Spencer Bivens

P Omaha Storm Chasers

Age 33 RHP 6'4" / 220 lbs AAA

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	30	MIX2 levels	54	2	98	3.03	3.84	19.4%	6.1%	0.8	K 18.0% · BB 5.8% · FIP 4.07
2025	31	MLBSF	54	0	81	4.00	3.45	17.8%	7.0%	1.1
2026	32	MIX2 levels	42	7	84	5.27	4.00	22.4%	9.0%	0.5	K 18.6% · BB 7.5% · FIP 4.27
2027PROJ	33	MLBKC	61	0	64	4.33	4.57	17.1%	7.3%	-0.0
2028PROJ93% MLB	34	MLBKC	29	0	30	4.66	4.88	16.2%	7.8%	-0.1
2029PROJ88% MLB	35	MLBKC	13	0	14	4.99	5.21	15.2%	8.4%	-0.1

Last 3 seasons WAR 2.4 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

FB Velo60

xwOBA vs48

K%20

CompsMike Buddie (age 31) · Ryan Brasier (age 33) · Jean Machi (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.33

FIP4.57

K%17.1%

BB%7.3%

K-BB%9.8%

Proj IP66

Value2027 · WAR

Runs saved vs league avg · 66 IP

Grades · Statcast · Contract

Scouting Grades

STUF3535

CTRL5555

CMD4545

K†4040

Statcast Percentiles

FB Velo

p6095.2

Whiff%

p1017.0%

p2017.8%

xwOBA vs

p480.314

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	28	MIX MLE	2 levels	27	0	43	188	48	22	5	0%	1.6	19.8%	13.5%	6.3%	3.1%	3.95	4.86	—
2022	28	MIX RAW	2 levels	27	0	43	188	48	22	5	0%	1.6	25.5%	11.7%	13.8%	2.7%	3.95	3.91	—
2023	29	MIX MLE	2 levels	33	4	93	396	92	38	6	12%	2.8	18.6%	10.6%	8.0%	1.9%	3.68	3.91	—
2023	29	MIX RAW	2 levels	33	4	93	396	92	38	6	12%	2.8	23.2%	9.6%	13.6%	1.5%	3.68	3.19	—
2024	30	MIX MLE	2 levels	54	2	98	407	79	25	12	4%	1.8	18.0%	5.8%	12.2%	3.2%	3.03	4.07	+0.6
2024	30	MIX MLE	2 levels	54	2	98	407	79	25	12	4%	1.8	18.0%	5.8%	12.2%	3.2%	3.03	4.07	+0.6
2024	30	MIX RAW	2 levels	54	2	98	407	79	25	12	4%	1.8	19.4%	6.1%	13.3%	2.9%	3.03	3.84	+0.8
2025	31	MLB MLE	San Francisco Giants	54	0	81	343	61	24	6	0%	1.5	17.8%	7.0%	10.8%	1.9%	4.00	3.52	+1.0
2025	31	MLB MLE	San Francisco Giants	54	0	81	343	61	24	6	0%	1.5	17.8%	7.0%	10.8%	1.9%	4.00	3.52	+1.0
2025	31	MLB RAW	San Francisco Giants	54	0	81	343	61	24	6	0%	1.5	17.8%	7.0%	10.8%	1.7%	4.00	3.45	+1.1
2026	32	MIX MLE	2 levels	42	7	84	379	85	34	11	17%	2.0	18.6%	7.5%	11.2%	3.3%	5.27	4.27	+0.3
2026	32	MIX MLE	2 levels	42	7	84	379	85	34	11	17%	2.0	18.6%	7.5%	11.2%	3.3%	5.27	4.27	+0.3
2026	32	MIX RAW	2 levels	42	7	84	379	85	34	11	17%	2.0	22.4%	9.0%	13.5%	2.9%	5.27	4.00	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			87	2	137	587	110	40	16	2%	1.6	18.7%	6.8%	11.9%	2.7%	4.00	3.89	+1.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	KC	61	0	64	270	46	20	8	0%	1.0	17.1%	7.3%	9.8%	2.9%	4.33	4.57	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	KC	31	0	32	137	22	11	4	0%	1.0	16.2%	7.8%	8.4%	3.2%	4.66	4.88	-0.1
2029	35	MLB MLE	KC	15	0	16	67	10	6	2	0%	1.1	15.2%	8.4%	6.9%	3.6%	4.99	5.21	-0.1
2028	34	MLB CTX	KC	29	0	30	127	21	10	4	0%	1.0	16.2%	7.8%	8.4%	3.2%	4.66	4.88	-0.1
2029	35	MLB CTX	KC	13	0	14	59	9	5	2	0%	1.1	15.2%	8.4%	6.9%	3.6%	4.99	5.21	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		129	2	181	773	140	55	22	2%	1.4	18.1%	7.1%	11.0%	2.9%	4.18	4.05	+1.1
/ 200 IP	—	RAW		142	2	200	852	154	61	24	2%	1.4	18.1%	7.1%	11.0%	2.9%	4.18	4.05	+1.2
Career	—	MLE		210	13	399	1713	316	143	45	6%	1.9	18.4%	8.4%	10.1%	2.6%	3.95	4.05	+0.8
/ 200 IP	—	MLE		105	7	200	859	158	72	23	6%	1.9	18.4%	8.4%	10.1%	2.6%	3.95	4.05	+0.9

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 AAAOmaha Storm Chasers · 76 IPFIP 3.95 → 4.27 (+0.31)K% 21.7% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.66%	—	×0.860	18.63%
BB% (unintentional) /BF	8.31%	—	×0.900	7.48%
HR / BF /BF	2.97%	÷1.000	×1.100	3.26%

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 3.95 → 4.27, 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 · 49 IPFIP 3.10 → 3.32 (+0.22)K% 20.5% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.49%	—	×0.860	17.62%
BB% (unintentional) /BF	7.32%	—	×0.900	6.59%
HR / BF /BF	1.46%	÷1.010	×1.100	1.59%

Result: FIP 3.10 → 3.32, 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 · 78 IPFIP 3.06 → 3.70 (+0.64)K% 21.8% → 17.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.82%	—	×0.810	17.67%
BB% (unintentional) /BF	10.30%	—	×1.100	11.33%
HR / BF /BF	0.91%	÷0.906	×1.200	1.20%

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 81).

Result: FIP 3.06 → 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).

2023 A+Eugene Emeralds · 15 IPFIP 3.80 → 4.91 (+1.11)K% 30.3% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.30%	—	×0.770	23.33%
BB% (unintentional) /BF	6.06%	—	×1.150	6.97%
HR / BF /BF	4.55%	÷1.076	×1.250	5.28%

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 3.80 → 4.91, 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 · 30 IPFIP 3.78 → 4.97 (+1.20)K% 27.5% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.48%	—	×0.740	20.34%
BB% (unintentional) /BF	13.74%	—	×1.180	16.21%
HR / BF /BF	2.29%	÷1.063	×1.300	2.80%

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 113).

Result: FIP 3.78 → 4.97, 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 · 13 IPFIP 4.14 → 4.61 (+0.47)K% 21.1% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.05%	—	×0.880	18.53%
BB% (unintentional) /BF	7.02%	—	×1.050	7.37%
HR / BF /BF	3.51%	÷0.989	×1.100	3.90%

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 4.14 → 4.61, 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
Spencer Bivens (OGILVIE)	—	—	4.57	17.1%	7.3%	2.9%	—	4.99	15.9%	7.9%	48	+0.42	—	—	—
Mike Buddie R 2002 · 4.26 FIP	31	SU	4.26	15.1%	7.6%	2.7%	.297	—	—	—	—	—	3.76	123	78
Ryan Brasier R 2021 · 4.85 FIP	33	SU	4.85	18.0%	8.0%	4.1%	.286	3.16	23.7%	17.9%	150	-1.69	2.31	426	78
Jean Machi R 2015 · 4.56 FIP	33	SU	4.56	16.3%	8.6%	3.2%	.276	4.24	18.5%	11.9%	128	-0.32	2.16	306	75
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	75
Arcenio Leon R 2019 · 3.61 FIP	32	SU	3.61	21.4%	8.1%	2.4%	.314	—	—	—	—	—	3.00	115	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
Tyler Walker R 2009 · 3.72 FIP	33	SU	3.72	18.0%	5.3%	2.7%	.243	3.77	20.7%	16.6%	35	+0.05	2.38	289	73
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	73
Mike James R 2001 · 4.52 FIP	33	SU	4.52	15.0%	8.7%	2.9%	.299	4.84	19.6%	9.8%	11	+0.32	2.87	314	73
Rudy Gonzalez R 2015 · 4.52 FIP	34	SW	4.52	13.5%	9.6%	2.4%	.347	3.84	14.0%	6.5%	79	-0.68	3.31	119	73
Willie Eyre R 2011 · 4.18 FIP	33	SU	4.18	13.9%	6.9%	2.5%	.182	—	—	—	—	—	2.87	164	72
Felipe Arredondo R 2019 · 4.65 FIP	32	SU	4.65	16.2%	7.1%	3.7%	.272	—	—	—	—	—	3.92	337	72
Tyler Sturdevant R 2017 · 4.48 FIP	31	SU	4.48	13.5%	6.7%	3.0%	.300	—	—	—	—	—	3.44	149	71
Miguel Mejia R 2019 · 4.41 FIP	31	SU	4.41	15.7%	10.7%	2.3%	.341	—	—	—	—	—	3.37	108	71
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	71
Jumbo Diaz R 2017 · 4.17 FIP	33	SU	4.17	20.0%	9.7%	2.8%	.302	2.90	24.2%	15.4%	98	-1.27	2.80	319	71
Tony Barnette R 2017 · 3.56 FIP	33	SU	3.56	22.6%	7.1%	2.7%	.335	2.61	25.0%	20.2%	26	-0.95	2.61	144	71
Jose Manuel Lopez R 2017 · 3.61 FIP	32	SU	3.61	20.4%	10.0%	1.8%	.331	6.14	17.9%	3.7%	41	+2.53	3.50	170	70
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	70
Brian Schlitter R 2019 · 4.40 FIP	33	SU	4.40	14.8%	6.3%	3.2%	.331	4.70	14.9%	5.8%	48	+0.30	3.27	300	70

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	1.3	50	17.8%	7.4%	1.12	4.23
Matt Wise ('08)	1.6	53	18.1%	7.9%	1.14	4.23
Tyler Walker ('10)	1.5	50	18.9%	8.5%	1.11	4.23
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
Cris Carpenter ('88-'96, 2 WAR*)	2.1	69	18.3%*	7.4%*	1.15*	4.29*
Larry Casian ('90-'98, 0 WAR*)	1.2	40	14.7%*	6.8%*	1.25*	4.37*
Jay Ritchie ('64-'68, 2 WAR*)	1.5	58	21.1%*	8.0%*	1.01*	4.21*