Eric Reyzelman

P Scranton/Wilkes-Barre RailRiders

Age 26 RHP 6'2" / 188 lbs AAA

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX3 levels	31	1	39	1.16	1.99	40.9%	12.3%	—	K 30.3% · BB 15.6% · FIP 3.81
2025	24	AAAScranton/Wilk…	34	0	42	4.29	5.50	23.9%	22.3%	—	K 20.6% · BB 20.1% · FIP 5.41
2026	25	MIX2 levels	42	1	52	5.92	3.76	33.0%	13.7%	—	K 27.7% · BB 12.6% · FIP 4.27
2027PROJ	26	MLBNYY	7	0	7	5.16	5.16	25.5%	16.9%	-0.0
2028PROJ33% MLB	27	MLBNYY	17	0	18	5.10	5.11	25.3%	16.2%	-0.1
2029PROJ50% MLB	28	MLBNYY	22	0	23	5.10	5.14	25.0%	15.8%	-0.2

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

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.3 / P90 1.5, comp-based) · star 0% · didn't stick 93%

CompsDennis Sarfate (age 27) · Esmerling Vasquez (age 26) · Mitchell Stumpo (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 131123vR 115

ERA5.16

FIP5.16

K%25.5%

BB%16.9%

K-BB%8.6%

Proj IP70

Value2027 · WAR

Runs saved vs league avg · 70 IP

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)
2022	21	MIX MLE	2 levels	4	0	4	21	8	4	0	0%	1.0	38.1%	19.0%	19.0%	0.0%	6.75	2.30	—
2022	21	MIX RAW	2 levels	4	0	4	21	8	4	0	0%	1.0	38.1%	19.0%	19.0%	0.0%	6.75	2.10	—
2023	22	ROK MLE	FCL Yankees	5	0	8	33	8	3	1	0%	1.5	24.2%	9.1%	15.2%	3.0%	8.22	3.87	—
2023	22	ROK RAW	FCL Yankees	5	0	8	33	8	3	1	0%	1.5	24.2%	9.1%	15.2%	3.0%	8.22	3.88	—
2024	23	MIX MLE	3 levels	31	1	39	154	63	19	2	3%	1.2	30.3%	15.6%	14.7%	2.4%	1.16	3.81	—
2024	23	MIX MLE	3 levels	31	1	39	154	63	19	2	3%	1.2	30.3%	15.6%	14.7%	2.4%	1.16	3.81	—
2024	23	MIX RAW	3 levels	31	1	39	154	63	19	2	3%	1.2	40.9%	12.3%	28.6%	1.3%	1.16	1.99	—
2025	24	AAA MLE	Scranton/Wilkes-Barre RailRiders	34	0	42	188	45	42	5	0%	1.2	20.6%	20.1%	0.5%	2.7%	4.29	5.41	—
2025	24	AAA MLE	Scranton/Wilkes-Barre RailRiders	34	0	42	188	45	42	5	0%	1.2	20.6%	20.1%	0.5%	2.7%	4.29	5.41	—
2025	24	AAA RAW	Scranton/Wilkes-Barre RailRiders	34	0	42	188	45	42	5	0%	1.2	23.9%	22.3%	1.6%	2.7%	4.29	5.50	—
2026	25	MIX MLE	2 levels	42	1	52	227	75	31	7	2%	1.2	27.7%	12.6%	15.1%	3.5%	5.92	4.27	—
2026	25	MIX MLE	2 levels	42	1	52	227	75	31	7	2%	1.2	27.7%	12.6%	15.1%	3.5%	5.92	4.27	—
2026	25	MIX RAW	2 levels	42	1	52	227	75	31	7	2%	1.2	33.0%	13.7%	19.4%	3.1%	5.92	3.76	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	NYY	7	0	7	30	8	5	1	0%	1.0	25.5%	16.9%	8.6%	3.1%	5.16	5.16	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	NYY	51	0	54	227	57	37	7	0%	1.1	25.3%	16.2%	9.1%	3.1%	5.10	5.11	-0.3
2029	28	MLB MLE	NYY	44	0	46	196	49	31	6	0%	1.1	25.0%	15.8%	9.2%	3.2%	5.10	5.14	-0.3
2030	29	MLB MLE	NYY	40	0	42	176	43	28	6	0%	1.0	24.7%	15.7%	9.0%	3.3%	5.16	5.23	-0.3
2028	27	MLB CTX	NYY	17	0	18	76	19	12	2	0%	1.1	25.3%	16.2%	9.1%	3.1%	5.10	5.11	-0.1
2029	28	MLB CTX	NYY	22	0	23	97	24	15	3	0%	1.0	25.0%	15.8%	9.2%	3.2%	5.10	5.14	-0.2
2030	29	MLB CTX	NYY	24	0	25	106	26	17	4	0%	1.0	24.7%	15.7%	9.0%	3.3%	5.16	5.23	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		63	0	66	278	69	44	9	0%	1.0	25.0%	15.9%	9.1%	3.2%	5.12	4.78	-0.2
/ 200 IP	—	RAW		190	0	200	844	209	133	27	0%	1.1	25.0%	15.9%	9.1%	3.2%	5.12	4.78	-0.5
Career	—	MLE		116	2	144	623	164	97	18	2%	1.2	26.4%	15.6%	10.7%	2.8%	4.31	4.41	-1.0
/ 200 IP	—	MLE		161	3	200	865	228	135	25	2%	1.2	26.4%	15.6%	10.7%	2.8%	4.31	4.41	-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 AAAScranton/Wilkes-Barre RailRiders · 34 IPFIP 4.67 → 4.95 (+0.27)K% 26.7% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.71%	—	×0.860	22.97%
BB% (unintentional) /BF	16.77%	—	×0.900	15.09%
HR / BF /BF	3.11%	÷1.000	×1.100	3.42%

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 4.67 → 4.95, 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 AASomerset Patriots · 17 IPFIP 1.44 → 2.62 (+1.19)K% 48.5% → 39.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	48.48%	—	×0.810	39.27%
BB% (unintentional) /BF	6.06%	—	×1.100	6.67%
HR / BF /BF	3.03%	÷1.000	×1.200	3.64%

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 1.44 → 2.62, 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 AAAScranton/Wilkes-Barre RailRiders · 42 IPFIP 5.37 → 5.41 (+0.04)K% 23.9% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.94%	—	×0.860	20.59%
BB% (unintentional) /BF	22.34%	—	×0.900	20.11%
HR / BF /BF	2.66%	÷1.070	×1.100	2.74%

Result: FIP 5.37 → 5.41, 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 AASomerset Patriots · 23 IPFIP 2.84 → 3.81 (+0.97)K% 37.4% → 30.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.37%	—	×0.810	30.27%
BB% (unintentional) /BF	14.14%	—	×1.100	15.56%
HR / BF /BF	2.02%	÷1.027	×1.200	2.36%

Result: FIP 2.84 → 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 A+Hudson Valley Renegades · 10 IPFIP 0.52 → 1.65 (+1.13)K% 47.2% → 36.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	47.22%	—	×0.770	36.36%
BB% (unintentional) /BF	11.11%	—	×1.150	12.78%
HR / BF /BF	0.00%	÷1.032	×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 106).

Result: FIP 0.52 → 1.65, 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).

2023 ROKFCL Yankees · 8 IPFIP 3.87 → 4.83 (+0.96)K% 24.2% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.24%	—	×0.680	16.48%
BB% (unintentional) /BF	9.09%	—	×1.250	11.36%
HR / BF /BF	3.03%	÷1.383	×1.400	3.07%

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 177).

Result: FIP 3.87 → 4.83, 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
Eric Reyzelman (OGILVIE)	—	—	—	—	—	3.1%	—	5.16	25.0%	9.1%	142	-0.00	—	—	—
Dennis Sarfate R 2008 · 4.42 FIP	27	SU	4.42	24.0%	16.7%	2.2%	.263	4.81	19.8%	5.9%	23	+0.39	4.42	103	89
Esmerling Vasquez R 2010 · 4.37 FIP	26	SU	4.37	22.9%	14.6%	2.5%	.278	4.23	12.5%	1.5%	62	-0.14	3.70	204	86
Mitchell Stumpo R 2022 · 4.55 FIP	26	SU	4.55	24.0%	16.8%	2.4%	.225	5.67	21.5%	6.6%	78	+1.12	3.97	158	84
Nick Ernst R 2022 · 5.05 FIP	25	SU	5.05	21.9%	14.6%	3.5%	.275	—	—	—	—	—	3.56	117	84
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	83
Zane Russell R 2024 · 4.95 FIP	24	SU	4.95	22.7%	18.3%	2.6%	.314	5.36	18.2%	6.7%	71	+0.41	4.63	108	82
Christopher Troye R 2024 · 5.46 FIP	25	SU	5.46	24.2%	17.0%	4.1%	.282	5.61	19.1%	-3.8%	30	+0.15	3.42	158	82
Eduardo Herrera R 2024 · 4.13 FIP	24	SU	4.13	25.5%	15.7%	2.2%	.284	4.44	16.7%	-5.0%	31	+0.31	4.13	127	82
Sam Gardner R 2023 · 4.04 FIP	26	SU	4.04	23.8%	15.1%	1.9%	.298	3.23	26.7%	16.4%	76	-0.81	2.28	121	81
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	81
Nolan Riggs R 2018 · 4.49 FIP	25	SU	4.49	20.7%	14.0%	2.5%	.300	—	—	—	—	—	2.36	132	81
Kyle Wilcox R 2019 · 5.16 FIP	25	SU	5.16	25.1%	21.2%	2.7%	.310	5.57	25.1%	-1.5%	13	+0.41	2.78	310	80
Stevie Branche R 2023 · 4.04 FIP	26	SU	4.04	25.6%	19.1%	1.2%	.274	5.67	19.3%	1.7%	28	+1.63	3.23	162	80
Nelson L. Alvarez R 2024 · 4.12 FIP	26	SU	4.12	23.2%	13.1%	2.4%	.282	4.70	18.5%	9.4%	35	+0.58	2.58	233	80
Matt Seelinger R 2021 · 5.37 FIP	26	SU	5.37	28.8%	18.3%	4.3%	.312	4.58	24.8%	12.2%	116	-0.79	3.13	371	80
Fernando Baez R 2017 · 5.37 FIP	25	SU	5.37	24.3%	21.2%	3.0%	.271	—	—	—	—	—	3.45	129	79
Ronald Peña R 2018 · 4.19 FIP	26	SU	4.19	23.4%	11.6%	2.9%	.273	4.52	18.7%	7.1%	88	+0.33	3.72	187	79
Braden Webb R 2021 · 5.15 FIP	26	SU	5.15	25.2%	14.8%	4.2%	.295	—	—	—	—	—	4.48	308	79
Carter Loewen R 2024 · 4.26 FIP	25	SU	4.26	23.1%	15.0%	2.2%	.312	4.16	20.0%	11.9%	23	-0.10	2.67	145	79
Addison Russ R 2021 · 4.58 FIP	26	SU	4.58	24.3%	15.5%	2.9%	.300	—	—	—	—	—	3.08	194	79

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	1.1	53	25.2%	16.3%	1.23	5.13
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
Doug Creek ('05)	1.4	58	22.2%	15.1%	1.52	5.32
Brian Bruney ('12)	1.3	43	21.2%	15.8%	0.94	4.68
Dwayne Henry ('84-'95, -1 WAR*)	1.7	67	23.8%*	14.2%*	0.90*	5.02*
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*