John Gant

P Omaha Storm Chasers

Age 34 RHP 6'4" / 200 lbs AAA

Overview

AAASP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2020	27	MLBSTL	17	0	15	2.40	2.10	29.5%	11.5%	0.4
2021	28	MLBMIN	39	21	110	4.09	4.49	18.7%	14.1%	1.2
2025	32	AAAKC	19	19	81	6.00	4.99	18.4%	12.0%	—	K 15.8% · BB 10.8% · FIP 5.06
2026	33	No MLB games played
2027PROJ	34	MLBKC	1	1	6	5.19	5.11	16.8%	10.8%	0.0
2028PROJ	35	MLBKC	6	6	40	5.34	5.45	15.9%	11.3%	-0.0
2029PROJ	36	MLBKC	5	5	30	5.63	5.82	14.8%	11.9%	-0.1

Last 3 seasons WAR 1.6 · Next 3 projected WAR -0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2021

K%26

xwOBA vs21

FB Velo14

CompsJuan Omar Espinoza (age 32) · Nelson Figueroa (age 34) · Tim Adleman (age 34)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 130121vR 113

ERA5.19

FIP5.11

K%16.8%

BB%10.8%

K-BB%6.0%

Proj IP62

Value2027 · WAR

Runs saved vs league avg · 62 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1491.9

Whiff%

p4524.6%

p2618.7%

xwOBA vs

p210.346

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	MIX MLE	2 levels	24	24	140	584	134	50	7	100%	5.8	18.3%	9.5%	8.8%	1.5%	3.08	3.56	—
2015	22	MIX RAW	2 levels	24	24	140	584	134	50	7	100%	5.8	22.9%	8.6%	14.4%	1.2%	3.08	2.91	—
2016	23	MIX MLE	3 levels	33	17	109	477	108	41	12	52%	3.3	21.2%	8.8%	12.4%	2.7%	4.38	3.88	+2.0
2016	23	MIX RAW	3 levels	33	17	109	477	108	41	12	52%	3.3	22.6%	8.6%	14.0%	2.5%	4.38	3.68	+2.2
2017	24	MIX MLE	2 levels	25	20	121	510	110	33	14	80%	4.8	19.2%	6.7%	12.5%	3.0%	3.95	4.00	+2.0
2017	24	MIX RAW	2 levels	25	20	121	510	110	33	14	80%	4.8	21.6%	6.5%	15.1%	2.7%	3.95	3.61	+2.6
2018	25	MIX MLE	2 levels	34	27	163	690	137	70	14	79%	4.8	19.1%	10.3%	8.9%	2.3%	2.93	4.04	+2.6
2018	25	MIX RAW	2 levels	34	27	163	690	137	70	14	79%	4.8	19.9%	10.1%	9.7%	2.0%	2.93	3.82	+3.1
2019	26	MLB MLE	St. Louis Cardinals	64	0	66	269	60	33	4	0%	1.0	22.3%	12.3%	10.0%	1.6%	3.66	3.65	+0.7
2019	26	MLB RAW	St. Louis Cardinals	64	0	66	269	60	33	4	0%	1.0	22.3%	12.3%	10.0%	1.5%	3.66	3.57	+0.8
2020	27	MLB MLE	St. Louis Cardinals	17	0	15	61	18	7	0	0%	0.9	29.5%	11.5%	18.0%	0.0%	2.40	2.06	+0.4
2020	27	MLB RAW	St. Louis Cardinals	17	0	15	61	18	7	0	0%	0.9	29.5%	11.5%	18.0%	0.0%	2.40	2.10	+0.4
2021	28	MLB MLE	Minnesota Twins	39	21	110	491	92	69	10	54%	2.8	18.7%	14.1%	4.7%	2.0%	4.09	4.41	+1.3
2021	28	MLB RAW	Minnesota Twins	39	21	110	491	92	69	10	54%	2.8	18.7%	14.1%	4.7%	2.0%	4.09	4.49	+1.2
2025	32	AAA MLE	Omaha Storm Chasers	19	19	81	375	69	45	12	100%	4.3	15.8%	10.8%	5.0%	3.5%	6.00	5.06	—
2025	32	AAA MLE	Omaha Storm Chasers	19	19	81	375	69	45	12	100%	4.3	15.8%	10.8%	5.0%	3.5%	6.00	5.06	—
2025	32	AAA RAW	Omaha Storm Chasers	19	19	81	375	69	45	12	100%	4.3	18.4%	12.0%	6.4%	3.2%	6.00	4.99	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			173	49	373	1606	325	190	34	28%	2.2	20.2%	11.8%	8.4%	2.1%	3.89	4.07	+2.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	KC	1	1	6	25	4	3	1	100%	6.0	16.8%	10.8%	6.0%	3.1%	5.19	5.11	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	KC	6	6	40	169	27	19	6	100%	6.7	15.9%	11.3%	4.5%	3.4%	5.34	5.45	-0.0
2029	36	MLB MLE	KC	5	5	30	125	18	15	5	100%	5.9	14.8%	11.9%	2.9%	3.8%	5.63	5.82	-0.1
2030	37	MLB MLE	KC	4	4	24	100	14	13	4	100%	6.0	13.8%	12.6%	1.2%	4.2%	5.98	6.22	-0.2
2028	35	MLB CTX	KC	6	6	40	169	27	19	6	100%	6.7	15.9%	11.3%	4.5%	3.4%	5.34	5.45	-0.0
2029	36	MLB CTX	KC	5	5	30	127	19	15	5	100%	6.0	14.8%	11.9%	2.9%	3.8%	5.63	5.82	-0.1
2030	37	MLB CTX	KC	4	4	24	101	14	13	4	100%	6.0	13.8%	12.6%	1.2%	4.2%	5.98	6.22	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		188	64	466	2000	384	237	49	34%	2.5	19.2%	11.8%	7.4%	2.4%	4.23	4.31	+1.3
/ 200 IP	—	RAW		81	27	200	858	165	102	21	34%	2.5	19.2%	11.8%	7.4%	2.4%	4.23	4.31	+0.6
Career	—	MLE		255	128	805	3457	667	352	80	50%	3.2	19.3%	10.2%	9.1%	2.3%	3.82	4.03	+5.4
/ 200 IP	—	MLE		63	32	200	859	166	87	20	50%	3.2	19.3%	10.2%	9.1%	2.3%	3.82	4.03	+2.3

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.

2025 AAAOmaha Storm Chasers · 81 IPFIP 4.82 → 5.06 (+0.24)K% 18.4% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.40%	—	×0.860	15.82%
BB% (unintentional) /BF	12.00%	—	×0.900	10.80%
HR / BF /BF	3.20%	÷1.003	×1.100	3.51%

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 101).

Result: FIP 4.82 → 5.06, 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 AAAMemphis Redbirds · 49 IPFIP 3.70 → 4.25 (+0.54)K% 20.7% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.69%	—	×0.880	18.21%
BB% (unintentional) /BF	7.88%	—	×1.050	8.28%
HR / BF /BF	2.46%	÷0.909	×1.100	2.98%

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 82).

Result: FIP 3.70 → 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).

2017 AAAMemphis Redbirds · 103 IPFIP 3.14 → 3.56 (+0.42)K% 22.8% → 20.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.81%	—	×0.880	20.07%
BB% (unintentional) /BF	5.53%	—	×1.050	5.81%
HR / BF /BF	2.30%	÷0.980	×1.100	2.59%

Result: FIP 3.14 → 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).

2016 AAAGwinnett Braves · 56 IPFIP 3.39 → 3.65 (+0.26)K% 23.3% → 20.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.27%	—	×0.880	20.47%
BB% (unintentional) /BF	8.98%	—	×1.050	9.43%
HR / BF /BF	2.04%	÷1.132	×1.100	1.98%

Result: FIP 3.39 → 3.65, 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).

2015 AAMississippi Braves · 100 IPFIP 2.97 → 3.62 (+0.65)K% 20.4% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.38%	—	×0.810	16.51%
BB% (unintentional) /BF	9.48%	—	×1.100	10.43%
HR / BF /BF	0.71%	÷0.784	×1.200	1.09%

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 57).

Result: FIP 2.97 → 3.62, 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).

2015 A+St. Lucie Mets · 40 IPFIP 2.74 → 3.41 (+0.67)K% 29.6% → 22.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.63%	—	×0.770	22.81%
BB% (unintentional) /BF	6.17%	—	×1.150	7.10%
HR / BF /BF	2.47%	÷1.269	×1.250	2.43%

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 154).

Result: FIP 2.74 → 3.41, 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).

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
John Gant (OGILVIE)	—	—	—	—	—	3.1%	—	5.76	15.0%	3.2%	93	+0.65	—	—	—
Juan Omar Espinoza R 2016 · 4.84 FIP	32	SP-	4.84	8.4%	9.2%	2.4%	.348	—	—	—	—	—	4.81	104	72
Nelson Figueroa R 2008 · 3.94 FIP	34	SW	3.94	17.1%	11.8%	1.4%	.306	3.96	17.5%	9.9%	192	+0.02	3.71	499	70
Tim Adleman R 2022 · 5.69 FIP	34	SP-	5.69	17.5%	8.6%	5.4%	.275	—	—	—	—	—	3.63	605	68
Marco Antonio Duarte R 2019 · 5.03 FIP	32	SW	5.03	12.2%	9.1%	3.3%	.420	—	—	—	—	—	4.07	203	66
Ivan Maldonado R 2015 · 4.60 FIP	35	SW	4.60	12.8%	8.7%	2.7%	.269	5.41	6.4%	-3.3%	104	+0.81	4.60	172	65
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	63
Chris Jakubauskas R 2011 · 4.42 FIP	32	SW	4.42	15.7%	7.9%	3.0%	.339	—	—	—	—	—	4.42	165	62
Tiago Da Silva R 2019 · 3.95 FIP	34	SW	3.95	15.0%	7.2%	2.2%	.365	—	—	—	—	—	2.21	287	62
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	59
Daniel Guerrero R 2019 · 5.59 FIP	34	SW	5.59	14.7%	11.1%	4.2%	.353	—	—	—	—	—	4.61	269	58
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	57
Guillermo Moscoso R 2018 · 5.07 FIP	34	SP-	5.07	18.2%	8.4%	4.5%	.318	4.35	12.6%	5.9%	104	-0.72	3.56	486	56
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	56
Fernando Rodriguez Jr. R 2018 · 4.07 FIP	34	SW	4.07	23.7%	9.9%	3.1%	.253	5.11	25.0%	13.8%	32	+1.04	3.34	335	55
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	54
Zach Neal R 2023 · 5.98 FIP	34	SW	5.98	15.6%	6.0%	6.3%	.291	—	—	—	—	—	4.24	732	53
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	52
Paolo Espino R 2021 · 4.32 FIP	34	SP-	4.32	20.2%	5.1%	4.2%	.277	4.81	16.6%	10.9%	260	+0.49	3.42	933	52
Juan Delgadillo R 2017 · 4.47 FIP	34	SP	4.47	10.9%	6.2%	2.7%	.311	—	—	—	—	—	4.47	143	52
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	51

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	2.6	66	18.9%	12.2%	0.97	4.34
Brian Boehringer ('04)	2.7	67	18.2%	11.5%	1.08	4.36
Jose Paniagua ('03)	1.8	60	17.3%	11.8%	1.01	4.49
Horacio Pina ('68-'78, 2 WAR*)	2.2	62	20.7%*	11.2%*	0.84*	4.01*
Jim Roland ('62-'72, 2 WAR*)	2.3	56	18.1%*	11.6%*	0.89*	3.98*
Bryce Florie ('01)	2.5	82	18.1%	11.1%	0.84	4.47
Jerry Don Gleaton ('79-'92, 2 WAR*)	2.2	64	19.4%*	10.2%*	1.05*	4.44*