Jared Kollar

P San Antonio Missions

Age 29 RHP 6'0" / 195 lbs AA peak 0.3 · 2028

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	MIX2 levels	21	19	88	3.36	3.16	18.4%	6.9%	—	K 14.5% · BB 7.7% · FIP 3.92
2024	26	MIX2 levels	29	23	131	3.65	3.38	20.3%	6.3%	—	K 16.8% · BB 6.4% · FIP 3.85
2025	27	MIX2 levels	31	16	113	6.79	5.17	13.8%	9.1%	—	K 11.4% · BB 9.0% · FIP 5.50
2026	28	No MLB games played
2027PROJ	29	MLBSD	1	1	2	5.55	5.55	10.9%	9.0%	-0.0
2028PROJ31% MLB	30	MLBSD	3	3	20	5.36	5.32	13.6%	8.4%	0.0
2029PROJ51% MLB	31	MLBSD	4	4	26	5.39	5.45	14.0%	8.8%	-0.0

Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control55Command40

CompsMiguel Ruiz (age 29) · Juan Omar Espinoza (age 31) · Scott McGregor (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 139130vR 122

ERA5.55

FIP5.55

K%10.9%

BB%9.0%

K-BB%1.9%

Proj IP80

Value2027 · WAR

Runs saved vs league avg · 80 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5555

CMD4040

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	24	A MLE	Lake Elsinore Storm	7	3	14	57	13	3	2	43%	2.0	16.9%	6.2%	10.7%	4.9%	5.27	5.13	—
2022	24	A RAW	Lake Elsinore Storm	7	3	14	57	13	3	2	43%	2.0	22.8%	5.3%	17.5%	3.5%	5.27	3.76	—
2023	25	MIX MLE	2 levels	21	19	88	376	69	26	5	90%	4.2	14.5%	7.7%	6.8%	1.9%	3.36	3.92	—
2023	25	MIX RAW	2 levels	21	19	88	376	69	26	5	90%	4.2	18.4%	6.9%	11.4%	1.3%	3.36	3.16	—
2024	26	MIX MLE	2 levels	29	23	131	552	112	35	12	79%	4.5	16.8%	6.4%	10.4%	2.5%	3.65	3.85	—
2024	26	MIX MLE	2 levels	29	23	131	552	112	35	12	79%	4.5	16.8%	6.4%	10.4%	2.5%	3.65	3.85	—
2024	26	MIX RAW	2 levels	29	23	131	552	112	35	12	79%	4.5	20.3%	6.3%	13.9%	2.2%	3.65	3.38	—
2025	27	MIX MLE	2 levels	31	16	113	514	71	47	18	52%	3.6	11.4%	9.0%	2.4%	4.1%	6.79	5.50	—
2025	27	MIX MLE	2 levels	31	16	113	514	71	47	18	52%	3.6	11.4%	9.0%	2.4%	4.1%	6.79	5.50	—
2025	27	MIX RAW	2 levels	31	16	113	514	71	47	18	52%	3.6	13.8%	9.1%	4.7%	3.5%	6.79	5.17	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	SD	1	1	2	8	1	1	0	100%	2.0	10.9%	9.0%	1.9%	3.4%	5.55	5.55	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	SD	10	10	63	264	36	22	9	100%	6.3	13.6%	8.4%	5.3%	3.5%	5.36	5.32	+0.1
2029	31	MLB MLE	SD	9	9	51	217	30	19	8	100%	5.7	14.0%	8.8%	5.2%	3.7%	5.39	5.45	-0.0
2028	30	MLB CTX	SD	3	3	20	84	12	7	3	100%	6.7	13.6%	8.4%	5.3%	3.5%	5.36	5.32	+0.0
2029	31	MLB CTX	SD	4	4	26	110	15	10	4	100%	6.5	14.0%	8.8%	5.2%	3.7%	5.39	5.45	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	8	46	194	27	17	7	100%	5.7	13.8%	8.6%	5.2%	3.6%	5.38	5.02	+0.2
/ 200 IP	—	RAW		33	33	200	844	117	74	30	100%	6.0	13.8%	8.6%	5.2%	3.6%	5.38	5.02	+0.9
Career	—	MLE		88	61	345	1499	215	114	45	69%	3.9	14.4%	7.6%	6.8%	3.0%	4.67	4.48	+0.0
/ 200 IP	—	MLE		51	35	200	868	125	66	26	69%	3.9	14.4%	7.6%	6.8%	3.0%	4.67	4.48	+0.0

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.

2025 AASan Antonio Missions · 66 IPFIP 3.43 → 4.06 (+0.63)K% 17.7% → 14.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.73%	—	×0.810	14.36%
BB% (unintentional) /BF	6.74%	—	×1.100	7.41%
HR / BF /BF	1.77%	÷0.950	×1.200	2.24%

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 90).

Result: FIP 3.43 → 4.06, 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 AAAEl Paso Chihuahuas · 47 IPFIP 6.94 → 7.27 (+0.33)K% 9.1% → 7.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	9.05%	—	×0.860	7.78%
BB% (unintentional) /BF	12.07%	—	×0.900	10.86%
HR / BF /BF	5.60%	÷0.981	×1.100	6.28%

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 96).

Result: FIP 6.94 → 7.27, 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 AASan Antonio Missions · 83 IPFIP 2.83 → 3.50 (+0.67)K% 22.1% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.13%	—	×0.810	17.92%
BB% (unintentional) /BF	5.17%	—	×1.100	5.69%
HR / BF /BF	1.72%	÷0.953	×1.200	2.17%

Result: FIP 2.83 → 3.50, 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 AAAEl Paso Chihuahuas · 48 IPFIP 4.32 → 4.45 (+0.13)K% 17.2% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.16%	—	×0.860	14.75%
BB% (unintentional) /BF	8.33%	—	×0.900	7.50%
HR / BF /BF	2.94%	÷1.078	×1.100	3.00%

Result: FIP 4.32 → 4.45, 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 AASan Antonio Missions · 51 IPFIP 4.15 → 5.05 (+0.90)K% 14.8% → 12.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.78%	—	×0.810	11.97%
BB% (unintentional) /BF	8.70%	—	×1.100	9.57%
HR / BF /BF	2.17%	÷0.820	×1.200	3.18%

Result: FIP 4.15 → 5.05, 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).

2023 A+Fort Wayne TinCaps · 38 IPFIP 1.60 → 2.14 (+0.54)K% 24.0% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.97%	—	×0.770	18.46%
BB% (unintentional) /BF	4.11%	—	×1.150	4.73%
HR / BF /BF	0.00%	÷0.848	×1.250	0.00%

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 70).

Result: FIP 1.60 → 2.14, 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 ALake Elsinore Storm · 14 IPFIP 3.77 → 5.13 (+1.36)K% 22.8% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.81%	—	×0.740	16.88%
BB% (unintentional) /BF	5.26%	—	×1.180	6.21%
HR / BF /BF	3.51%	÷0.938	×1.300	4.86%

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 88).

Result: FIP 3.77 → 5.13, 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
Jared Kollar (OGILVIE)	—	—	5.55	10.9%	9.0%	3.4%	—	5.38	13.8%	5.2%	114	-0.17	—	—	—
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	85
Juan Omar Espinoza R 2015 · 4.81 FIP	31	SP-	4.81	8.9%	6.6%	3.0%	.346	4.84	8.4%	-0.8%	52	+0.03	4.81	104	84
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	84
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	82
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	81
Colin Bates R 2015 · 4.57 FIP	27	SP-	4.57	10.5%	6.5%	2.8%	.301	—	—	—	—	—	4.57	111	81
Robert Ellis R 2001 · 4.84 FIP	30	SP	4.84	9.9%	7.7%	2.9%	.287	8.08	9.0%	-2.2%	18	+3.24	4.84	110	78
Travis Driskill R 2002 · 4.95 FIP	30	SP-	4.95	13.2%	8.0%	3.6%	.291	4.26	15.3%	12.0%	48	-0.69	4.26	181	78
Andres Ivan Meza R 2015 · 4.45 FIP	28	SP	4.45	10.9%	5.6%	2.9%	.322	4.14	12.5%	4.0%	85	-0.31	4.14	275	77
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	76
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	75
Jordan Cooper R 2015 · 5.01 FIP	26	SP	5.01	9.2%	10.2%	2.5%	.305	—	—	—	—	—	5.01	106	75
Luis Mateo R 2019 · 5.55 FIP	29	SP-	5.55	8.6%	13.4%	2.7%	.303	—	—	—	—	—	3.48	160	74
Alfonso Sanchez R 2017 · 4.51 FIP	29	SW	4.51	12.5%	9.8%	2.2%	.346	7.58	8.6%	1.4%	39	+3.07	4.51	224	72
Daniel Guerrero R 2016 · 4.81 FIP	31	SP	4.81	12.4%	11.6%	2.3%	.328	4.93	11.7%	2.0%	175	+0.12	4.61	269	72
Caleb Clay R 2015 · 4.67 FIP	27	SP	4.67	9.9%	6.9%	2.8%	.324	—	—	—	—	—	4.67	111	71
Kyle Friedrichs R 2021 · 4.73 FIP	29	SP-	4.73	13.9%	6.2%	3.7%	.286	—	—	—	—	—	3.53	603	70
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	70
Jon Leicester R 2007 · 4.44 FIP	28	SP-	4.44	11.0%	9.0%	2.1%	.292	—	—	—	—	—	3.76	113	70
Brian Powell R 2002 · 5.53 FIP	28	SP-	5.53	11.8%	8.3%	4.3%	.276	4.45	14.5%	7.3%	39	-1.08	4.45	212	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	1.0	65	12.6%	8.7%	1.36	5.45
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Mike Lincoln ('10)	1.9	54	14.1%	8.9%	1.32	5.33
J. C. Ramirez ('13-'19, -0 WAR*)	1.4	72	15.1%*	8.7%*	1.30*	4.83*
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Russ Swan ('89-'94, -2 WAR*)	1.3	89	12.3%*	9.9%*	1.13*	5.09*
Paul Reuschel ('75-'79, 1 WAR*)	2.0	79	16.8%*	7.6%*	1.29*	4.76*