Hayden Birdsong

P San Francisco Giants

Age 25 RHP 6'5" / 225 lbs MLB peak 0.4 · 2028 ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	21	MIX3 levels	28	25	101	3.31	2.23	34.9%	10.3%	—	K 26.7% · BB 11.9% · FIP 3.29
2024	22	MIX3 levels	29	29	129	3.76	3.89	29.3%	12.4%	2.3	K 26.7% · BB 12.6% · FIP 4.32
2025	23	MIX2 levels	31	20	105	5.33	5.18	23.3%	13.6%	0.3	K 22.0% · BB 13.0% · FIP 5.27
2026	24	No MLB games played
2027PROJ	25	MLBSF	7	7	40	4.97	5.06	24.9%	13.5%	0.2
2028PROJ95% MLB	26	MLBSF	11	11	66	5.01	5.04	25.1%	13.5%	0.3
2029PROJ95% MLB	27	MLBSF	9	9	56	5.05	5.07	25.1%	13.6%	0.2

Last 3 seasons WAR 2.6 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo64

K%53

xwOBA vs31

CompsJake Lee (age 24) · Landon Knack (age 25) · Burch Smith (age 23)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 126118vR 110

ERA4.97

FIP5.06

K%24.9%

BB%13.5%

K-BB%11.3%

Proj IP41

Value2027 · WAR

Runs saved vs league avg · 41 IP

Grades · Statcast · Contract

Scouting Grades

STUF5555

CTRL3030

CMD4545

K†6060

Statcast Percentiles

FB Velo

p6495.5

Whiff%

p7028.4%

p5322.8%

xwOBA vs

p310.334

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	20	MIX MLE	2 levels	7	0	12	48	23	3	0	0%	1.7	47.9%	6.2%	41.7%	0.0%	3.09	-0.15	—
2022	20	MIX RAW	2 levels	7	0	12	48	23	3	0	0%	1.7	47.9%	6.2%	41.7%	0.0%	3.09	-0.07	—
2023	21	MIX MLE	3 levels	28	25	101	427	149	44	6	89%	3.6	26.7%	11.9%	14.8%	1.7%	3.31	3.29	—
2023	21	MIX RAW	3 levels	28	25	101	427	149	44	6	89%	3.6	34.9%	10.3%	24.6%	1.4%	3.31	2.23	—
2024	22	MIX MLE	3 levels	29	29	129	556	163	69	17	100%	4.5	26.7%	12.6%	14.1%	3.4%	3.76	4.32	+1.6
2024	22	MIX MLE	3 levels	29	29	129	556	163	69	17	100%	4.5	26.7%	12.6%	14.1%	3.4%	3.76	4.32	+1.6
2024	22	MIX RAW	3 levels	29	29	129	556	163	69	17	100%	4.5	29.3%	12.4%	16.9%	3.1%	3.76	3.89	+2.3
2025	23	MIX MLE	2 levels	31	20	105	493	115	67	19	65%	3.4	22.0%	13.0%	9.0%	4.3%	5.33	5.27	+0.2
2025	23	MIX MLE	2 levels	31	20	105	493	115	67	19	65%	3.4	22.0%	13.0%	9.0%	4.3%	5.33	5.27	+0.2
2025	23	MIX RAW	2 levels	31	20	105	493	115	67	19	65%	3.4	23.3%	13.6%	9.7%	3.9%	5.33	5.18	+0.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			37	26	138	613	156	80	21	70%	3.7	25.4%	13.1%	12.4%	3.4%	4.77	4.56	+1.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	25	MLB	SF	7	7	40	169	42	23	6	100%	5.7	24.9%	13.5%	11.3%	3.6%	4.97	5.06	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	26	MLB MLE	SF	12	12	70	294	74	40	11	100%	5.8	25.1%	13.5%	11.6%	3.6%	5.01	5.04	+0.3
2029	27	MLB MLE	SF	10	10	59	248	62	34	9	100%	5.9	25.1%	13.6%	11.5%	3.6%	5.05	5.07	+0.2
2030	28	MLB MLE	SF	9	9	52	220	55	30	8	100%	5.8	24.9%	13.7%	11.2%	3.7%	5.12	5.16	+0.1
2031	29	MLB MLE	SF	7	7	43	182	44	25	7	100%	6.1	24.3%	13.9%	10.4%	3.9%	5.24	5.32	+0.0
2032	30	MLB MLE	SF	6	6	34	141	33	20	6	100%	5.6	23.6%	14.2%	9.4%	4.1%	5.41	5.53	-0.0
2028	26	MLB CTX	SF	11	11	66	279	70	38	10	100%	6.0	25.1%	13.5%	11.6%	3.6%	5.01	5.04	+0.3
2029	27	MLB CTX	SF	9	9	56	236	59	32	9	100%	6.2	25.1%	13.6%	11.5%	3.6%	5.05	5.07	+0.2
2030	28	MLB CTX	SF	8	8	49	207	52	28	8	100%	6.1	24.9%	13.7%	11.2%	3.7%	5.12	5.16	+0.1
2031	29	MLB CTX	SF	7	7	41	173	42	24	7	100%	5.9	24.3%	13.9%	10.4%	3.9%	5.24	5.32	+0.0
2032	30	MLB CTX	SF	5	5	32	135	32	19	6	100%	6.4	23.6%	14.2%	9.4%	4.1%	5.41	5.53	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		78	67	382	1643	411	221	60	86%	4.9	25.0%	13.5%	11.5%	3.6%	5.00	4.68	+3.2
/ 200 IP	—	RAW		41	35	200	861	215	116	31	86%	4.9	25.0%	13.5%	11.5%	3.6%	5.00	4.68	+1.7
Career	—	MLE		95	74	346	1524	394	188	48	78%	3.6	25.9%	12.3%	13.5%	3.1%	4.08	4.19	+2.0
/ 200 IP	—	MLE		55	43	200	880	228	109	28	78%	3.6	25.9%	12.3%	13.5%	3.1%	4.08	4.19	+1.0

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 AAASacramento River Cats · 39 IPFIP 5.55 → 6.07 (+0.53)K% 24.1% → 20.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.10%	—	×0.860	20.73%
BB% (unintentional) /BF	15.38%	—	×0.900	13.85%
HR / BF /BF	4.62%	÷0.938	×1.100	5.41%

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 88).

Result: FIP 5.55 → 6.07, 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 AARichmond Flying Squirrels · 48 IPFIP 3.16 → 3.96 (+0.80)K% 30.7% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.65%	—	×0.810	24.83%
BB% (unintentional) /BF	10.05%	—	×1.100	11.06%
HR / BF /BF	2.51%	÷1.062	×1.200	2.84%

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 112).

Result: FIP 3.16 → 3.96, 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 AAASacramento River Cats · 9 IPFIP 3.40 → 3.73 (+0.33)K% 33.3% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.860	28.67%
BB% (unintentional) /BF	14.29%	—	×0.900	12.86%
HR / BF /BF	2.38%	÷1.010	×1.100	2.59%

Result: FIP 3.40 → 3.73, 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).

2023 ASan Jose Giants · 42 IPFIP 1.40 → 2.51 (+1.11)K% 38.0% → 28.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.04%	—	×0.740	28.15%
BB% (unintentional) /BF	11.96%	—	×1.180	14.11%
HR / BF /BF	0.00%	÷0.890	×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 78).

Result: FIP 1.40 → 2.51, 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 A+Eugene Emeralds · 36 IPFIP 2.71 → 3.73 (+1.02)K% 33.1% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.09%	—	×0.770	25.48%
BB% (unintentional) /BF	6.47%	—	×1.150	7.45%
HR / BF /BF	2.88%	÷1.076	×1.250	3.34%

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 115).

Result: FIP 2.71 → 3.73, 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).

2023 AARichmond Flying Squirrels · 23 IPFIP 3.06 → 4.07 (+1.01)K% 31.7% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.73%	—	×0.810	25.70%
BB% (unintentional) /BF	12.50%	—	×1.100	13.75%
HR / BF /BF	1.92%	÷0.906	×1.200	2.55%

Result: FIP 3.06 → 4.07, 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 ASan Jose Giants · 6 IPFIP 1.21 → 2.28 (+1.07)K% 37.9% → 28.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.93%	—	×0.740	28.07%
BB% (unintentional) /BF	10.34%	—	×1.180	12.21%
HR / BF /BF	0.00%	÷1.063	×1.300	0.00%

Result: FIP 1.21 → 2.28, 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
Hayden Birdsong (OGILVIE)	—	—	5.06	24.9%	13.5%	3.6%	—	5.08	25.0%	11.5%	180	+0.02	—	—	—
Jake Lee R 2019 · 4.65 FIP	24	SP-	4.65	25.7%	12.4%	3.9%	.296	3.52	18.7%	10.3%	40	-1.13	2.78	181	74
Landon Knack R 2022 · 4.38 FIP	25	SP	4.38	23.0%	10.5%	3.4%	.335	4.41	21.2%	12.3%	382	+0.03	3.64	556	73
Burch Smith R 2013 · 5.18 FIP	23	SP-	5.18	27.5%	12.0%	5.3%	.326	—	—	—	—	—	3.50	418	72
Andrew Politi R 2021 · 5.21 FIP	25	SP-	5.21	21.0%	12.2%	4.3%	.320	4.04	22.9%	13.8%	138	-1.17	3.38	292	71
Sean Mooney R 2022 · 4.70 FIP	24	SP-	4.70	24.7%	13.5%	3.6%	.277	—	—	—	—	—	3.36	102	71
Luis Quiñones R 2022 · 4.77 FIP	25	SP	4.77	23.5%	17.5%	2.6%	.289	4.80	22.4%	10.8%	160	+0.03	3.69	326	70
Griffin Canning R 2021 · 5.21 FIP	25	SP	5.21	22.4%	10.1%	5.0%	.295	4.55	21.1%	13.3%	299	-0.66	3.60	809	70
Brad Peacock R 2013 · 4.92 FIP	25	SP-	4.92	21.1%	10.1%	4.2%	.267	4.33	20.6%	10.7%	280	-0.59	2.97	748	69
Michael Knorr R 2024 · 5.56 FIP	24	SP-	5.56	21.6%	12.5%	4.9%	.314	4.95	22.3%	9.7%	83	-0.61	4.30	181	68
Brett Daniels R 2021 · 4.67 FIP	25	SP-	4.67	22.3%	13.0%	3.3%	.357	4.69	18.9%	3.2%	77	+0.02	3.95	270	68
Ricky Castro R 2024 · 3.99 FIP	24	SP-	3.99	20.4%	8.6%	2.8%	.287	5.11	19.0%	10.6%	178	+1.12	3.99	241	68
Blair Henley R 2021 · 5.02 FIP	24	SP-	5.02	20.8%	12.2%	3.9%	.450	4.51	17.7%	5.4%	170	-0.51	3.97	187	68
Tanner Hall R 2024 · 4.67 FIP	22	SP-	4.67	18.8%	11.2%	3.2%	.295	5.33	10.1%	-4.6%	72	+0.66	4.67	137	67
Alfredo Figaro R 2009 · 4.98 FIP	25	SP-	4.98	19.3%	12.0%	3.6%	.370	4.42	7.2%	-1.5%	15	-0.56	3.75	143	67
Jackson Kowar R 2022 · 5.25 FIP	25	SP-	5.25	20.1%	12.0%	4.3%	.356	4.53	20.1%	7.0%	104	-0.72	3.98	489	66
Paxton Schultz R 2023 · 4.87 FIP	25	SP-	4.87	19.5%	11.9%	3.5%	.319	4.02	23.3%	14.9%	227	-0.85	3.83	543	66
Tyler Uberstine R 2022 · 4.19 FIP	23	SP-	4.19	19.5%	10.5%	2.6%	.302	4.27	22.8%	15.4%	121	+0.08	2.98	262	66
Khristian Curtis R 2024 · 5.48 FIP	22	SP	5.48	18.8%	14.4%	3.9%	.275	4.62	20.6%	8.4%	216	-0.86	4.60	291	66
Cade Smith R 2024 · 3.86 FIP	22	SP	3.86	23.2%	13.3%	1.9%	.273	5.35	18.2%	6.6%	157	+1.49	3.86	243	65
Matt Wise R 2001 · 4.98 FIP	25	SP-	4.98	23.7%	8.1%	5.2%	.271	3.50	13.5%	7.2%	53	-1.48	3.33	302	65

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	2.2	55	25.0%	13.5%	1.40	5.00
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*
Amir Garrett ('24)	1.7	55	26.7%	13.3%	1.52	4.95
Frank LaCorte ('75-'84, -4 WAR*)	2.5	61	25.0%*	12.0%*	1.43*	5.83*
Paul Spoljaric ('00)	1.4	69	22.1%	12.9%	1.33	5.52
Armando Almanza ('05)	1.1	54	24.4%	14.3%	1.43	4.82
Jeff Jones ('80-'84, -2 WAR*)	1.0	41	22.0%*	12.4%*	1.48*	4.53*