Evan Shawver

P Albuquerque Isotopes

Age 27 LHP 6'0" / 175 lbs AAA

Overview

AAAPROSPECT

ETA2028MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	AACOL	36	6	50	2.90	3.36	23.9%	13.9%	—	K 19.4% · BB 15.3% · FIP 4.08
2025	25	AACOL	36	0	53	5.30	4.01	23.0%	9.5%	—	K 18.7% · BB 10.4% · FIP 4.35
2026	26	MIX2 levels	33	4	62	3.18	3.47	20.9%	8.8%	—	K 17.7% · BB 8.2% · FIP 3.79
2027PROJ	27	MLBCOL	7	0	7	4.69	4.69	17.8%	10.1%	-0.0
2028PROJ43% MLB	28	MLBCOL	21	0	22	4.70	4.74	18.2%	10.1%	-0.0
2029PROJ59% MLB	29	MLBCOL	25	0	26	4.77	4.84	18.4%	10.3%	-0.1

Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff45Control45Command45

Career WAR0.0 WAR median (P10 -0.2 / P90 0.7, comp-based) · star 0% · didn't stick 95%

CompsRyan Verdugo (age 28) · Juan Grullon (age 26) · Greg Nappo (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 106114vR 122

ERA4.69

FIP4.69

K%17.8%

BB%10.1%

K-BB%7.7%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF4545

CTRL4545

CMD4545

K†4045

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)
2021	21	ROK MLE	ACL Rockies	4	0	4	13	1	1	0	0%	1.0	7.7%	7.7%	0.0%	0.0%	0.00	3.42	—
2021	21	ROK RAW	ACL Rockies	4	0	4	13	1	1	0	0%	1.0	7.7%	7.7%	0.0%	0.0%	0.00	3.35	—
2022	22	MIX MLE	2 levels	15	15	66	284	70	26	8	100%	4.4	18.8%	10.6%	8.2%	2.7%	4.07	4.32	—
2022	22	MIX RAW	2 levels	15	15	66	284	70	26	8	100%	4.4	24.6%	9.2%	15.5%	2.8%	4.07	3.73	—
2023	23	A+ MLE	Spokane Indians	24	4	50	237	49	34	7	17%	2.1	15.9%	16.5%	-0.6%	3.5%	5.94	5.78	—
2023	23	A+ RAW	Spokane Indians	24	4	50	237	49	34	7	17%	2.1	20.7%	14.3%	6.3%	3.0%	5.94	5.00	—
2024	24	AA MLE	Hartford Yard Goats	36	6	50	209	50	29	2	17%	1.4	19.4%	15.3%	4.1%	1.3%	2.90	4.08	—
2024	24	AA MLE	Hartford Yard Goats	36	6	50	209	50	29	2	17%	1.4	19.4%	15.3%	4.1%	1.3%	2.90	4.08	—
2024	24	AA RAW	Hartford Yard Goats	36	6	50	209	50	29	2	17%	1.4	23.9%	13.9%	10.0%	1.0%	2.90	3.36	—
2025	25	AA MLE	Hartford Yard Goats	36	0	53	243	56	23	7	0%	1.5	18.7%	10.4%	8.3%	2.8%	5.30	4.35	—
2025	25	AA MLE	Hartford Yard Goats	36	0	53	243	56	23	7	0%	1.5	18.7%	10.4%	8.3%	2.8%	5.30	4.35	—
2025	25	AA RAW	Hartford Yard Goats	36	0	53	243	56	23	7	0%	1.5	23.0%	9.5%	13.6%	2.9%	5.30	4.01	—
2026	26	MIX MLE	2 levels	33	4	62	273	57	24	5	12%	1.9	17.7%	8.2%	9.5%	2.1%	3.18	3.79	—
2026	26	MIX MLE	2 levels	33	4	62	273	57	24	5	12%	1.9	17.7%	8.2%	9.5%	2.1%	3.18	3.79	—
2026	26	MIX RAW	2 levels	33	4	62	273	57	24	5	12%	1.9	20.9%	8.8%	12.1%	1.8%	3.18	3.47	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	COL	7	0	7	30	5	3	1	0%	1.0	17.8%	10.1%	7.7%	2.6%	4.69	4.69	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	COL	50	0	53	223	41	23	6	0%	1.1	18.2%	10.1%	8.1%	2.8%	4.70	4.74	-0.1
2029	29	MLB MLE	COL	42	0	44	187	34	19	5	0%	1.1	18.4%	10.3%	8.1%	2.9%	4.77	4.84	-0.1
2028	28	MLB CTX	COL	21	0	22	93	17	9	3	0%	1.0	18.2%	10.1%	8.1%	2.8%	4.70	4.74	-0.0
2029	29	MLB CTX	COL	25	0	26	110	20	11	3	0%	1.0	18.4%	10.3%	8.1%	2.9%	4.77	4.84	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		46	0	49	205	38	21	6	0%	1.1	18.3%	10.2%	8.1%	2.8%	4.74	4.41	+0.1
/ 200 IP	—	RAW		190	0	200	844	156	86	25	0%	1.1	18.3%	10.2%	8.1%	2.8%	4.74	4.41	+0.3
Career	—	MLE		148	29	285	1259	226	150	31	20%	1.9	18.0%	11.9%	6.1%	2.5%	4.17	4.44	-0.3
/ 200 IP	—	MLE		104	20	200	884	159	105	22	20%	1.9	18.0%	11.9%	6.1%	2.5%	4.17	4.44	-0.6

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 AAAAlbuquerque Isotopes · 48 IPFIP 3.28 → 3.49 (+0.21)K% 21.2% → 18.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.23%	—	×0.860	18.25%
BB% (unintentional) /BF	9.43%	—	×0.900	8.49%
HR / BF /BF	1.42%	÷1.000	×1.100	1.56%

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 → 3.49, 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).

2026 AAHartford Yard Goats · 14 IPFIP 4.07 → 4.83 (+0.76)K% 19.7% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.67%	—	×0.810	15.93%
BB% (unintentional) /BF	6.56%	—	×1.100	7.21%
HR / BF /BF	3.28%	÷1.000	×1.200	3.93%

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 4.07 → 4.83, 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 AAHartford Yard Goats · 53 IPFIP 3.93 → 4.35 (+0.42)K% 23.0% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.05%	—	×0.810	18.67%
BB% (unintentional) /BF	9.47%	—	×1.100	10.41%
HR / BF /BF	2.88%	÷1.255	×1.200	2.75%

Result: FIP 3.93 → 4.35, 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 AAHartford Yard Goats · 50 IPFIP 3.36 → 4.08 (+0.72)K% 23.9% → 19.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.92%	—	×0.810	19.38%
BB% (unintentional) /BF	13.88%	—	×1.100	15.26%
HR / BF /BF	0.96%	÷0.916	×1.200	1.25%

Result: FIP 3.36 → 4.08, 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+Spokane Indians · 50 IPFIP 4.79 → 5.78 (+0.99)K% 20.7% → 15.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.68%	—	×0.770	15.92%
BB% (unintentional) /BF	14.35%	—	×1.150	16.50%
HR / BF /BF	2.95%	÷1.047	×1.250	3.53%

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 109).

Result: FIP 4.79 → 5.78, 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).

2022 A+Spokane Indians · 50 IPFIP 4.19 → 4.75 (+0.56)K% 24.9% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.89%	—	×0.770	19.16%
BB% (unintentional) /BF	9.50%	—	×1.150	10.93%
HR / BF /BF	3.62%	÷1.316	×1.250	3.44%

Result: FIP 4.19 → 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).

2022 AFresno Grizzlies · 16 IPFIP 2.09 → 2.80 (+0.70)K% 23.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.740	17.62%
BB% (unintentional) /BF	7.94%	—	×1.180	9.37%
HR / BF /BF	0.00%	÷0.947	×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 2.09 → 2.80, 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
Evan Shawver (OGILVIE)	—	—	4.69	17.8%	10.1%	2.6%	—	4.79	18.3%	8.1%	97	+0.10	—	—	—
Ryan Verdugo L 2015 · 3.61 FIP	28	SU	3.61	19.8%	10.8%	1.5%	.281	3.36	22.7%	17.3%	82	-0.25	3.36	153	87
Juan Grullon L 2016 · 4.64 FIP	26	SU	4.64	19.8%	10.9%	3.3%	.305	—	—	—	—	—	4.64	134	82
Greg Nappo L 2016 · 5.09 FIP	27	SU	5.09	17.2%	10.3%	3.9%	.285	6.26	12.3%	-0.3%	11	+1.17	3.37	144	82
Colton Johnson L 2024 · 3.92 FIP	26	SU	3.92	20.8%	11.0%	2.1%	.309	4.53	12.2%	-0.4%	48	+0.61	3.92	106	82
Stephen Peterson L 2015 · 4.59 FIP	27	SU	4.59	13.0%	9.5%	2.5%	.284	3.04	17.3%	6.3%	55	-1.55	3.04	120	81
Jimmy Reyes L 2016 · 3.82 FIP	27	SU	3.82	14.6%	6.2%	2.1%	.313	4.92	13.8%	5.8%	66	+1.10	3.02	200	80
Diego Barrera L 2024 · 3.69 FIP	24	SU	3.69	17.9%	9.2%	1.7%	.310	4.55	17.9%	7.4%	89	+0.86	3.66	155	79
Eric Jokisch L 2016 · 4.64 FIP	27	SW	4.64	12.4%	9.6%	2.5%	.330	3.93	15.2%	7.6%	283	-0.71	3.78	427	79
Brendan Nail L 2023 · 4.36 FIP	27	SU	4.36	19.3%	10.5%	2.8%	.262	—	—	—	—	—	3.45	165	79
Michael Johnson L 2018 · 5.19 FIP	27	SU	5.19	13.4%	10.0%	3.6%	.301	—	—	—	—	—	3.92	256	78
Ozzie Mendez L 2015 · 4.16 FIP	27	SU	4.16	14.6%	6.7%	2.6%	.269	3.99	11.3%	3.0%	68	-0.17	3.95	161	77
Haylen Green L 2023 · 4.09 FIP	25	SU	4.09	18.6%	10.8%	2.2%	.317	—	—	—	—	—	4.02	104	77
Will Gilbert L 2019 · 4.42 FIP	25	SU	4.42	19.9%	10.3%	3.1%	.306	—	—	—	—	—	2.92	141	77
Mac Lardner L 2023 · 3.66 FIP	25	SU	3.66	17.5%	9.4%	1.5%	.308	—	—	—	—	—	3.66	186	77
Hayden Howard L 2019 · 3.76 FIP	25	SU	3.76	17.5%	8.4%	1.9%	.328	—	—	—	—	—	3.76	200	77
Ben Onyshko L 2023 · 4.39 FIP	26	SU	4.39	16.1%	10.2%	2.5%	.268	—	—	—	—	—	3.50	219	77
Brad Kuntz L 2018 · 4.10 FIP	26	SU	4.10	20.9%	11.7%	2.4%	.352	—	—	—	—	—	2.35	197	76
Mitchell Tyranski L 2024 · 4.90 FIP	26	SU	4.90	21.0%	12.3%	3.7%	.234	3.46	20.5%	4.0%	57	-1.44	3.46	145	76
David Rollins L 2017 · 5.58 FIP	27	SU	5.58	18.0%	12.1%	4.5%	.260	5.68	15.9%	12.5%	20	+0.10	3.59	132	76
Jose Molina L 2016 · 4.17 FIP	25	SW	4.17	14.4%	8.9%	2.1%	.347	—	—	—	—	—	3.65	144	76

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	0.8	56	18.1%	10.1%	1.06	4.71
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Mike Matthews ('05)	1.2	61	16.3%	11.3%	1.07	4.54
Chris Resop ('13)	1.2	61	18.6%	10.3%	0.85	4.62
Vic Darensbourg ('05)	1.5	50	17.0%	9.3%	1.01	4.96
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*