Ryan Harvey

P West Michigan Whitecaps

Age 26 RHP 6'3" / 195 lbs A+

Overview

A+PROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	ANYY	11	10	31	6.03	3.10	24.8%	13.5%	—	K 18.4% · BB 15.9% · FIP 4.08
2025	24	MIX3 levels	14	0	19	2.79	2.58	28.9%	9.2%	—	K 28.9% · BB 9.2% · FIP 2.54
2026	25	MIX2 levels	37	0	58	4.06	4.16	21.3%	7.0%	—	K 16.2% · BB 8.4% · FIP 4.74
2027PROJ	26	MLBDET	—	—	0	4.79	4.79	18.0%	9.1%	—
2028PROJ37% MLB	27	MLBDET	14	0	15	4.77	4.78	18.6%	9.2%	-0.0
2029PROJ59% MLB	28	MLBDET	19	0	20	4.79	4.83	18.8%	9.3%	-0.1

Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsTyler Yates (age 26) · Jarret Whorff (age 25) · Jorge Reyes (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 124116vR 108

ERA4.79

FIP4.79

K%18.0%

BB%9.1%

K-BB%9.0%

Proj IP36

Value2027 · WAR

Runs saved vs league avg · 36 IP

Grades · Contract

Scouting Grades

K†4545

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)
2023	22	MIX MLE	2 levels	13	12	46	202	48	22	6	92%	3.5	16.7%	13.1%	3.6%	3.4%	3.94	5.20	—
2023	22	MIX RAW	2 levels	13	12	46	202	48	22	6	92%	3.5	23.8%	10.9%	12.9%	3.0%	3.94	4.15	—
2024	23	A MLE	Tampa Tarpons	11	10	31	141	35	19	1	91%	2.8	18.4%	15.9%	2.5%	0.9%	6.03	4.08	—
2024	23	A MLE	Tampa Tarpons	11	10	31	141	35	19	1	91%	2.8	18.4%	15.9%	2.5%	0.9%	6.03	4.08	—
2024	23	A RAW	Tampa Tarpons	11	10	31	141	35	19	1	91%	2.8	24.8%	13.5%	11.3%	0.7%	6.03	3.10	—
2025	24	MIX MLE	3 levels	14	0	19	76	22	7	1	0%	1.4	28.9%	9.2%	19.7%	1.3%	2.79	2.54	—
2025	24	MIX MLE	3 levels	14	0	19	76	22	7	1	0%	1.4	28.9%	9.2%	19.7%	1.3%	2.79	2.54	—
2025	24	MIX RAW	3 levels	14	0	19	76	22	7	1	0%	1.4	28.9%	9.2%	19.7%	1.3%	2.79	2.58	—
2026	25	MIX MLE	2 levels	37	0	58	258	55	18	9	0%	1.6	16.2%	8.4%	7.8%	3.5%	4.06	4.74	—
2026	25	MIX MLE	2 levels	37	0	58	258	55	18	9	0%	1.6	16.2%	8.4%	7.8%	3.5%	4.06	4.74	—
2026	25	MIX RAW	2 levels	37	0	58	258	55	18	9	0%	1.6	21.3%	7.0%	14.3%	3.5%	4.06	4.16	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	DET	—	—	0	—	—	—	—	—	—	18.0%	9.1%	9.0%	3.1%	4.79	4.79	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	DET	38	0	40	169	31	15	5	0%	1.1	18.6%	9.2%	9.4%	3.1%	4.77	4.78	-0.1
2029	28	MLB MLE	DET	33	0	35	147	28	14	5	0%	1.1	18.8%	9.3%	9.5%	3.2%	4.79	4.83	-0.1
2028	27	MLB CTX	DET	14	0	15	63	12	6	2	0%	1.1	18.6%	9.2%	9.4%	3.1%	4.77	4.78	-0.0
2029	28	MLB CTX	DET	19	0	20	84	16	8	3	0%	1.1	18.8%	9.3%	9.5%	3.2%	4.79	4.83	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		33	0	35	148	28	14	5	0%	1.1	18.7%	9.2%	9.5%	3.2%	4.78	4.43	+0.1
/ 200 IP	—	RAW		190	0	200	844	159	80	28	0%	1.1	18.7%	9.2%	9.5%	3.2%	4.78	4.43	+0.3
Career	—	MLE		75	22	154	677	124	77	18	29%	2.1	18.2%	11.4%	6.8%	2.7%	4.27	4.49	-0.2
/ 200 IP	—	MLE		97	29	200	879	160	101	24	29%	2.1	18.2%	11.4%	6.8%	2.7%	4.27	4.49	-0.6

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 A+West Michigan Whitecaps · 56 IPFIP 3.80 → 4.74 (+0.94)K% 21.1% → 16.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.05%	—	×0.770	16.21%
BB% (unintentional) /BF	7.29%	—	×1.150	8.38%
HR / BF /BF	2.83%	÷1.000	×1.250	3.54%

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 3.80 → 4.74, 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).

2025 ALakeland Flying Tigers · 12 IPFIP 3.10 → 3.80 (+0.70)K% 18.8% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.75%	—	×0.740	13.87%
BB% (unintentional) /BF	12.50%	—	×1.180	14.75%
HR / BF /BF	0.00%	÷0.864	×1.300	0.00%

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 73).

Result: FIP 3.10 → 3.80, 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).

2024 ATampa Tarpons · 31 IPFIP 3.10 → 4.08 (+0.98)K% 24.8% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.82%	—	×0.740	18.37%
BB% (unintentional) /BF	13.48%	—	×1.180	15.90%
HR / BF /BF	0.71%	÷0.979	×1.300	0.94%

Result: FIP 3.10 → 4.08, 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 ATampa Tarpons · 26 IPFIP 5.30 → 6.36 (+1.06)K% 16.8% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.81%	—	×0.740	12.44%
BB% (unintentional) /BF	13.27%	—	×1.180	15.66%
HR / BF /BF	3.54%	÷1.086	×1.300	4.24%

Result: FIP 5.30 → 6.36, 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 · 19 IPFIP 2.58 → 3.72 (+1.15)K% 32.6% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.58%	—	×0.680	22.16%
BB% (unintentional) /BF	7.87%	—	×1.250	9.83%
HR / BF /BF	2.25%	÷1.383	×1.400	2.28%

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 2.58 → 3.72, 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 Harvey (OGILVIE)	—	—	4.79	18.0%	9.1%	3.1%	—	4.80	18.7%	9.5%	75	+0.01	—	—	—
Tyler Yates R 2004 · 4.47 FIP	26	SW	4.47	15.4%	9.6%	2.6%	.333	3.64	22.5%	13.5%	116	-0.83	3.23	248	85
Jarret Whorff R 2024 · 4.04 FIP	25	SU	4.04	18.9%	10.2%	2.3%	.271	4.52	19.6%	12.0%	123	+0.48	3.88	257	83
Jorge Reyes R 2015 · 4.58 FIP	27	SW	4.58	15.9%	8.5%	3.2%	.307	3.49	14.2%	6.2%	129	-1.09	3.39	227	83
Derek Gordon R 2016 · 4.62 FIP	25	SW	4.62	19.9%	9.3%	3.7%	.315	—	—	—	—	—	4.62	146	82
R.J. Alaniz R 2017 · 3.91 FIP	26	SU	3.91	20.7%	8.9%	2.6%	.318	3.28	23.8%	15.0%	96	-0.63	2.45	362	82
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	82
Brett McKinney R 2017 · 4.66 FIP	26	SU	4.66	18.5%	9.9%	3.4%	.287	—	—	—	—	—	3.43	183	82
Donovan Hand R 2013 · 4.72 FIP	27	SW	4.72	12.9%	7.0%	3.3%	.279	4.30	11.1%	6.8%	97	-0.42	4.30	305	81
Jose Rafael De Paula R 2017 · 4.46 FIP	26	SU	4.46	19.9%	9.8%	3.3%	.278	4.79	22.7%	10.3%	89	+0.33	2.64	315	81
Troy Neiman R 2017 · 4.03 FIP	26	SU	4.03	18.1%	8.3%	2.5%	.282	—	—	—	—	—	4.03	199	80
Cesar Gomez R 2024 · 4.50 FIP	26	SU	4.50	15.7%	9.1%	2.9%	.338	5.17	14.1%	5.8%	63	+0.67	4.11	345	80
Jonathan Hughes R 2023 · 4.31 FIP	26	SU	4.31	17.1%	9.2%	2.7%	.283	3.54	17.1%	4.9%	50	-0.77	3.44	219	80
Taylor Grover R 2017 · 4.93 FIP	26	SW	4.93	20.0%	10.9%	3.9%	.320	4.89	16.2%	8.9%	14	-0.04	3.68	239	80
Jon Leicester R 2004 · 4.69 FIP	25	SU	4.69	20.0%	8.6%	4.0%	.280	4.44	11.0%	2.0%	32	-0.25	3.76	113	80
Stephen Kohlscheen R 2015 · 3.83 FIP	26	SU	3.83	15.6%	8.1%	1.9%	.311	3.98	22.8%	15.0%	90	+0.15	2.52	167	80
Spencer Stockton R 2022 · 4.18 FIP	26	SU	4.18	20.2%	10.3%	2.7%	.276	5.45	18.9%	6.4%	63	+1.27	1.93	233	80
Daniel Corcino R 2017 · 3.93 FIP	26	SU	3.93	21.7%	11.4%	2.2%	.292	4.91	19.0%	7.9%	223	+0.98	3.84	318	80
Conor Steinbaugh R 2024 · 4.74 FIP	25	SU	4.74	16.0%	9.9%	3.2%	.281	6.29	15.0%	2.1%	44	+1.55	4.74	111	80
Josh Zeid R 2013 · 4.00 FIP	26	SU	4.00	20.3%	9.3%	2.6%	.287	4.75	16.2%	4.8%	183	+0.75	4.00	313	79
Kyle Martin R 2017 · 4.41 FIP	26	SU	4.41	18.3%	10.0%	2.9%	.304	3.22	23.0%	10.0%	51	-1.19	3.01	214	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	0.6	37	18.5%	9.2%	1.21	4.78
Sam Long ('25)	1.1	42	19.5%	9.7%	1.28	4.65
Drew VerHagen ('23)	1.4	47	19.1%	9.4%	1.37	4.98
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Randy Flores ('10)	1.2	42	17.7%	9.3%	1.04	4.61
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*