Ryan Walker

P San Francisco Giants

Age 31 RHP 6'2" / 215 lbs MLB peak 0.2 · 2027

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MLBSF	76	1	80	1.91	2.08	32.1%	5.5%	2.4
2025	29	MLBSF	68	0	61	4.11	2.77	22.6%	6.0%	1.3
2026	30	MIX2 levels	57	0	68	4.74	4.20	18.5%	9.1%	0.3	K 17.0% · BB 8.7% · FIP 4.37
2027PROJ	31	MLBSF	40	0	42	3.92	4.08	20.6%	7.0%	0.2
2028PROJ95% MLB	32	MLBSF	26	0	27	4.17	4.34	19.9%	7.4%	0.1

Last 3 seasons WAR 4.0 · Next 2 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo47

xwOBA vs40

K%10

CompsJeff Fulchino (age 31) · Chris Hatcher (age 31) · Tony Barnette (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 111103vR 95

ERA3.92

FIP4.08

K%20.6%

BB%7.0%

K-BB%13.6%

Proj IP42

Value2027 · WAR

Runs saved vs league avg · 42 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL6060

CMD6565

K†5050

Statcast Percentiles

FB Velo

p4794.3

Whiff%

p1014.9%

p1014.8%

xwOBA vs

p400.323

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)
2018	22	MIX MLE	2 levels	8	0	12	50	12	4	0	0%	1.5	24.0%	8.0%	16.0%	0.0%	1.46	2.09	—
2018	22	MIX RAW	2 levels	8	0	12	50	12	4	0	0%	1.5	24.0%	8.0%	16.0%	0.0%	1.46	2.13	—
2019	23	A MLE	Augusta GreenJackets	37	0	59	247	61	14	1	0%	1.6	18.3%	6.7%	11.6%	0.5%	3.36	2.67	—
2019	23	A RAW	Augusta GreenJackets	37	0	59	247	61	14	1	0%	1.6	24.7%	5.7%	19.0%	0.4%	3.36	1.96	—
2021	25	MIX MLE	2 levels	39	0	49	205	66	10	4	0%	1.3	25.2%	6.7%	18.5%	2.8%	3.65	3.35	—
2021	25	MIX RAW	2 levels	39	0	49	205	66	10	4	0%	1.3	32.2%	4.9%	27.3%	2.0%	3.65	2.09	—
2022	26	MIX MLE	2 levels	50	0	53	242	65	27	1	0%	1.1	22.2%	12.9%	9.3%	0.6%	3.74	3.21	—
2022	26	MIX RAW	2 levels	50	0	53	242	65	27	1	0%	1.1	26.9%	11.2%	15.7%	0.4%	3.74	2.42	—
2023	27	MIX MLE	2 levels	64	16	82	337	101	32	8	25%	1.3	29.0%	9.3%	19.8%	2.6%	2.64	3.23	+1.3
2023	27	MIX RAW	2 levels	64	16	82	337	101	32	8	25%	1.3	30.0%	9.5%	20.5%	2.4%	2.64	3.08	+1.4
2024	28	MLB MLE	San Francisco Giants	76	1	80	308	99	17	5	1%	1.1	32.1%	5.5%	26.6%	1.8%	1.91	2.05	+2.4
2024	28	MLB MLE	San Francisco Giants	76	1	80	308	99	17	5	1%	1.1	32.1%	5.5%	26.6%	1.8%	1.91	2.05	+2.4
2024	28	MLB RAW	San Francisco Giants	76	1	80	308	99	17	5	1%	1.1	32.1%	5.5%	26.6%	1.6%	1.91	2.08	+2.4
2025	29	MLB MLE	San Francisco Giants	68	0	61	266	60	16	4	0%	0.9	22.6%	6.0%	16.5%	1.6%	4.11	2.85	+1.2
2025	29	MLB MLE	San Francisco Giants	68	0	61	266	60	16	4	0%	0.9	22.6%	6.0%	16.5%	1.6%	4.11	2.85	+1.2
2025	29	MLB RAW	San Francisco Giants	68	0	61	266	60	16	4	0%	0.9	22.6%	6.0%	16.5%	1.5%	4.11	2.77	+1.3
2026	30	MIX MLE	2 levels	57	0	68	298	55	27	8	0%	1.2	17.0%	8.7%	8.3%	2.9%	4.74	4.37	+0.1
2026	30	MIX MLE	2 levels	57	0	68	298	55	27	8	0%	1.2	17.0%	8.7%	8.3%	2.9%	4.74	4.37	+0.1
2026	30	MIX RAW	2 levels	57	0	68	298	55	27	8	0%	1.2	18.5%	9.1%	9.4%	2.7%	4.74	4.20	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			226	14	235	992	260	73	22	6%	1.0	26.2%	7.4%	18.9%	2.2%	3.56	3.04	+4.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	SF	40	0	42	177	37	12	5	0%	1.1	20.6%	7.0%	13.6%	2.7%	3.92	4.08	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	SF	27	0	29	121	24	9	4	0%	1.1	19.9%	7.4%	12.5%	2.9%	4.17	4.34	+0.1
2028	32	MLB CTX	SF	26	0	27	114	23	8	3	0%	1.0	19.9%	7.4%	12.5%	2.9%	4.17	4.34	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		252	14	263	1107	283	81	25	6%	1.0	25.6%	7.4%	18.2%	2.3%	3.62	3.13	+4.4
/ 200 IP	—	RAW		192	11	200	843	216	62	19	6%	1.0	25.6%	7.4%	18.2%	2.3%	3.62	3.13	+3.4
Career	—	MLE		399	17	465	1953	470	156	36	4%	1.2	24.1%	8.0%	16.1%	1.8%	3.31	3.08	+4.3
/ 200 IP	—	MLE		172	7	200	840	202	67	15	4%	1.2	24.1%	8.0%	16.1%	1.8%	3.31	3.08	+3.3

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 AAASacramento River Cats · 36 IPFIP 3.34 → 3.62 (+0.28)K% 22.4% → 19.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.38%	—	×0.860	19.24%
BB% (unintentional) /BF	7.69%	—	×0.900	6.92%
HR / BF /BF	2.10%	÷1.000	×1.100	2.31%

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 3.34 → 3.62, 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).

2023 AAASacramento River Cats · 20 IPFIP 1.84 → 2.08 (+0.23)K% 31.1% → 26.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.08%	—	×0.860	26.73%
BB% (unintentional) /BF	10.81%	—	×0.900	9.73%
HR / BF /BF	0.00%	÷1.057	×1.100	0.00%

Result: FIP 1.84 → 2.08, 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).

2022 AARichmond Flying Squirrels · 46 IPFIP 2.54 → 3.21 (+0.67)K% 27.5% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.45%	—	×0.810	22.24%
BB% (unintentional) /BF	11.76%	—	×1.100	12.94%
HR / BF /BF	0.49%	÷0.929	×1.200	0.63%

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 86).

Result: FIP 2.54 → 3.21, 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 AAASacramento River Cats · 7 IPFIP 2.10 → 2.39 (+0.29)K% 23.7% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.68%	—	×0.880	20.84%
BB% (unintentional) /BF	7.89%	—	×1.050	8.29%
HR / BF /BF	0.00%	÷0.989	×1.100	0.00%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 98).

Result: FIP 2.10 → 2.39, 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).

2021 A+Eugene Emeralds · 40 IPFIP 2.36 → 3.35 (+0.99)K% 32.7% → 25.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.75%	—	×0.770	25.22%
BB% (unintentional) /BF	5.85%	—	×1.150	6.73%
HR / BF /BF	2.34%	÷1.049	×1.250	2.79%

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 110).

Result: FIP 2.36 → 3.35, 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 AARichmond Flying Squirrels · 9 IPFIP 0.62 → 1.09 (+0.47)K% 29.4% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.41%	—	×0.810	23.82%
BB% (unintentional) /BF	0.00%	—	×1.100	0.00%
HR / BF /BF	0.00%	÷0.923	×1.200	0.00%

Result: FIP 0.62 → 1.09, 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).

2019 AAugusta GreenJackets · 59 IPFIP 1.95 → 2.67 (+0.72)K% 24.7% → 18.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.70%	—	×0.740	18.28%
BB% (unintentional) /BF	5.67%	—	×1.180	6.69%
HR / BF /BF	0.40%	÷1.082	×1.300	0.49%

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 116).

Result: FIP 1.95 → 2.67, 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).

2018 ROKAZL Giants Orange · 7 IPFIP 1.29 → 2.39 (+1.09)K% 32.1% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.14%	—	×0.680	21.86%
BB% (unintentional) /BF	7.14%	—	×1.250	8.93%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 100).

Result: FIP 1.29 → 2.39, 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).

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 Walker (OGILVIE)	—	—	4.08	20.6%	7.0%	2.7%	—	4.34	19.9%	12.5%	29	+0.26	—	—	—
Jeff Fulchino R 2011 · 4.44 FIP	31	SU	4.44	20.4%	11.1%	3.0%	.302	—	—	—	—	—	3.36	178	78
Chris Hatcher R 2016 · 4.61 FIP	31	SU	4.61	23.8%	9.4%	4.2%	.283	4.69	22.0%	13.8%	96	+0.08	2.51	246	77
Tony Barnette R 2016 · 3.05 FIP	32	SU	3.05	19.9%	6.1%	1.6%	.281	3.26	23.4%	17.0%	84	+0.21	2.61	144	77
Cristhian Martinez R 2012 · 3.09 FIP	30	SU	3.09	20.8%	4.8%	2.1%	.326	—	—	—	—	—	3.09	204	76
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	76
Mark Serrano R 2017 · 3.56 FIP	31	SU	3.56	21.9%	6.4%	2.7%	.240	5.25	20.2%	12.3%	42	+1.69	3.16	120	76
Matt Lindstrom R 2011 · 2.96 FIP	31	SU	2.96	15.9%	4.4%	1.2%	.277	3.21	17.0%	9.5%	142	+0.25	2.40	443	76
Manny Acosta R 2012 · 4.49 FIP	31	SU	4.49	21.3%	11.1%	3.2%	.295	—	—	—	—	—	3.08	350	75
Alex Wilson R 2018 · 4.16 FIP	31	SU	4.16	17.6%	5.3%	3.4%	.232	5.06	19.4%	13.4%	62	+0.90	2.93	382	74
Juan Sandoval R 2015 · 3.82 FIP	34	SU	3.82	15.4%	6.0%	2.3%	.294	3.33	17.4%	8.8%	116	-0.49	3.24	225	74
Tom Wilhelmsen R 2015 · 3.07 FIP	31	SU	3.07	22.5%	9.7%	1.1%	.298	5.78	13.8%	4.1%	86	+2.71	2.72	398	74
Mike DeJean R 2002 · 3.80 FIP	31	SU	3.80	19.9%	9.5%	2.1%	.265	3.66	19.6%	10.5%	206	-0.14	2.82	622	74
Mike Broadway R 2018 · 4.65 FIP	31	SU	4.65	23.0%	10.6%	3.9%	.282	—	—	—	—	—	1.74	195	74
Brian Schlitter R 2016 · 3.28 FIP	30	SU	3.28	20.6%	10.8%	1.0%	.333	3.81	14.4%	6.6%	110	+0.53	3.27	300	74
Al Reyes R 2001 · 4.12 FIP	31	SU	4.12	19.2%	10.0%	2.5%	.305	3.40	21.8%	11.1%	34	-0.72	2.60	411	74
Scott Atchison R 2007 · 4.55 FIP	31	SU	4.55	19.1%	7.6%	3.8%	.297	4.59	16.2%	9.5%	60	+0.04	2.52	340	73
Brian Sanches R 2010 · 4.24 FIP	31	SU	4.24	21.3%	10.6%	2.9%	.217	4.35	19.6%	8.5%	62	+0.11	3.39	229	73
Geoff Geary R 2008 · 3.39 FIP	31	SU	3.39	17.2%	8.8%	1.1%	.220	5.49	12.4%	3.1%	20	+2.10	3.16	345	73
Bo Schultz R 2016 · 3.90 FIP	30	SU	3.90	14.4%	5.2%	2.5%	.276	2.73	16.4%	8.4%	27	-1.17	2.73	141	73
Jared Burton R 2012 · 3.09 FIP	31	SU	3.09	22.4%	6.1%	2.0%	.212	3.59	19.9%	12.6%	144	+0.50	3.09	367	73

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	1.5	51	24.8%	7.8%	0.91	3.66
Mike Schooler ('88-'93, 5 WAR*)	1.5	49	26.9%*	8.0%*	0.96*	3.68*
Todd Worrell ('97)	1.7	55	23.4%	7.5%	0.95	3.58
Héctor Rondón ('20)	2.2	54	24.2%	7.4%	1.03	3.49
David Carpenter ('19)	1.1	43	23.5%	8.4%	0.92	3.69
Carlos Diaz ('82-'86, 2 WAR*)	1.3	52	25.1%*	8.7%*	0.91*	3.84*
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*