Andrew Saalfrank

P Arizona Diamondbacks

Age 29 LHP 6'3" / 205 lbs MLB ILInjured 60-Day (D60)

Overview

MLBRPIL-6040-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	25	MIX3 levels	54	0	74	2.18	2.28	31.9%	11.9%	2.0	K 28.9% · BB 12.9% · FIP 2.73
2024	26	MIX2 levels	20	0	25	3.96	3.46	27.2%	12.6%	0.3	K 25.3% · BB 9.5% · FIP 3.29
2025	27	MIX3 levels	40	0	42	3.64	3.60	19.7%	12.1%	0.5	K 16.8% · BB 8.0% · FIP 3.20
2026	28	No MLB games played
2027PROJ	29	MLBARI	24	0	25	4.43	4.64	19.1%	10.0%	-0.0
2028PROJ81% MLB	30	MLBARI	31	0	33	4.65	4.82	18.9%	10.2%	-0.1
2029PROJ86% MLB	31	MLBARI	27	0	28	4.85	5.01	18.4%	10.5%	-0.1

Last 3 seasons WAR 2.8 · Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2025

xwOBA vs50

K%13

FB Velo10

CompsKyle Lobstein (age 29) · Grant Dayton (age 29) · Tyler Olson (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 105113vR 121

ERA4.43

FIP4.64

K%19.1%

BB%10.0%

K-BB%9.2%

Proj IP33

Value2027 · WAR

Runs saved vs league avg · 33 IP

Grades · Statcast · Contract

Scouting Grades

STUF6060

CTRL4545

CMD3535

K†4545

Statcast Percentiles

FB Velo

p1089.2

Whiff%

p6727.9%

p1316.8%

xwOBA vs

p500.312

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)
2019	21	ROK MLE	ACL D-backs	1	0	1	4	1	1	0	0%	1.0	25.0%	25.0%	0.0%	0.0%	0.00	4.16	—
2019	21	ROK RAW	ACL D-backs	1	0	1	4	1	1	0	0%	1.0	25.0%	25.0%	0.0%	0.0%	0.00	4.10	—
2022	24	MIX MLE	2 levels	38	0	54	240	70	27	4	0%	1.4	22.7%	12.8%	10.0%	2.1%	3.52	3.97	—
2022	24	MIX RAW	2 levels	38	0	54	240	70	27	4	0%	1.4	29.2%	11.2%	17.9%	1.7%	3.52	2.97	—
2023	25	MIX MLE	3 levels	54	0	74	310	99	37	2	0%	1.4	28.9%	12.9%	16.0%	0.8%	2.18	2.73	+1.6
2023	25	MIX RAW	3 levels	54	0	74	310	99	37	2	0%	1.4	31.9%	11.9%	20.0%	0.6%	2.18	2.28	+2.0
2024	26	MIX MLE	2 levels	20	0	25	103	28	13	2	0%	1.2	25.3%	9.5%	15.9%	2.1%	3.96	3.29	+0.4
2024	26	MIX MLE	2 levels	20	0	25	103	28	13	2	0%	1.2	25.3%	9.5%	15.9%	2.1%	3.96	3.29	+0.4
2024	26	MIX RAW	2 levels	20	0	25	103	28	13	2	0%	1.2	27.2%	12.6%	14.6%	1.9%	3.96	3.46	+0.3
2025	27	MIX MLE	3 levels	40	0	42	173	34	21	2	0%	1.1	16.8%	8.0%	8.8%	0.9%	3.64	3.20	+0.7
2025	27	MIX MLE	3 levels	40	0	42	173	34	21	2	0%	1.1	16.8%	8.0%	8.8%	0.9%	3.64	3.20	+0.7
2025	27	MIX RAW	3 levels	40	0	42	173	34	21	2	0%	1.1	19.7%	12.1%	7.5%	1.2%	3.64	3.60	+0.5
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			40	0	40	162	25	15	1	0%	1.0	15.4%	9.3%	6.2%	0.6%	1.79	3.30	+0.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	ARI	24	0	25	106	20	11	3	0%	1.0	19.1%	10.0%	9.2%	2.8%	4.43	4.64	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	ARI	38	0	40	170	32	17	5	0%	1.1	18.9%	10.2%	8.7%	3.0%	4.65	4.82	-0.1
2029	31	MLB MLE	ARI	31	0	33	138	26	15	4	0%	1.1	18.4%	10.5%	8.0%	3.2%	4.85	5.01	-0.2
2030	32	MLB MLE	ARI	26	0	28	117	21	13	4	0%	1.1	17.9%	10.8%	7.1%	3.4%	5.07	5.23	-0.2
2028	30	MLB CTX	ARI	31	0	33	139	26	14	4	0%	1.1	18.9%	10.2%	8.7%	3.0%	4.65	4.82	-0.1
2029	31	MLB CTX	ARI	27	0	28	118	22	12	4	0%	1.0	18.4%	10.5%	8.0%	3.2%	4.85	5.01	-0.1
2030	32	MLB CTX	ARI	24	0	25	106	19	11	4	0%	1.0	17.9%	10.8%	7.1%	3.4%	5.07	5.23	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		121	0	126	523	92	53	13	0%	1.0	17.5%	10.1%	7.4%	2.4%	3.86	4.21	+0.5
/ 200 IP	—	RAW		193	0	200	831	146	84	21	0%	1.0	17.5%	10.1%	7.4%	2.4%	3.86	4.21	+0.8
Career	—	MLE		153	0	196	830	200	95	11	0%	1.3	24.1%	11.4%	12.7%	1.4%	3.08	3.26	+0.1
/ 200 IP	—	MLE		156	0	200	847	204	97	12	0%	1.3	24.1%	11.4%	12.7%	1.4%	3.08	3.26	+0.1

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 AAAReno Aces · 11 IPFIP 4.13 → 4.48 (+0.35)K% 28.6% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.57%	—	×0.860	24.57%
BB% (unintentional) /BF	18.37%	—	×0.900	16.53%
HR / BF /BF	2.04%	÷0.904	×1.100	2.48%

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 81).

Result: FIP 4.13 → 4.48, 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 AAAReno Aces · 24 IPFIP 3.10 → 3.29 (+0.19)K% 29.5% → 25.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.47%	—	×0.860	25.35%
BB% (unintentional) /BF	10.53%	—	×0.900	9.47%
HR / BF /BF	2.11%	÷1.124	×1.100	2.06%

Result: FIP 3.10 → 3.29, 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 AAAmarillo Sod Poodles · 33 IPFIP 2.20 → 2.89 (+0.69)K% 31.9% → 25.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.91%	—	×0.810	25.85%
BB% (unintentional) /BF	14.18%	—	×1.100	15.60%
HR / BF /BF	0.00%	÷1.637	×1.200	0.00%

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 227).

Result: FIP 2.20 → 2.89, 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 AAAReno Aces · 31 IPFIP 2.18 → 2.56 (+0.38)K% 37.5% → 32.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.860	32.25%
BB% (unintentional) /BF	10.94%	—	×0.900	9.84%
HR / BF /BF	1.56%	÷1.012	×1.100	1.70%

Result: FIP 2.18 → 2.56, 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).

2022 A+Hillsboro Hops · 40 IPFIP 2.47 → 3.56 (+1.09)K% 30.6% → 23.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.64%	—	×0.770	23.59%
BB% (unintentional) /BF	10.40%	—	×1.150	11.97%
HR / BF /BF	1.16%	÷0.848	×1.250	1.70%

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 70).

Result: FIP 2.47 → 3.56, 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).

2022 AAAmarillo Sod Poodles · 14 IPFIP 4.30 → 5.03 (+0.74)K% 25.4% → 20.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.37%	—	×0.810	20.55%
BB% (unintentional) /BF	13.43%	—	×1.100	14.78%
HR / BF /BF	2.99%	÷1.094	×1.200	3.27%

Result: FIP 4.30 → 5.03, 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
Andrew Saalfrank (OGILVIE)	—	—	4.64	19.1%	10.0%	2.8%	—	4.99	18.5%	8.0%	101	+0.35	—	—	—
Kyle Lobstein L 2019 · 3.93 FIP	29	SU	3.93	19.6%	11.0%	2.0%	.316	3.55	19.9%	10.9%	45	-0.38	3.33	419	69
Grant Dayton L 2017 · 5.39 FIP	29	SU	5.39	19.6%	10.8%	4.7%	.212	4.52	30.4%	23.8%	66	-0.87	1.63	277	69
Tyler Olson L 2019 · 3.86 FIP	29	SU	3.86	20.0%	10.0%	2.1%	.326	3.96	21.6%	12.9%	31	+0.10	3.15	263	68
Raul Valdes L 2010 · 4.02 FIP	32	SU	4.02	21.4%	9.9%	2.7%	.301	3.14	27.4%	22.5%	78	-0.88	2.29	160	68
Chasen Shreve L 2019 · 3.95 FIP	29	SU	3.95	24.4%	11.1%	2.7%	.269	4.59	23.9%	13.0%	108	+0.64	1.33	483	67
Jose Meraz L 2017 · 4.34 FIP	29	SU	4.34	16.4%	10.3%	2.4%	.282	3.80	10.5%	-2.0%	30	-0.54	3.78	110	67
Keith Hessler L 2018 · 4.96 FIP	29	SU	4.96	19.8%	13.3%	3.4%	.348	—	—	—	—	—	3.31	228	66
Buddy Boshers L 2017 · 4.56 FIP	29	SU	4.56	18.9%	8.0%	3.7%	.300	3.47	24.1%	15.6%	112	-1.09	2.76	239	66
Jeff Ibarra L 2017 · 3.64 FIP	29	SU	3.64	18.1%	7.0%	2.1%	.342	2.85	20.6%	17.2%	29	-0.79	2.85	101	66
Colton Johnson L 2024 · 3.92 FIP	26	SU	3.92	20.8%	11.0%	2.1%	.309	4.53	12.2%	-0.4%	48	+0.61	3.92	106	66
Darin Downs L 2014 · 3.78 FIP	29	SU	3.78	18.2%	11.5%	1.4%	.255	4.06	12.9%	8.7%	16	+0.28	2.83	107	66
Ryan Verdugo L 2015 · 3.61 FIP	28	SU	3.61	19.8%	10.8%	1.5%	.281	3.36	22.7%	17.3%	82	-0.25	3.36	153	65
Colt Hynes L 2013 · 4.76 FIP	28	SU	4.76	15.5%	8.3%	3.5%	.361	3.49	19.3%	12.8%	96	-1.27	3.42	169	65
Jared Koenig L 2023 · 4.12 FIP	29	SU	4.12	21.3%	9.2%	3.0%	.364	2.91	23.7%	16.2%	148	-1.21	2.79	475	65
Andrew Barbosa L 2017 · 4.67 FIP	29	SU	4.67	20.2%	9.6%	3.8%	.301	—	—	—	—	—	2.70	175	65
Tony Sipp L 2012 · 4.57 FIP	29	SU	4.57	21.9%	9.4%	3.9%	.252	3.22	28.6%	20.4%	143	-1.35	2.22	504	65
Doug Slaten L 2008 · 4.56 FIP	28	SU	4.56	13.6%	8.8%	2.7%	.264	3.63	19.2%	10.2%	57	-0.93	3.22	139	64
Chad Zerbe L 2001 · 3.75 FIP	29	SU	3.75	13.6%	6.2%	1.8%	.299	3.88	9.4%	2.6%	106	+0.13	3.75	145	64
Josh Edgin L 2016 · 3.64 FIP	29	SU	3.64	22.1%	13.2%	1.3%	.359	3.81	23.2%	13.6%	80	+0.17	2.62	195	64
Stephen Randolph L 2003 · 4.83 FIP	29	SU	4.83	18.5%	14.8%	2.6%	.247	5.69	15.8%	-3.0%	82	+0.86	4.83	155	64

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	0.9	36	17.9%	10.5%	0.98	4.06
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Manny Acosta ('12)	1.2	41	20.5%	10.9%	1.09	3.99
Mark Dewey ('90-'96, 3 WAR*)	1.2	42	18.7%*	9.6%*	0.80*	3.89*
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Jim Poole ('00)	1.8	45	16.1%	9.8%	1.02	4.31
Chris Ray ('11)	1.4	47	19.1%	10.2%	1.12	4.10