JP Sears

P El Paso Chihuahuas

Age 31 LHP 5'11" / 180 lbs AAA peak 0.2 · 2027

Overview

AAASP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	28	MLBOakland Athle…	32	32	181	4.38	4.41	18.1%	6.5%	2.1
2025	29	MIX2 levels	31	31	149	4.88	5.04	20.7%	6.5%	0.6	K 20.4% · BB 6.4% · FIP 4.99
2026	30	MIX2 levels	31	26	118	6.71	4.32	20.7%	9.1%	1.5	K 18.5% · BB 8.4% · FIP 4.42
2027PROJ	31	MLBSD	8	8	48	4.80	4.98	18.4%	7.4%	0.2
2028PROJ	32	MLBSD	8	8	51	5.06	5.24	17.6%	7.8%	0.1
2029PROJ	33	MLBSD	9	9	53	5.17	5.25	18.8%	7.4%	0.1

Last 3 seasons WAR 4.2 · Next 3 projected WAR 0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo29

xwOBA vs22

K%18

CompsJohn Bale (age 29) · Kaz Ishii (age 31) · Brandon Mann (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 112120vR 128

ERA4.80

FIP4.98

K%18.4%

BB%7.4%

K-BB%11.0%

Proj IP48

Value2027 · WAR

Runs saved vs league avg · 48 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2993.0

Whiff%

p1720.7%

p1817.5%

xwOBA vs

p220.345

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)
2017	21	A MLE	Clinton LumberKings	10	0	17	67	29	8	0	0%	1.7	32.0%	14.1%	17.9%	0.0%	0.00	2.18	—
2017	21	A RAW	Clinton LumberKings	10	0	17	67	29	8	0	0%	1.7	43.3%	11.9%	31.3%	0.0%	0.00	1.10	—
2018	22	A MLE	Charleston RiverDogs	11	10	54	215	54	11	7	91%	4.9	18.6%	6.0%	12.5%	5.2%	2.67	5.16	—
2018	22	A RAW	Charleston RiverDogs	11	10	54	215	54	11	7	91%	4.9	25.1%	5.1%	20.0%	3.3%	2.67	3.40	—
2019	23	A+ MLE	Tampa Tarpons	13	6	49	206	45	16	3	46%	3.7	16.8%	8.9%	7.9%	1.9%	4.07	3.85	—
2019	23	A+ RAW	Tampa Tarpons	13	6	49	206	45	16	3	46%	3.7	21.8%	7.8%	14.1%	1.5%	4.07	3.04	—
2021	25	MIX MLE	2 levels	25	18	104	415	136	29	11	72%	4.2	27.6%	7.6%	20.1%	2.8%	3.46	3.26	—
2021	25	MIX RAW	2 levels	25	18	104	415	136	29	11	72%	4.2	32.8%	7.0%	25.8%	2.7%	3.46	2.70	—
2022	26	MIX MLE	2 levels	29	21	118	468	111	29	11	72%	4.1	22.2%	6.3%	15.9%	2.5%	2.98	3.41	+2.8
2022	26	MIX RAW	2 levels	29	21	118	468	111	29	11	72%	4.1	23.7%	6.2%	17.5%	2.4%	2.98	3.17	+3.2
2023	27	MLB MLE	Oakland Athletics	32	32	172	735	161	51	34	100%	5.4	21.9%	6.9%	15.0%	5.1%	4.54	4.92	+0.9
2023	27	MLB RAW	Oakland Athletics	32	32	172	735	161	51	34	100%	5.4	21.9%	6.9%	15.0%	4.6%	4.54	4.68	+1.4
2024	28	MLB MLE	Oakland Athletics	32	32	181	758	137	49	28	100%	5.6	18.1%	6.5%	11.6%	4.1%	4.38	4.62	+1.6
2024	28	MLB MLE	Oakland Athletics	32	32	181	758	137	49	28	100%	5.6	18.1%	6.5%	11.6%	4.1%	4.38	4.62	+1.6
2024	28	MLB RAW	Oakland Athletics	32	32	181	758	137	49	28	100%	5.6	18.1%	6.5%	11.6%	3.7%	4.38	4.41	+2.1
2025	29	MIX MLE	2 levels	31	31	149	642	133	42	33	100%	4.8	20.4%	6.4%	13.9%	5.1%	4.88	4.99	+0.7
2025	29	MIX MLE	2 levels	31	31	149	642	133	42	33	100%	4.8	20.4%	6.4%	13.9%	5.1%	4.88	4.99	+0.7
2025	29	MIX RAW	2 levels	31	31	149	642	133	42	33	100%	4.8	20.7%	6.5%	14.2%	5.1%	4.88	5.04	+0.6
2026	30	MIX MLE	2 levels	31	26	118	540	112	49	17	84%	3.8	18.5%	8.4%	10.1%	3.3%	6.71	4.42	+1.3
2026	30	MIX MLE	2 levels	31	26	118	540	112	49	17	84%	3.8	18.5%	8.4%	10.1%	3.3%	6.71	4.42	+1.3
2026	30	MIX RAW	2 levels	31	26	118	540	112	49	17	84%	3.8	20.7%	9.1%	11.7%	3.1%	6.71	4.32	+1.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			116	108	591	2507	491	169	106	93%	5.1	19.6%	6.7%	12.8%	4.2%	4.54	4.63	+5.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	SD	8	8	48	203	37	15	8	100%	6.0	18.4%	7.4%	11.0%	3.9%	4.80	4.98	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	SD	9	9	51	216	38	17	9	100%	5.7	17.6%	7.8%	9.9%	4.1%	5.06	5.24	+0.1
2029	33	MLB MLE	SD	9	9	53	224	42	17	10	100%	5.9	18.8%	7.4%	11.3%	4.4%	5.17	5.25	+0.1
2028	32	MLB CTX	SD	8	8	51	215	38	17	9	100%	6.4	17.6%	7.8%	9.9%	4.1%	5.06	5.24	+0.1
2029	33	MLB CTX	SD	9	9	53	224	42	17	10	100%	5.9	18.8%	7.4%	11.3%	4.4%	5.17	5.25	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		133	125	695	2947	571	202	125	94%	5.2	19.4%	6.9%	12.5%	4.2%	4.62	4.66	+6.0
/ 200 IP	—	RAW		38	36	200	847	164	58	36	94%	5.2	19.4%	6.9%	12.5%	4.2%	4.62	4.66	+1.7
Career	—	MLE		214	176	962	4046	843	288	157	82%	4.5	20.8%	7.1%	13.7%	3.9%	4.31	4.38	+5.5
/ 200 IP	—	MLE		45	37	200	841	175	60	33	82%	4.5	20.8%	7.1%	13.7%	3.9%	4.31	4.38	+1.6

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 AAAEl Paso Chihuahuas · 85 IPFIP 3.98 → 4.27 (+0.29)K% 21.9% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.91%	—	×0.860	18.85%
BB% (unintentional) /BF	9.57%	—	×0.900	8.61%
HR / BF /BF	2.77%	÷1.000	×1.100	3.05%

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 3.98 → 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).

2025 AAAEl Paso Chihuahuas · 14 IPFIP 4.89 → 5.42 (+0.53)K% 27.1% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.12%	—	×0.860	23.32%
BB% (unintentional) /BF	10.17%	—	×0.900	9.15%
HR / BF /BF	5.08%	÷0.981	×1.100	5.70%

Result: FIP 4.89 → 5.42, 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 AAALas Vegas Aviators · 48 IPFIP 1.69 → 2.08 (+0.38)K% 33.3% → 29.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.880	29.33%
BB% (unintentional) /BF	3.89%	—	×1.050	4.08%
HR / BF /BF	1.67%	÷1.075	×1.100	1.70%

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 115).

Result: FIP 1.69 → 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).

2021 AASomerset Patriots · 51 IPFIP 2.90 → 3.77 (+0.87)K% 33.6% → 27.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.65%	—	×0.810	27.26%
BB% (unintentional) /BF	8.53%	—	×1.100	9.38%
HR / BF /BF	2.84%	÷1.053	×1.200	3.24%

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 111).

Result: FIP 2.90 → 3.77, 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 AAAScranton/Wilkes-Barre RailRiders · 53 IPFIP 2.44 → 2.74 (+0.30)K% 31.9% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.86%	—	×0.880	28.04%
BB% (unintentional) /BF	5.39%	—	×1.050	5.66%
HR / BF /BF	2.45%	÷1.149	×1.100	2.35%

Result: FIP 2.44 → 2.74, 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 A+Tampa Tarpons · 49 IPFIP 3.04 → 3.85 (+0.81)K% 21.8% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.84%	—	×0.770	16.82%
BB% (unintentional) /BF	7.77%	—	×1.150	8.93%
HR / BF /BF	1.46%	÷0.960	×1.250	1.90%

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 92).

Result: FIP 3.04 → 3.85, 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 ACharleston RiverDogs · 54 IPFIP 3.41 → 5.16 (+1.74)K% 25.1% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.12%	—	×0.740	18.59%
BB% (unintentional) /BF	5.12%	—	×1.180	6.04%
HR / BF /BF	3.26%	÷0.811	×1.300	5.22%

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 62).

Result: FIP 3.41 → 5.16, 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 AClinton LumberKings · 17 IPFIP 0.96 → 2.18 (+1.22)K% 43.3% → 32.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	43.28%	—	×0.740	32.03%
BB% (unintentional) /BF	11.94%	—	×1.180	14.09%
HR / BF /BF	0.00%	÷0.931	×1.300	0.00%

Result: FIP 0.96 → 2.18, 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
JP Sears (OGILVIE)	—	—	—	—	—	3.9%	—	5.25	18.2%	10.6%	104	+0.27	—	—	—
John Bale L 2003 · 4.12 FIP	29	SP	4.12	19.0%	5.1%	3.6%	.305	—	—	—	—	—	2.49	168	57
Kaz Ishii L 2005 · 5.23 FIP	31	SP	5.23	13.3%	11.5%	3.3%	.258	—	—	—	—	—	4.51	564	56
Brandon Mann L 2016 · 4.72 FIP	32	SP	4.72	19.4%	7.9%	4.1%	.320	3.97	19.0%	7.6%	128	-0.75	3.59	190	55
Marlon Arias L 2015 · 4.32 FIP	30	SP	4.32	16.8%	12.2%	2.0%	.330	3.73	17.2%	9.5%	22	-0.59	3.73	154	51
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	51
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	50
Arturo Lopez L 2015 · 4.80 FIP	32	SP	4.80	13.7%	6.2%	3.8%	.301	4.80	10.9%	4.2%	217	+0.00	4.34	445	49
Tomas Solis L 2015 · 4.20 FIP	32	SP	4.20	15.0%	6.2%	2.9%	.264	5.09	12.0%	3.7%	159	+0.89	4.20	327	49
Wei-Yin Chen L 2016 · 4.51 FIP	31	SP	4.51	19.2%	4.6%	4.5%	.299	4.37	19.6%	13.1%	235	-0.14	3.63	1,065	48
Sean Nolin L 2021 · 4.54 FIP	31	SP-	4.54	20.4%	8.9%	3.7%	.316	5.87	19.3%	12.9%	23	+1.33	3.79	309	48
Yusei Kikuchi L 2022 · 5.19 FIP	31	SP-	5.19	27.3%	12.8%	5.1%	.281	3.78	25.4%	18.1%	522	-1.41	3.23	1,056	48
Santiago Gutierrez L 2017 · 3.95 FIP	31	SP-	3.95	15.0%	8.2%	2.0%	.366	6.54	17.1%	3.7%	46	+2.59	3.90	341	47
Joey Lucchesi L 2024 · 4.73 FIP	31	SP-	4.73	14.9%	10.1%	2.9%	.293	3.65	22.6%	15.8%	102	-1.08	3.12	817	47
Marco Tovar L 2019 · 4.78 FIP	30	SP	4.78	12.6%	5.6%	3.7%	.316	—	—	—	—	—	3.78	327	47
Carlos Teller L 2017 · 4.63 FIP	30	SP	4.63	12.2%	9.6%	2.5%	.322	4.90	13.1%	-1.1%	60	+0.27	3.75	333	47
Kelvin Marte L 2019 · 5.25 FIP	31	SP	5.25	12.0%	10.8%	3.3%	.340	—	—	—	—	—	3.44	360	47
Irwin Delgado L 2019 · 4.73 FIP	30	SP	4.73	15.6%	9.5%	3.2%	.404	—	—	—	—	—	3.52	383	45
Brad Mills L 2016 · 6.13 FIP	31	SP	6.13	14.4%	11.8%	5.0%	.299	—	—	—	—	—	4.22	243	45
Randy Keisler L 2007 · 5.51 FIP	31	SP-	5.51	6.5%	6.5%	3.9%	.281	—	—	—	—	—	5.07	135	44
Alejandro Astorga L 2017 · 4.01 FIP	30	SP	4.01	14.4%	8.2%	2.0%	.306	—	—	—	—	—	3.72	311	44

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	3.7	93	19.3%	7.0%	1.63	4.63
Jaime Barria ('23)	2.3	77	17.9%	7.7%	1.61	4.38
Sam Gaviglio ('20)	1.5	99	19.1%	7.2%	1.67	4.88
Jerry Garvin ('77-'82, 4 WAR*)	3.0	101	19.3%*	8.4%*	1.44*	4.52*
Vidal Nuño ('18)	1.9	75	19.6%	6.6%	1.55	4.06
Mark Grant ('84-'93, 0 WAR*)	3.2	91	18.0%*	8.5%*	1.41*	4.84*
Pat Underwood ('79-'83, 1 WAR*)	1.7	115	20.9%*	6.3%*	1.57*	4.52*