Jonah Tong

P Syracuse Mets

Age 24 RHP 6'1" / 180 lbs AAA Svc 0.0 · Ctrl thru 2032 peak 1.0 · 2029

Overview

AAASP40-MANROOKIEPre-ArbFA 2033

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	21	MIX3 levels	25	23	113	3.03	1.86	34.2%	10.0%	—	K 25.8% · BB 11.5% · FIP 2.61
2025	22	MIX3 levels	27	27	132	2.31	1.82	38.0%	10.6%	6.2	K 31.7% · BB 11.9% · FIP 2.54
2026	23	MIX2 levels	30	27	138	4.38	4.63	26.6%	12.1%	1.2	K 23.7% · BB 11.2% · FIP 4.91
2027PROJ	24	MLBNYM	9	9	49	4.35	4.52	27.0%	11.5%	0.5
2028PROJ86% MLB	25	MLBNYM	13	13	74	4.36	4.39	26.9%	10.6%	0.9
2029PROJ91% MLB	26	MLBNYM	14	14	83	4.35	4.35	26.8%	10.3%	1.0

Last 3 seasons WAR 7.5 · Next 3 projected WAR 2.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2032Service0.372First FA2033

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Arb-1$3M2031Arb-2$5M2032Arb-3$6M

Skills · percentileStatcast 2026

xwOBA vs90

K%67

FB Velo55

Form3.92 ERA (proj 4.35) · K 31.0% (proj 27.0%) · BB 8.0% (proj 11.5%) ▲▲ last 60d · 21 IP through Oct 27

Career WAR0.8 WAR median (P10 -0.4 / P90 16, comp-based) · star 2% · didn't stick 58%

CompsShohei Ohtani (age 24) · Ryan Garcia (age 24) · Jake Lee (age 24)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119111vR 103

ERA4.35

FIP4.52

K%27.0%

BB%11.5%

K-BB%15.5%

Proj IP63

Value2027 · WAR

Runs saved vs league avg · 63 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$23M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p5594.9

Whiff%

p8130.2%

p6725.4%

xwOBA vs

p900.274

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status Pre-Arb

MLB Debut 2025

Service 0.372 yrs.days

Team Control Through 2032

First FA Year 2033

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.5	$2M	+$1M
2028	Pre-Arb	$0.8M	+0.9	$3M	+$3M
2029	Pre-Arb	$0.8M	+1.0	$7M	+$6M
2030	Arb-1	$3M	+1.0	$6M	+$4M
2031	Arb-2	$5M	+0.9	$3M	+$0.0M (cut)
2032	Arb-3	$6M	+0.7	$2M	+$0.0M (cut)
Totals		$6M		$23M	+$14M

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)
2023	20	MIX MLE	2 levels	10	8	21	100	38	22	3	80%	2.1	28.8%	27.5%	1.3%	2.3%	6.00	5.41	—
2023	20	MIX RAW	2 levels	10	8	21	100	38	22	3	80%	2.1	38.0%	22.0%	16.0%	3.0%	6.00	4.48	—
2024	21	MIX MLE	3 levels	25	23	113	468	160	47	3	92%	4.5	25.8%	11.5%	14.3%	0.4%	3.03	2.61	—
2024	21	MIX MLE	3 levels	25	23	113	468	160	47	3	92%	4.5	25.8%	11.5%	14.3%	0.4%	3.03	2.61	—
2024	21	MIX RAW	3 levels	25	23	113	468	160	47	3	92%	4.5	34.2%	10.0%	24.1%	0.6%	3.03	1.86	—
2025	22	MIX MLE	3 levels	27	27	132	529	201	56	5	100%	4.9	31.7%	11.9%	19.8%	1.1%	2.31	2.54	+4.8
2025	22	MIX MLE	3 levels	27	27	132	529	201	56	5	100%	4.9	31.7%	11.9%	19.8%	1.1%	2.31	2.54	+4.8
2025	22	MIX RAW	3 levels	27	27	132	529	201	56	5	100%	4.9	38.0%	10.6%	27.4%	0.9%	2.31	1.82	+6.2
2026	23	MIX MLE	2 levels	30	27	138	601	160	73	24	90%	4.6	23.7%	11.2%	12.5%	4.4%	4.38	4.91	+0.8
2026	23	MIX MLE	2 levels	30	27	138	601	160	73	24	90%	4.6	23.7%	11.2%	12.5%	4.4%	4.38	4.91	+0.8
2026	23	MIX RAW	2 levels	30	27	138	601	160	73	24	90%	4.6	26.6%	12.1%	14.5%	4.0%	4.38	4.63	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			12	9	49	221	56	23	5	75%	4.1	25.3%	10.4%	14.9%	2.3%	5.29	3.55	+1.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	24	MLB	NYM	9	9	49	207	56	24	7	100%	5.4	27.0%	11.5%	15.5%	3.4%	4.35	4.52	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	25	MLB MLE	NYM	15	15	85	360	97	38	12	100%	5.7	26.9%	10.6%	16.3%	3.3%	4.36	4.39	+1.0
2029	26	MLB MLE	NYM	15	15	92	387	103	40	13	100%	6.1	26.8%	10.3%	16.4%	3.3%	4.35	4.35	+1.1
2030	27	MLB MLE	NYM	15	15	91	383	101	39	13	100%	6.0	26.5%	10.3%	16.2%	3.4%	4.37	4.38	+1.1
2031	28	MLB MLE	NYM	15	15	88	370	97	38	13	100%	5.8	26.3%	10.4%	15.9%	3.4%	4.43	4.47	+1.0
2032	29	MLB MLE	NYM	13	13	77	326	84	35	12	100%	5.9	25.7%	10.6%	15.1%	3.6%	4.55	4.63	+0.7
2033	30	MLB MLE	NYM	11	11	64	271	68	30	10	100%	5.8	25.0%	10.9%	14.1%	3.8%	4.72	4.83	+0.4
2034	31	MLB MLE	NYM	8	8	50	210	51	24	8	100%	6.2	24.2%	11.2%	13.0%	4.0%	4.93	5.07	+0.2
2035	32	MLB MLE	NYM	6	6	36	152	35	18	6	100%	6.0	23.4%	11.7%	11.8%	4.3%	5.16	5.32	+0.0
2028	25	MLB CTX	NYM	13	13	74	312	84	33	10	100%	5.7	26.9%	10.6%	16.3%	3.3%	4.36	4.39	+0.9
2029	26	MLB CTX	NYM	14	14	83	350	94	36	12	100%	5.9	26.8%	10.3%	16.4%	3.3%	4.35	4.35	+1.0
2030	27	MLB CTX	NYM	14	14	84	355	94	36	12	100%	6.0	26.5%	10.3%	16.2%	3.3%	4.37	4.38	+1.0
2031	28	MLB CTX	NYM	14	14	82	346	91	36	12	100%	5.9	26.3%	10.4%	15.9%	3.4%	4.43	4.47	+0.9
2032	29	MLB CTX	NYM	12	12	73	308	79	33	11	100%	6.1	25.7%	10.6%	15.1%	3.6%	4.55	4.63	+0.7
2033	30	MLB CTX	NYM	10	10	61	258	64	28	10	100%	6.1	25.0%	10.9%	14.1%	3.8%	4.71	4.82	+0.4
2034	31	MLB CTX	NYM	8	8	47	198	48	22	8	100%	5.9	24.2%	11.2%	13.0%	4.0%	4.92	5.06	+0.2
2035	32	MLB CTX	NYM	6	6	34	144	34	17	6	100%	5.7	23.4%	11.7%	11.8%	4.3%	5.15	5.31	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		102	99	588	2496	645	265	86	97%	5.8	25.8%	10.6%	15.2%	3.4%	4.60	4.15	+8.7
/ 200 IP	—	RAW		35	34	200	849	219	90	29	97%	5.8	25.8%	10.6%	15.2%	3.4%	4.60	4.15	+3.0
Career	—	MLE		92	85	404	1698	460	211	36	92%	4.4	27.1%	12.4%	14.6%	2.1%	3.41	3.57	+6.6
/ 200 IP	—	MLE		46	42	200	841	227	105	18	92%	4.4	27.1%	12.4%	14.6%	2.1%	3.41	3.57	+2.1

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 AAASyracuse Mets · 107 IPFIP 5.01 → 5.43 (+0.42)K% 27.0% → 23.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.98%	—	×0.860	23.20%
BB% (unintentional) /BF	12.63%	—	×0.900	11.37%
HR / BF /BF	4.71%	÷1.000	×1.100	5.18%

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 5.01 → 5.43, 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 AABinghamton Rumble Ponies · 102 IPFIP 1.33 → 2.19 (+0.85)K% 40.8% → 33.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.81%	—	×0.810	33.05%
BB% (unintentional) /BF	11.08%	—	×1.100	12.19%
HR / BF /BF	0.50%	÷0.990	×1.200	0.61%

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 98).

Result: FIP 1.33 → 2.19, 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 AAASyracuse Mets · 12 IPFIP 0.75 → 1.12 (+0.36)K% 37.8% → 32.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.78%	—	×0.860	32.49%
BB% (unintentional) /BF	6.67%	—	×0.900	6.00%
HR / BF /BF	0.00%	÷1.167	×1.100	0.00%

Result: FIP 0.75 → 1.12, 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).

2024 A+Brooklyn Cyclones · 85 IPFIP 2.17 → 2.94 (+0.77)K% 30.3% → 23.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.30%	—	×0.770	23.33%
BB% (unintentional) /BF	10.47%	—	×1.150	12.04%
HR / BF /BF	0.55%	÷1.341	×1.250	0.51%

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 168).

Result: FIP 2.17 → 2.94, 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 ASt. Lucie Mets · 19 IPFIP -0.44 → 0.89 (+1.33)K% 52.9% → 39.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	52.94%	—	×0.740	39.18%
BB% (unintentional) /BF	7.35%	—	×1.180	8.68%
HR / BF /BF	0.00%	÷0.826	×1.300	0.00%

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 65).

Result: FIP -0.44 → 0.89, 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 AABinghamton Rumble Ponies · 9 IPFIP 2.76 → 4.15 (+1.39)K% 37.8% → 30.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.84%	—	×0.810	30.65%
BB% (unintentional) /BF	10.81%	—	×1.100	11.89%
HR / BF /BF	2.70%	÷0.834	×1.200	3.89%

Result: FIP 2.76 → 4.15, 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).

2023 ROKFCL Mets · 13 IPFIP 3.24 → 5.41 (+2.16)K% 42.4% → 28.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	42.37%	—	×0.680	28.81%
BB% (unintentional) /BF	22.03%	—	×1.250	27.54%
HR / BF /BF	1.69%	÷1.040	×1.400	2.28%

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 108).

Result: FIP 3.24 → 5.41, 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).

2023 ASt. Lucie Mets · 8 IPFIP 5.88 → 7.13 (+1.25)K% 31.7% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.71%	—	×0.740	23.46%
BB% (unintentional) /BF	21.95%	—	×1.180	25.90%
HR / BF /BF	4.88%	÷1.274	×1.300	4.98%

Result: FIP 5.88 → 7.13, 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
Jonah Tong (OGILVIE)	—	—	—	—	—	3.4%	—	4.37	26.7%	16.3%	268	-0.15	—	—	—
Shohei Ohtani R 2018 · 3.43 FIP	24	SP	3.43	29.9%	10.4%	2.8%	.267	3.14	29.3%	21.4%	130	-0.29	1.76	613	78
Ryan Garcia R 2022 · 3.74 FIP	24	SP	3.74	23.2%	10.7%	2.3%	.239	5.53	19.8%	6.6%	278	+1.79	3.74	362	78
Jake Lee R 2019 · 4.65 FIP	24	SP-	4.65	25.7%	12.4%	3.9%	.296	3.52	18.7%	10.3%	40	-1.13	2.78	181	77
Trent Palmer R 2022 · 4.79 FIP	23	SP	4.79	22.0%	10.4%	4.1%	.284	4.83	12.8%	-9.4%	22	+0.04	3.51	140	77
Bud Norris R 2009 · 4.47 FIP	24	SP	4.47	21.7%	9.6%	3.6%	.309	4.01	22.5%	13.5%	508	-0.46	3.51	1,221	77
Dylan DeLucia R 2024 · 3.88 FIP	23	SP	3.88	21.6%	7.4%	3.0%	.241	5.29	18.0%	7.2%	197	+1.41	3.88	232	75
Sam Benschoter R 2022 · 3.71 FIP	24	SP-	3.71	26.3%	9.2%	3.0%	.344	4.96	18.7%	8.6%	306	+1.25	3.61	441	75
Ryan Jennings R 2023 · 3.43 FIP	24	SP-	3.43	23.4%	11.9%	1.5%	.316	4.31	22.9%	10.2%	109	+0.88	3.43	142	74
Trevor May R 2014 · 4.40 FIP	24	SP	4.40	20.7%	9.9%	3.3%	.369	3.18	25.0%	19.1%	157	-1.22	3.05	477	73
Cole Sands R 2021 · 3.67 FIP	24	SP	3.67	23.3%	11.5%	1.9%	.269	3.53	25.0%	17.4%	216	-0.14	2.28	474	73
Kyle Bradish R 2021 · 3.60 FIP	24	SP	3.60	26.4%	10.6%	2.5%	.333	3.30	24.9%	17.2%	345	-0.30	2.20	750	73
Brody McCullough R 2023 · 3.58 FIP	23	SP	3.58	23.1%	10.3%	2.1%	.267	4.45	21.3%	11.7%	42	+0.87	3.58	129	72
Jared Karros R 2024 · 3.36 FIP	23	SP	3.36	21.9%	9.2%	1.7%	.281	7.71	12.4%	2.7%	52	+4.35	3.36	191	72
Burch Smith R 2013 · 5.18 FIP	23	SP-	5.18	27.5%	12.0%	5.3%	.326	—	—	—	—	—	3.50	418	72
Rafael Montero R 2014 · 5.04 FIP	23	SP-	5.04	21.6%	11.9%	4.1%	.298	4.32	19.3%	8.2%	296	-0.72	2.43	714	72
Jared Lyons R 2024 · 4.72 FIP	23	SP	4.72	22.1%	14.4%	3.0%	.258	4.13	17.6%	8.7%	173	-0.59	3.28	265	71
Cade Smith R 2024 · 3.86 FIP	22	SP	3.86	23.2%	13.3%	1.9%	.273	5.35	18.2%	6.6%	157	+1.49	3.86	243	71
Ben Gross R 2021 · 4.05 FIP	24	SP-	4.05	23.0%	8.8%	3.2%	.359	4.85	17.6%	2.0%	22	+0.80	4.05	118	70
Gabriel Hughes R 2023 · 5.12 FIP	21	SP	5.12	22.2%	10.0%	4.8%	.302	3.85	18.8%	11.1%	207	-1.27	3.22	274	70
Jaxon Wiggins R 2024 · 3.53 FIP	22	SP	3.53	22.5%	12.8%	1.3%	.286	3.71	23.6%	9.6%	102	+0.18	3.11	154	70

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	3.5	69	26.0%	10.7%	1.33	4.57
Calvin Schiraldi ('84-'91, 2 WAR*)	2.8	92	25.3%*	11.1%*	1.35*	4.71*
Doug Bair ('76-'90, 7 WAR*)	4.5	76	25.2%*	10.4%*	1.22*	4.12*
Tim Stoddard ('75-'89, 4 WAR*)	3.6	66	26.2%*	11.2%*	1.14*	4.24*
Robert Stephenson ('25)	1.9	62	25.9%	10.1%	1.54	4.59
Tony Cingrani ('18)	1.7	56	25.8%	11.3%	1.26	4.01
Hansel Robles ('22)	2.1	61	25.3%	10.2%	1.20	4.11