Luis Ghisays

P ACL Cubs

Age 21 RHP 5'11" / 188 lbs ROK peak 0.6 · 2032

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	19	ROKDSL Cubs Red	12	12	49	4.22	3.06	24.3%	7.6%	—	K 16.5% · BB 9.5% · FIP 4.58
2026	20	ROKCHC	15	1	26	6.23	4.45	23.1%	10.7%	—	K 15.7% · BB 13.4% · FIP 6.01
2027PROJ	21	MLBCHC	—	—	0	5.43	5.43	15.9%	12.8%	—
2028PROJ49% MLB	22	MLBCHC	3	3	18	5.18	5.09	17.8%	11.6%	0.1
2029PROJ73% MLB	23	MLBCHC	5	5	27	4.97	4.87	18.9%	10.8%	0.2

Next 3 projected WAR 0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control45Command40

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsTrent Fennell (age 22) · Juan Perez (age 21) · Seth McClung (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136128vR 120

ERA5.43

FIP5.43

K%15.9%

BB%12.8%

K-BB%3.1%

Proj IP36

Value2027 · WAR

Runs saved vs league avg · 36 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL4545

CMD4040

K†3050

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)
2024	18	ROK MLE	DSL Cubs Red	11	11	35	158	32	19	4	100%	3.2	13.8%	15.0%	-1.3%	3.5%	6.37	5.74	—
2024	18	ROK MLE	DSL Cubs Red	11	11	35	158	32	19	4	100%	3.2	13.8%	15.0%	-1.3%	3.5%	6.37	5.74	—
2024	18	ROK RAW	DSL Cubs Red	11	11	35	158	32	19	4	100%	3.2	20.3%	12.0%	8.2%	2.5%	6.37	4.37	—
2025	19	ROK MLE	DSL Cubs Red	12	12	49	210	51	16	4	100%	4.1	16.5%	9.5%	7.0%	3.0%	4.22	4.58	—
2025	19	ROK MLE	DSL Cubs Red	12	12	49	210	51	16	4	100%	4.1	16.5%	9.5%	7.0%	3.0%	4.22	4.58	—
2025	19	ROK RAW	DSL Cubs Red	12	12	49	210	51	16	4	100%	4.1	24.3%	7.6%	16.7%	1.9%	4.22	3.06	—
2026	20	ROK MLE	ACL Cubs	15	1	26	121	28	13	4	7%	1.7	15.7%	13.4%	2.3%	4.6%	6.23	6.01	—
2026	20	ROK MLE	ACL Cubs	15	1	26	121	28	13	4	7%	1.7	15.7%	13.4%	2.3%	4.6%	6.23	6.01	—
2026	20	ROK RAW	ACL Cubs	15	1	26	121	28	13	4	7%	1.7	23.1%	10.7%	12.4%	3.3%	6.23	4.45	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	CHC	—	—	0	—	—	—	—	—	—	15.9%	12.8%	3.1%	3.1%	5.43	5.43	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	CHC	7	7	37	157	28	18	5	100%	5.3	17.8%	11.6%	6.2%	3.0%	5.18	5.09	+0.1
2029	23	MLB MLE	CHC	7	7	37	157	30	17	5	100%	5.3	18.9%	10.8%	8.1%	2.9%	4.97	4.87	+0.2
2030	24	MLB MLE	CHC	7	7	37	157	31	16	5	100%	5.3	19.7%	10.4%	9.3%	2.9%	4.82	4.74	+0.3
2031	25	MLB MLE	CHC	6	6	34	143	29	15	4	100%	5.6	20.2%	10.2%	10.0%	2.9%	4.72	4.66	+0.3
2032	26	MLB MLE	CHC	6	6	34	143	29	14	4	100%	5.6	20.4%	10.1%	10.2%	2.9%	4.67	4.64	+0.3
2033	27	MLB MLE	CHC	6	6	33	139	28	14	4	100%	5.5	20.3%	10.2%	10.1%	3.0%	4.67	4.68	+0.3
2028	22	MLB CTX	CHC	3	3	18	76	14	9	2	100%	6.0	17.8%	11.6%	6.2%	3.0%	5.18	5.09	+0.1
2029	23	MLB CTX	CHC	5	5	27	114	22	12	3	100%	5.4	18.9%	10.8%	8.1%	2.9%	4.97	4.87	+0.2
2030	24	MLB CTX	CHC	6	6	31	131	26	14	4	100%	5.2	19.7%	10.4%	9.3%	2.9%	4.82	4.74	+0.2
2031	25	MLB CTX	CHC	5	5	30	127	26	13	4	100%	6.0	20.2%	10.2%	10.0%	2.9%	4.72	4.66	+0.3
2032	26	MLB CTX	CHC	5	5	31	131	27	13	4	100%	6.2	20.4%	10.1%	10.2%	2.9%	4.67	4.64	+0.3
2033	27	MLB CTX	CHC	5	5	31	131	27	13	4	100%	6.2	20.3%	10.2%	10.1%	3.0%	4.67	4.68	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		29	29	167	707	139	74	21	100%	5.8	19.7%	10.5%	9.2%	2.9%	4.81	4.37	+2.0
/ 200 IP	—	RAW		35	35	200	844	166	88	25	100%	5.7	19.7%	10.5%	9.2%	2.9%	4.81	4.37	+2.4
Career	—	MLE		38	24	110	489	75	60	17	63%	2.9	15.4%	12.3%	3.2%	3.6%	5.38	5.31	+1.5
/ 200 IP	—	MLE		69	44	200	886	137	109	32	63%	2.9	15.4%	12.3%	3.2%	3.6%	5.38	5.31	+1.4

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 ROKACL Cubs · 26 IPFIP 4.32 → 6.01 (+1.69)K% 23.1% → 15.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.14%	—	×0.680	15.74%
BB% (unintentional) /BF	10.74%	—	×1.250	13.43%
HR / BF /BF	3.31%	÷1.000	×1.400	4.63%

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 4.32 → 6.01, 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).

2025 ROKDSL Cubs Red · 49 IPFIP 3.06 → 4.58 (+1.52)K% 24.3% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.29%	—	×0.680	16.51%
BB% (unintentional) /BF	7.62%	—	×1.250	9.52%
HR / BF /BF	1.90%	÷0.876	×1.400	3.05%

Result: FIP 3.06 → 4.58, 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 ROKDSL Cubs Red · 35 IPFIP 4.30 → 5.74 (+1.44)K% 20.3% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.25%	—	×0.680	13.77%
BB% (unintentional) /BF	12.03%	—	×1.250	15.03%
HR / BF /BF	2.53%	÷1.025	×1.400	3.46%

Result: FIP 4.30 → 5.74, 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
Luis Ghisays (OGILVIE)	—	—	5.43	15.9%	12.8%	3.1%	—	4.90	18.8%	7.9%	111	-0.53	—	—	—
Trent Fennell R 2018 · 4.48 FIP	22	SP-	4.48	14.5%	12.5%	1.9%	.317	4.46	20.9%	7.5%	89	-0.02	4.08	163	89
Juan Perez R 2016 · 5.39 FIP	21	SW	5.39	15.4%	14.1%	3.3%	.321	4.52	10.8%	0.0%	56	-0.87	4.52	113	88
Seth McClung R 2003 · 5.63 FIP	22	SW	5.63	15.0%	14.4%	3.6%	.241	5.29	15.3%	2.8%	212	-0.34	2.52	430	85
Jhoster Baez R 2024 · 4.57 FIP	19	SP-	4.57	17.3%	14.8%	1.9%	.283	5.93	15.9%	-5.0%	73	+1.36	4.57	110	84
Luis Rujano R 2024 · 4.54 FIP	21	SW	4.54	17.0%	12.3%	2.4%	.361	4.80	17.9%	-0.8%	97	+0.26	4.54	203	84
Juan Mendez R 2021 · 4.45 FIP	22	SW	4.45	20.5%	14.2%	2.3%	.271	5.07	21.9%	6.1%	128	+0.62	3.69	156	83
Luis Rosario R 2018 · 4.68 FIP	21	SP-	4.68	17.5%	11.8%	2.8%	.323	—	—	—	—	—	2.46	206	82
Jonathan Petit R 2022 · 4.64 FIP	21	SP-	4.64	16.3%	9.1%	3.2%	.272	5.11	15.6%	2.4%	113	+0.47	2.70	189	82
Sasagi Sanchez R 2015 · 4.48 FIP	21	SW	4.48	11.4%	9.4%	2.1%	.289	4.45	12.7%	4.0%	108	-0.03	3.48	180	82
Jheyson Caraballo R 2017 · 5.25 FIP	21	SW	5.25	11.9%	10.6%	3.3%	.322	—	—	—	—	—	3.39	101	81
Tanner Cooper R 2021 · 4.71 FIP	21	SW	4.71	17.1%	14.1%	2.3%	.338	5.15	14.4%	6.7%	121	+0.44	4.51	148	81
Noah Skirrow R 2021 · 4.55 FIP	23	SP-	4.55	18.4%	11.5%	2.8%	.306	4.71	16.1%	6.1%	316	+0.16	3.97	371	81
Ryan Long R 2022 · 4.33 FIP	22	SW	4.33	17.1%	11.6%	2.2%	.263	4.69	16.6%	7.3%	292	+0.36	4.20	433	80
Carlos Romero R 2021 · 5.46 FIP	22	SW	5.46	13.1%	11.5%	3.6%	.309	4.55	21.7%	7.6%	188	-0.91	3.49	370	80
Jeff Manship R 2009 · 4.69 FIP	24	SW	4.69	14.4%	10.3%	2.7%	.330	4.23	14.9%	9.5%	51	-0.46	2.83	250	80
Luis Garcia R 2018 · 4.30 FIP	21	SP-	4.30	17.9%	13.4%	1.8%	.295	3.65	27.4%	17.5%	264	-0.65	3.40	535	80
Ben Ethridge R 2023 · 4.45 FIP	22	SP-	4.45	14.4%	13.2%	1.7%	.250	6.04	13.0%	2.0%	66	+1.59	4.45	144	80
David Rodriguez R 2024 · 4.50 FIP	22	SP-	4.50	13.5%	11.7%	1.9%	.316	3.85	16.9%	9.9%	125	-0.65	3.80	184	80
Axel Rios R 2016 · 4.70 FIP	23	SW	4.70	13.1%	13.5%	1.8%	.333	4.06	15.2%	3.2%	97	-0.64	3.50	153	80
Nathan Eovaldi R 2011 · 4.23 FIP	21	SP-	4.23	15.8%	13.7%	1.3%	.257	3.53	16.3%	9.8%	425	-0.70	2.44	1,848	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	1.2	35	19.0%	10.9%	1.14	4.93
Pedro Borbón ('03)	1.4	45	18.5%	11.1%	1.10	4.68
Will Cunnane ('04)	1.4	46	18.9%	10.4%	1.25	5.26
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*