Jeffrey Springs

P Athletics

Age 34 LHP 6'3" / 218 lbs MLB

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	31	MIX3 levels	19	19	65	3.88	3.19	26.1%	5.7%	1.7	K 23.8% · BB 5.4% · FIP 3.47
2025	32	MLBOAK	32	30	171	4.11	4.56	19.4%	7.6%	1.7
2026	33	MIX2 levels	30	30	146	6.12	5.80	18.0%	8.8%	-0.7	K 17.8% · BB 9.0% · FIP 5.87
2027PROJ	34	MLBOAK	93	0	98	5.19	5.57	17.8%	8.4%	-1.1
2028PROJ	35	MLBOAK	47	0	49	5.62	5.91	16.8%	9.0%	-0.7
2029PROJ	36	MLBOAK	23	0	24	6.01	6.28	15.8%	9.6%	-0.4

Last 3 seasons WAR 2.8 · Next 3 projected WAR -2.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs27

K%20

FB Velo10

Form6.66 ERA (proj 5.19) · K 19.4% (proj 17.8%) · BB 7.8% (proj 8.4%) · last 60d · 24 IP through Oct 27

CompsChris Narveson (age 34) · Tomas Solis (age 34) · Pedro Borbón (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 117125vR 134

ERA5.19

FIP5.57

K%17.8%

BB%8.4%

K-BB%9.3%

Proj IP98

Value2027 · WAR

Runs saved vs league avg · 98 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.3

Whiff%

p3322.9%

p2017.8%

xwOBA vs

p270.339

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)
2015	22	A MLE	Hickory Crawdads	2	0	3	11	6	1	0	0%	1.7	54.5%	9.1%	45.5%	0.0%	0.00	-0.35	—
2015	22	A RAW	Hickory Crawdads	2	0	3	11	6	1	0	0%	1.7	54.5%	9.1%	45.5%	0.0%	0.00	0.40	—
2016	23	MIX MLE	2 levels	31	9	80	331	92	29	10	29%	2.6	21.0%	10.1%	10.9%	3.2%	3.73	4.37	—
2016	23	MIX RAW	2 levels	31	9	80	331	92	29	10	29%	2.6	27.8%	8.8%	19.0%	3.0%	3.73	3.51	—
2017	24	A+ MLE	Down East Wood Ducks	31	17	112	472	146	36	13	55%	3.6	23.8%	8.8%	15.0%	3.5%	3.69	4.10	—
2017	24	A+ RAW	Down East Wood Ducks	31	17	112	472	146	36	13	55%	3.6	30.9%	7.6%	23.3%	2.8%	3.69	2.97	—
2018	25	MIX MLE	3 levels	51	2	89	376	129	32	6	4%	1.7	29.9%	8.9%	21.1%	1.6%	3.86	2.58	+2.1
2018	25	MIX RAW	3 levels	51	2	89	376	129	32	6	4%	1.7	34.3%	8.5%	25.8%	1.6%	3.86	2.15	+2.6
2019	26	MIX MLE	3 levels	33	2	41	187	47	23	5	6%	1.3	20.6%	14.8%	5.8%	2.5%	5.66	4.60	-0.0
2019	26	MIX RAW	3 levels	33	2	41	187	47	23	5	6%	1.3	25.1%	12.3%	12.8%	2.7%	5.66	4.07	+0.2
2020	27	MLB MLE	Boston Red Sox	16	0	20	99	28	6	5	0%	1.3	28.3%	6.1%	22.2%	5.2%	7.08	4.32	+0.1
2020	27	MLB RAW	Boston Red Sox	16	0	20	99	28	6	5	0%	1.3	28.3%	6.1%	22.2%	5.1%	7.08	4.43	+0.0
2021	28	MLB MLE	Tampa Bay Rays	43	0	45	179	63	13	9	0%	1.0	35.2%	7.3%	27.9%	5.2%	3.43	3.89	+0.4
2021	28	MLB RAW	Tampa Bay Rays	43	0	45	179	63	13	9	0%	1.0	35.2%	7.3%	27.9%	5.0%	3.43	3.77	+0.4
2022	29	MLB MLE	Tampa Bay Rays	33	25	135	549	144	31	14	76%	4.1	26.2%	5.6%	20.6%	2.6%	2.46	3.04	+3.9
2022	29	MLB RAW	Tampa Bay Rays	33	25	135	549	144	31	14	76%	4.1	26.2%	5.6%	20.6%	2.6%	2.46	3.00	+4.0
2023	30	MLB MLE	Tampa Bay Rays	3	3	16	55	24	4	1	100%	5.3	43.6%	7.3%	36.4%	1.9%	0.56	1.36	+0.9
2023	30	MLB RAW	Tampa Bay Rays	3	3	16	55	24	4	1	100%	5.3	43.6%	7.3%	36.4%	1.8%	0.56	1.66	+0.8
2024	31	MIX MLE	3 levels	19	19	65	280	73	16	8	100%	3.4	23.8%	5.4%	18.3%	3.1%	3.88	3.47	+1.5
2024	31	MIX MLE	3 levels	19	19	65	280	73	16	8	100%	3.4	23.8%	5.4%	18.3%	3.1%	3.88	3.47	+1.5
2024	31	MIX RAW	3 levels	19	19	65	280	73	16	8	100%	3.4	26.1%	5.7%	20.4%	2.9%	3.88	3.19	+1.7
2025	32	MLB MLE	Athletics	32	30	171	713	138	54	28	94%	5.3	19.4%	7.6%	11.8%	4.0%	4.11	4.64	+1.5
2025	32	MLB MLE	Athletics	32	30	171	713	138	54	28	94%	5.3	19.4%	7.6%	11.8%	4.0%	4.11	4.64	+1.5
2025	32	MLB RAW	Athletics	32	30	171	713	138	54	28	94%	5.3	19.4%	7.6%	11.8%	3.9%	4.11	4.56	+1.7
2026	33	MIX MLE	2 levels	30	30	146	646	116	57	35	100%	4.9	17.8%	9.0%	8.7%	5.7%	6.12	5.87	-0.8
2026	33	MIX MLE	2 levels	30	30	146	646	116	57	35	100%	4.9	17.8%	9.0%	8.7%	5.7%	6.12	5.87	-0.8
2026	33	MIX RAW	2 levels	30	30	146	646	116	57	35	100%	4.9	18.0%	8.8%	9.1%	5.4%	6.12	5.80	-0.7
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			206	96	627	2663	609	212	105	47%	3.0	22.9%	8.0%	14.9%	3.9%	4.22	4.35	+1.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	OAK	93	0	98	414	73	35	19	0%	1.1	17.8%	8.4%	9.3%	4.6%	5.19	5.57	-1.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	OAK	47	0	49	207	35	19	10	0%	1.0	16.8%	9.0%	7.8%	4.9%	5.62	5.91	-0.7
2029	36	MLB MLE	OAK	22	0	24	100	16	10	5	0%	1.1	15.8%	9.6%	6.2%	5.3%	6.01	6.28	-0.4
2028	35	MLB CTX	OAK	47	0	49	207	35	19	10	0%	1.0	16.8%	9.0%	7.8%	4.9%	5.62	5.91	-0.7
2029	36	MLB CTX	OAK	23	0	24	101	16	10	5	0%	1.0	15.8%	9.6%	6.2%	5.3%	6.01	6.28	-0.4
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		275	96	700	2970	660	240	121	35%	2.5	22.2%	8.1%	14.1%	4.1%	4.38	4.48	+0.6
/ 200 IP	—	RAW		79	27	200	849	189	69	35	35%	2.5	22.2%	8.1%	14.1%	4.1%	4.38	4.48	+0.2
Career	—	MLE		324	137	923	3898	918	319	142	42%	2.8	23.5%	8.2%	15.4%	3.6%	4.08	4.14	+0.2
/ 200 IP	—	MLE		70	30	200	844	199	69	31	42%	2.8	23.5%	8.2%	15.4%	3.6%	4.08	4.14	+0.1

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.

2024 AAADurham Bulls · 30 IPFIP 2.73 → 3.03 (+0.30)K% 24.6% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.60%	—	×0.860	21.16%
BB% (unintentional) /BF	3.17%	—	×0.900	2.86%
HR / BF /BF	2.38%	÷1.061	×1.100	2.47%

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 112).

Result: FIP 2.73 → 3.03, 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 AAANashville Sounds · 7 IPFIP 1.31 → 2.00 (+0.68)K% 46.2% → 40.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	46.15%	—	×0.880	40.62%
BB% (unintentional) /BF	0.00%	—	×1.050	0.00%
HR / BF /BF	3.85%	÷0.998	×1.100	4.24%

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 100).

Result: FIP 1.31 → 2.00, 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 AAFrisco RoughRiders · 37 IPFIP 0.68 → 1.51 (+0.83)K% 43.9% → 35.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.87%	—	×0.810	35.54%
BB% (unintentional) /BF	4.52%	—	×1.100	4.97%
HR / BF /BF	1.29%	÷1.088	×1.200	1.42%

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 118).

Result: FIP 0.68 → 1.51, 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).

2018 AAARound Rock Express · 19 IPFIP 1.83 → 2.31 (+0.48)K% 37.5% → 33.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.880	33.00%
BB% (unintentional) /BF	15.00%	—	×1.050	15.75%
HR / BF /BF	0.00%	÷0.978	×1.100	0.00%

Result: FIP 1.83 → 2.31, 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).

2017 A+Down East Wood Ducks · 112 IPFIP 2.97 → 4.10 (+1.13)K% 30.9% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.93%	—	×0.770	23.82%
BB% (unintentional) /BF	7.63%	—	×1.150	8.77%
HR / BF /BF	2.75%	÷0.995	×1.250	3.46%

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 99).

Result: FIP 2.97 → 4.10, 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).

2016 A+High Desert Mavericks · 49 IPFIP 4.57 → 5.32 (+0.75)K% 23.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.85%	—	×0.770	18.37%
BB% (unintentional) /BF	9.63%	—	×1.150	11.08%
HR / BF /BF	4.13%	÷1.194	×1.250	4.32%

Result: FIP 4.57 → 5.32, 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).

2016 AHickory Crawdads · 31 IPFIP 1.49 → 2.52 (+1.03)K% 35.4% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.40%	—	×0.740	26.19%
BB% (unintentional) /BF	7.08%	—	×1.180	8.35%
HR / BF /BF	0.88%	÷1.100	×1.300	1.05%

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 120).

Result: FIP 1.49 → 2.52, 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
Jeffrey Springs (OGILVIE)	—	—	—	—	—	4.6%	—	6.03	16.5%	7.3%	73	+0.46	—	—	—
Chris Narveson L 2016 · 4.59 FIP	34	SP-	4.59	16.2%	8.5%	3.2%	.253	4.59	12.2%	1.8%	103	+0.00	4.00	625	43
Tomas Solis L 2017 · 5.48 FIP	34	SP	5.48	11.3%	7.9%	4.2%	.322	6.44	8.9%	1.4%	57	+0.96	4.20	327	33
Pedro Borbón L 2002 · 4.57 FIP	34	SU	4.57	21.6%	7.3%	4.3%	.277	—	—	—	—	—	2.26	264	33
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	31
Santiago Gutierrez L 2019 · 6.54 FIP	33	SU	6.54	17.1%	13.4%	5.8%	.293	—	—	—	—	—	3.90	341	30
Tim Byrdak L 2008 · 5.18 FIP	34	SU	5.18	19.8%	11.4%	4.2%	.229	4.30	22.4%	10.5%	138	-0.88	2.85	320	30
Tom Martin L 2004 · 4.74 FIP	34	SU	4.74	14.7%	7.8%	3.4%	.278	3.96	14.7%	7.1%	86	-0.78	3.40	303	29
Chris Michalak L 2006 · 5.71 FIP	35	SP-	5.71	6.2%	8.6%	3.7%	.273	—	—	—	—	—	4.71	186	28
James Jones L 2023 · 4.67 FIP	34	SU	4.67	13.7%	11.5%	2.3%	.246	—	—	—	—	—	3.58	127	27
Ryan Buchter L 2021 · 5.24 FIP	34	SU	5.24	22.9%	13.2%	4.4%	.267	—	—	—	—	—	2.37	296	26
Zach Neal R 2023 · 5.98 FIP	34	SW	5.98	15.6%	6.0%	6.3%	.291	—	—	—	—	—	4.24	732	25
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	25
Tim Adleman R 2022 · 5.69 FIP	34	SP-	5.69	17.5%	8.6%	5.4%	.275	—	—	—	—	—	3.63	605	22
Edwin Escobar L 2024 · 5.12 FIP	32	SU	5.12	19.6%	14.0%	3.5%	.275	—	—	—	—	—	4.28	218	22
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	22
Pete Walker R 2003 · 5.73 FIP	34	SW	5.73	12.0%	9.1%	4.5%	.267	4.70	14.0%	5.1%	114	-1.03	4.45	327	22
Jarrett Grube R 2016 · 4.74 FIP	34	SP-	4.74	18.9%	7.2%	4.2%	.280	4.41	15.8%	7.7%	134	-0.33	3.75	393	21
Ryan Feierabend L 2019 · 6.58 FIP	33	SP	6.58	15.7%	7.4%	7.0%	.284	—	—	—	—	—	4.97	174	21
Dan Runzler L 2019 · 4.84 FIP	34	SU	4.84	16.0%	13.0%	2.6%	.284	—	—	—	—	—	2.84	187	20
Doug Creek L 2003 · 5.00 FIP	34	SU	5.00	15.9%	13.0%	2.9%	.255	6.28	17.8%	10.9%	22	+1.28	4.48	277	20

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	4.0	73	21.6%	8.2%	1.60	4.48
Joe Price ('80-'90, 7 WAR*)	4.5	82	23.3%*	8.8%*	1.49*	4.15*
Daniel Norris ('23)	2.9	73	21.5%	8.9%	1.39	4.73
Drew Smyly ('24)	5.7	104	23.1%	7.7%	1.49	4.20
Matt Wisler ('22)	2.5	63	20.1%	7.6%	1.40	4.59
Chuck Cary ('85-'93, 3 WAR*)	2.1	68	24.6%*	8.7%*	1.45*	4.41*
Jerry Garvin ('77-'82, 4 WAR*)	3.0	101	19.3%*	8.4%*	1.44*	4.52*