Jon Duplantier

P Oklahoma City Baseball Club

Age 33 RHP 6'4" / 229 lbs AAA

Overview

AAASPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	28	AAAOklahoma City…	34	14	94	4.80	5.10	25.5%	13.3%	—	K 22.4% · BB 14.0% · FIP 5.53
2023	29	A+PHI	3	3	10	8.38	4.86	27.3%	11.4%	—	K 27.3% · BB 11.4% · FIP 4.73
2024	30	MIX2 levels	23	7	56	4.20	3.51	27.4%	16.1%	—	K 24.0% · BB 15.5% · FIP 3.94
2025	31	No MLB games played
2026	32	No MLB games played
2027PROJ	33	MLBLAD	3	3	16	4.57	4.75	21.9%	11.1%	0.1
2028PROJ6% MLB	34	MLBLAD	1	1	6	4.81	5.01	21.0%	11.2%	0.0
2029PROJMLE	35	MLBLAD	1	1	1	5.07	5.28	20.1%	11.5%	0.0

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%15

FB Velo10

xwOBA vs10

CompsKenshin Kawakami (age 34) · Austin Bibens-Dirkx (age 33) · Junior Guerra (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.57

FIP4.75

K%21.9%

BB%11.1%

K-BB%10.8%

Proj IP156

Value2027 · WAR

Runs saved vs league avg · 156 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1091.2

Whiff%

p1820.8%

p1517.1%

xwOBA vs

p100.389

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	23	MIX MLE	2 levels	25	24	136	527	165	41	6	96%	5.4	23.7%	9.0%	14.6%	1.6%	1.39	3.10	—
2017	23	MIX RAW	2 levels	25	24	136	527	165	41	6	96%	5.4	31.3%	7.8%	23.5%	1.1%	1.39	2.15	—
2018	24	MIX MLE	2 levels	16	16	74	300	77	30	4	100%	4.6	20.2%	11.3%	8.9%	1.8%	2.55	3.84	—
2018	24	MIX RAW	2 levels	16	16	74	300	77	30	4	100%	4.6	25.7%	10.0%	15.7%	1.3%	2.55	2.94	—
2019	25	MIX MLE	4 levels	31	17	80	354	84	48	4	55%	2.6	22.0%	14.0%	8.0%	0.9%	4.97	3.54	+1.8
2019	25	MIX RAW	4 levels	31	17	80	354	84	48	4	55%	2.6	23.7%	13.6%	10.2%	1.1%	4.97	3.45	+1.9
2021	27	MIX MLE	3 levels	8	7	21	110	17	13	6	88%	2.6	17.1%	11.4%	5.7%	7.6%	11.14	7.25	-0.4
2021	27	MIX RAW	3 levels	8	7	21	110	17	13	6	88%	2.6	15.5%	11.8%	3.6%	5.5%	11.14	7.05	-0.4
2022	28	AAA MLE	Oklahoma City Dodgers	34	14	94	428	109	57	18	41%	2.8	22.4%	14.0%	8.4%	4.6%	4.80	5.53	—
2022	28	AAA RAW	Oklahoma City Dodgers	34	14	94	428	109	57	18	41%	2.8	25.5%	13.3%	12.1%	4.2%	4.80	5.10	—
2023	29	A+ MLE	Jersey Shore BlueClaws	3	3	10	44	12	5	2	100%	3.2	27.3%	11.4%	15.9%	4.5%	8.38	4.73	—
2023	29	A+ RAW	Jersey Shore BlueClaws	3	3	10	44	12	5	2	100%	3.2	27.3%	11.4%	15.9%	4.5%	8.38	4.86	—
2024	30	MIX MLE	2 levels	23	7	56	248	68	40	3	30%	2.4	24.0%	15.5%	8.4%	1.6%	4.20	3.94	—
2024	30	MIX MLE	2 levels	23	7	56	248	68	40	3	30%	2.4	24.0%	15.5%	8.4%	1.6%	4.20	3.94	—
2024	30	MIX RAW	2 levels	23	7	56	248	68	40	3	30%	2.4	27.4%	16.1%	11.3%	1.2%	4.20	3.51	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			19	7	50	233	46	25	7	37%	2.6	19.7%	10.7%	9.0%	3.0%	6.70	4.59	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	LAD	3	3	16	68	15	7	2	100%	5.3	21.9%	11.1%	10.8%	3.1%	4.57	4.75	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	LAD	19	19	112	472	99	53	16	100%	5.9	21.0%	11.2%	9.8%	3.4%	4.81	5.01	+0.5
2029	35	MLB MLE	LAD	14	14	86	363	73	42	14	100%	6.1	20.1%	11.5%	8.6%	3.7%	5.07	5.28	+0.1
2028	34	MLB CTX	LAD	1	1	6	25	5	3	1	100%	6.0	21.0%	11.2%	9.8%	3.4%	4.81	5.01	+0.0
2029	35	MLB CTX	LAD	1	1	1	4	1	0	0	100%	1.0	20.1%	11.5%	8.6%	3.7%	5.07	5.28	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		20	8	57	263	52	28	8	40%	2.8	19.9%	10.8%	9.1%	3.1%	6.47	4.47	+0.1
/ 200 IP	—	RAW		71	29	200	927	183	99	28	41%	2.8	19.9%	10.8%	9.1%	3.1%	6.47	4.47	+0.2
Career	—	MLE		140	88	470	2011	449	247	51	63%	3.4	22.3%	12.3%	10.1%	2.5%	3.78	4.17	+1.1
/ 200 IP	—	MLE		60	37	200	856	191	105	22	63%	3.4	22.3%	12.3%	10.1%	2.5%	3.78	4.17	+0.9

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 AAAOklahoma City Baseball Club · 51 IPFIP 3.66 → 3.94 (+0.28)K% 27.9% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.88%	—	×0.860	23.97%
BB% (unintentional) /BF	17.26%	—	×0.900	15.53%
HR / BF /BF	1.33%	÷0.896	×1.100	1.63%

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 79).

Result: FIP 3.66 → 3.94, 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 AATulsa Drillers · 5 IPFIP 1.76 → 2.18 (+0.42)K% 22.7% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.73%	—	×0.810	18.41%
BB% (unintentional) /BF	4.55%	—	×1.100	5.00%
HR / BF /BF	0.00%	÷1.063	×1.200	0.00%

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 113).

Result: FIP 1.76 → 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).

2023 A+Jersey Shore BlueClaws · 10 IPFIP 4.73 → 6.62 (+1.89)K% 27.3% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.27%	—	×0.770	21.00%
BB% (unintentional) /BF	11.36%	—	×1.150	13.07%
HR / BF /BF	4.55%	÷0.858	×1.250	6.62%

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 72).

Result: FIP 4.73 → 6.62, 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).

2022 AAAOklahoma City Dodgers · 94 IPFIP 4.94 → 5.53 (+0.58)K% 25.5% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.47%	—	×0.880	22.41%
BB% (unintentional) /BF	13.32%	—	×1.050	13.98%
HR / BF /BF	4.21%	÷0.997	×1.100	4.64%

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 99).

Result: FIP 4.94 → 5.53, 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 AAAReno Aces · 7 IPFIP 5.51 → 5.95 (+0.44)K% 11.4% → 10.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	11.43%	—	×0.880	10.06%
BB% (unintentional) /BF	14.29%	—	×1.050	15.00%
HR / BF /BF	2.86%	÷0.958	×1.100	3.28%

Result: FIP 5.51 → 5.95, 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 AAAReno Aces · 38 IPFIP 3.33 → 3.70 (+0.38)K% 26.2% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.19%	—	×0.880	23.05%
BB% (unintentional) /BF	16.67%	—	×1.050	17.50%
HR / BF /BF	0.60%	÷1.077	×1.100	0.61%

Result: FIP 3.33 → 3.70, 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 AAJackson Generals · 67 IPFIP 3.10 → 3.84 (+0.74)K% 24.9% → 20.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.91%	—	×0.810	20.18%
BB% (unintentional) /BF	10.26%	—	×1.100	11.28%
HR / BF /BF	1.47%	÷0.954	×1.200	1.84%

Result: FIP 3.10 → 3.84, 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 ROKACL D-backs · 7 IPFIP 1.22 → 2.36 (+1.14)K% 33.3% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.33%	—	×0.680	22.67%
BB% (unintentional) /BF	7.41%	—	×1.250	9.26%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. 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 1.22 → 2.36, 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
Jon Duplantier (OGILVIE)	—	—	—	—	—	3.1%	—	5.13	20.6%	9.3%	198	+0.38	—	—	—
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	62
Austin Bibens-Dirkx R 2018 · 4.89 FIP	33	SP-	4.89	17.9%	7.6%	4.3%	.322	4.82	15.9%	9.5%	147	-0.07	3.97	567	61
Junior Guerra R 2018 · 3.99 FIP	33	SP	3.99	22.3%	9.0%	3.0%	.309	4.12	21.2%	9.1%	173	+0.13	3.18	646	60
Zach Neal R 2022 · 5.53 FIP	33	SP-	5.53	16.1%	5.7%	5.6%	.321	5.98	15.6%	9.6%	101	+0.45	4.24	732	58
Pete Walker R 2002 · 4.59 FIP	33	SP-	4.59	13.4%	7.7%	3.0%	.279	5.16	12.0%	2.8%	139	+0.57	4.45	327	57
Deck McGuire R 2022 · 5.12 FIP	33	SP-	5.12	15.7%	13.1%	3.1%	.279	—	—	—	—	—	3.41	622	54
Marco Quevedo R 2019 · 5.17 FIP	32	SP-	5.17	13.6%	11.4%	3.2%	.344	—	—	—	—	—	4.13	300	51
Shawn Haviland R 2017 · 5.00 FIP	31	SP-	5.00	16.3%	8.1%	4.1%	.261	—	—	—	—	—	3.69	283	50
Jarrett Grube R 2015 · 3.75 FIP	33	SP	3.75	18.7%	4.2%	3.1%	.285	4.57	17.3%	9.6%	253	+0.82	3.75	393	50
Mickey Jannis R 2021 · 5.68 FIP	33	SP-	5.68	12.1%	11.8%	3.8%	.303	—	—	—	—	—	2.82	659	49
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	48
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	48
Mike Burns R 2009 · 4.90 FIP	31	SP-	4.90	17.2%	6.6%	4.4%	.307	—	—	—	—	—	3.10	104	47
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	47
Osvaldo Fernandez R 2001 · 4.53 FIP	32	SP-	4.53	9.6%	8.2%	2.2%	.324	—	—	—	—	—	4.25	387	47
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	47
Cory Riordan R 2016 · 4.24 FIP	30	SP	4.24	14.3%	5.0%	3.1%	.341	—	—	—	—	—	4.24	154	46
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	45
Casey Lawrence R 2021 · 4.08 FIP	33	SP-	4.08	20.0%	5.2%	3.7%	.284	4.99	15.9%	10.6%	440	+0.91	3.57	1,374	45
Jonathan Castellanos R 2015 · 3.63 FIP	33	SP	3.63	12.2%	6.5%	1.3%	.313	4.15	11.8%	3.5%	216	+0.52	3.40	394	44

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	2.0	101	21.0%	11.2%	1.28	5.01
Bill Butler ('69-'77, 2 WAR*)	3.0	99	22.0%*	11.3%*	1.30*	4.83*
James Kaprielian ('23)	1.6	106	20.5%	9.7%	1.30	4.61
Rich Hand ('70-'73, 1 WAR*)	2.4	122	17.8%*	11.3%*	1.34*	4.83*
Kyle Wright ('23)	1.4	94	21.9%	9.7%	1.25	4.45
Jeff Robinson ('87-'92, 0 WAR*)	3.5	118	18.3%*	10.9%*	1.38*	5.14*
Mike Bolsinger ('17)	1.2	58	20.5%	9.6%	1.33	4.92