Chayce McDermott

P Syracuse Mets

Age 28 RHP 6'3" / 190 lbs AAA

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	23	22	104	3.89	3.56	32.2%	13.6%	2.3	K 28.3% · BB 12.3% · FIP 3.80
2025	26	MIX3 levels	30	12	68	7.38	5.21	22.2%	17.6%	-0.5	K 19.2% · BB 15.8% · FIP 4.99
2026	27	MIX2 levels	45	1	49	4.22	3.51	31.9%	14.6%	0.6	K 29.9% · BB 13.7% · FIP 3.27
2027PROJ	28	MLBNYM	93	0	98	4.98	4.65	26.1%	14.9%	-0.1
2028PROJ78% MLB	29	MLBNYM	80	0	84	4.82	4.74	25.5%	14.4%	-0.2
2029PROJ84% MLB	30	MLBNYM	72	0	76	4.84	4.88	24.9%	14.2%	-0.3

Last 3 seasons WAR 2.4 · Next 3 projected WAR -0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.1 / P90 0.5, comp-based) · star 0% · didn't stick 96%

CompsCarlos Torres (age 27) · Jose De La Torre (age 27) · Peyton Gray (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122113vR 105

ERA4.98

FIP4.65

K%26.1%

BB%14.9%

K-BB%11.2%

Proj IP139

Value2027 · WAR

Runs saved vs league avg · 139 IP

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	22	MIX MLE	2 levels	7	4	21	85	40	11	3	57%	3.0	33.0%	15.9%	17.1%	4.5%	2.95	4.79	—
2021	22	MIX RAW	2 levels	7	4	21	85	40	11	3	57%	3.0	47.1%	12.9%	34.1%	3.5%	2.95	2.73	—
2022	23	MIX MLE	2 levels	27	18	104	457	160	64	17	67%	3.8	27.3%	15.9%	11.4%	4.2%	5.56	5.13	—
2022	23	MIX RAW	2 levels	27	18	104	457	160	64	17	67%	3.8	35.0%	14.0%	21.0%	3.7%	5.56	4.00	—
2023	24	MIX MLE	2 levels	26	22	119	492	152	68	9	85%	4.6	25.7%	14.2%	11.4%	1.9%	3.10	3.77	—
2023	24	MIX RAW	2 levels	26	22	119	492	152	68	9	85%	4.6	30.9%	13.8%	17.1%	1.8%	3.10	3.24	—
2024	25	MIX MLE	2 levels	23	22	104	456	147	62	12	96%	4.5	28.3%	12.3%	15.9%	2.8%	3.89	3.80	+2.0
2024	25	MIX MLE	2 levels	23	22	104	456	147	62	12	96%	4.5	28.3%	12.3%	15.9%	2.8%	3.89	3.80	+2.0
2024	25	MIX RAW	2 levels	23	22	104	456	147	62	12	96%	4.5	32.2%	13.6%	18.6%	2.6%	3.89	3.56	+2.3
2025	26	MIX MLE	3 levels	30	12	68	324	72	57	9	40%	2.3	19.2%	15.8%	3.4%	2.8%	7.38	4.99	-0.4
2025	26	MIX MLE	3 levels	30	12	68	324	72	57	9	40%	2.3	19.2%	15.8%	3.4%	2.8%	7.38	4.99	-0.4
2025	26	MIX RAW	3 levels	30	12	68	324	72	57	9	40%	2.3	22.2%	17.6%	4.6%	2.8%	7.38	5.21	-0.5
2026	27	MIX MLE	2 levels	45	1	49	226	72	33	5	2%	1.1	29.9%	13.7%	16.1%	1.7%	4.22	3.27	+0.7
2026	27	MIX MLE	2 levels	45	1	49	226	72	33	5	2%	1.1	29.9%	13.7%	16.1%	1.7%	4.22	3.27	+0.7
2026	27	MIX RAW	2 levels	45	1	49	226	72	33	5	2%	1.1	31.9%	14.6%	17.3%	2.2%	4.22	3.51	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			10	2	20	105	18	18	6	20%	2.0	17.1%	17.1%	0.0%	5.7%	10.18	7.82	-0.8
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	NYM	93	0	98	414	108	62	11	0%	1.1	26.1%	14.9%	11.2%	2.7%	4.98	4.65	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	NYM	103	0	108	455	116	65	13	0%	1.0	25.5%	14.4%	11.1%	2.9%	4.82	4.74	-0.2
2029	30	MLB MLE	NYM	86	0	91	383	95	54	12	0%	1.1	24.9%	14.2%	10.7%	3.1%	4.84	4.88	-0.3
2028	29	MLB CTX	NYM	80	0	84	355	90	51	10	0%	1.1	25.5%	14.4%	11.1%	2.9%	4.82	4.74	-0.2
2029	30	MLB CTX	NYM	72	0	76	321	80	46	10	0%	1.1	24.9%	14.2%	10.7%	3.1%	4.84	4.88	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		163	2	181	781	188	115	26	1%	1.1	24.1%	14.7%	9.4%	3.4%	5.43	4.77	-0.5
/ 200 IP	—	RAW		180	2	200	866	208	127	29	1%	1.1	24.1%	14.7%	9.4%	3.4%	5.43	4.77	-0.5
Career	—	MLE		158	79	465	2040	538	295	58	50%	2.9	26.4%	14.4%	11.9%	2.8%	4.56	4.26	+0.8
/ 200 IP	—	MLE		68	34	200	877	231	127	25	50%	2.9	26.4%	14.4%	11.9%	2.8%	4.56	4.26	+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 AAASyracuse Mets · 41 IPFIP 2.97 → 3.27 (+0.30)K% 34.7% → 29.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.74%	—	×0.860	29.87%
BB% (unintentional) /BF	15.26%	—	×0.900	13.74%
HR / BF /BF	1.58%	÷1.000	×1.100	1.74%

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 2.97 → 3.27, 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 AAANorfolk Tides · 58 IPFIP 4.24 → 4.47 (+0.24)K% 22.7% → 19.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.73%	—	×0.860	19.55%
BB% (unintentional) /BF	15.91%	—	×0.900	14.32%
HR / BF /BF	1.89%	÷0.945	×1.100	2.20%

Result: FIP 4.24 → 4.47, 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 AAANorfolk Tides · 100 IPFIP 3.44 → 3.80 (+0.36)K% 32.9% → 28.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.88%	—	×0.860	28.27%
BB% (unintentional) /BF	13.70%	—	×0.900	12.33%
HR / BF /BF	2.51%	÷0.996	×1.100	2.77%

Result: FIP 3.44 → 3.80, 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 AABowie Baysox · 68 IPFIP 3.60 → 4.28 (+0.68)K% 30.7% → 24.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.66%	—	×0.810	24.84%
BB% (unintentional) /BF	15.33%	—	×1.100	16.86%
HR / BF /BF	2.09%	÷1.208	×1.200	2.08%

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 142).

Result: FIP 3.60 → 4.28, 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 AAANorfolk Tides · 51 IPFIP 2.75 → 3.06 (+0.31)K% 31.2% → 26.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.22%	—	×0.860	26.85%
BB% (unintentional) /BF	11.71%	—	×0.900	10.54%
HR / BF /BF	1.46%	÷0.995	×1.100	1.62%

Result: FIP 2.75 → 3.06, 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).

2022 A+Aberdeen IronBirds · 77 IPFIP 3.27 → 4.57 (+1.29)K% 36.3% → 27.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.26%	—	×0.770	27.92%
BB% (unintentional) /BF	12.87%	—	×1.150	14.80%
HR / BF /BF	2.92%	÷1.029	×1.250	3.55%

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 106).

Result: FIP 3.27 → 4.57, 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 AABowie Baysox · 27 IPFIP 6.00 → 6.81 (+0.81)K% 31.3% → 25.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.30%	—	×0.810	25.36%
BB% (unintentional) /BF	17.39%	—	×1.100	19.13%
HR / BF /BF	6.09%	÷1.170	×1.200	6.24%

Result: FIP 6.00 → 6.81, 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 AFayetteville Woodpeckers · 18 IPFIP 3.27 → 4.79 (+1.52)K% 44.6% → 33.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	44.59%	—	×0.740	33.00%
BB% (unintentional) /BF	13.51%	—	×1.180	15.95%
HR / BF /BF	4.05%	÷1.176	×1.300	4.48%

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 135).

Result: FIP 3.27 → 4.79, 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
Chayce McDermott (OGILVIE)	—	—	—	—	—	2.7%	—	4.80	25.2%	10.9%	198	+0.15	—	—	—
Carlos Torres R 2010 · 4.50 FIP	27	SW	4.50	18.3%	11.3%	2.8%	.438	3.89	20.1%	13.2%	139	-0.61	2.89	604	63
Jose De La Torre R 2013 · 5.22 FIP	27	SU	5.22	28.3%	18.9%	3.9%	.308	3.87	17.6%	6.6%	110	-1.35	2.64	141	62
Peyton Gray R 2021 · 4.27 FIP	26	SU	4.27	29.2%	14.1%	3.4%	.307	—	—	—	—	—	3.62	160	62
Jeff Ames R 2019 · 4.45 FIP	28	SU	4.45	25.6%	16.8%	2.5%	.351	—	—	—	—	—	3.85	272	61
David Lebron R 2021 · 5.56 FIP	27	SU	5.56	26.7%	14.7%	5.2%	.278	—	—	—	—	—	4.28	144	61
Jason García R 2021 · 4.76 FIP	28	SP-	4.76	17.7%	13.5%	2.6%	.349	—	—	—	—	—	4.16	356	60
Jefry Rodriguez R 2021 · 5.03 FIP	28	SW	5.03	19.4%	13.5%	3.4%	.287	4.58	19.8%	6.8%	64	-0.45	3.30	578	60
Emmanuel Chapman R 2024 · 4.08 FIP	25	SW	4.08	19.7%	10.6%	2.4%	.256	4.52	17.8%	1.3%	117	+0.44	3.81	198	59
Nelson Gonzalez R 2018 · 5.03 FIP	28	SW	5.03	19.2%	8.2%	4.6%	.311	6.22	16.9%	4.6%	74	+1.19	3.42	258	59
Luis Santos R 2019 · 4.31 FIP	28	SU	4.31	22.9%	10.0%	3.4%	.312	—	—	—	—	—	3.53	472	59
Calvin Drummond R 2016 · 3.55 FIP	26	SW	3.55	16.9%	11.1%	0.9%	.316	—	—	—	—	—	3.48	112	59
Spencer Bivens R 2022 · 4.86 FIP	28	SU	4.86	19.8%	13.5%	3.1%	.265	3.85	18.1%	10.3%	272	-1.01	3.52	391	59
Mayckol Guaipe R 2019 · 4.18 FIP	28	SW	4.18	26.0%	7.6%	4.2%	.432	—	—	—	—	—	1.88	136	58
Shawn Dubin R 2024 · 3.51 FIP	28	SU	3.51	23.7%	12.6%	1.5%	.326	4.60	19.3%	11.7%	34	+1.09	3.02	341	58
Jason Bulger R 2008 · 4.60 FIP	29	SU	4.60	27.4%	12.3%	4.1%	.293	3.94	25.1%	13.3%	90	-0.66	3.78	106	58
Coleman Huntley III R 2021 · 3.85 FIP	28	SW	3.85	20.2%	7.4%	2.8%	.348	3.56	23.4%	13.2%	86	-0.29	2.38	160	58
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	58
Kiko Calero R 2003 · 3.54 FIP	28	SU	3.54	31.5%	11.1%	3.1%	.273	3.11	26.1%	18.9%	159	-0.43	2.27	298	57
Dustin Nippert R 2009 · 4.09 FIP	28	SP-	4.09	18.0%	9.7%	2.3%	.271	4.49	17.9%	6.1%	57	+0.40	3.83	268	57
Luis Mateo R 2017 · 4.60 FIP	27	SU	4.60	17.6%	11.2%	2.9%	.309	5.55	8.6%	-4.8%	43	+0.95	3.48	160	57

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	1.8	119	25.0%	14.7%	1.19	5.19
Kazuhisa Ishii ('02-'05, 1 WAR*)	2.8	141	19.8%*	13.6%*	1.14*	4.72*
Les Cain ('68-'72, 2 WAR*)	1.9	93	24.6%*	12.9%*	1.00*	4.66*
Dan Warthen ('75-'78, 1 WAR*)	1.5	102	24.8%*	14.2%*	1.27*	4.86*
Tim Lollar ('80-'86, 3 WAR*)	4.5	129	21.2%*	12.2%*	1.35*	4.94*
Tony Saunders ('99)	1.7	115	19.7%	13.2%	0.86	4.56
Rick Ankiel ('04)	1.2	81	25.9%	12.5%	1.19	3.90