Chad Dallas

P Buffalo Bisons

Age 27 RHP 5'11" / 206 lbs AAA peak 0.2 · 2027

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	23	MIX2 levels	23	23	123	3.65	3.64	27.9%	9.5%	—	K 22.3% · BB 10.6% · FIP 4.57
2024	24	MIX2 levels	16	16	67	6.21	4.53	19.9%	8.0%	—	K 15.3% · BB 7.7% · FIP 4.95
2026	26	MIX2 levels	33	12	86	3.47	3.32	24.2%	9.7%	1.3	K 21.4% · BB 8.9% · FIP 3.53
2027PROJ	27	MLBTOR	7	7	40	4.22	4.29	21.3%	9.0%	0.5
2028PROJ79% MLB	28	MLBTOR	6	6	37	4.31	4.37	21.4%	9.2%	0.4
2029PROJ84% MLB	29	MLBTOR	6	6	33	4.44	4.53	20.9%	9.4%	0.3

Last 3 seasons WAR 1.3 · Next 3 projected WAR 1.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

K%74

xwOBA vs74

FB Velo62

Career WAR0.0 WAR median (P10 -0.4 / P90 1.5, comp-based) · star 0% · didn't stick 92%

CompsRicky Castro (age 24) · Erik Hiljus (age 28) · Antonio Guzman (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 98

ERA4.22

FIP4.29

K%21.3%

BB%9.0%

K-BB%12.3%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Statcast · Contract

Scouting Grades

K†5050

Statcast Percentiles

FB Velo

p6295.4

Whiff%

p6828.1%

p7426.6%

xwOBA vs

p740.289

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	22	A+ MLE	Vancouver Canadians	21	21	88	405	86	51	13	100%	4.2	16.4%	14.5%	1.9%	4.2%	4.60	5.87	—
2022	22	A+ RAW	Vancouver Canadians	21	21	88	405	86	51	13	100%	4.2	21.2%	12.6%	8.6%	3.2%	4.60	4.80	—
2023	23	MIX MLE	2 levels	23	23	123	516	144	49	16	100%	5.4	22.3%	10.6%	11.8%	3.7%	3.65	4.57	—
2023	23	MIX RAW	2 levels	23	23	123	516	144	49	16	100%	5.4	27.9%	9.5%	18.4%	3.1%	3.65	3.64	—
2024	24	MIX MLE	2 levels	16	16	67	301	60	24	11	100%	4.2	15.3%	7.7%	7.6%	4.0%	6.21	4.95	—
2024	24	MIX MLE	2 levels	16	16	67	301	60	24	11	100%	4.2	15.3%	7.7%	7.6%	4.0%	6.21	4.95	—
2024	24	MIX RAW	2 levels	16	16	67	301	60	24	11	100%	4.2	19.9%	8.0%	12.0%	3.7%	6.21	4.53	—
2026	26	MIX MLE	2 levels	33	12	86	372	90	36	7	36%	2.6	21.4%	8.9%	12.5%	2.0%	3.47	3.53	+1.1
2026	26	MIX MLE	2 levels	33	12	86	372	90	36	7	36%	2.6	21.4%	8.9%	12.5%	2.0%	3.47	3.53	+1.1
2026	26	MIX RAW	2 levels	33	12	86	372	90	36	7	36%	2.6	24.2%	9.7%	14.5%	1.9%	3.47	3.32	+1.3
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			6	0	14	64	17	8	2	0%	2.4	26.6%	12.5%	14.1%	3.1%	5.02	4.22	+0.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	TOR	7	7	40	169	36	15	4	100%	5.7	21.3%	9.0%	12.3%	2.7%	4.22	4.29	+0.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	TOR	8	8	46	196	42	18	5	100%	5.8	21.4%	9.2%	12.2%	2.8%	4.31	4.37	+0.6
2029	29	MLB MLE	TOR	7	7	40	168	35	16	5	100%	5.7	20.9%	9.4%	11.5%	3.0%	4.44	4.53	+0.4
2028	28	MLB CTX	TOR	6	6	37	156	33	14	4	100%	6.2	21.4%	9.2%	12.2%	2.8%	4.31	4.37	+0.4
2029	29	MLB CTX	TOR	6	6	33	139	29	13	4	100%	5.5	20.9%	9.4%	11.5%	3.0%	4.44	4.53	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		18	12	84	360	80	36	11	67%	4.7	22.1%	9.9%	12.3%	2.9%	4.48	4.08	+1.3
/ 200 IP	—	RAW		42	28	200	853	190	85	26	66%	4.8	22.1%	9.9%	12.3%	2.9%	4.48	4.08	+3.1
Career	—	MLE		93	72	364	1594	307	169	55	77%	3.9	19.3%	10.6%	8.6%	3.5%	4.31	4.73	+1.2
/ 200 IP	—	MLE		51	40	200	877	169	93	31	77%	3.9	19.3%	10.6%	8.6%	3.5%	4.31	4.73	+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.

2026 AAABuffalo Bisons · 71 IPFIP 3.14 → 3.40 (+0.25)K% 23.7% → 20.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.70%	—	×0.860	20.38%
BB% (unintentional) /BF	9.09%	—	×0.900	8.18%
HR / BF /BF	1.62%	÷1.000	×1.100	1.79%

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 3.14 → 3.40, 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 AAABuffalo Bisons · 61 IPFIP 4.63 → 4.95 (+0.32)K% 17.8% → 15.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.79%	—	×0.860	15.30%
BB% (unintentional) /BF	8.54%	—	×0.900	7.69%
HR / BF /BF	3.56%	÷0.990	×1.100	3.95%

Result: FIP 4.63 → 4.95, 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).

2024 ROKFCL Blue Jays · 6 IPFIP 1.62 → 4.38 (+2.76)K% 50.0% → 34.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	50.00%	—	×0.680	34.00%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
HR / BF /BF	5.00%	÷0.925	×1.400	7.56%

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 85).

Result: FIP 1.62 → 4.38, 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 AANew Hampshire Fisher Cats · 97 IPFIP 4.04 → 4.96 (+0.92)K% 25.8% → 20.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.85%	—	×0.810	20.93%
BB% (unintentional) /BF	8.94%	—	×1.100	9.83%
HR / BF /BF	3.62%	÷1.000	×1.200	4.35%

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 100).

Result: FIP 4.04 → 4.96, 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+Vancouver Canadians · 27 IPFIP 2.07 → 2.99 (+0.93)K% 36.3% → 27.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.27%	—	×0.770	27.93%
BB% (unintentional) /BF	11.76%	—	×1.150	13.53%
HR / BF /BF	0.98%	÷1.253	×1.250	0.98%

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 151).

Result: FIP 2.07 → 2.99, 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+Vancouver Canadians · 88 IPFIP 4.66 → 5.87 (+1.20)K% 21.2% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.23%	—	×0.770	16.35%
BB% (unintentional) /BF	12.59%	—	×1.150	14.48%
HR / BF /BF	3.21%	÷0.952	×1.250	4.22%

Result: FIP 4.66 → 5.87, 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
Chad Dallas (OGILVIE)	—	—	4.29	21.3%	9.0%	2.7%	—	4.44	21.2%	11.9%	86	+0.15	—	—	—
Ricky Castro R 2024 · 3.99 FIP	24	SP-	3.99	20.4%	8.6%	2.8%	.287	5.11	19.0%	10.6%	178	+1.12	3.99	241	78
Erik Hiljus R 2001 · 3.35 FIP	28	SP-	3.35	23.1%	6.9%	2.4%	.321	6.07	14.1%	4.4%	46	+2.72	3.35	112	77
Antonio Guzman R 2015 · 3.60 FIP	27	SP	3.60	18.8%	11.2%	1.2%	.328	3.47	20.6%	11.3%	170	-0.13	3.15	254	73
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	73
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	73
Justin Topa R 2018 · 4.15 FIP	27	SP-	4.15	15.1%	7.9%	2.4%	.374	2.69	19.2%	12.6%	40	-1.46	2.67	284	72
Sam Lewis R 2019 · 3.41 FIP	27	SP-	3.41	21.0%	10.8%	1.3%	.246	—	—	—	—	—	2.21	224	72
Nick Payero R 2024 · 4.21 FIP	24	SP-	4.21	16.5%	6.3%	3.1%	.285	5.81	16.6%	4.6%	107	+1.60	4.21	178	71
Raynel Espinal R 2019 · 3.90 FIP	27	SP-	3.90	22.4%	7.1%	3.2%	.313	4.01	22.3%	12.4%	224	+0.11	2.48	507	70
Chase Whitley R 2016 · 4.10 FIP	27	SP-	4.10	19.5%	7.0%	3.2%	.217	3.22	18.0%	11.8%	81	-0.88	3.09	235	69
Jimmy Endersby R 2024 · 4.54 FIP	26	SP-	4.54	17.3%	8.0%	3.4%	.257	2.86	17.2%	12.8%	36	-1.68	2.86	357	69
Ramon Ramirez R 2008 · 4.31 FIP	25	SP-	4.31	20.0%	10.5%	2.9%	.200	—	—	—	—	—	3.65	182	69
Kyle Lloyd R 2018 · 4.23 FIP	27	SP-	4.23	18.2%	9.8%	2.6%	.336	4.75	17.2%	9.3%	110	+0.52	3.50	572	68
Shawn Dubin R 2023 · 4.87 FIP	27	SP-	4.87	20.0%	12.9%	3.3%	.292	3.97	21.8%	11.4%	79	-0.90	3.02	341	68
Brendan Beck R 2023 · 3.19 FIP	24	SP	3.19	22.5%	6.7%	2.1%	.289	3.67	22.0%	14.9%	279	+0.48	3.19	310	68
Alejandro Martinez R 2015 · 4.46 FIP	26	SP-	4.46	17.5%	10.9%	2.7%	.393	4.24	9.2%	3.9%	53	-0.22	4.24	166	68
Jonathan Pintaro R 2024 · 3.42 FIP	26	SP	3.42	18.9%	9.4%	1.3%	.264	4.07	23.9%	12.1%	153	+0.65	3.42	223	67
Connor Grey R 2021 · 3.82 FIP	27	SP-	3.82	22.1%	8.1%	2.8%	.286	4.37	16.2%	7.0%	104	+0.55	2.70	461	67
Jake Lee R 2022 · 3.27 FIP	27	SP-	3.27	16.8%	7.1%	1.3%	.338	5.88	15.9%	9.6%	93	+2.61	2.78	181	67
Bryce Morrow R 2015 · 4.31 FIP	27	SP-	4.31	12.8%	7.9%	2.4%	.316	5.44	10.1%	-0.2%	50	+1.13	4.31	125	66

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	0.8	53	21.7%	9.5%	1.09	4.37
Kevin Quackenbush ('21)	1.0	52	21.0%	9.2%	1.04	4.41
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
Dave Baldwin ('66-'73, 2 WAR*)	1.1	56	22.2%*	9.2%*	0.96*	3.97*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*
John Johnstone ('00)	1.4	56	19.4%	9.5%	1.23	4.01
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*