Javier Assad

P Chicago Cubs

Age 30 RHP 6'1" / 200 lbs MLB peak 0.2 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MLBCHC	29	29	147	3.73	4.47	19.4%	9.9%	1.6
2025	28	MIX3 levels	13	12	55	3.25	3.24	19.1%	8.3%	1.5	K 16.3% · BB 8.3% · FIP 3.55
2026	29	MIX2 levels	35	18	119	4.15	4.69	17.0%	7.5%	1.0	K 16.4% · BB 7.3% · FIP 4.85
2027PROJ	30	MLBCHC	8	8	50	4.62	4.98	16.3%	7.8%	0.2
2028PROJ	31	MLBCHC	7	7	41	4.98	5.21	15.5%	8.2%	0.1
2029PROJ	32	MLBCHC	5	5	29	5.27	5.47	14.7%	8.6%	-0.0

Last 3 seasons WAR 4.0 · Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs39

FB Velo36

K%12

Form3.10 ERA (proj 4.62) · K 18.1% (proj 16.3%) · BB 9.5% (proj 7.8%) · last 90d · 29 IP through Oct 27

CompsChi Chi González (age 30) · David Hale (age 30) · Luke Hudson (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.62

FIP4.98

K%16.3%

BB%7.8%

K-BB%8.4%

Proj IP50

Value2027 · WAR

Runs saved vs league avg · 50 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p3693.5

Whiff%

p1015.9%

p1216.7%

xwOBA vs

p390.324

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)
2016	19	ROK MLE	AZL Cubs	10	7	38	166	42	13	1	70%	3.8	17.2%	9.8%	7.4%	0.8%	2.87	3.35	—
2016	19	ROK RAW	AZL Cubs	10	7	38	166	42	13	1	70%	3.8	25.3%	7.8%	17.5%	0.6%	2.87	2.25	—
2018	21	A MLE	South Bend Cubs	23	21	106	473	89	31	6	91%	4.6	13.9%	7.7%	6.2%	1.9%	4.40	3.93	—
2018	21	A RAW	South Bend Cubs	23	21	106	473	89	31	6	91%	4.6	18.8%	6.6%	12.3%	1.3%	4.40	3.03	—
2019	22	A+ MLE	Myrtle Beach Pelicans	22	22	116	481	91	41	11	100%	5.3	14.6%	9.8%	4.8%	3.0%	3.87	4.75	—
2019	22	A+ RAW	Myrtle Beach Pelicans	22	22	116	481	91	41	11	100%	5.3	18.9%	8.5%	10.4%	2.3%	3.87	3.82	—
2021	24	AA MLE	Tennessee Smokies	21	20	93	419	74	32	12	95%	4.4	14.3%	8.4%	5.9%	3.3%	5.32	4.75	—
2021	24	AA RAW	Tennessee Smokies	21	20	93	419	74	32	12	95%	4.4	17.7%	7.6%	10.0%	2.9%	5.32	4.22	—
2022	25	MIX MLE	3 levels	32	29	146	614	141	55	14	91%	4.6	20.0%	9.5%	10.5%	2.6%	2.77	4.02	+2.4
2022	25	MIX RAW	3 levels	32	29	146	614	141	55	14	91%	4.6	23.0%	9.0%	14.0%	2.3%	2.77	3.55	+3.3
2023	26	MIX MLE	2 levels	36	14	124	513	109	47	13	39%	3.4	20.8%	9.0%	11.8%	2.6%	3.12	3.93	+0.9
2023	26	MIX RAW	2 levels	36	14	124	513	109	47	13	39%	3.4	21.2%	9.2%	12.1%	2.5%	3.12	3.84	+1.0
2024	27	MLB MLE	Chicago Cubs	29	29	147	638	124	63	20	100%	5.1	19.4%	9.9%	9.6%	3.3%	3.73	4.50	+1.5
2024	27	MLB MLE	Chicago Cubs	29	29	147	638	124	63	20	100%	5.1	19.4%	9.9%	9.6%	3.3%	3.73	4.50	+1.5
2024	27	MLB RAW	Chicago Cubs	29	29	147	638	124	63	20	100%	5.1	19.4%	9.9%	9.6%	3.1%	3.73	4.47	+1.6
2025	28	MIX MLE	3 levels	13	12	55	230	44	19	3	92%	4.3	16.3%	8.3%	8.0%	1.4%	3.25	3.55	+1.2
2025	28	MIX MLE	3 levels	13	12	55	230	44	19	3	92%	4.3	16.3%	8.3%	8.0%	1.4%	3.25	3.55	+1.2
2025	28	MIX RAW	3 levels	13	12	55	230	44	19	3	92%	4.3	19.1%	8.3%	10.9%	1.3%	3.25	3.24	+1.5
2026	29	MIX MLE	2 levels	35	18	119	494	84	37	19	51%	3.4	16.4%	7.3%	9.1%	4.0%	4.15	4.85	+0.8
2026	29	MIX MLE	2 levels	35	18	119	494	84	37	19	51%	3.4	16.4%	7.3%	9.1%	4.0%	4.15	4.85	+0.8
2026	29	MIX RAW	2 levels	35	18	119	494	84	37	19	51%	3.4	17.0%	7.5%	9.5%	3.8%	4.15	4.69	+1.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			106	65	425	1784	334	161	56	61%	4.0	18.7%	9.0%	9.7%	3.1%	3.47	4.38	+5.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	CHC	8	8	50	211	34	17	7	100%	6.2	16.3%	7.8%	8.4%	3.4%	4.62	4.98	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	CHC	7	7	41	173	27	14	6	100%	5.9	15.5%	8.2%	7.3%	3.7%	4.98	5.21	+0.1
2029	32	MLB MLE	CHC	5	5	29	124	18	11	5	100%	5.9	14.7%	8.6%	6.1%	3.9%	5.27	5.47	-0.0
2028	31	MLB CTX	CHC	7	7	41	173	27	14	6	100%	5.9	15.5%	8.2%	7.3%	3.7%	4.98	5.21	+0.1
2029	32	MLB CTX	CHC	5	5	29	122	18	11	5	100%	5.8	14.7%	8.6%	6.1%	3.9%	5.27	5.47	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		118	77	496	2081	379	186	67	65%	4.2	18.2%	8.9%	9.3%	3.2%	3.70	4.46	+5.4
/ 200 IP	—	RAW		47	31	200	840	153	75	27	65%	4.2	18.2%	8.9%	9.3%	3.2%	3.70	4.46	+2.2
Career	—	MLE		221	172	945	4028	696	358	112	78%	4.3	17.3%	8.9%	8.4%	2.8%	3.74	4.28	+5.1
/ 200 IP	—	MLE		47	36	200	852	147	76	24	78%	4.3	17.3%	8.9%	8.4%	2.8%	3.74	4.28	+2.1

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 AAAIowa Cubs · 25 IPFIP 4.19 → 4.43 (+0.24)K% 18.1% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.10%	—	×0.860	15.57%
BB% (unintentional) /BF	9.48%	—	×0.900	8.53%
HR / BF /BF	2.59%	÷1.000	×1.100	2.84%

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 4.19 → 4.43, 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).

2025 AAAIowa Cubs · 15 IPFIP 2.53 → 2.67 (+0.13)K% 22.4% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.39%	—	×0.860	19.25%
BB% (unintentional) /BF	10.45%	—	×0.900	9.40%
HR / BF /BF	0.00%	÷1.125	×1.100	0.00%

Result: FIP 2.53 → 2.67, 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 AAAIowa Cubs · 15 IPFIP 2.51 → 2.64 (+0.14)K% 23.4% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.44%	—	×0.860	20.16%
BB% (unintentional) /BF	10.94%	—	×0.900	9.84%
HR / BF /BF	0.00%	÷0.965	×1.100	0.00%

Result: FIP 2.51 → 2.64, 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).

2022 AATennessee Smokies · 72 IPFIP 3.30 → 4.02 (+0.72)K% 24.7% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.75%	—	×0.810	20.05%
BB% (unintentional) /BF	9.36%	—	×1.100	10.30%
HR / BF /BF	2.01%	÷1.010	×1.200	2.38%

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 102).

Result: FIP 3.30 → 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).

2022 AAAIowa Cubs · 37 IPFIP 3.07 → 3.51 (+0.43)K% 24.8% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.83%	—	×0.880	21.85%
BB% (unintentional) /BF	4.70%	—	×1.050	4.93%
HR / BF /BF	2.68%	÷0.996	×1.100	2.96%

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 3.07 → 3.51, 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 · 93 IPFIP 4.15 → 4.75 (+0.61)K% 17.7% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.66%	—	×0.810	14.31%
BB% (unintentional) /BF	7.64%	—	×1.100	8.40%
HR / BF /BF	2.86%	÷1.050	×1.200	3.27%

Result: FIP 4.15 → 4.75, 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 · 116 IPFIP 3.84 → 4.75 (+0.92)K% 18.9% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.92%	—	×0.770	14.57%
BB% (unintentional) /BF	8.52%	—	×1.150	9.80%
HR / BF /BF	2.29%	÷0.956	×1.250	2.99%

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 3.84 → 4.75, 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).

2018 ASouth Bend Cubs · 106 IPFIP 3.04 → 3.93 (+0.89)K% 18.8% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.82%	—	×0.740	13.92%
BB% (unintentional) /BF	6.55%	—	×1.180	7.73%
HR / BF /BF	1.27%	÷0.881	×1.300	1.87%

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 76).

Result: FIP 3.04 → 3.93, 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
Javier Assad (OGILVIE)	—	—	—	—	—	3.4%	—	5.32	15.2%	6.8%	70	+0.34	—	—	—
Chi Chi González R 2022 · 4.30 FIP	30	SP-	4.30	17.6%	8.0%	3.0%	.315	5.33	11.2%	5.6%	122	+1.03	4.01	800	69
David Hale R 2018 · 4.22 FIP	30	SP-	4.22	15.4%	7.5%	2.7%	.299	3.65	17.1%	11.3%	114	-0.57	3.30	581	68
Luke Hudson R 2006 · 3.81 FIP	29	SP-	3.81	14.5%	8.4%	1.6%	.307	—	—	—	—	—	3.81	235	68
Chris Heston R 2017 · 5.88 FIP	29	SP-	5.88	13.6%	10.0%	4.9%	.368	—	—	—	—	—	3.81	321	67
Odrisamer Despaigne R 2017 · 4.09 FIP	30	SW	4.09	13.7%	8.7%	1.9%	.270	3.53	19.1%	10.5%	220	-0.56	3.13	689	67
Tim Adleman R 2017 · 5.35 FIP	29	SP-	5.35	20.3%	9.4%	5.1%	.276	4.30	22.8%	15.0%	117	-1.05	3.63	605	66
Austin Bibens-Dirkx R 2015 · 3.97 FIP	30	SP	3.97	17.4%	7.1%	2.6%	.315	4.94	15.9%	8.7%	305	+0.97	3.97	567	66
Scott Carroll R 2015 · 3.92 FIP	30	SW	3.92	12.7%	7.7%	1.7%	.286	5.07	11.2%	2.6%	128	+1.15	3.92	377	65
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	64
Dylan Axelrod R 2015 · 4.75 FIP	30	SP-	4.75	14.1%	6.6%	3.6%	.304	4.28	13.7%	7.4%	133	-0.47	2.88	468	64
Elian Leyva R 2019 · 4.30 FIP	30	SP-	4.30	17.0%	8.5%	2.9%	.323	—	—	—	—	—	3.10	158	64
Kohei Arihara R 2022 · 4.58 FIP	29	SP-	4.58	16.4%	7.2%	3.5%	.333	—	—	—	—	—	4.58	135	64
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	63
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	63
Adrian Sampson R 2022 · 4.22 FIP	30	SP	4.22	16.1%	6.2%	3.1%	.278	4.88	14.4%	7.0%	244	+0.66	3.23	1,012	62
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	62
Jeremy Kehrt R 2016 · 4.17 FIP	30	SP	4.17	12.7%	7.4%	2.2%	.333	4.71	8.5%	-4.6%	21	+0.54	3.37	262	62
Alfredo Simon R 2011 · 4.05 FIP	30	SP-	4.05	16.6%	6.8%	2.7%	.308	3.64	16.7%	10.2%	345	-0.41	2.83	784	62
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	61
Luke Irvine R 2016 · 4.31 FIP	27	SP-	4.31	13.4%	9.8%	2.0%	.302	—	—	—	—	—	4.31	104	61

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	2.7	68	18.0%	8.9%	1.26	3.79
Manny Sarmiento ('76-'83, 4 WAR*)	2.6	86	18.9%*	8.1%*	1.20*	4.00*
Vicente Romo ('68-'82, 5 WAR*)	3.2	81	20.5%*	9.7%*	1.21*	4.01*
Tom House ('71-'78, 3 WAR*)	2.7	77	17.3%*	7.8%*	1.25*	4.14*
Randall Delgado ('18)	2.7	78	20.1%	8.8%	1.11	4.10
Kendall Graveman ('25)	3.3	96	17.6%	8.1%	1.06	4.03
Scott Sullivan ('04)	3.7	92	19.8%	8.9%	1.09	3.98