Grant Rogers

P Buffalo Bisons

Age 26 RHP 6'7" / 230 lbs AAA Svc 0.0 · Ctrl thru 2032 peak 0.5 · 2028

Overview

AAAPROSPECTPre-ArbFA 2033

OGV OFP35OGV rank#1219ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	23	MIX2 levels	21	20	112	3.87	3.12	23.2%	6.1%	—	K 17.4% · BB 7.2% · FIP 4.08
2025	24	MIX2 levels	28	28	150	3.47	3.19	17.8%	5.9%	—	K 14.2% · BB 6.6% · FIP 3.90
2026	25	AAATOR	28	28	130	6.73	4.97	12.9%	6.9%	—	K 11.1% · BB 6.2% · FIP 5.08
2027PROJ	26	MLBTOR	3	3	16	5.02	5.02	11.6%	5.7%	0.1
2028PROJ33% MLB	27	MLBTOR	7	7	43	4.97	4.98	12.6%	6.0%	0.2
2029PROJ50% MLB	28	MLBTOR	10	10	58	4.97	5.01	13.2%	6.2%	0.3

Next 3 projected WAR 0.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2032Service0.0First FA2033

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Arb-1$0.8M2031Arb-2$0.4M2032Ext$7M

Career WAR0.0 WAR median (P10 -0.7 / P90 2.3, comp-based) · star 0% · didn't stick 91%

CompsGreg Peavey (age 27) · Brandon Sinnery (age 25) · Lindsey Caughel (age 26)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129120vR 112

ERA5.02

FIP5.02

K%11.6%

BB%5.7%

K-BB%5.9%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit+$3M ctrl surplus

Contract

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

Status Pre-Arb

MLB Debut 2027

Service 0 yrs (est)

Team Control Through 2032

First FA Year 2033

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+0.1	$0.3M	+$0.0M (cut)
2028	Pre-Arb	$0.8M	+0.2	$0.7M	+$0.0M
2029	Pre-Arb	$0.8M	+0.3	$1M	+$0.4M
2030	Arb-1	$0.8M	+0.2	$0.6M	+$0.1M
2031	Arb-2	$0.4M	+0.1	$0.3M	+$0.0M
2032	Ext	beyond projection horizon · no WAR estimate
Totals		$3M		$3M	+$0.5M

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)
2024	23	MIX MLE	2 levels	21	20	112	457	106	28	10	95%	5.3	17.4%	7.2%	10.2%	2.8%	3.87	4.08	—
2024	23	MIX MLE	2 levels	21	20	112	457	106	28	10	95%	5.3	17.4%	7.2%	10.2%	2.8%	3.87	4.08	—
2024	23	MIX RAW	2 levels	21	20	112	457	106	28	10	95%	5.3	23.2%	6.1%	17.1%	2.2%	3.87	3.12	—
2025	24	MIX MLE	2 levels	28	28	150	646	115	38	10	100%	5.4	14.2%	6.6%	7.6%	2.1%	3.47	3.90	—
2025	24	MIX MLE	2 levels	28	28	150	646	115	38	10	100%	5.4	14.2%	6.6%	7.6%	2.1%	3.47	3.90	—
2025	24	MIX RAW	2 levels	28	28	150	646	115	38	10	100%	5.4	17.8%	5.9%	11.9%	1.5%	3.47	3.19	—
2026	25	AAA MLE	Buffalo Bisons	28	28	130	595	77	41	21	100%	4.6	11.1%	6.2%	4.9%	3.9%	6.73	5.08	—
2026	25	AAA MLE	Buffalo Bisons	28	28	130	595	77	41	21	100%	4.6	11.1%	6.2%	4.9%	3.9%	6.73	5.08	—
2026	25	AAA RAW	Buffalo Bisons	28	28	130	595	77	41	21	100%	4.6	12.9%	6.9%	6.1%	3.5%	6.73	4.97	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	26	MLB	TOR	3	3	16	68	8	4	2	100%	5.3	11.6%	5.7%	5.9%	3.3%	5.02	5.02	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	27	MLB MLE	TOR	22	22	129	546	69	33	18	100%	5.9	12.6%	6.0%	6.7%	3.3%	4.97	4.98	+0.6
2029	28	MLB MLE	TOR	19	19	115	487	64	30	16	100%	6.1	13.2%	6.2%	7.0%	3.4%	4.97	5.01	+0.5
2030	29	MLB MLE	TOR	17	17	104	440	59	29	15	100%	6.1	13.4%	6.6%	6.9%	3.5%	5.04	5.10	+0.4
2031	30	MLB MLE	TOR	16	16	94	396	53	27	15	100%	5.9	13.3%	6.9%	6.4%	3.7%	5.17	5.26	+0.1
2028	27	MLB CTX	TOR	7	7	43	182	23	11	6	100%	6.1	12.6%	6.0%	6.7%	3.3%	4.97	4.98	+0.2
2029	28	MLB CTX	TOR	10	10	58	245	32	15	8	100%	5.8	13.2%	6.2%	7.0%	3.4%	4.97	5.01	+0.3
2030	29	MLB CTX	TOR	10	10	63	266	36	17	9	100%	6.3	13.4%	6.6%	6.9%	3.5%	5.04	5.10	+0.2
2031	30	MLB CTX	TOR	11	11	64	270	36	19	10	100%	5.8	13.3%	6.9%	6.4%	3.7%	5.17	5.26	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		38	38	227	957	126	62	33	100%	6.0	13.2%	6.5%	6.7%	3.5%	5.05	4.72	+1.8
/ 200 IP	—	RAW		33	33	200	844	111	55	29	100%	6.0	13.2%	6.5%	6.7%	3.5%	5.05	4.72	+1.6
Career	—	MLE		77	76	392	1698	237	112	50	99%	5.1	14.0%	6.6%	7.4%	2.9%	4.66	4.36	+1.6
/ 200 IP	—	MLE		39	39	200	867	121	57	25	99%	5.1	14.0%	6.6%	7.4%	2.9%	4.66	4.36	+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 AAABuffalo Bisons · 130 IPFIP 4.82 → 5.08 (+0.26)K% 12.9% → 11.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.94%	—	×0.860	11.13%
BB% (unintentional) /BF	6.89%	—	×0.900	6.20%
HR / BF /BF	3.53%	÷1.000	×1.100	3.88%

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 4.82 → 5.08, 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 AANew Hampshire Fisher Cats · 111 IPFIP 3.32 → 4.00 (+0.68)K% 16.0% → 13.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.00%	—	×0.810	12.96%
BB% (unintentional) /BF	4.21%	—	×1.100	4.63%
HR / BF /BF	1.89%	÷0.885	×1.200	2.57%

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 77).

Result: FIP 3.32 → 4.00, 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 A+Vancouver Canadians · 40 IPFIP 2.83 → 3.62 (+0.79)K% 22.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.81%	—	×0.770	17.56%
BB% (unintentional) /BF	10.53%	—	×1.150	12.11%
HR / BF /BF	0.58%	÷0.855	×1.250	0.85%

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 71).

Result: FIP 2.83 → 3.62, 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).

2024 ADunedin Blue Jays · 74 IPFIP 3.69 → 4.82 (+1.13)K% 22.7% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.65%	—	×0.740	16.76%
BB% (unintentional) /BF	7.12%	—	×1.180	8.40%
HR / BF /BF	2.91%	÷1.003	×1.300	3.77%

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 101).

Result: FIP 3.69 → 4.82, 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+Vancouver Canadians · 38 IPFIP 1.93 → 2.55 (+0.62)K% 24.3% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.32%	—	×0.770	18.73%
BB% (unintentional) /BF	4.05%	—	×1.150	4.66%
HR / BF /BF	0.68%	÷1.062	×1.250	0.80%

Result: FIP 1.93 → 2.55, 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
Grant Rogers (OGILVIE)	—	—	—	—	—	3.3%	—	5.03	13.1%	6.8%	349	+0.01	—	—	—
Greg Peavey R 2015 · 4.39 FIP	27	SP	4.39	11.2%	6.5%	2.6%	.289	—	—	—	—	—	4.39	147	89
Brandon Sinnery R 2015 · 4.73 FIP	25	SP	4.73	11.0%	6.9%	3.1%	.296	—	—	—	—	—	4.73	154	88
Lindsey Caughel R 2017 · 4.49 FIP	26	SP	4.49	14.6%	6.5%	3.3%	.276	5.12	13.3%	5.0%	29	+0.63	4.49	187	86
Gabriel Arias R 2015 · 4.42 FIP	25	SP	4.42	13.1%	7.2%	2.8%	.299	—	—	—	—	—	4.11	195	85
Mario Gonzalez R 2015 · 4.32 FIP	28	SP	4.32	12.6%	6.0%	2.8%	.302	4.20	16.2%	10.8%	233	-0.12	3.94	368	83
Juan Carlos Sulbaran R 2016 · 4.65 FIP	26	SP	4.65	15.0%	8.9%	3.1%	.289	—	—	—	—	—	4.65	278	81
Matt Milburn R 2019 · 4.87 FIP	26	SP	4.87	10.8%	6.0%	3.5%	.318	5.89	11.9%	6.6%	190	+1.02	1.59	648	81
Nick Petree R 2015 · 4.15 FIP	25	SP	4.15	11.4%	6.9%	2.1%	.306	—	—	—	—	—	4.15	122	81
Jason Simontacchi R 2002 · 4.79 FIP	28	SP	4.79	12.0%	8.3%	3.0%	.252	5.30	12.2%	4.5%	142	+0.51	4.79	356	79
Caleb Clay R 2015 · 4.67 FIP	27	SP	4.67	9.9%	6.9%	2.8%	.324	—	—	—	—	—	4.67	111	79
Carlos Pimentel R 2016 · 4.30 FIP	26	SP	4.30	16.1%	9.7%	2.4%	.339	4.61	11.9%	-0.6%	13	+0.31	4.30	301	79
Angel Sánchez R 2015 · 3.94 FIP	25	SP	3.94	14.8%	6.5%	2.3%	.264	3.80	23.7%	18.5%	68	-0.14	3.77	284	79
Asher Wojciechowski R 2015 · 4.30 FIP	26	SP	4.30	15.7%	8.5%	2.6%	.323	4.61	20.4%	12.2%	287	+0.31	3.15	678	78
Chandler Champlain R 2024 · 4.72 FIP	25	SP	4.72	16.7%	8.1%	3.6%	.298	4.77	15.3%	8.7%	247	+0.05	4.56	628	78
Elih Villanueva R 2015 · 3.83 FIP	29	SP	3.83	11.0%	5.5%	1.8%	.269	5.48	14.1%	8.1%	57	+1.65	3.83	225	78
Victor Mateo R 2015 · 4.32 FIP	26	SP	4.32	10.3%	9.3%	1.7%	.273	5.45	10.2%	-2.0%	51	+1.13	4.32	199	78
Ricky Knapp R 2017 · 3.92 FIP	25	SP	3.92	11.1%	5.0%	2.0%	.317	—	—	—	—	—	3.38	456	78
Manuel Flores R 2015 · 4.03 FIP	29	SP	4.03	13.8%	7.1%	2.2%	.317	3.57	14.4%	9.2%	263	-0.46	3.46	515	78
Kyle Luckham R 2024 · 4.81 FIP	24	SP	4.81	13.6%	5.9%	3.8%	.297	3.92	14.0%	6.3%	232	-0.89	3.78	501	78
Ryan Hawks R 2024 · 5.26 FIP	23	SP	5.26	13.6%	7.3%	4.4%	.303	5.12	13.6%	4.3%	221	-0.14	4.78	342	78

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	3.0	122	12.7%	6.2%	1.32	5.03
Jae Weong Seo ('07)	3.0	121	12.9%	7.0%	1.28	4.60
Nick Blackburn ('12)	4.1	164	10.8%	5.6%	1.29	4.85
Brian Bannister ('10)	3.3	133	13.2%	7.7%	1.16	5.08
Ken Schrom ('80-'87, 3 WAR*)	4.5	150	13.4%*	8.1%*	1.41*	4.77*
Glenn Abbott ('73-'84, 4 WAR*)	6.4	129	13.9%*	6.4%*	1.57*	4.74*
Don August ('88-'91, 1 WAR*)	2.2	147	12.7%*	8.1%*	1.26*	5.01*