Andrew Suárez

P Norfolk Tides

Age 34 LHP 6'0" / 202 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2020	27	MLBSF	6	0	10	3.72	5.27	11.9%	14.3%	-0.1
2023	30	MIX2 levels	41	3	92	5.01	4.38	20.9%	9.7%	0.2	K 18.5% · BB 9.1% · FIP 4.61
2024	31	AAABAL	10	0	14	5.93	4.34	19.4%	8.1%	—	K 16.6% · BB 7.3% · FIP 4.57
2025	32	No MLB games played
2026	33	No MLB games played
2027PROJ	34	MLBBAL	1	1	1	4.40	4.51	21.5%	9.1%	0.0
2028PROJ6% MLB	35	MLBBAL	1	1	1	4.75	4.93	20.5%	9.7%	0.0

Last 3 seasons WAR 0.1 · Next 2 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2023

FB Velo19

K%10

xwOBA vs10

CompsKwang Hyun Kim (age 33) · Juan Antonio Pena (age 37) · Hisanori Takahashi (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 103111vR 119

ERA4.40

FIP4.51

K%21.5%

BB%9.1%

K-BB%12.4%

Proj IP7

Value2027 · WAR

Runs saved vs league avg · 7 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1992.3

Whiff%

p1019.4%

p1013.1%

xwOBA vs

p100.366

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)
2015	22	MIX MLE	2 levels	6	3	20	75	22	3	2	50%	3.3	21.6%	4.0%	17.6%	4.3%	1.80	4.12	—
2015	22	MIX RAW	2 levels	6	3	20	75	22	3	2	50%	3.3	29.3%	4.0%	25.3%	2.7%	1.80	2.65	—
2016	23	MIX MLE	2 levels	24	24	144	602	124	29	13	100%	6.0	16.5%	5.3%	11.1%	2.6%	3.63	3.84	—
2016	23	MIX RAW	2 levels	24	24	144	602	124	29	13	100%	6.0	20.6%	4.8%	15.8%	2.2%	3.63	3.16	—
2017	24	MIX MLE	2 levels	26	24	156	666	135	40	10	92%	6.0	17.3%	6.4%	10.8%	1.9%	3.30	3.52	—
2017	24	MIX RAW	2 levels	26	24	156	666	135	40	10	92%	6.0	20.3%	6.0%	14.3%	1.5%	3.30	2.97	—
2018	25	MIX MLE	3 levels	33	33	184	760	153	53	23	100%	5.6	19.7%	7.0%	12.7%	3.4%	4.07	4.19	+2.6
2018	25	MIX RAW	3 levels	33	33	184	760	153	53	23	100%	5.6	20.1%	7.0%	13.2%	3.0%	4.07	3.93	+3.2
2019	26	MIX MLE	2 levels	39	17	121	543	82	41	18	44%	3.1	13.8%	7.8%	6.0%	3.6%	5.74	4.88	-0.5
2019	26	MIX RAW	2 levels	39	17	121	543	82	41	18	44%	3.1	15.1%	7.6%	7.6%	3.3%	5.74	4.70	-0.2
2020	27	MLB MLE	San Francisco Giants	6	0	10	42	5	6	1	0%	1.6	11.9%	14.3%	-2.4%	2.4%	3.72	5.21	-0.1
2020	27	MLB RAW	San Francisco Giants	6	0	10	42	5	6	1	0%	1.6	11.9%	14.3%	-2.4%	2.4%	3.72	5.27	-0.1
2023	30	MIX MLE	2 levels	41	3	92	412	86	40	13	7%	2.2	18.5%	9.1%	9.4%	3.5%	5.01	4.61	-0.1
2023	30	MIX RAW	2 levels	41	3	92	412	86	40	13	7%	2.2	20.9%	9.7%	11.2%	3.2%	5.01	4.38	+0.2
2024	31	AAA MLE	Norfolk Tides	10	0	14	62	12	5	2	0%	1.4	16.6%	7.3%	9.4%	3.6%	5.93	4.57	—
2024	31	AAA MLE	Norfolk Tides	10	0	14	62	12	5	2	0%	1.4	16.6%	7.3%	9.4%	3.6%	5.93	4.57	—
2024	31	AAA RAW	Norfolk Tides	10	0	14	62	12	5	2	0%	1.4	19.4%	8.1%	11.3%	3.2%	5.93	4.34	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			69	31	230	985	177	77	38	45%	3.3	18.0%	7.8%	10.2%	3.9%	4.96	4.71	-0.4
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	34	MLB	BAL	1	1	1	4	1	0	0	100%	1.0	21.5%	9.1%	12.4%	3.1%	4.40	4.51	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	35	MLB MLE	BAL	2	2	17	70	14	7	2	100%	8.3	20.5%	9.7%	10.9%	3.4%	4.67	4.85	+0.1
2028	35	MLB CTX	BAL	1	1	1	4	1	0	0	100%	1.0	20.5%	9.7%	10.9%	3.6%	4.75	4.93	+0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		69	31	231	989	178	77	38	45%	3.4	18.0%	7.8%	10.2%	3.9%	4.96	4.69	-0.4
/ 200 IP	—	RAW		60	27	200	855	154	67	33	45%	3.3	18.0%	7.8%	10.2%	3.9%	4.96	4.69	-0.3
Career	—	MLE		185	104	739	3162	547	222	95	56%	4.0	17.3%	7.0%	10.3%	3.0%	4.18	4.17	+1.9
/ 200 IP	—	MLE		50	28	200	856	148	60	26	56%	4.0	17.3%	7.0%	10.3%	3.0%	4.18	4.17	+1.6

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.

2024 AAANorfolk Tides · 14 IPFIP 4.26 → 4.57 (+0.31)K% 19.4% → 16.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.35%	—	×0.860	16.65%
BB% (unintentional) /BF	8.06%	—	×0.900	7.26%
HR / BF /BF	3.23%	÷0.996	×1.100	3.56%

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 99).

Result: FIP 4.26 → 4.57, 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 AAAMemphis Redbirds · 64 IPFIP 3.32 → 3.68 (+0.35)K% 24.5% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.47%	—	×0.860	21.04%
BB% (unintentional) /BF	8.87%	—	×0.900	7.98%
HR / BF /BF	2.13%	÷0.955	×1.100	2.45%

Result: FIP 3.32 → 3.68, 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).

2019 AAASacramento River Cats · 88 IPFIP 4.34 → 4.64 (+0.30)K% 14.4% → 12.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.43%	—	×0.880	12.70%
BB% (unintentional) /BF	7.34%	—	×1.050	7.71%
HR / BF /BF	2.78%	÷1.027	×1.100	2.98%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, 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 105).

Result: FIP 4.34 → 4.64, 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).

2018 AAASacramento River Cats · 17 IPFIP 2.39 → 2.70 (+0.32)K% 24.6% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.62%	—	×0.880	21.66%
BB% (unintentional) /BF	10.77%	—	×1.050	11.31%
HR / BF /BF	0.00%	÷0.998	×1.100	0.00%

Result: FIP 2.39 → 2.70, 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).

2018 A+San Jose Giants · 7 IPFIP 1.97 → 2.55 (+0.58)K% 23.3% → 18.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.33%	—	×0.770	17.97%
BB% (unintentional) /BF	6.67%	—	×1.150	7.67%
HR / BF /BF	0.00%	÷0.924	×1.250	0.00%

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 85).

Result: FIP 1.97 → 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).

2017 AAASacramento River Cats · 89 IPFIP 3.17 → 3.66 (+0.49)K% 20.9% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.94%	—	×0.880	18.43%
BB% (unintentional) /BF	6.54%	—	×1.050	6.87%
HR / BF /BF	1.83%	÷0.889	×1.100	2.27%

Result: FIP 3.17 → 3.66, 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).

2017 AARichmond Flying Squirrels · 67 IPFIP 2.71 → 3.33 (+0.62)K% 19.4% → 15.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.37%	—	×0.810	15.69%
BB% (unintentional) /BF	5.28%	—	×1.100	5.81%
HR / BF /BF	1.06%	÷0.848	×1.200	1.49%

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 70).

Result: FIP 2.71 → 3.33, 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).

2016 AARichmond Flying Squirrels · 114 IPFIP 3.41 → 4.05 (+0.65)K% 18.6% → 15.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.63%	—	×0.810	15.09%
BB% (unintentional) /BF	4.97%	—	×1.100	5.47%
HR / BF /BF	2.28%	÷0.978	×1.200	2.79%

Result: FIP 3.41 → 4.05, 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 Suárez (OGILVIE)	—	—	—	—	—	3.1%	—	4.85	20.5%	10.9%	17	+0.34	—	—	—
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	62
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	62
Hisanori Takahashi L 2010 · 3.50 FIP	35	SW	3.50	22.1%	7.0%	2.5%	.292	3.81	21.1%	15.0%	118	+0.31	3.50	240	60
Orlando Lara L 2019 · 4.09 FIP	34	SP	4.09	22.0%	7.8%	3.4%	.329	—	—	—	—	—	3.85	426	59
Daniel Rodriguez L 2019 · 4.77 FIP	34	SP	4.77	20.8%	7.8%	4.5%	.329	—	—	—	—	—	2.89	391	58
Chris Narveson L 2016 · 4.59 FIP	34	SP-	4.59	16.2%	8.5%	3.2%	.253	4.59	12.2%	1.8%	103	+0.00	4.00	625	57
Tsuyoshi Wada L 2015 · 3.66 FIP	34	SP	3.66	16.8%	7.1%	2.0%	.307	—	—	—	—	—	3.60	188	53
Luke Westphal L 2022 · 4.35 FIP	33	SW	4.35	24.2%	13.4%	2.9%	.302	5.19	15.7%	-0.7%	26	+0.84	2.97	294	51
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	50
Mauricio Lara L 2015 · 3.62 FIP	36	SP	3.62	13.9%	6.9%	1.5%	.310	3.69	12.1%	5.1%	220	+0.07	3.62	444	50
Arturo Lopez L 2017 · 4.34 FIP	34	SP	4.34	10.3%	5.4%	2.6%	.342	5.46	12.2%	5.4%	117	+1.12	4.34	445	45
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	45
Tomas Solis L 2017 · 5.48 FIP	34	SP	5.48	11.3%	7.9%	4.2%	.322	6.44	8.9%	1.4%	57	+0.96	4.20	327	42
Jorge Castillo L 2016 · 4.94 FIP	34	SP	4.94	13.0%	4.6%	4.3%	.246	4.93	16.8%	9.2%	179	-0.01	4.50	408	42
Alejandro Soto L 2019 · 4.03 FIP	33	SW	4.03	17.1%	6.9%	2.7%	.376	—	—	—	—	—	3.96	280	37
Jarrett Grube R 2016 · 4.74 FIP	34	SP-	4.74	18.9%	7.2%	4.2%	.280	4.41	15.8%	7.7%	134	-0.33	3.75	393	36
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	36
Francisley Bueno L 2015 · 3.77 FIP	34	SP	3.77	14.8%	7.1%	1.9%	.315	3.99	13.3%	6.6%	110	+0.22	2.43	188	34
Paolo Espino R 2021 · 4.32 FIP	34	SP-	4.32	20.2%	5.1%	4.2%	.277	4.81	16.6%	10.9%	260	+0.49	3.42	933	34
Albert Suárez R 2024 · 4.00 FIP	34	SP-	4.00	19.5%	6.8%	3.1%	.293	4.14	17.8%	10.6%	80	+0.14	3.58	616	30

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	1.3	51	18.2%	8.2%	1.47	4.93
Brad Lincoln ('14)	1.1	56	17.4%	7.9%	1.30	4.74
Mike Willis ('77-'81, 0 WAR*)	1.5	59	18.4%*	9.6%*	1.45*	4.77*
Buddy Carlyle ('15)	1.5	58	18.5%	8.5%	1.32	5.14
JC Ramírez ('19)	1.4	72	16.4%	8.4%	1.44	4.71
John Strohmayer ('70-'74, -1 WAR*)	1.6	78	19.6%*	9.2%*	1.42*	5.14*
John Boozer ('62-'69, -2 WAR*)	2.0	66	21.1%*	9.0%*	1.46*	5.15*