Rob Griswold

P Rome Emperors

Age 29 RHP 6'1" / 185 lbs A+

Overview

A+PROSPECT

ETA2029MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	MIX2 levels	38	0	49	3.31	2.86	21.8%	6.3%	—	K 16.6% · BB 6.2% · FIP 3.57
2024	26	A+ATL	30	0	49	3.47	3.59	17.0%	5.0%	—	K 13.1% · BB 5.8% · FIP 4.63
2025	27	A+ATL	33	0	50	4.65	3.97	10.8%	6.1%	—	K 8.3% · BB 7.0% · FIP 4.73
2026	28	No MLB games played
2027PROJ	29	MLBATL	—	—	0	5.40	5.40	10.0%	8.9%	—
2028PROJ30% MLB	30	MLBATL	13	0	14	5.40	5.47	11.0%	9.2%	-0.1
2029PROJ51% MLB	31	MLBATL	18	0	19	5.48	5.58	11.5%	9.6%	-0.2

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff20Control55Command30

CompsEder Llamas (age 29) · Luis Angel Daniel (age 30) · Jesus Adrian Castillo (age 31)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 136128vR 119

ERA5.40

FIP5.40

K%10.0%

BB%8.9%

K-BB%1.1%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF2020

CTRL5555

CMD3030

K†3030

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	24	A MLE	Augusta GreenJackets	39	0	59	255	58	18	7	0%	1.5	16.8%	8.3%	8.5%	3.2%	4.12	4.47	—
2022	24	A RAW	Augusta GreenJackets	39	0	59	255	58	18	7	0%	1.5	22.7%	7.1%	15.7%	2.7%	4.12	3.59	—
2023	25	MIX MLE	2 levels	38	0	49	206	45	13	3	0%	1.3	16.6%	6.2%	10.4%	2.0%	3.31	3.57	—
2023	25	MIX RAW	2 levels	38	0	49	206	45	13	3	0%	1.3	21.8%	6.3%	15.5%	1.5%	3.31	2.86	—
2024	26	A+ MLE	Rome Emperors	30	0	49	218	37	11	5	0%	1.6	13.1%	5.8%	7.3%	3.5%	3.47	4.63	—
2024	26	A+ MLE	Rome Emperors	30	0	49	218	37	11	5	0%	1.6	13.1%	5.8%	7.3%	3.5%	3.47	4.63	—
2024	26	A+ RAW	Rome Emperors	30	0	49	218	37	11	5	0%	1.6	17.0%	5.0%	11.9%	2.3%	3.47	3.59	—
2025	27	A+ MLE	Rome Emperors	33	0	50	231	25	14	4	0%	1.5	8.3%	7.0%	1.4%	2.6%	4.65	4.73	—
2025	27	A+ MLE	Rome Emperors	33	0	50	231	25	14	4	0%	1.5	8.3%	7.0%	1.4%	2.6%	4.65	4.73	—
2025	27	A+ RAW	Rome Emperors	33	0	50	231	25	14	4	0%	1.5	10.8%	6.1%	4.8%	1.7%	4.65	3.97	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	ATL	—	—	0	—	—	—	—	—	—	10.0%	8.9%	1.1%	3.0%	5.40	5.40	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	ATL	45	0	47	198	22	18	6	0%	1.0	11.0%	9.2%	1.8%	3.2%	5.40	5.47	-0.5
2029	31	MLB MLE	ATL	36	0	38	158	18	15	5	0%	1.0	11.5%	9.6%	1.9%	3.4%	5.48	5.58	-0.4
2028	30	MLB CTX	ATL	13	0	14	59	6	5	2	0%	1.1	11.0%	9.2%	1.8%	3.2%	5.40	5.47	-0.1
2029	31	MLB CTX	ATL	18	0	19	80	9	8	3	0%	1.1	11.5%	9.6%	1.9%	3.4%	5.48	5.58	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		32	0	33	140	16	13	5	0%	1.0	11.3%	9.4%	1.9%	3.3%	5.45	5.16	-0.2
/ 200 IP	—	RAW		190	0	200	844	96	78	30	0%	1.1	11.3%	9.4%	1.9%	3.3%	5.45	5.16	-1.4
Career	—	MLE		140	0	208	910	125	63	26	0%	1.5	13.7%	6.9%	6.8%	2.8%	3.90	4.37	-0.9
/ 200 IP	—	MLE		135	0	200	876	120	60	25	0%	1.5	13.7%	6.9%	6.8%	2.8%	3.90	4.37	-2.2

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.

2025 A+Rome Emperors · 50 IPFIP 3.90 → 4.73 (+0.83)K% 10.8% → 8.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.82%	—	×0.770	8.33%
BB% (unintentional) /BF	6.06%	—	×1.150	6.97%
HR / BF /BF	1.73%	÷0.819	×1.250	2.64%

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 64).

Result: FIP 3.90 → 4.73, 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+Rome Emperors · 49 IPFIP 3.56 → 4.63 (+1.06)K% 17.0% → 13.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.97%	—	×0.770	13.07%
BB% (unintentional) /BF	5.05%	—	×1.150	5.80%
HR / BF /BF	2.29%	÷0.831	×1.250	3.45%

Result: FIP 3.56 → 4.63, 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+Rome Braves · 44 IPFIP 2.85 → 3.57 (+0.72)K% 21.6% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.62%	—	×0.770	16.65%
BB% (unintentional) /BF	5.41%	—	×1.150	6.22%
HR / BF /BF	1.62%	÷1.022	×1.250	1.98%

Result: FIP 2.85 → 3.57, 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).

2023 AAugusta GreenJackets · 5 IPFIP 2.90 → 3.75 (+0.85)K% 23.8% → 17.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.740	17.62%
BB% (unintentional) /BF	14.29%	—	×1.180	16.86%
HR / BF /BF	0.00%	÷0.976	×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 95).

Result: FIP 2.90 → 3.75, 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 AAugusta GreenJackets · 59 IPFIP 3.58 → 4.47 (+0.89)K% 22.7% → 16.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.75%	—	×0.740	16.83%
BB% (unintentional) /BF	7.06%	—	×1.180	8.33%
HR / BF /BF	2.75%	÷1.127	×1.300	3.17%

Result: FIP 3.58 → 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
Rob Griswold (OGILVIE)	—	—	5.40	10.0%	8.9%	3.0%	—	5.52	11.2%	1.8%	84	+0.12	—	—	—
Eder Llamas R 2015 · 4.84 FIP	29	SU	4.84	12.3%	8.8%	3.0%	.261	3.64	11.3%	4.6%	120	-1.20	3.23	171	88
Luis Angel Daniel R 2015 · 4.47 FIP	30	SU	4.47	9.9%	6.9%	2.4%	.292	4.36	11.6%	2.4%	107	-0.11	4.16	156	86
Jesus Adrian Castillo R 2015 · 4.37 FIP	31	SU	4.37	9.8%	9.5%	1.6%	.307	3.52	13.2%	7.9%	80	-0.85	2.23	173	85
Willie Eyre R 2007 · 4.53 FIP	29	SU	4.53	13.7%	9.1%	2.6%	.306	2.87	11.1%	5.5%	18	-1.66	2.87	164	82
Benjamin Sandoval R 2016 · 5.13 FIP	29	SU	5.13	6.7%	11.3%	2.1%	.292	5.51	9.0%	-4.4%	49	+0.38	4.66	146	82
Jose Casilla R 2016 · 4.65 FIP	27	SU	4.65	13.0%	8.0%	3.0%	.314	—	—	—	—	—	3.06	104	81
Lance Carter R 2004 · 4.95 FIP	29	SU	4.95	10.7%	6.2%	3.6%	.243	5.11	9.1%	1.9%	69	+0.16	3.63	248	80
Tony Fiore R 2000 · 5.61 FIP	28	SU	5.61	10.8%	9.5%	4.0%	.321	4.76	14.3%	3.5%	127	-0.85	4.60	142	80
Brian Bass R 2009 · 4.70 FIP	27	SU	4.70	13.5%	9.8%	2.8%	.321	—	—	—	—	—	4.70	176	79
Jeff Gray R 2011 · 4.36 FIP	29	SU	4.36	10.7%	8.8%	1.9%	.284	5.43	11.0%	1.7%	52	+1.07	3.46	127	79
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	79
Ryan Doolittle R 2016 · 4.38 FIP	28	SU	4.38	13.9%	7.1%	2.8%	.269	—	—	—	—	—	4.03	101	78
Santiago Casilla R 2009 · 4.44 FIP	29	SU	4.44	15.0%	9.4%	2.6%	.324	3.29	22.1%	13.0%	170	-1.15	2.76	647	78
Fernando Villalobos R 2015 · 5.33 FIP	30	SU	5.33	8.3%	13.1%	2.3%	.365	4.36	11.4%	3.1%	109	-0.97	4.00	152	77
Jason Boyd R 2002 · 5.81 FIP	29	SU	5.81	13.7%	10.7%	4.6%	.290	4.74	15.0%	3.7%	65	-1.07	3.68	128	77
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	76
Kyle McMyne R 2017 · 4.84 FIP	27	SU	4.84	12.5%	12.8%	2.1%	.330	—	—	—	—	—	3.93	181	76
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	75
Roman Colon R 2009 · 4.94 FIP	29	SU	4.94	13.2%	9.5%	3.2%	.264	—	—	—	—	—	2.64	177	74
Eddie Bonine R 2010 · 4.54 FIP	29	SU	4.54	8.6%	6.6%	2.4%	.308	—	—	—	—	—	4.40	129	74

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	51	10.7%	9.2%	1.22	5.42
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Eric Gunderson ('00)	1.1	76	13.3%	8.1%	1.14	4.95
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*
Russ Swan ('89-'94, -2 WAR*)	1.3	89	12.3%*	9.9%*	1.13*	5.09*
Chuck Hartenstein ('66-'77, -1 WAR*)	1.5	59	13.7%*	7.2%*	1.50*	5.28*