Johan Simon

P Erie SeaWolves

Age 26 LHP 6'1" / 166 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	ROKTOR	3	1	13	2.08	1.64	32.7%	0.0%	—	K 32.7% · BB 0.0% · FIP 1.46
2025	24	MIX3 levels	31	0	71	3.42	2.65	25.1%	9.2%	—	K 17.7% · BB 10.6% · FIP 3.45
2026	25	AADET	41	0	55	5.86	3.77	26.7%	14.3%	—	K 21.6% · BB 15.7% · FIP 4.50
2027PROJ	26	MLBDET	1	0	1	5.10	5.10	19.7%	14.2%	-0.0
2028PROJ38% MLB	27	MLBDET	18	0	19	5.05	5.06	20.1%	13.8%	-0.1
2029PROJ60% MLB	28	MLBDET	25	0	26	5.05	5.09	20.2%	13.6%	-0.2

Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control45Command45

Career WAR0.0 WAR median (P10 -0.2 / P90 1.0, comp-based) · star 0% · didn't stick 96%

CompsMatt Purke (age 26) · Colton Johnson (age 26) · Juan Grullon (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 114122vR 130

ERA5.10

FIP5.10

K%19.7%

BB%14.2%

K-BB%5.5%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL4545

CMD4545

K†4550

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	20	ROK MLE	DSL Blue Jays	7	5	22	86	25	7	1	71%	3.1	19.8%	10.2%	9.6%	1.4%	3.74	3.51	—
2021	20	ROK RAW	DSL Blue Jays	7	5	22	86	25	7	1	71%	3.1	29.1%	8.1%	20.9%	1.2%	3.74	2.36	—
2022	21	ROK MLE	FCL Blue Jays	11	3	27	117	33	16	0	27%	2.5	19.2%	17.1%	2.1%	0.0%	2.96	3.65	—
2022	21	ROK RAW	FCL Blue Jays	11	3	27	117	33	16	0	27%	2.5	28.2%	13.7%	14.5%	0.0%	2.96	2.44	—
2023	22	ROK MLE	FCL Blue Jays	10	1	14	65	14	8	2	10%	1.4	14.6%	15.4%	-0.7%	4.3%	8.36	6.17	—
2023	22	ROK RAW	FCL Blue Jays	10	1	14	65	14	8	2	10%	1.4	21.5%	12.3%	9.2%	3.1%	8.36	4.67	—
2024	23	ROK MLE	FCL Blue Jays	3	1	13	49	16	0	1	33%	4.3	32.7%	0.0%	32.7%	2.0%	2.08	1.46	—
2024	23	ROK MLE	FCL Blue Jays	3	1	13	49	16	0	1	33%	4.3	32.7%	0.0%	32.7%	2.0%	2.08	1.46	—
2024	23	ROK RAW	FCL Blue Jays	3	1	13	49	16	0	1	33%	4.3	32.7%	0.0%	32.7%	2.0%	2.08	1.64	—
2025	24	MIX MLE	3 levels	31	0	71	315	79	29	3	0%	2.3	17.7%	10.6%	7.2%	0.9%	3.42	3.45	—
2025	24	MIX MLE	3 levels	31	0	71	315	79	29	3	0%	2.3	17.7%	10.6%	7.2%	0.9%	3.42	3.45	—
2025	24	MIX RAW	3 levels	31	0	71	315	79	29	3	0%	2.3	25.1%	9.2%	15.9%	1.0%	3.42	2.65	—
2026	25	AA MLE	Erie SeaWolves	41	0	55	266	71	38	5	0%	1.3	21.6%	15.7%	5.9%	2.3%	5.86	4.50	—
2026	25	AA MLE	Erie SeaWolves	41	0	55	266	71	38	5	0%	1.3	21.6%	15.7%	5.9%	2.3%	5.86	4.50	—
2026	25	AA RAW	Erie SeaWolves	41	0	55	266	71	38	5	0%	1.3	26.7%	14.3%	12.4%	1.9%	5.86	3.77	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	DET	1	0	1	4	1	1	0	0%	1.0	19.7%	14.2%	5.5%	2.7%	5.10	5.10	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	DET	49	0	52	218	44	30	6	0%	1.1	20.1%	13.8%	6.2%	2.8%	5.05	5.06	-0.3
2029	28	MLB MLE	DET	42	0	44	185	37	25	5	0%	1.0	20.2%	13.6%	6.6%	2.9%	5.05	5.09	-0.3
2030	29	MLB MLE	DET	38	0	39	166	33	23	5	0%	1.0	20.1%	13.6%	6.5%	3.1%	5.11	5.18	-0.3
2028	27	MLB CTX	DET	18	0	19	80	16	11	2	0%	1.1	20.1%	13.8%	6.2%	2.8%	5.05	5.06	-0.1
2029	28	MLB CTX	DET	25	0	26	110	22	15	3	0%	1.0	20.2%	13.6%	6.6%	2.9%	5.05	5.09	-0.2
2030	29	MLB CTX	DET	27	0	28	118	24	16	4	0%	1.0	20.1%	13.6%	6.5%	3.1%	5.11	5.18	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		70	0	73	310	62	42	9	0%	1.0	20.1%	13.7%	6.5%	2.9%	5.07	4.74	-0.2
/ 200 IP	—	RAW		190	0	200	844	169	114	25	0%	1.1	20.1%	13.7%	6.5%	2.9%	5.07	4.74	-0.4
Career	—	MLE		103	10	202	898	178	114	14	10%	2.0	19.9%	12.7%	7.2%	1.6%	4.31	3.88	-0.9
/ 200 IP	—	MLE		102	10	200	888	176	112	14	10%	2.0	19.9%	12.7%	7.2%	1.6%	4.31	3.88	-1.3

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 AAErie SeaWolves · 55 IPFIP 3.69 → 4.50 (+0.82)K% 26.7% → 21.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.69%	—	×0.810	21.62%
BB% (unintentional) /BF	14.29%	—	×1.100	15.71%
HR / BF /BF	1.88%	÷1.000	×1.200	2.26%

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 3.69 → 4.50, 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).

2025 ADunedin Blue Jays · 40 IPFIP 2.43 → 3.17 (+0.74)K% 24.5% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.46%	—	×0.740	18.10%
BB% (unintentional) /BF	8.70%	—	×1.180	10.26%
HR / BF /BF	0.54%	÷1.284	×1.300	0.55%

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 157).

Result: FIP 2.43 → 3.17, 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+Vancouver Canadians · 19 IPFIP 3.15 → 4.07 (+0.92)K% 22.0% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.95%	—	×0.770	16.90%
BB% (unintentional) /BF	9.76%	—	×1.150	11.22%
HR / BF /BF	1.22%	÷0.855	×1.250	1.78%

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 71).

Result: FIP 3.15 → 4.07, 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 AANew Hampshire Fisher Cats · 11 IPFIP 2.76 → 3.81 (+1.05)K% 32.7% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.65%	—	×0.810	26.45%
BB% (unintentional) /BF	10.20%	—	×1.100	11.22%
HR / BF /BF	2.04%	÷0.885	×1.200	2.77%

Result: FIP 2.76 → 3.81, 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 ROKFCL Blue Jays · 13 IPFIP 1.46 → 2.92 (+1.46)K% 32.7% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.65%	—	×0.680	22.20%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	2.04%	÷0.925	×1.400	3.09%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 85).

Result: FIP 1.46 → 2.92, 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 ROKFCL Blue Jays · 14 IPFIP 4.53 → 6.17 (+1.64)K% 21.5% → 14.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.54%	—	×0.680	14.65%
BB% (unintentional) /BF	12.31%	—	×1.250	15.38%
HR / BF /BF	3.08%	÷1.005	×1.400	4.29%

Result: FIP 4.53 → 6.17, 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 ROKFCL Blue Jays · 27 IPFIP 2.45 → 3.65 (+1.20)K% 28.2% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.21%	—	×0.680	19.18%
BB% (unintentional) /BF	13.68%	—	×1.250	17.09%
HR / BF /BF	0.00%	÷0.904	×1.400	0.00%

Result: FIP 2.45 → 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).

2021 ROKDSL Blue Jays · 22 IPFIP 2.31 → 3.51 (+1.19)K% 29.1% → 19.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.07%	—	×0.680	19.77%
BB% (unintentional) /BF	8.14%	—	×1.250	10.17%
HR / BF /BF	1.16%	÷1.134	×1.400	1.44%

Result: FIP 2.31 → 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).

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
Johan Simon (OGILVIE)	—	—	5.10	19.7%	14.2%	2.7%	—	5.10	20.1%	6.4%	135	+0.00	—	—	—
Matt Purke L 2016 · 4.25 FIP	26	SU	4.25	19.1%	13.9%	1.8%	.284	3.54	21.4%	8.8%	112	-0.71	3.01	226	89
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	83
Juan Grullon L 2016 · 4.64 FIP	26	SU	4.64	19.8%	10.9%	3.3%	.305	—	—	—	—	—	4.64	134	83
Sean Keselica L 2019 · 4.47 FIP	26	SU	4.47	18.0%	14.5%	1.9%	.314	—	—	—	—	—	2.79	235	83
Graeme Stinson L 2023 · 4.85 FIP	25	SU	4.85	19.5%	15.6%	2.6%	.302	—	—	—	—	—	3.56	146	82
Russell Smith L 2024 · 4.00 FIP	25	SU	4.00	19.0%	13.9%	1.4%	.266	—	—	—	—	—	4.00	175	82
Matt Thornton L 2004 · 4.18 FIP	27	SU	4.18	20.3%	16.2%	1.4%	.304	4.18	21.8%	11.5%	167	-0.00	1.71	663	82
Brian Moran L 2015 · 4.50 FIP	26	SU	4.50	17.7%	14.1%	2.0%	.318	2.74	25.0%	17.4%	80	-1.76	1.80	421	82
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	82
Stephen Randolph L 2003 · 4.83 FIP	29	SU	4.83	18.5%	14.8%	2.6%	.247	5.69	15.8%	-3.0%	82	+0.86	4.83	155	81
Phil Pfeifer L 2018 · 4.15 FIP	26	SU	4.15	17.4%	15.7%	1.0%	.279	4.06	21.4%	11.5%	161	-0.09	3.61	307	80
Brad Kuntz L 2018 · 4.10 FIP	26	SU	4.10	20.9%	11.7%	2.4%	.352	—	—	—	—	—	2.35	197	80
Will Lamb L 2017 · 5.78 FIP	26	SU	5.78	20.0%	14.0%	4.7%	.322	—	—	—	—	—	3.64	178	80
Rob Zastryzny L 2018 · 4.31 FIP	26	SU	4.31	18.4%	11.0%	2.5%	.264	4.81	19.8%	10.8%	142	+0.50	3.31	634	80
John Bale L 2001 · 4.41 FIP	27	SU	4.41	18.6%	15.0%	1.8%	.219	4.12	19.0%	13.9%	46	-0.29	2.49	168	80
Haylen Green L 2023 · 4.09 FIP	25	SU	4.09	18.6%	10.8%	2.2%	.317	—	—	—	—	—	4.02	104	80
Luis Perez L 2011 · 4.35 FIP	26	SU	4.35	18.4%	8.8%	3.1%	.317	3.32	22.3%	13.2%	42	-1.03	3.32	173	80
Tom Windle L 2018 · 4.56 FIP	26	SU	4.56	19.0%	11.8%	2.9%	.269	4.37	17.2%	1.8%	74	-0.19	3.68	330	80
Fabian Williamson L 2015 · 5.31 FIP	26	SU	5.31	17.4%	17.9%	2.6%	.289	4.16	20.0%	8.2%	77	-1.15	3.39	154	80
Jeff Belge L 2024 · 4.20 FIP	26	SU	4.20	19.4%	12.3%	2.1%	.250	—	—	—	—	—	3.30	175	80

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	51	20.0%	13.9%	1.10	5.08
Doug Bochtler ('00)	1.3	65	18.6%	14.4%	1.25	4.57
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Richie Lewis ('98)	1.5	59	18.1%	14.1%	1.38	4.88
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*