Stephen Jones

P Jacksonville Jumbo Shrimp

Age 30 RHP 6'4" / 230 lbs AAA

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	AAACOL	20	0	21	13.08	7.08	19.3%	17.8%	—	K 16.6% · BB 16.0% · FIP 5.77
2025	28	MIX2 levels	46	1	62	3.94	3.51	21.2%	7.3%	—	K 17.9% · BB 7.4% · FIP 4.41
2026	29	MIX2 levels	49	0	65	3.99	3.28	29.4%	15.0%	—	K 24.9% · BB 14.4% · FIP 3.66
2027PROJ	30	MLBMIA	7	0	7	4.58	4.58	22.1%	12.1%	-0.0
2028PROJ37% MLB	31	MLBMIA	18	0	19	4.67	4.75	21.8%	12.2%	-0.0
2029PROJ55% MLB	32	MLBMIA	22	0	23	4.82	4.95	21.5%	12.4%	-0.1

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

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control55Command50

Career WAR0.0 WAR median (P10 -0.0 / P90 0.1, comp-based) · star 0% · didn't stick 98%

CompsDustin Molleken (age 30) · Jim Miller (age 30) · Joe Nelson (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 120112vR 104

ERA4.58

FIP4.58

K%22.1%

BB%12.1%

K-BB%9.9%

Proj IP68

Value2027 · WAR

Runs saved vs league avg · 68 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL5555

CMD5050

K†5555

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	24	MIX MLE	2 levels	45	0	49	201	63	19	4	0%	1.1	23.8%	11.0%	12.8%	2.1%	3.86	3.62	—
2021	24	MIX RAW	2 levels	45	0	49	201	63	19	4	0%	1.1	31.3%	9.5%	21.9%	2.0%	3.86	2.75	—
2022	25	AA MLE	Hartford Yard Goats	47	0	58	239	67	24	6	0%	1.2	22.7%	11.0%	11.7%	3.0%	2.64	4.25	—
2022	25	AA RAW	Hartford Yard Goats	47	0	58	239	67	24	6	0%	1.2	28.0%	10.0%	18.0%	2.5%	2.64	3.38	—
2023	26	MIX MLE	2 levels	53	0	63	305	83	35	9	0%	1.2	22.6%	11.0%	11.6%	3.1%	7.86	4.31	—
2023	26	MIX RAW	2 levels	53	0	63	305	83	35	9	0%	1.2	27.2%	11.5%	15.7%	3.0%	7.86	3.99	—
2024	27	AAA MLE	Albuquerque Isotopes	20	0	21	135	26	24	5	0%	1.1	16.6%	16.0%	0.6%	3.7%	13.08	5.77	—
2024	27	AAA MLE	Albuquerque Isotopes	20	0	21	135	26	24	5	0%	1.1	16.6%	16.0%	0.6%	3.7%	13.08	5.77	—
2024	27	AAA RAW	Albuquerque Isotopes	20	0	21	135	26	24	5	0%	1.1	19.3%	17.8%	1.5%	3.7%	13.08	7.08	—
2025	28	MIX MLE	2 levels	46	1	62	259	55	19	6	2%	1.3	17.9%	7.4%	10.4%	3.4%	3.94	4.41	—
2025	28	MIX MLE	2 levels	46	1	62	259	55	19	6	2%	1.3	17.9%	7.4%	10.4%	3.4%	3.94	4.41	—
2025	28	MIX RAW	2 levels	46	1	62	259	55	19	6	2%	1.3	21.2%	7.3%	13.9%	2.3%	3.94	3.51	—
2026	29	MIX MLE	2 levels	49	0	65	293	86	44	4	0%	1.3	24.9%	14.4%	10.5%	1.5%	3.99	3.66	—
2026	29	MIX MLE	2 levels	49	0	65	293	86	44	4	0%	1.3	24.9%	14.4%	10.5%	1.5%	3.99	3.66	—
2026	29	MIX RAW	2 levels	49	0	65	293	86	44	4	0%	1.3	29.4%	15.0%	14.3%	1.4%	3.99	3.28	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	MIA	7	0	7	30	7	4	1	0%	1.0	22.1%	12.1%	9.9%	2.6%	4.58	4.58	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	MIA	49	0	51	216	47	26	6	0%	1.0	21.8%	12.2%	9.6%	2.9%	4.67	4.75	-0.1
2029	32	MLB MLE	MIA	40	0	42	175	38	22	5	0%	1.0	21.5%	12.4%	9.1%	3.1%	4.82	4.95	-0.2
2028	31	MLB CTX	MIA	18	0	19	80	17	10	2	0%	1.1	21.8%	12.2%	9.6%	2.9%	4.67	4.75	-0.0
2029	32	MLB CTX	MIA	22	0	23	97	21	12	3	0%	1.0	21.5%	12.4%	9.1%	3.1%	4.82	4.95	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		40	0	42	176	38	22	5	0%	1.0	21.6%	12.3%	9.3%	3.0%	4.75	4.48	+0.0
/ 200 IP	—	RAW		190	0	200	844	182	106	24	0%	1.1	21.6%	12.3%	9.3%	3.0%	4.75	4.48	+0.2
Career	—	MLE		260	1	318	1432	313	165	39	0%	1.2	21.8%	11.5%	10.3%	2.7%	5.09	4.23	-0.3
/ 200 IP	—	MLE		163	1	200	900	196	104	25	0%	1.2	21.8%	11.5%	10.3%	2.7%	5.09	4.23	-0.7

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 AAAJacksonville Jumbo Shrimp · 49 IPFIP 3.06 → 3.32 (+0.26)K% 30.6% → 26.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.59%	—	×0.860	26.31%
BB% (unintentional) /BF	14.16%	—	×0.900	12.74%
HR / BF /BF	1.37%	÷1.000	×1.100	1.51%

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 3.06 → 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).

2026 AAPensacola Blue Wahoos · 17 IPFIP 3.90 → 4.68 (+0.78)K% 25.7% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.68%	—	×0.810	20.80%
BB% (unintentional) /BF	17.57%	—	×1.100	19.32%
HR / BF /BF	1.35%	÷1.000	×1.200	1.62%

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 100).

Result: FIP 3.90 → 4.68, 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 AASan Antonio Missions · 54 IPFIP 3.58 → 4.41 (+0.83)K% 22.1% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.07%	—	×0.810	17.88%
BB% (unintentional) /BF	6.76%	—	×1.100	7.43%
HR / BF /BF	2.70%	÷0.950	×1.200	3.41%

Result: FIP 3.58 → 4.41, 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 · 7 IPFIP 3.10 → 3.15 (+0.05)K% 16.2% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.22%	—	×0.860	13.95%
BB% (unintentional) /BF	10.81%	—	×0.900	9.73%
HR / BF /BF	0.00%	÷0.981	×1.100	0.00%

Result: FIP 3.10 → 3.15, 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 AAAAlbuquerque Isotopes · 21 IPFIP 5.76 → 5.77 (+0.01)K% 19.3% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.26%	—	×0.860	16.56%
BB% (unintentional) /BF	17.78%	—	×0.900	16.00%
HR / BF /BF	3.70%	÷1.096	×1.100	3.72%

Result: FIP 5.76 → 5.77, 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).

2023 AAAAlbuquerque Isotopes · 31 IPFIP 5.41 → 5.54 (+0.14)K% 19.5% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.54%	—	×0.860	16.80%
BB% (unintentional) /BF	13.79%	—	×0.900	12.41%
HR / BF /BF	4.02%	÷1.062	×1.100	4.17%

Result: FIP 5.41 → 5.54, 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 AAHartford Yard Goats · 32 IPFIP 1.84 → 2.68 (+0.84)K% 37.4% → 30.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.40%	—	×0.810	30.30%
BB% (unintentional) /BF	8.40%	—	×1.100	9.24%
HR / BF /BF	1.53%	÷1.040	×1.200	1.76%

Result: FIP 1.84 → 2.68, 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 AAHartford Yard Goats · 58 IPFIP 3.38 → 4.25 (+0.87)K% 28.0% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.03%	—	×0.810	22.71%
BB% (unintentional) /BF	10.04%	—	×1.100	11.05%
HR / BF /BF	2.51%	÷0.992	×1.200	3.04%

Result: FIP 3.38 → 4.25, 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
Stephen Jones (OGILVIE)	—	—	4.58	22.1%	12.1%	2.6%	—	4.84	21.6%	9.4%	93	+0.26	—	—	—
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	89
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	89
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	88
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	85
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	85
Esteban Haro R 2016 · 4.55 FIP	30	SU	4.55	17.1%	10.2%	2.9%	.338	3.83	11.6%	6.3%	75	-0.72	3.76	164	80
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	79
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	77
Tyler Yates R 2008 · 3.90 FIP	30	SU	3.90	19.0%	11.2%	1.8%	.293	5.06	16.1%	5.4%	12	+1.16	3.23	248	76
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	75
Javy Guerra R 2016 · 4.29 FIP	30	SU	4.29	21.3%	13.9%	2.3%	.303	3.95	19.5%	13.0%	193	-0.34	2.94	409	75
Wil Browning R 2017 · 4.44 FIP	28	SU	4.44	17.9%	13.1%	2.2%	.359	—	—	—	—	—	2.14	162	75
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	75
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	75
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	74
Leonel Campos R 2017 · 3.70 FIP	30	SU	3.70	25.7%	11.8%	2.3%	.241	—	—	—	—	—	2.62	168	74
Chris Smith R 2018 · 3.72 FIP	29	SU	3.72	24.1%	9.3%	2.7%	.319	—	—	—	—	—	2.17	199	73
Danny Farquhar R 2017 · 3.62 FIP	30	SU	3.62	22.3%	11.0%	1.8%	.247	—	—	—	—	—	1.67	351	73
Kiko Calero R 2005 · 3.51 FIP	30	SU	3.51	22.7%	7.0%	2.6%	.252	3.23	23.3%	13.9%	99	-0.28	2.27	298	73
Jason Bulger R 2009 · 3.78 FIP	30	SU	3.78	26.0%	11.1%	2.7%	.247	4.36	22.5%	9.0%	24	+0.58	3.78	106	73

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	0.8	54	21.8%	12.2%	1.09	4.67
Fred Lasher ('63-'71, -1 WAR*)	1.0	50	21.5%*	11.9%*	1.05*	4.68*
Tyler Yates ('09)	1.2	62	19.7%	12.0%	0.94	5.12
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*
José Cisnero ('24)	1.4	46	24.0%	11.3%	1.01	4.16
Valerio De Los Santos ('08)	1.3	51	18.7%	11.5%	1.30	4.57
Ed Glynn ('75-'85, -0 WAR*)	1.3	53	23.5%*	12.9%*	1.22*	4.69*