Chandler Champlain

P Rochester Red Wings

Age 28 RHP 6'5" / 220 lbs AAA peak 0.5 · 2027

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	28	27	140	5.07	4.47	19.9%	8.8%	—	K 16.7% · BB 8.1% · FIP 4.72
2025	26	AAAKC	29	25	119	7.84	4.88	17.7%	9.0%	—	K 15.2% · BB 8.1% · FIP 4.97
2026	27	AAAWSH	28	19	128	3.95	4.20	17.9%	5.8%	—	K 15.4% · BB 5.2% · FIP 4.58
2027PROJ	28	MLBWSH	2	2	9	5.16	5.16	14.3%	7.4%	0.0
2028PROJ37% MLB	29	MLBWSH	4	4	26	5.14	5.19	14.8%	7.7%	0.1
2029PROJ55% MLB	30	MLBWSH	6	6	36	5.05	5.03	17.0%	7.2%	0.2

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

Stuff40Control50Command40

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

CompsAndres Ivan Meza (age 28) · Travis Smith (age 29) · Luke Irvine (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 131123vR 115

ERA5.16

FIP5.16

K%14.3%

BB%7.4%

K-BB%6.9%

Proj IP88

Value2027 · WAR

Runs saved vs league avg · 88 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL5050

CMD4040

K†3040

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)
2022	23	MIX MLE	2 levels	24	22	105	464	116	30	14	92%	4.4	18.6%	7.6%	11.1%	3.8%	5.98	4.56	—
2022	23	MIX RAW	2 levels	24	22	105	464	116	30	14	92%	4.4	25.0%	6.5%	18.5%	3.0%	5.98	3.48	—
2023	24	MIX MLE	2 levels	25	25	135	549	125	43	16	100%	5.4	18.0%	8.8%	9.2%	3.9%	3.33	4.81	—
2023	24	MIX RAW	2 levels	25	25	135	549	125	43	16	100%	5.4	22.8%	7.8%	14.9%	2.9%	3.33	3.74	—
2024	25	MIX MLE	2 levels	28	27	140	604	120	53	21	96%	5.0	16.7%	8.1%	8.6%	3.7%	5.07	4.72	—
2024	25	MIX MLE	2 levels	28	27	140	604	120	53	21	96%	5.0	16.7%	8.1%	8.6%	3.7%	5.07	4.72	—
2024	25	MIX RAW	2 levels	28	27	140	604	120	53	21	96%	5.0	19.9%	8.8%	11.1%	3.5%	5.07	4.47	—
2025	26	AAA MLE	Omaha Storm Chasers	29	25	119	565	100	51	20	86%	4.1	15.2%	8.1%	7.1%	3.9%	7.84	4.97	—
2025	26	AAA MLE	Omaha Storm Chasers	29	25	119	565	100	51	20	86%	4.1	15.2%	8.1%	7.1%	3.9%	7.84	4.97	—
2025	26	AAA RAW	Omaha Storm Chasers	29	25	119	565	100	51	20	86%	4.1	17.7%	9.0%	8.7%	3.5%	7.84	4.88	—
2026	27	AAA MLE	Rochester Red Wings	28	19	128	515	92	30	18	68%	4.6	15.4%	5.2%	10.1%	3.8%	3.95	4.58	—
2026	27	AAA MLE	Rochester Red Wings	28	19	128	515	92	30	18	68%	4.6	15.4%	5.2%	10.1%	3.8%	3.95	4.58	—
2026	27	AAA RAW	Rochester Red Wings	28	19	128	515	92	30	18	68%	4.6	17.9%	5.8%	12.0%	3.5%	3.95	4.20	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	WSH	2	2	9	38	5	3	1	100%	4.5	14.3%	7.4%	6.9%	3.5%	5.16	5.16	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	WSH	12	12	70	294	44	23	11	100%	5.8	14.8%	7.7%	7.1%	3.6%	5.14	5.19	+0.2
2029	30	MLB MLE	WSH	11	11	65	274	47	20	10	100%	5.9	17.0%	7.2%	9.8%	3.8%	5.05	5.03	+0.3
2030	31	MLB MLE	WSH	9	9	57	239	40	18	9	100%	6.3	16.9%	7.6%	9.3%	4.0%	5.12	5.20	+0.1
2028	29	MLB CTX	WSH	4	4	26	110	16	8	4	100%	6.5	14.8%	7.7%	7.1%	3.6%	5.14	5.19	+0.1
2029	30	MLB CTX	WSH	6	6	36	152	26	11	6	100%	6.0	17.0%	7.2%	9.8%	3.8%	5.05	5.03	+0.2
2030	31	MLB CTX	WSH	6	6	38	160	27	12	6	100%	6.3	16.9%	7.6%	9.3%	4.0%	5.12	5.20	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		17	17	100	421	69	31	16	100%	5.9	16.4%	7.5%	8.9%	3.8%	5.10	4.76	+0.7
/ 200 IP	—	RAW		33	33	200	844	138	62	32	100%	6.0	16.4%	7.5%	8.9%	3.8%	5.10	4.76	+1.5
Career	—	MLE		134	118	628	2697	451	205	102	88%	4.7	16.7%	7.6%	9.1%	3.8%	5.14	4.74	+0.6
/ 200 IP	—	MLE		43	38	200	859	144	65	33	88%	4.7	16.7%	7.6%	9.1%	3.8%	5.14	4.74	+0.6

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 AAARochester Red Wings · 128 IPFIP 4.25 → 4.58 (+0.33)K% 17.9% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.86%	—	×0.860	15.36%
BB% (unintentional) /BF	5.83%	—	×0.900	5.24%
HR / BF /BF	3.50%	÷1.000	×1.100	3.84%

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 4.25 → 4.58, 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 AAAOmaha Storm Chasers · 119 IPFIP 4.69 → 4.97 (+0.28)K% 17.7% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.70%	—	×0.860	15.22%
BB% (unintentional) /BF	9.03%	—	×0.900	8.12%
HR / BF /BF	3.54%	÷1.003	×1.100	3.88%

Result: FIP 4.69 → 4.97, 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 AAAOmaha Storm Chasers · 104 IPFIP 5.05 → 5.09 (+0.04)K% 15.5% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.48%	—	×0.860	13.32%
BB% (unintentional) /BF	9.89%	—	×0.900	8.90%
HR / BF /BF	3.66%	÷1.111	×1.100	3.62%

Result: FIP 5.05 → 5.09, 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 AANorthwest Arkansas Naturals · 36 IPFIP 2.40 → 3.50 (+1.10)K% 34.5% → 28.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.53%	—	×0.810	27.97%
BB% (unintentional) /BF	5.04%	—	×1.100	5.54%
HR / BF /BF	2.88%	÷0.920	×1.200	3.75%

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 84).

Result: FIP 2.40 → 3.50, 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 AANorthwest Arkansas Naturals · 73 IPFIP 4.36 → 5.56 (+1.20)K% 21.2% → 17.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.19%	—	×0.810	17.17%
BB% (unintentional) /BF	8.28%	—	×1.100	9.11%
HR / BF /BF	3.64%	÷0.872	×1.200	5.01%

Result: FIP 4.36 → 5.56, 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).

2023 A+Quad Cities River Bandits · 62 IPFIP 3.05 → 3.90 (+0.85)K% 24.7% → 19.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.70%	—	×0.770	19.02%
BB% (unintentional) /BF	7.29%	—	×1.150	8.38%
HR / BF /BF	2.02%	÷1.033	×1.250	2.45%

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 107).

Result: FIP 3.05 → 3.90, 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 ATampa Tarpons · 73 IPFIP 3.26 → 4.60 (+1.33)K% 30.5% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.52%	—	×0.740	22.58%
BB% (unintentional) /BF	6.17%	—	×1.180	7.28%
HR / BF /BF	3.57%	÷1.026	×1.300	4.53%

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 105).

Result: FIP 3.26 → 4.60, 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+Quad Cities River Bandits · 32 IPFIP 3.86 → 4.47 (+0.61)K% 14.1% → 10.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.10%	—	×0.770	10.86%
BB% (unintentional) /BF	7.05%	—	×1.150	8.11%
HR / BF /BF	1.92%	÷1.047	×1.250	2.30%

Result: FIP 3.86 → 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).

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
Chandler Champlain (OGILVIE)	—	—	5.16	14.3%	7.4%	3.5%	—	5.14	16.2%	8.7%	191	-0.02	—	—	—
Andres Ivan Meza R 2015 · 4.45 FIP	28	SP	4.45	10.9%	5.6%	2.9%	.322	4.14	12.5%	4.0%	85	-0.31	4.14	275	87
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	86
Luke Irvine R 2016 · 4.31 FIP	27	SP-	4.31	13.4%	9.8%	2.0%	.302	—	—	—	—	—	4.31	104	82
Robert Ellis R 2001 · 4.84 FIP	30	SP	4.84	9.9%	7.7%	2.9%	.287	8.08	9.0%	-2.2%	18	+3.24	4.84	110	82
Caleb Clay R 2015 · 4.67 FIP	27	SP	4.67	9.9%	6.9%	2.8%	.324	—	—	—	—	—	4.67	111	81
Marco Antonio Duarte R 2015 · 4.07 FIP	28	SP	4.07	15.5%	9.1%	2.0%	.306	4.73	9.0%	-1.2%	38	+0.66	4.07	203	79
Omar Bencomo R 2017 · 4.50 FIP	28	SP-	4.50	18.9%	6.3%	4.0%	.333	4.48	14.9%	10.1%	186	-0.02	3.70	381	78
Frank Batista R 2015 · 4.29 FIP	26	SP-	4.29	12.1%	8.2%	2.1%	.280	—	—	—	—	—	4.29	118	78
Travis Driskill R 2002 · 4.95 FIP	30	SP-	4.95	13.2%	8.0%	3.6%	.291	4.26	15.3%	12.0%	48	-0.69	4.26	181	78
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	78
Rolando Valdez R 2015 · 4.07 FIP	29	SP	4.07	13.3%	5.9%	2.4%	.301	3.78	13.2%	7.9%	176	-0.29	3.06	258	78
Marco Quevedo R 2015 · 4.13 FIP	28	SP	4.13	9.0%	6.4%	1.8%	.262	4.67	11.9%	6.3%	135	+0.54	4.13	300	78
Jason Forjet R 2016 · 4.48 FIP	26	SP	4.48	15.9%	5.5%	3.7%	.260	—	—	—	—	—	3.36	197	78
Joe Roa R 2002 · 4.60 FIP	30	SP-	4.60	11.7%	3.7%	3.7%	.278	4.47	15.5%	9.3%	121	-0.13	4.28	258	77
Jordan Cooper R 2015 · 5.01 FIP	26	SP	5.01	9.2%	10.2%	2.5%	.305	—	—	—	—	—	5.01	106	76
Brady Rodgers R 2019 · 5.44 FIP	28	SP-	5.44	14.7%	9.0%	4.4%	.270	—	—	—	—	—	1.98	354	76
Brannon Easterling R 2017 · 4.40 FIP	26	SP-	4.40	12.7%	8.2%	2.4%	.322	—	—	—	—	—	3.50	334	76
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	76
Tyler Herron R 2016 · 4.40 FIP	29	SP	4.40	13.4%	6.9%	2.9%	.389	4.02	16.4%	7.7%	60	-0.38	4.02	117	76
Austin Bibens-Dirkx R 2015 · 3.97 FIP	30	SP	3.97	17.4%	7.1%	2.6%	.315	4.94	15.9%	8.7%	305	+0.97	3.97	567	76

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	1.4	70	15.6%	7.5%	1.43	5.12
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Bob Wells ('02)	3.2	79	15.0%	7.2%	1.43	5.03
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*
Travis Harper ('06)	2.1	69	15.0%	7.5%	1.33	4.94
Paul Reuschel ('75-'79, 1 WAR*)	2.0	79	16.8%*	7.6%*	1.29*	4.76*
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*