Randy Constanza

P DSL Tigers 1

Age 20 LHP 6'2" / 175 lbs ROK

Overview

ROKPROSPECT

ETA2028MLB%0%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2025	18	ROKDSL Tigers 2	4	5	7.20	4.50	15.4%	19.2%	—	K 15.4% · BB 19.2% · FIP 4.24
2026	19	ROKDSL Tigers 1	14	20	7.65	5.05	16.7%	15.6%	—	K 11.3% · BB 19.5% · FIP 6.22
2027PROJ	20	MLBDET	11	12	5.47	5.47	20.1%	16.1%	-0.1
2028PROJ49% MLB	21	MLBDET	10	10	5.20	5.10	20.9%	14.0%	-0.1

Next 2 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

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

CompsCD Pelham (age 20) · Enrique Perez (age 20) · Boone Logan (age 21)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 121129vR 137

ERA5.47

FIP5.47

K%20.1%

BB%16.1%

K-BB%3.9%

Proj IP12

Value2027 · WAR

Runs saved vs league avg · 12 IP

Grades · Contract

Scouting Grades

K†5050

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 industry-standard fWAR.

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)
2025	18	ROK MLE	DSL Tigers 2	4	0	5	26	4	5	0	0%	1.2	15.4%	19.2%	-3.8%	0.0%	7.20	4.24	—
2025	18	ROK MLE	DSL Tigers 2	4	0	5	26	4	5	0	0%	1.2	15.4%	19.2%	-3.8%	0.0%	7.20	4.24	—
2025	18	ROK RAW	DSL Tigers 2	4	0	5	26	4	5	0	0%	1.2	15.4%	19.2%	-3.8%	0.0%	7.20	4.50	—
2026	19	ROK MLE	DSL Tigers 1	14	0	20	96	16	15	2	0%	1.4	11.3%	19.5%	-8.2%	2.9%	7.65	6.22	—
2026	19	ROK MLE	DSL Tigers 1	14	0	20	96	16	15	2	0%	1.4	11.3%	19.5%	-8.2%	2.9%	7.65	6.22	—
2026	19	ROK RAW	DSL Tigers 1	14	0	20	96	16	15	2	0%	1.4	16.7%	15.6%	1.0%	2.1%	7.65	5.05	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	20	MLB	DET	11	0	12	51	10	8	2	0%	1.1	20.1%	16.1%	3.9%	3.0%	5.47	5.47	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	21	MLB MLE	DET	19	0	20	84	18	12	2	0%	1.1	20.9%	14.0%	6.9%	2.9%	5.20	5.10	-0.1
2028	21	MLB CTX	DET	10	0	10	42	9	6	1	0%	1.0	20.9%	14.0%	6.9%	2.9%	5.20	5.10	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	42	9	6	1	0%	1.1	20.9%	14.0%	6.9%	2.9%	5.20	4.72	-0.0
/ 200 IP	—	RAW		190	0	200	844	183	122	20	0%	1.1	20.9%	14.0%	6.9%	2.9%	5.20	4.72	-0.4
Career	—	MLE		18	0	25	122	15	24	3	0%	1.4	12.2%	19.5%	-7.3%	2.3%	7.56	5.80	-0.1
/ 200 IP	—	MLE		144	0	200	976	119	190	22	0%	1.4	12.2%	19.5%	-7.3%	2.3%	7.56	5.80	-1.3

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
Randy Constanza (OGILVIE)	—	—	5.47	20.1%	16.1%	3.0%	—	5.10	20.9%	6.9%	20	-0.37	—	—	—
CD Pelham L 2015 · 4.77 FIP	20	SU	4.77	18.8%	18.7%	1.6%	.286	4.00	20.4%	7.8%	109	-0.77	3.39	288	85
Enrique Perez L 2018 · 4.81 FIP	20	SU	4.81	16.2%	14.3%	2.3%	.286	—	—	—	—	—	3.76	133	84
Boone Logan L 2006 · 4.69 FIP	21	SU	4.69	16.1%	14.0%	2.1%	.302	4.14	17.2%	10.5%	110	-0.55	2.58	442	83
Austin Hamilton L 2017 · 4.92 FIP	23	SU	4.92	17.0%	15.6%	2.3%	.329	4.20	16.3%	8.9%	109	-0.72	4.02	135	82
Brendan Nail L 2019 · 4.88 FIP	23	SU	4.88	23.8%	16.4%	3.1%	.305	3.83	26.2%	15.2%	87	-1.05	3.45	165	82
Peter Bonilla L 2024 · 4.63 FIP	19	SU	4.63	20.9%	18.3%	1.8%	.250	6.24	19.5%	-5.4%	51	+1.61	4.27	134	81
Gregori Louis L 2023 · 6.48 FIP	20	SU	6.48	17.3%	20.4%	4.1%	.241	4.37	19.6%	2.9%	111	-2.11	3.58	149	80
Matt Minnick L 2019 · 5.59 FIP	23	SU	5.59	17.2%	14.1%	3.9%	.302	4.67	23.5%	12.1%	105	-0.92	3.81	147	80
Yenfri Sosa L 2024 · 6.08 FIP	20	SU	6.08	19.0%	21.3%	3.4%	.309	4.41	21.7%	7.4%	38	-1.67	2.49	128	79
Deyer Zapata L 2024 · 5.79 FIP	20	SU	5.79	18.0%	15.3%	4.1%	.319	3.77	16.2%	7.0%	15	-2.02	3.77	130	79
Trevor Seidenberger L 2015 · 4.64 FIP	23	SU	4.64	18.1%	14.3%	2.3%	.248	6.29	13.1%	-1.8%	52	+1.65	4.64	101	79
Daniel Gonzalez L 2022 · 5.66 FIP	20	SU	5.66	16.3%	14.0%	3.9%	.310	4.44	23.2%	1.7%	55	-1.22	4.34	136	79
Jeff Belge L 2021 · 4.91 FIP	23	SU	4.91	24.0%	18.8%	2.7%	.343	3.68	24.2%	10.4%	131	-1.23	3.30	175	79
Max Green L 2018 · 4.87 FIP	22	SU	4.87	15.7%	13.3%	2.6%	.352	4.41	13.9%	6.6%	86	-0.46	4.19	169	78
Denny Bentley L 2018 · 4.85 FIP	20	SU	4.85	19.6%	10.3%	3.8%	.318	2.88	25.4%	10.3%	58	-1.97	2.88	175	77
Tim Collins L 2011 · 4.36 FIP	21	SU	4.36	20.3%	15.6%	1.8%	.255	3.47	25.9%	15.6%	144	-0.89	3.16	297	77
Nicolo Pinazzi L 2021 · 4.55 FIP	21	SU	4.55	25.7%	21.3%	1.7%	.389	5.41	22.7%	0.2%	76	+0.86	2.58	155	77
Joseph Menefee L 2023 · 4.50 FIP	23	SU	4.50	21.9%	18.5%	1.7%	.361	4.71	24.8%	6.0%	99	+0.21	3.22	146	77
Julian Bosnic L 2023 · 5.72 FIP	23	SU	5.72	22.5%	21.0%	3.4%	.206	4.74	19.1%	-0.1%	90	-0.98	4.31	136	77
Daniel Juarez L 2021 · 4.75 FIP	20	SU	4.75	25.6%	19.2%	2.5%	.170	4.09	21.8%	9.3%	131	-0.66	3.68	221	76