	3.0%	4.17	4.21	+0.2
2030	29	MLB MLE	CLE	46	0	48	204	45	16	6	0%	1.0	22.2%	7.8%	14.4%	3.2%	4.28	4.35	+0.1
2028	27	MLB CTX	CLE	21	0	22	93	21	7	3	0%	1.0	22.5%	7.2%	15.2%	2.9%	4.10	4.11	+0.1
2029	28	MLB CTX	CLE	30	0	32	135	30	10	4	0%	1.1	22.4%	7.5%	14.9%	3.0%	4.17	4.21	+0.1
2030	29	MLB CTX	CLE	32	0	34	144	32	11	5	0%	1.1	22.2%	7.8%	14.4%	3.2%	4.28	4.35	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		84	0	88	371	83	28	11	0%	1.0	22.3%	7.6%	14.8%	3.1%	4.19	3.86	+0.7
/ 200 IP	—	RAW		190	0	200	844	189	64	25	0%	1.1	22.3%	7.6%	14.8%	3.1%	4.19	3.86	+1.6
Career	—	MLE		143	2	270	1189	213	112	29	1%	1.9	17.9%	9.4%	8.5%	2.4%	4.24	4.12	+0.6
/ 200 IP	—	MLE		106	1	200	882	158	83	22	1%	1.9	17.9%	9.4%	8.5%	2.4%	4.24	4.12	+0.8

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 AAAkron RubberDucks · 57 IPFIP 2.71 → 3.57 (+0.86)K% 31.1% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.09%	—	×0.810	25.18%
BB% (unintentional) /BF	6.72%	—	×1.100	7.39%
HR / BF /BF	2.52%	÷1.000	×1.200	3.03%

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 2.71 → 3.57, 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 AAAColumbus Clippers · 8 IPFIP 8.46 → 9.04 (+0.58)K% 14.6% → 12.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.63%	—	×0.860	12.59%
BB% (unintentional) /BF	9.76%	—	×0.900	8.78%
HR / BF /BF	9.76%	÷1.000	×1.100	10.73%

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 8.46 → 9.04, 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+Lake County Captains · 54 IPFIP 2.34 → 3.11 (+0.78)K% 25.9% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.86%	—	×0.770	19.91%
BB% (unintentional) /BF	5.60%	—	×1.150	6.44%
HR / BF /BF	1.29%	÷1.011	×1.250	1.60%

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 102).

Result: FIP 2.34 → 3.11, 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 AAAkron RubberDucks · 16 IPFIP 2.92 → 3.65 (+0.73)K% 24.3% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.29%	—	×0.810	19.67%
BB% (unintentional) /BF	8.57%	—	×1.100	9.43%
HR / BF /BF	1.43%	÷0.926	×1.200	1.85%

Result: FIP 2.92 → 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).

2024 ALynchburg Hillcats · 67 IPFIP 3.38 → 4.59 (+1.21)K% 20.6% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.60%	—	×0.740	15.24%
BB% (unintentional) /BF	7.31%	—	×1.180	8.62%
HR / BF /BF	1.99%	÷0.844	×1.300	3.07%

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 69).

Result: FIP 3.38 → 4.59, 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 ALynchburg Hillcats · 69 IPFIP 4.15 → 5.03 (+0.88)K% 16.3% → 12.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.29%	—	×0.740	12.05%
BB% (unintentional) /BF	12.05%	—	×1.180	14.22%
HR / BF /BF	1.63%	÷1.017	×1.300	2.08%

Result: FIP 4.15 → 5.03, 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).

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
Jack Jasiak (OGILVIE)	—	—	4.05	22.4%	6.9%	2.9%	—	4.22	22.4%	14.9%	160	+0.17	—	—	—
Simon Castro R 2015 · 3.28 FIP	27	SU	3.28	26.4%	8.5%	2.4%	.320	3.58	26.0%	17.6%	128	+0.30	3.01	185	85
Joe Broussard R 2017 · 3.83 FIP	26	SU	3.83	23.5%	7.9%	3.1%	.316	3.72	21.1%	12.0%	95	-0.11	2.62	304	85
Santiago Casilla R 2007 · 3.58 FIP	27	SU	3.58	23.7%	7.8%	2.7%	.257	3.60	19.8%	10.7%	154	+0.02	2.76	647	85
Shay Schanaman R 2024 · 4.34 FIP	24	SU	4.34	21.0%	7.6%	3.7%	.292	6.05	16.4%	2.8%	90	+1.71	4.34	148	85
John Brebbia R 2016 · 4.11 FIP	26	SU	4.11	18.6%	6.6%	3.2%	.346	3.20	27.6%	21.4%	215	-0.91	2.89	576	85
Ryan Brasier R 2016 · 3.68 FIP	28	SU	3.68	25.0%	7.7%	3.1%	.289	3.09	24.2%	17.9%	130	-0.59	2.31	426	85
Ryan Garton R 2016 · 3.14 FIP	26	SU	3.14	21.8%	6.3%	2.0%	.325	3.97	24.1%	12.0%	175	+0.83	3.14	307	84
Matt Pushard R 2024 · 3.87 FIP	26	SU	3.87	24.1%	8.9%	3.0%	.242	3.29	22.2%	14.0%	115	-0.58	2.84	220	84
Kaleb Bowman R 2023 · 3.88 FIP	26	SU	3.88	22.0%	7.5%	3.1%	.333	4.65	17.5%	6.2%	170	+0.77	3.88	203	83
Colton Murray R 2016 · 3.97 FIP	26	SU	3.97	21.2%	9.4%	2.7%	.295	4.27	21.8%	13.1%	41	+0.30	3.34	187	83
Jhan Mariñez R 2015 · 3.50 FIP	26	SU	3.50	23.1%	9.3%	2.1%	.244	3.70	18.9%	11.1%	168	+0.20	3.16	253	83
R.J. Alaniz R 2017 · 3.91 FIP	26	SU	3.91	20.7%	8.9%	2.6%	.318	3.28	23.8%	15.0%	96	-0.63	2.45	362	83
Joe Navilhon R 2019 · 3.23 FIP	26	SU	3.23	20.5%	7.7%	1.6%	.322	4.28	23.4%	16.7%	99	+1.05	2.25	273	83
Trent Harris R 2024 · 3.45 FIP	25	SU	3.45	26.9%	9.5%	2.6%	.258	3.36	24.7%	16.7%	121	-0.09	3.06	198	83
Joshua Loeschorn R 2023 · 3.86 FIP	23	SU	3.86	24.5%	7.7%	3.4%	.272	4.43	17.1%	8.4%	83	+0.57	3.08	151	83
Shawn Camp R 2004 · 4.18 FIP	28	SU	4.18	17.8%	5.2%	3.5%	.305	3.88	15.5%	10.5%	164	-0.30	2.79	589	83
Ryan Halstead R 2018 · 4.08 FIP	26	SU	4.08	18.0%	6.7%	3.0%	.296	3.24	16.1%	8.7%	64	-0.84	3.12	222	83
Ian Gardeck R 2015 · 2.93 FIP	24	SU	2.93	22.4%	7.7%	1.4%	.319	—	—	—	—	—	2.93	105	83
Trevin Michael R 2024 · 4.40 FIP	26	SU	4.40	22.9%	7.6%	4.1%	.256	3.54	23.7%	11.7%	105	-0.86	2.66	198	82
Jonathan Aro R 2017 · 3.72 FIP	26	SU	3.72	25.3%	6.9%	3.4%	.252	3.56	14.6%	8.1%	108	-0.16	2.57	323	82

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	58	22.4%	7.3%	1.16	4.14
Shawn Tolleson ('16)	1.1	54	23.1%	8.3%	1.28	3.92
Michael Tonkin ('25)	1.6	55	23.2%	8.1%	1.28	4.23
Charlie Furbush ('15)	1.3	52	24.5%	8.1%	1.04	3.97
Tim Crews ('87-'92, 3 WAR*)	2.1	71	20.8%*	6.2%*	1.09*	4.11*
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*