Robert Cranz

P Harrisburg Senators

Age 24 RHP 6'3" / 207 lbs AA

Overview

AAPROSPECT

ETA2028MLB%2%

Year	Age	Lvl / Team	G	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	21	AWSH	4	6	0.00	1.27	33.3%	4.8%	—	K 33.3% · BB 4.8% · FIP 0.89
2025	22	MIX2 levels	30	36	2.02	3.02	33.3%	11.9%	—	K 25.7% · BB 15.0% · FIP 3.99
2026	23	MIX3 levels	48	54	5.17	3.03	31.5%	13.3%	—	K 25.3% · BB 13.8% · FIP 3.78
2027PROJ	24	MLBWSH	1	1	4.73	4.73	23.2%	13.4%	-0.0
2028PROJ44% MLB	25	MLBWSH	16	17	4.59	4.53	23.6%	12.0%	0.0
2029PROJ67% MLB	26	MLBWSH	22	23	4.52	4.49	23.8%	11.8%	0.0

Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.4 / P90 1.0, comp-based) · star 0% · didn't stick 94%

CompsHarrison Cohen (age 24) · Logan VanWey (age 24) · Shawn Tolleson (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.73

FIP4.73

K%23.2%

BB%13.4%

K-BB%9.8%

Proj IP32

Value2027 · WAR

Runs saved vs league avg · 32 IP

Grades · Contract

Scouting Grades

K†5555

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	21	A MLE	Fredericksburg Nationals	4	0	6	21	7	1	0	0%	1.5	33.3%	4.8%	28.6%	0.0%	0.00	0.89	—
2024	21	A MLE	Fredericksburg Nationals	4	0	6	21	7	1	0	0%	1.5	33.3%	4.8%	28.6%	0.0%	0.00	0.89	—
2024	21	A RAW	Fredericksburg Nationals	4	0	6	21	7	1	0	0%	1.5	33.3%	4.8%	28.6%	0.0%	0.00	1.27	—
2025	22	MIX MLE	2 levels	30	0	36	135	45	16	3	0%	1.2	25.7%	15.0%	10.7%	2.1%	2.02	3.99	—
2025	22	MIX MLE	2 levels	30	0	36	135	45	16	3	0%	1.2	25.7%	15.0%	10.7%	2.1%	2.02	3.99	—
2025	22	MIX RAW	2 levels	30	0	36	135	45	16	3	0%	1.2	33.3%	11.9%	21.5%	2.2%	2.02	3.02	—
2026	23	MIX MLE	3 levels	48	0	54	241	76	32	4	0%	1.1	25.3%	13.8%	11.5%	2.0%	5.17	3.78	—
2026	23	MIX MLE	3 levels	48	0	54	241	76	32	4	0%	1.1	25.3%	13.8%	11.5%	2.0%	5.17	3.78	—
2026	23	MIX RAW	3 levels	48	0	54	241	76	32	4	0%	1.1	31.5%	13.3%	18.3%	1.7%	5.17	3.03	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	WSH	1	0	1	4	1	1	0	0%	1.0	23.2%	13.4%	9.8%	2.8%	4.73	4.73	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	WSH	37	0	39	163	38	20	5	0%	1.0	23.6%	12.0%	11.6%	2.8%	4.59	4.53	+0.0
2029	26	MLB MLE	WSH	33	0	35	148	35	17	4	0%	1.1	23.8%	11.8%	12.0%	2.8%	4.52	4.49	+0.0
2030	27	MLB MLE	WSH	32	0	33	140	33	16	4	0%	1.0	23.7%	11.7%	12.0%	2.8%	4.52	4.52	+0.0
2028	25	MLB CTX	WSH	16	0	17	72	17	9	2	0%	1.1	23.6%	12.0%	11.6%	2.8%	4.59	4.53	+0.0
2029	26	MLB CTX	WSH	22	0	23	97	23	11	3	0%	1.0	23.8%	11.8%	12.0%	2.8%	4.52	4.49	+0.0
2030	27	MLB CTX	WSH	25	0	26	110	26	13	3	0%	1.0	23.7%	11.7%	12.0%	2.8%	4.52	4.52	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		63	0	66	279	66	33	8	0%	1.0	23.7%	11.8%	11.9%	2.8%	4.54	4.13	+0.3
/ 200 IP	—	RAW		190	0	200	844	200	100	24	0%	1.1	23.7%	11.8%	11.9%	2.8%	4.54	4.13	+1.0
Career	—	MLE		82	0	96	397	103	54	8	0%	1.2	25.9%	13.7%	12.1%	1.9%	3.67	3.70	+0.0
/ 200 IP	—	MLE		171	0	200	830	215	114	16	0%	1.2	25.9%	13.7%	12.1%	1.9%	3.67	3.70	+0.1

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 AAHarrisburg Senators · 26 IPFIP 2.33 → 3.30 (+0.96)K% 36.4% → 29.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.36%	—	×0.810	29.45%
BB% (unintentional) /BF	6.36%	—	×1.100	7.00%
HR / BF /BF	2.73%	÷1.000	×1.200	3.27%

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 2.33 → 3.30, 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 A+Wilmington Blue Rocks · 16 IPFIP 1.95 → 3.09 (+1.14)K% 40.9% → 31.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.91%	—	×0.770	31.50%
BB% (unintentional) /BF	18.18%	—	×1.150	20.91%
HR / BF /BF	0.00%	÷1.000	×1.250	0.00%

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 100).

Result: FIP 1.95 → 3.09, 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 AAARochester Red Wings · 12 IPFIP 5.31 → 5.30 (−0.01)K% 13.8% → 11.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	13.85%	—	×0.860	11.91%
BB% (unintentional) /BF	20.00%	—	×0.900	18.00%
HR / BF /BF	1.54%	÷1.000	×1.100	1.69%

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 5.31 → 5.30, 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 AFredericksburg Nationals · 31 IPFIP 2.71 → 3.99 (+1.29)K% 34.7% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.75%	—	×0.740	25.71%
BB% (unintentional) /BF	12.71%	—	×1.180	15.00%
HR / BF /BF	1.69%	÷1.040	×1.300	2.12%

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 108).

Result: FIP 2.71 → 3.99, 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 AFredericksburg Nationals · 6 IPFIP 0.89 → 1.73 (+0.84)K% 33.3% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.740	24.67%
BB% (unintentional) /BF	4.76%	—	×1.180	5.62%
HR / BF /BF	0.00%	÷1.078	×1.300	0.00%

Result: FIP 0.89 → 1.73, 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
Robert Cranz (OGILVIE)	—	—	4.73	23.2%	13.4%	2.8%	—	4.51	23.7%	11.8%	107	-0.22	—	—	—
Harrison Cohen R 2023 · 4.56 FIP	24	SU	4.56	22.4%	13.4%	3.0%	.282	4.18	22.3%	9.0%	119	-0.38	2.12	165	93
Logan VanWey R 2023 · 4.34 FIP	24	SU	4.34	23.9%	14.0%	2.7%	.301	3.74	25.9%	15.2%	147	-0.60	2.97	194	92
Shawn Tolleson R 2012 · 3.86 FIP	24	SU	3.86	24.4%	11.9%	2.4%	.265	3.47	24.4%	18.5%	144	-0.39	3.05	218	90
Ben Hecht R 2019 · 4.51 FIP	24	SU	4.51	22.7%	12.9%	3.1%	.293	7.98	14.1%	-11.4%	13	+3.47	4.39	155	90
Craig Schlitter R 2016 · 4.53 FIP	24	SU	4.53	22.7%	15.4%	2.5%	.298	4.67	14.7%	4.2%	171	+0.14	4.25	222	90
Max Alba R 2023 · 4.47 FIP	24	SU	4.47	20.6%	12.6%	2.7%	.290	5.29	16.7%	9.8%	248	+0.82	4.47	303	90
Michael Wuertz R 2004 · 4.46 FIP	25	SU	4.46	24.2%	12.9%	3.2%	.243	3.39	26.1%	16.6%	189	-1.07	2.27	414	90
Luis Ramirez R 2016 · 3.71 FIP	24	SU	3.71	24.0%	12.6%	1.9%	.286	—	—	—	—	—	3.71	104	89
Maikel Cleto R 2014 · 4.24 FIP	25	SU	4.24	23.2%	15.2%	2.1%	.256	3.45	25.4%	14.5%	106	-0.79	2.59	185	89
Cameron Gann R 2017 · 4.22 FIP	24	SU	4.22	21.4%	12.4%	2.5%	.296	5.36	21.1%	6.8%	23	+1.14	3.58	146	89
CJ Weins R 2024 · 4.55 FIP	23	SU	4.55	24.7%	15.9%	2.8%	.276	5.77	16.2%	-4.4%	76	+1.22	4.55	117	89
Aaron Kurcz R 2015 · 3.98 FIP	24	SU	3.98	22.4%	13.6%	1.9%	.331	4.05	16.1%	8.0%	105	+0.07	3.31	213	88
Colin McKee R 2018 · 5.00 FIP	24	SU	5.00	24.2%	14.7%	3.8%	.330	4.35	27.7%	12.9%	97	-0.65	4.18	148	88
Cole Gordon R 2019 · 4.09 FIP	23	SU	4.09	22.0%	12.7%	2.3%	.243	5.19	20.9%	9.5%	83	+1.10	4.09	112	88
Brandon Cunniff R 2015 · 4.28 FIP	26	SU	4.28	24.5%	13.2%	2.9%	.256	4.32	20.3%	9.0%	115	+0.04	3.89	180	88
Stephen Jones R 2021 · 3.62 FIP	24	SU	3.62	23.8%	11.0%	2.1%	.304	4.50	21.7%	10.0%	142	+0.88	3.62	311	88
Ricardo Velez R 2023 · 4.44 FIP	24	SU	4.44	22.4%	10.9%	3.4%	.261	4.09	18.8%	8.1%	138	-0.35	3.83	166	88
Dakota Mekkes R 2019 · 4.58 FIP	24	SU	4.58	23.1%	15.4%	2.7%	.290	4.85	16.7%	1.8%	70	+0.27	2.94	246	87
Zack Jones R 2015 · 3.57 FIP	24	SU	3.57	23.9%	14.0%	1.3%	.280	3.64	28.1%	10.9%	57	+0.07	2.57	109	87
Brandon Johnson R 2023 · 4.94 FIP	24	SU	4.94	22.4%	14.2%	3.5%	.327	4.47	22.1%	12.1%	189	-0.47	3.35	250	87

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	0.7	35	23.6%	12.2%	1.08	4.59
David Aardsma ('15)	1.7	48	23.1%	12.4%	1.09	4.27
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
José Cisnero ('24)	1.4	46	24.0%	11.3%	1.01	4.16
Yorkis Perez ('02)	1.4	40	20.8%	11.8%	0.93	4.44
Gene Harris ('89-'95, -1 WAR*)	1.2	40	20.0%*	12.5%*	0.98*	4.96*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*