Hyun-il Choi

P Harrisburg Senators

Age 27 RHP 6'2" / 215 lbs AA peak 0.4 · 2027

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	23	A+LAD	16	13	60	3.75	3.47	18.1%	4.7%	—	K 13.9% · BB 5.4% · FIP 4.31
2024	24	MIX2 levels	24	21	115	4.92	3.84	20.2%	7.9%	—	K 16.9% · BB 7.4% · FIP 4.28
2025	25	MIX2 levels	30	20	116	4.87	5.03	17.8%	6.9%	—	K 14.9% · BB 7.1% · FIP 5.81
2026	26	No MLB games played
2027PROJ	27	MLBWSH	1	1	2	5.19	5.19	14.0%	7.6%	0.0
2028PROJ38% MLB	28	MLBWSH	4	4	23	5.15	5.19	14.8%	8.0%	0.1
2029PROJ56% MLB	29	MLBWSH	5	5	30	5.18	5.25	15.2%	8.3%	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

Stuff35Control55Command45

CompsBryce Morrow (age 27) · Edgar Alberto Garcia (age 27) · David Griffin (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 132124vR 116

ERA5.19

FIP5.19

K%14.0%

BB%7.6%

K-BB%6.4%

Proj IP77

Value2027 · WAR

Runs saved vs league avg · 77 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5555

CMD4545

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)
2019	19	ROK MLE	AZL Dodgers Mota	14	11	65	262	71	11	6	79%	4.6	18.4%	5.2%	13.2%	3.2%	2.63	3.97	—
2019	19	ROK RAW	AZL Dodgers Mota	14	11	65	262	71	11	6	79%	4.6	27.1%	4.2%	22.9%	2.3%	2.63	2.62	—
2021	21	MIX MLE	2 levels	24	11	106	415	106	18	12	46%	4.4	19.1%	5.0%	14.1%	3.9%	3.55	4.26	—
2021	21	MIX RAW	2 levels	24	11	106	415	106	18	12	46%	4.4	25.5%	4.3%	21.2%	2.9%	3.55	3.08	—
2022	22	MIX MLE	2 levels	2	1	4	17	4	0	0	50%	2.0	23.5%	0.0%	23.5%	0.0%	4.50	1.11	—
2022	22	MIX RAW	2 levels	2	1	4	17	4	0	0	50%	2.0	23.5%	0.0%	23.5%	0.0%	4.50	1.10	—
2023	23	A+ MLE	Great Lakes Loons	16	13	60	254	46	12	6	81%	3.8	13.9%	5.4%	8.5%	3.1%	3.75	4.31	—
2023	23	A+ RAW	Great Lakes Loons	16	13	60	254	46	12	6	81%	3.8	18.1%	4.7%	13.4%	2.4%	3.75	3.47	—
2024	24	MIX MLE	2 levels	24	21	115	505	102	40	13	88%	4.8	16.9%	7.4%	9.5%	3.0%	4.92	4.28	—
2024	24	MIX MLE	2 levels	24	21	115	505	102	40	13	88%	4.8	16.9%	7.4%	9.5%	3.0%	4.92	4.28	—
2024	24	MIX RAW	2 levels	24	21	115	505	102	40	13	88%	4.8	20.2%	7.9%	12.3%	2.6%	4.92	3.84	—
2025	25	MIX MLE	2 levels	30	20	116	494	88	34	23	67%	3.9	14.9%	7.1%	7.7%	5.6%	4.87	5.81	—
2025	25	MIX MLE	2 levels	30	20	116	494	88	34	23	67%	3.9	14.9%	7.1%	7.7%	5.6%	4.87	5.81	—
2025	25	MIX RAW	2 levels	30	20	116	494	88	34	23	67%	3.9	17.8%	6.9%	10.9%	4.7%	4.87	5.03	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	WSH	1	1	2	8	1	1	0	100%	2.0	14.0%	7.6%	6.4%	3.5%	5.19	5.19	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	WSH	10	10	62	261	39	21	9	100%	6.2	14.8%	8.0%	6.9%	3.6%	5.15	5.19	+0.1
2029	29	MLB MLE	WSH	9	9	54	226	34	19	8	100%	5.9	15.2%	8.3%	7.0%	3.7%	5.18	5.25	+0.1
2030	30	MLB MLE	WSH	8	8	47	200	31	17	8	100%	5.9	15.3%	8.6%	6.7%	3.8%	5.28	5.38	+0.0
2028	28	MLB CTX	WSH	4	4	23	97	14	8	3	100%	5.8	14.8%	8.0%	6.9%	3.6%	5.15	5.19	+0.1
2029	29	MLB CTX	WSH	5	5	30	127	19	10	5	100%	6.0	15.2%	8.3%	7.0%	3.7%	5.18	5.25	+0.1
2030	30	MLB CTX	WSH	5	5	32	135	21	12	5	100%	6.4	15.3%	8.6%	6.7%	3.8%	5.28	5.38	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		14	14	85	360	55	30	13	100%	6.1	15.2%	8.3%	6.8%	3.7%	5.21	4.90	+0.5
/ 200 IP	—	RAW		33	33	200	844	129	70	31	100%	6.1	15.2%	8.3%	6.8%	3.7%	5.21	4.90	+1.1
Career	—	MLE		110	77	467	1947	326	121	75	70%	4.2	16.7%	6.2%	10.5%	3.9%	4.12	4.60	+0.2
/ 200 IP	—	MLE		47	33	200	834	140	52	32	70%	4.2	16.7%	6.2%	10.5%	3.9%	4.12	4.60	+0.3

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.

2025 AAHarrisburg Senators · 108 IPFIP 4.83 → 5.81 (+0.98)K% 18.3% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.34%	—	×0.810	14.86%
BB% (unintentional) /BF	6.49%	—	×1.100	7.14%
HR / BF /BF	4.47%	÷0.963	×1.200	5.57%

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 93).

Result: FIP 4.83 → 5.81, 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).

2025 AAARochester Red Wings · 8 IPFIP 6.87 → 7.40 (+0.53)K% 12.8% → 11.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.77%	—	×0.860	10.98%
BB% (unintentional) /BF	10.64%	—	×0.900	9.57%
HR / BF /BF	6.38%	÷0.960	×1.100	7.32%

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 92).

Result: FIP 6.87 → 7.40, 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 AAAOklahoma City Baseball Club · 74 IPFIP 4.09 → 4.45 (+0.35)K% 17.6% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.55%	—	×0.860	15.10%
BB% (unintentional) /BF	10.03%	—	×0.900	9.03%
HR / BF /BF	2.19%	÷0.896	×1.100	2.69%

Result: FIP 4.09 → 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).

2024 AATulsa Drillers · 42 IPFIP 3.33 → 4.01 (+0.68)K% 24.7% → 20.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.73%	—	×0.810	20.03%
BB% (unintentional) /BF	4.30%	—	×1.100	4.73%
HR / BF /BF	3.23%	÷1.063	×1.200	3.64%

Result: FIP 3.33 → 4.01, 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+Great Lakes Loons · 60 IPFIP 3.47 → 4.31 (+0.85)K% 18.1% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.11%	—	×0.770	13.94%
BB% (unintentional) /BF	4.72%	—	×1.150	5.43%
HR / BF /BF	2.36%	÷0.951	×1.250	3.10%

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 90).

Result: FIP 3.47 → 4.31, 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 ARancho Cucamonga Quakes · 65 IPFIP 2.67 → 4.03 (+1.36)K% 30.5% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.49%	—	×0.740	22.56%
BB% (unintentional) /BF	2.85%	—	×1.180	3.36%
HR / BF /BF	3.25%	÷0.965	×1.300	4.38%

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 93).

Result: FIP 2.67 → 4.03, 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).

2021 A+Great Lakes Loons · 41 IPFIP 3.67 → 4.60 (+0.93)K% 18.3% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.34%	—	×0.770	14.12%
BB% (unintentional) /BF	6.51%	—	×1.150	7.49%
HR / BF /BF	2.37%	÷0.930	×1.250	3.18%

Result: FIP 3.67 → 4.60, 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 ROKAZL Dodgers Mota · 65 IPFIP 2.60 → 3.97 (+1.37)K% 27.1% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.10%	—	×0.680	18.43%
BB% (unintentional) /BF	4.20%	—	×1.250	5.25%
HR / BF /BF	2.29%	÷1.000	×1.400	3.21%

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 100).

Result: FIP 2.60 → 3.97, 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
Hyun-il Choi (OGILVIE)	—	—	5.19	14.0%	7.6%	3.5%	—	5.27	15.1%	6.9%	163	+0.08	—	—	—
Bryce Morrow R 2015 · 4.31 FIP	27	SP-	4.31	12.8%	7.9%	2.4%	.316	5.44	10.1%	-0.2%	50	+1.13	4.31	125	87
Edgar Alberto Garcia R 2015 · 5.24 FIP	27	SP-	5.24	11.6%	9.8%	3.4%	.263	4.28	15.3%	5.2%	167	-0.96	4.01	272	84
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	83
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	83
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	82
Nick Payero R 2024 · 4.21 FIP	24	SP-	4.21	16.5%	6.3%	3.1%	.285	5.81	16.6%	4.6%	107	+1.60	4.21	178	82
Frank Batista R 2015 · 4.29 FIP	26	SP-	4.29	12.1%	8.2%	2.1%	.280	—	—	—	—	—	4.29	118	81
Nestor Molina R 2016 · 4.83 FIP	27	SP	4.83	15.0%	8.0%	3.6%	.304	3.61	17.0%	10.2%	289	-1.22	3.01	401	81
Luke Irvine R 2016 · 4.31 FIP	27	SP-	4.31	13.4%	9.8%	2.0%	.302	—	—	—	—	—	4.31	104	81
Colin Bates R 2015 · 4.57 FIP	27	SP-	4.57	10.5%	6.5%	2.8%	.301	—	—	—	—	—	4.57	111	81
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	81
Terance Marin R 2016 · 4.91 FIP	26	SP-	4.91	11.2%	7.7%	3.2%	.294	4.22	12.4%	7.5%	88	-0.69	3.54	322	80
Justin Topa R 2018 · 4.15 FIP	27	SP-	4.15	15.1%	7.9%	2.4%	.374	2.69	19.2%	12.6%	40	-1.46	2.67	284	80
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	80
Jared Mortensen R 2015 · 4.42 FIP	27	SP-	4.42	16.9%	7.8%	3.2%	.287	4.99	20.9%	2.1%	72	+0.57	4.42	200	80
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	80
Mike Augliera R 2015 · 4.27 FIP	25	SP-	4.27	12.0%	7.2%	2.3%	.350	—	—	—	—	—	4.27	114	79
Ivan Zavala R 2015 · 4.51 FIP	28	SP-	4.51	7.0%	4.7%	2.6%	.312	4.73	12.2%	4.3%	50	+0.22	4.27	209	79
Mike McCarthy R 2015 · 4.78 FIP	27	SP-	4.78	9.4%	9.1%	2.4%	.280	5.03	6.2%	-3.5%	37	+0.25	4.78	153	78
Alejandro Martinez R 2015 · 4.46 FIP	26	SP-	4.46	17.5%	10.9%	2.7%	.393	4.24	9.2%	3.9%	53	-0.22	4.24	166	78

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	60	14.8%	8.1%	1.40	5.20
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Ricky Stone ('07)	1.3	64	15.2%	8.0%	1.55	4.68
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Larry Casian ('90-'98, 0 WAR*)	1.2	40	14.7%*	6.8%*	1.25*	4.37*
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*