Mitch Spence

P Omaha Storm Chasers

Age 29 RHP 6'1" / 185 lbs AAA

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MLBOakland Athle…	35	24	151	4.58	4.03	19.4%	6.8%	2.5
2025	27	MIX2 levels	40	15	114	5.38	4.52	18.8%	7.0%	0.0	K 18.0% · BB 6.7% · FIP 4.48
2026	28	MIX2 levels	19	17	83	7.13	4.88	18.4%	8.1%	0.5	K 16.0% · BB 7.6% · FIP 5.07
2027PROJ	29	MLBKC	15	15	89	5.05	5.07	17.0%	7.5%	0.3
2028PROJ95% MLB	30	MLBKC	8	8	45	5.19	5.28	16.3%	7.8%	0.1
2029PROJ95% MLB	31	MLBKC	6	6	34	5.22	5.24	17.5%	7.4%	0.1

Last 3 seasons WAR 3.0 · Next 3 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

CompsRoss Ohlendorf (age 29) · Zack Segovia (age 32) · Chris Heston (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA5.05

FIP5.07

K%17.0%

BB%7.5%

K-BB%9.4%

Proj IP89

Value2027 · WAR

Runs saved vs league avg · 89 IP

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)
2021	23	A+ MLE	Hudson Valley Renegades	23	20	105	448	118	37	10	87%	4.6	20.3%	9.5%	10.8%	2.8%	3.94	4.12	—
2021	23	A+ RAW	Hudson Valley Renegades	23	20	105	448	118	37	10	87%	4.6	26.3%	8.3%	18.1%	2.2%	3.94	3.15	—
2022	24	MIX MLE	2 levels	27	25	130	564	127	42	17	93%	4.8	18.8%	8.0%	10.8%	3.4%	4.70	4.42	—
2022	24	MIX RAW	2 levels	27	25	130	564	127	42	17	93%	4.8	22.5%	7.4%	15.1%	3.0%	4.70	3.81	—
2023	25	AAA MLE	Scranton/Wilkes-Barre RailRiders	29	29	163	703	153	53	30	100%	5.6	18.7%	6.8%	11.9%	4.6%	4.47	4.91	—
2023	25	AAA RAW	Scranton/Wilkes-Barre RailRiders	29	29	163	703	153	53	30	100%	5.6	21.8%	7.5%	14.2%	4.3%	4.47	4.59	—
2024	26	MLB MLE	Oakland Athletics	35	24	151	651	126	44	20	69%	4.3	19.4%	6.8%	12.6%	3.4%	4.58	4.17	+2.2
2024	26	MLB MLE	Oakland Athletics	35	24	151	651	126	44	20	69%	4.3	19.4%	6.8%	12.6%	3.4%	4.58	4.17	+2.2
2024	26	MLB RAW	Oakland Athletics	35	24	151	651	126	44	20	69%	4.3	19.4%	6.8%	12.6%	3.1%	4.58	4.03	+2.5
2025	27	MIX MLE	2 levels	40	15	114	516	97	36	19	38%	2.8	18.0%	6.7%	11.2%	3.7%	5.38	4.48	+0.1
2025	27	MIX MLE	2 levels	40	15	114	516	97	36	19	38%	2.8	18.0%	6.7%	11.2%	3.7%	5.38	4.48	+0.1
2025	27	MIX RAW	2 levels	40	15	114	516	97	36	19	38%	2.8	18.8%	7.0%	11.8%	3.7%	5.38	4.52	+0.0
2026	28	MIX MLE	2 levels	19	17	83	381	70	31	15	89%	4.4	16.0%	7.6%	8.5%	4.3%	7.13	5.07	+0.3
2026	28	MIX MLE	2 levels	19	17	83	381	70	31	15	89%	4.4	16.0%	7.6%	8.5%	4.3%	7.13	5.07	+0.3
2026	28	MIX RAW	2 levels	19	17	83	381	70	31	15	89%	4.4	18.4%	8.1%	10.2%	3.9%	7.13	4.88	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			70	33	245	1082	198	77	39	47%	3.5	18.3%	7.1%	11.2%	3.6%	5.39	4.49	+0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	KC	15	15	89	376	64	28	14	100%	5.9	17.0%	7.5%	9.4%	3.8%	5.05	5.07	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	KC	8	8	47	199	32	16	8	100%	5.9	16.3%	7.8%	8.4%	4.0%	5.19	5.28	+0.1
2029	31	MLB MLE	KC	6	6	35	149	26	11	6	100%	5.9	17.5%	7.4%	10.1%	4.2%	5.22	5.24	+0.1
2028	30	MLB CTX	KC	8	8	45	190	31	15	8	100%	5.6	16.3%	7.8%	8.4%	4.0%	5.19	5.28	+0.1
2029	31	MLB CTX	KC	6	6	34	144	25	11	6	100%	5.7	17.5%	7.4%	10.1%	4.2%	5.22	5.24	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		83	46	324	1413	254	102	52	55%	3.9	17.9%	7.2%	10.7%	3.7%	5.35	4.54	+3.3
/ 200 IP	—	RAW		51	28	200	873	157	63	32	55%	3.9	17.9%	7.2%	10.7%	3.7%	5.35	4.54	+2.0
Career	—	MLE		173	130	747	3263	608	243	122	75%	4.3	18.6%	7.5%	11.2%	3.7%	4.89	4.52	+2.7
/ 200 IP	—	MLE		46	35	200	874	163	65	33	75%	4.3	18.6%	7.5%	11.2%	3.7%	4.89	4.52	+1.7

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 · 74 IPFIP 4.32 → 4.67 (+0.35)K% 19.7% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.69%	—	×0.860	16.94%
BB% (unintentional) /BF	6.77%	—	×0.900	6.09%
HR / BF /BF	3.69%	÷1.000	×1.100	4.06%

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 4.32 → 4.67, 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).

2025 AAALas Vegas Aviators · 29 IPFIP 3.49 → 3.56 (+0.07)K% 22.0% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.99%	—	×0.860	18.91%
BB% (unintentional) /BF	8.51%	—	×0.900	7.66%
HR / BF /BF	2.13%	÷1.183	×1.100	1.98%

Result: FIP 3.49 → 3.56, 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 AAAScranton/Wilkes-Barre RailRiders · 163 IPFIP 4.56 → 4.91 (+0.35)K% 21.8% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.76%	—	×0.860	18.72%
BB% (unintentional) /BF	7.54%	—	×0.900	6.79%
HR / BF /BF	4.27%	÷1.017	×1.100	4.62%

Result: FIP 4.56 → 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 AASomerset Patriots · 79 IPFIP 4.03 → 4.80 (+0.77)K% 22.9% → 18.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.90%	—	×0.810	18.55%
BB% (unintentional) /BF	7.54%	—	×1.100	8.29%
HR / BF /BF	3.48%	÷1.032	×1.200	4.05%

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 106).

Result: FIP 4.03 → 4.80, 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).

2022 AAAScranton/Wilkes-Barre RailRiders · 51 IPFIP 3.43 → 3.81 (+0.39)K% 21.9% → 19.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.92%	—	×0.880	19.29%
BB% (unintentional) /BF	7.31%	—	×1.050	7.67%
HR / BF /BF	2.28%	÷1.006	×1.100	2.50%

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 101).

Result: FIP 3.43 → 3.81, 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+Hudson Valley Renegades · 105 IPFIP 3.15 → 4.12 (+0.97)K% 26.3% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.34%	—	×0.770	20.28%
BB% (unintentional) /BF	8.26%	—	×1.150	9.50%
HR / BF /BF	2.23%	÷1.000	×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 100).

Result: FIP 3.15 → 4.12, 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
Mitch Spence (OGILVIE)	—	—	—	—	—	3.8%	—	5.26	16.8%	9.2%	82	+0.19	—	—	—
Ross Ohlendorf R 2012 · 4.60 FIP	29	SP-	4.60	16.7%	10.3%	2.9%	.337	3.67	20.8%	14.6%	116	-0.93	3.30	617	70
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	67
Chris Heston R 2017 · 5.88 FIP	29	SP-	5.88	13.6%	10.0%	4.9%	.368	—	—	—	—	—	3.81	321	67
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	66
Jason Berken R 2012 · 6.06 FIP	28	SP-	6.06	11.6%	7.4%	5.5%	.333	4.34	13.5%	6.9%	113	-1.72	3.37	468	65
Ariel Prieto R 2000 · 4.24 FIP	30	SP-	4.24	12.8%	8.8%	2.0%	.345	—	—	—	—	—	4.05	340	61
Brian Tollberg R 2002 · 4.98 FIP	29	SP	4.98	11.5%	5.9%	3.8%	.339	—	—	—	—	—	4.02	297	61
Erik Hiljus R 2002 · 6.07 FIP	29	SP	6.07	14.1%	9.7%	5.3%	.281	—	—	—	—	—	3.35	112	61
Andrew Triggs R 2018 · 4.68 FIP	29	SP	4.68	23.6%	9.9%	4.2%	.263	—	—	—	—	—	1.66	242	61
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	61
Reinier Roibal R 2019 · 4.91 FIP	30	SP	4.91	17.5%	11.8%	3.3%	.426	—	—	—	—	—	3.11	133	60
Seth Greisinger R 2004 · 5.38 FIP	29	SP-	5.38	15.5%	6.0%	5.1%	.327	—	—	—	—	—	4.53	219	60
Rolando Valdez R 2015 · 4.07 FIP	29	SP	4.07	13.3%	5.9%	2.4%	.301	3.78	13.2%	7.9%	176	-0.29	3.06	258	60
Juan Omar Espinoza R 2015 · 4.81 FIP	31	SP-	4.81	8.9%	6.6%	3.0%	.346	4.84	8.4%	-0.8%	52	+0.03	4.81	104	59
J.P. France R 2024 · 5.15 FIP	29	SP	5.15	18.2%	9.9%	4.2%	.317	4.82	18.0%	3.9%	71	-0.33	4.04	577	59
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	59
Cody Anderson R 2019 · 4.33 FIP	28	SP	4.33	18.9%	7.5%	3.4%	.328	—	—	—	—	—	3.69	279	59
Ariel Peña R 2017 · 3.99 FIP	28	SP	3.99	22.5%	12.0%	2.3%	.304	6.07	19.9%	-5.7%	21	+2.08	3.74	223	59
Stan Spencer R 2000 · 4.42 FIP	30	SP	4.42	19.2%	8.7%	3.4%	.259	—	—	—	—	—	3.61	119	58
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	58

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	2.1	83	17.7%	7.4%	1.44	5.28
Jason Berken ('12)	1.2	83	14.3%	8.0%	1.41	5.36
Andrew Suárez ('23)	1.2	77	18.0%	8.1%	1.48	4.96
Sal Romano ('21)	1.4	92	17.2%	8.9%	1.34	5.23
Paul Reuschel ('75-'79, 1 WAR*)	2.0	79	16.8%*	7.6%*	1.29*	4.76*
John Strohmayer ('70-'74, -1 WAR*)	1.6	78	19.6%*	9.2%*	1.42*	5.14*
Mike Gardiner ('90-'95, -1 WAR*)	2.0	98	18.3%*	8.8%*	1.37*	5.10*