Ryan Shreve

P Montgomery Biscuits

Age 29 RHP 6'7" / 233 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	AASTL	44	0	71	4.54	4.66	20.4%	8.7%	—	K 16.5% · BB 9.6% · FIP 5.29
2024	26	MIX2 levels	40	0	73	4.19	3.63	22.3%	8.0%	—	K 18.4% · BB 7.7% · FIP 3.88
2025	27	MIX2 levels	30	1	59	6.71	5.27	13.6%	10.4%	—	K 11.4% · BB 10.4% · FIP 5.07
2026	28	No MLB games played
2027PROJ	29	MLBTB	1	0	1	5.06	5.06	15.2%	9.6%	-0.0
2028PROJ31% MLB	30	MLBTB	10	0	10	5.09	5.16	15.7%	9.9%	-0.1

Next 2 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsAngel Castro (age 32) · Eder Llamas (age 29) · Willie Eyre (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA5.06

FIP5.06

K%15.2%

BB%9.6%

K-BB%5.6%

Proj IP43

Value2027 · WAR

Runs saved vs league avg · 43 IP

Grades · Contract

Scouting Grades

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)
2021	23	MIX MLE	3 levels	29	1	50	211	73	21	2	3%	1.7	25.9%	11.8%	14.0%	1.4%	3.62	3.16	—
2021	23	MIX RAW	3 levels	29	1	50	211	73	21	2	3%	1.7	34.6%	10.0%	24.6%	0.9%	3.62	1.95	—
2022	24	A+ MLE	Cedar Rapids Kernels	28	2	38	159	39	14	2	7%	1.4	18.9%	10.1%	8.8%	1.7%	3.08	3.70	—
2022	24	A+ RAW	Cedar Rapids Kernels	28	2	38	159	39	14	2	7%	1.4	24.5%	8.8%	15.7%	1.3%	3.08	2.84	—
2023	25	AA MLE	Springfield Cardinals	44	0	71	309	63	27	12	0%	1.6	16.5%	9.6%	6.9%	4.3%	4.54	5.29	—
2023	25	AA RAW	Springfield Cardinals	44	0	71	309	63	27	12	0%	1.6	20.4%	8.7%	11.7%	3.9%	4.54	4.66	—
2024	26	MIX MLE	2 levels	40	0	73	314	70	25	8	0%	1.8	18.4%	7.7%	10.7%	2.5%	4.19	3.88	—
2024	26	MIX MLE	2 levels	40	0	73	314	70	25	8	0%	1.8	18.4%	7.7%	10.7%	2.5%	4.19	3.88	—
2024	26	MIX RAW	2 levels	40	0	73	314	70	25	8	0%	1.8	22.3%	8.0%	14.3%	2.5%	4.19	3.63	—
2025	27	MIX MLE	2 levels	30	1	59	279	38	29	9	3%	2.0	11.4%	10.4%	1.0%	2.9%	6.71	5.07	—
2025	27	MIX MLE	2 levels	30	1	59	279	38	29	9	3%	2.0	11.4%	10.4%	1.0%	2.9%	6.71	5.07	—
2025	27	MIX RAW	2 levels	30	1	59	279	38	29	9	3%	2.0	13.6%	10.4%	3.2%	3.2%	6.71	5.27	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	TB	1	0	1	4	1	0	0	0%	1.0	15.2%	9.6%	5.6%	3.0%	5.06	5.06	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	TB	29	0	31	130	20	13	4	0%	1.1	15.7%	9.9%	5.8%	3.2%	5.09	5.16	-0.2
2028	30	MLB CTX	TB	10	0	10	42	7	4	1	0%	1.0	15.7%	9.9%	5.8%	3.2%	5.09	5.16	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	0	10	41	6	4	1	0%	1.1	15.7%	9.9%	5.8%	3.2%	5.09	4.78	-0.0
/ 200 IP	—	RAW		190	0	200	844	125	83	21	0%	1.1	15.7%	9.9%	5.8%	3.2%	5.09	4.78	-0.5
Career	—	MLE		171	4	291	1272	225	124	35	2%	1.7	17.7%	9.8%	8.0%	2.7%	4.55	4.34	-0.2
/ 200 IP	—	MLE		118	3	200	874	155	85	24	2%	1.7	17.7%	9.8%	8.0%	2.7%	4.55	4.34	-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.

2025 AAMontgomery Biscuits · 30 IPFIP 4.20 → 4.76 (+0.56)K% 12.0% → 9.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.97%	—	×0.810	9.70%
BB% (unintentional) /BF	10.56%	—	×1.100	11.62%
HR / BF /BF	1.41%	÷0.922	×1.200	1.83%

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 84).

Result: FIP 4.20 → 4.76, 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 AAADurham Bulls · 29 IPFIP 5.90 → 5.39 (−0.52)K% 15.3% → 13.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.33%	—	×0.860	13.18%
BB% (unintentional) /BF	10.22%	—	×0.900	9.20%
HR / BF /BF	5.11%	÷1.380	×1.100	4.07%

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 176).

Result: FIP 5.90 → 5.39, 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 AASpringfield Cardinals · 41 IPFIP 2.78 → 3.11 (+0.33)K% 27.1% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.06%	—	×0.810	21.92%
BB% (unintentional) /BF	5.29%	—	×1.100	5.82%
HR / BF /BF	2.35%	÷1.386	×1.200	2.04%

Result: FIP 2.78 → 3.11, 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 AAAMemphis Redbirds · 32 IPFIP 4.62 → 4.80 (+0.18)K% 16.7% → 14.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.67%	—	×0.860	14.33%
BB% (unintentional) /BF	11.11%	—	×0.900	10.00%
HR / BF /BF	2.78%	÷1.020	×1.100	2.99%

Result: FIP 4.62 → 4.80, 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 AASpringfield Cardinals · 71 IPFIP 4.62 → 5.29 (+0.68)K% 20.4% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.39%	—	×0.810	16.51%
BB% (unintentional) /BF	8.74%	—	×1.100	9.61%
HR / BF /BF	3.88%	÷1.080	×1.200	4.32%

Result: FIP 4.62 → 5.29, 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).

2022 A+Cedar Rapids Kernels · 38 IPFIP 2.83 → 3.70 (+0.86)K% 24.5% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.53%	—	×0.770	18.89%
BB% (unintentional) /BF	8.81%	—	×1.150	10.13%
HR / BF /BF	1.26%	÷0.948	×1.250	1.66%

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 2.83 → 3.70, 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+Cedar Rapids Kernels · 35 IPFIP 1.85 → 2.82 (+0.98)K% 33.8% → 26.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.79%	—	×0.770	26.02%
BB% (unintentional) /BF	9.66%	—	×1.150	11.10%
HR / BF /BF	0.69%	÷0.920	×1.250	0.94%

Result: FIP 1.85 → 2.82, 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 AFort Myers Mighty Mussels · 14 IPFIP 2.55 → 3.95 (+1.41)K% 34.4% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.43%	—	×0.740	25.48%
BB% (unintentional) /BF	11.48%	—	×1.180	13.54%
HR / BF /BF	1.64%	÷0.908	×1.300	2.35%

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 82).

Result: FIP 2.55 → 3.95, 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).

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
Ryan Shreve (OGILVIE)	—	—	5.06	15.2%	9.6%	3.0%	—	5.16	15.7%	5.8%	31	+0.10	—	—	—
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	88
Eder Llamas R 2015 · 4.84 FIP	29	SU	4.84	12.3%	8.8%	3.0%	.261	3.64	11.3%	4.6%	120	-1.20	3.23	171	85
Willie Eyre R 2007 · 4.53 FIP	29	SU	4.53	13.7%	9.1%	2.6%	.306	2.87	11.1%	5.5%	18	-1.66	2.87	164	85
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	85
Drew Hayes R 2016 · 3.99 FIP	28	SU	3.99	13.8%	10.1%	1.4%	.302	—	—	—	—	—	3.35	117	84
Ryan Doolittle R 2016 · 4.38 FIP	28	SU	4.38	13.9%	7.1%	2.8%	.269	—	—	—	—	—	4.03	101	83
Jose Casilla R 2016 · 4.65 FIP	27	SU	4.65	13.0%	8.0%	3.0%	.314	—	—	—	—	—	3.06	104	83
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	83
Santiago Casilla R 2009 · 4.44 FIP	29	SU	4.44	15.0%	9.4%	2.6%	.324	3.29	22.1%	13.0%	170	-1.15	2.76	647	83
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	82
Jason Boyd R 2002 · 5.81 FIP	29	SU	5.81	13.7%	10.7%	4.6%	.290	4.74	15.0%	3.7%	65	-1.07	3.68	128	81
Tony Fiore R 2000 · 5.61 FIP	28	SU	5.61	10.8%	9.5%	4.0%	.321	4.76	14.3%	3.5%	127	-0.85	4.60	142	81
Esteban Haro R 2015 · 4.14 FIP	29	SU	4.14	11.6%	8.4%	1.7%	.302	4.25	15.6%	7.8%	78	+0.11	3.76	164	81
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	81
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	81
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	80
Ronald Peña R 2021 · 4.49 FIP	29	SU	4.49	16.5%	10.4%	2.7%	.288	—	—	—	—	—	3.72	187	80
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	80
Adrian Garza R 2017 · 4.47 FIP	29	SU	4.47	16.0%	7.0%	3.4%	.351	5.18	9.7%	4.1%	113	+0.71	3.94	229	79
Brandon Puffer R 2004 · 5.23 FIP	28	SU	5.23	13.5%	11.2%	3.4%	.328	—	—	—	—	—	3.55	108	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	0.4	37	15.4%	9.7%	1.19	5.07
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Vic Darensbourg ('05)	1.5	50	17.0%	9.3%	1.01	4.96
Tom Martin ('07)	1.6	53	15.8%	10.1%	1.02	4.92
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Dave Leiper ('84-'96, 0 WAR*)	1.4	46	15.6%*	9.1%*	0.94*	4.28*