Luis Quiñones

P Wichita Wind Surge

Age 30 RHP 6'0" / 205 lbs AA

Overview

AAPROSPECT

MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	36	1	74	5.09	3.53	24.8%	14.6%	—	K 21.1% · BB 13.0% · FIP 3.69
2025	28	ROKTOR	3	2	3	8.10	5.20	42.9%	14.3%	—	K 42.9% · BB 14.3% · FIP 5.21
2026	29	MIX2 levels	18	1	21	3.43	3.86	38.5%	22.0%	—	K 30.7% · BB 24.0% · FIP 5.06
2027PROJ	30	MLBMIN	—	—	0	5.06	5.06	25.3%	17.1%	—
2028PROJ31% MLB	31	MLBMIN	5	0	5	5.10	5.18	24.7%	16.6%	-0.0

Next 2 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 -0.1 / P90 0.0, comp-based) · star 0% · didn't stick 100%

CompsCody Hall (age 30) · Jared Mortensen (age 28) · Jim Miller (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 129121vR 113

ERA5.06

FIP5.06

K%25.3%

BB%17.1%

K-BB%8.2%

Proj IP16

Value2027 · WAR

Runs saved vs league avg · 16 IP

Grades · Contract

Scouting Grades

K†6060

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)
2021	24	MIX MLE	2 levels	17	17	75	341	115	65	6	100%	4.4	26.6%	21.5%	5.0%	2.3%	4.06	4.82	—
2021	24	MIX RAW	2 levels	17	17	75	341	115	65	6	100%	4.4	33.7%	19.1%	14.7%	1.8%	4.06	3.67	—
2022	25	MIX MLE	2 levels	21	17	78	341	105	54	7	81%	3.7	23.5%	17.5%	6.0%	2.6%	5.21	4.77	—
2022	25	MIX RAW	2 levels	21	17	78	341	105	54	7	81%	3.7	30.8%	15.8%	15.0%	2.1%	5.21	3.65	—
2023	26	MIX MLE	2 levels	31	13	93	395	110	39	19	42%	3.0	23.5%	10.4%	13.1%	6.0%	5.30	5.75	—
2023	26	MIX RAW	2 levels	31	13	93	395	110	39	19	42%	3.0	27.8%	9.9%	18.0%	4.8%	5.30	4.64	—
2024	27	MIX MLE	2 levels	36	1	74	343	85	50	4	3%	2.1	21.1%	13.0%	8.0%	1.3%	5.09	3.69	—
2024	27	MIX MLE	2 levels	36	1	74	343	85	50	4	3%	2.1	21.1%	13.0%	8.0%	1.3%	5.09	3.69	—
2024	27	MIX RAW	2 levels	36	1	74	343	85	50	4	3%	2.1	24.8%	14.6%	10.2%	1.2%	5.09	3.53	—
2025	28	ROK MLE	FCL Blue Jays	3	2	3	14	6	2	1	67%	1.1	42.9%	14.3%	28.6%	7.1%	8.10	5.21	—
2025	28	ROK MLE	FCL Blue Jays	3	2	3	14	6	2	1	67%	1.1	42.9%	14.3%	28.6%	7.1%	8.10	5.21	—
2025	28	ROK RAW	FCL Blue Jays	3	2	3	14	6	2	1	67%	1.1	42.9%	14.3%	28.6%	7.1%	8.10	5.20	—
2026	29	MIX MLE	2 levels	18	1	21	91	35	20	2	6%	1.2	30.7%	24.0%	6.7%	2.8%	3.43	5.06	—
2026	29	MIX MLE	2 levels	18	1	21	91	35	20	2	6%	1.2	30.7%	24.0%	6.7%	2.8%	3.43	5.06	—
2026	29	MIX RAW	2 levels	18	1	21	91	35	20	2	6%	1.2	38.5%	22.0%	16.5%	2.2%	3.43	3.86	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	MIN	—	—	0	—	—	—	—	—	—	25.3%	17.1%	8.2%	2.8%	5.06	5.06	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	MIN	16	0	16	69	17	12	2	0%	1.0	24.7%	16.6%	8.0%	3.1%	5.10	5.18	-0.1
2028	31	MLB CTX	MIN	5	0	5	21	5	4	1	0%	1.0	24.7%	16.6%	8.0%	3.1%	5.10	5.18	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		5	0	5	22	5	4	1	0%	1.0	24.7%	16.6%	8.0%	3.1%	5.10	4.80	-0.0
/ 200 IP	—	RAW		190	0	200	844	195	156	39	0%	1.1	24.7%	16.6%	8.0%	3.1%	5.10	4.80	-0.6
Career	—	MLE		126	51	345	1525	370	243	48	40%	2.7	24.2%	15.9%	8.3%	3.2%	4.88	4.81	-0.1
/ 200 IP	—	MLE		73	30	200	884	214	141	28	40%	2.7	24.2%	15.9%	8.3%	3.2%	4.88	4.81	-1.5

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 AAWichita Wind Surge · 20 IPFIP 3.93 → 5.06 (+1.14)K% 37.9% → 30.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.93%	—	×0.810	30.72%
BB% (unintentional) /BF	21.84%	—	×1.100	24.02%
HR / BF /BF	2.30%	÷1.000	×1.200	2.76%

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 3.93 → 5.06, 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 · 73 IPFIP 3.51 → 3.69 (+0.18)K% 24.5% → 21.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.48%	—	×0.860	21.06%
BB% (unintentional) /BF	14.45%	—	×0.900	13.01%
HR / BF /BF	1.18%	÷0.990	×1.100	1.31%

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 98).

Result: FIP 3.51 → 3.69, 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 · 86 IPFIP 4.61 → 5.75 (+1.14)K% 29.1% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.05%	—	×0.810	23.53%
BB% (unintentional) /BF	9.50%	—	×1.100	10.45%
HR / BF /BF	5.03%	÷1.000	×1.200	6.03%

Result: FIP 4.61 → 5.75, 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).

2023 AAABuffalo Bisons · 7 IPFIP 4.93 → 5.24 (+0.32)K% 16.2% → 13.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.22%	—	×0.860	13.95%
BB% (unintentional) /BF	13.51%	—	×0.900	12.16%
HR / BF /BF	2.70%	÷0.916	×1.100	3.24%

Result: FIP 4.93 → 5.24, 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 AANew Hampshire Fisher Cats · 71 IPFIP 3.89 → 4.77 (+0.87)K% 29.0% → 23.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.98%	—	×0.810	23.47%
BB% (unintentional) /BF	15.92%	—	×1.100	17.52%
HR / BF /BF	2.23%	÷1.027	×1.200	2.61%

Result: FIP 3.89 → 4.77, 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 ADunedin Blue Jays · 7 IPFIP 0.60 → 2.07 (+1.48)K% 51.9% → 38.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	51.85%	—	×0.740	38.37%
BB% (unintentional) /BF	14.81%	—	×1.180	17.48%
HR / BF /BF	0.00%	÷0.916	×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 83).

Result: FIP 0.60 → 2.07, 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).

2021 A+Vancouver Canadians · 39 IPFIP 3.45 → 4.79 (+1.34)K% 35.8% → 27.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.75%	—	×0.770	27.53%
BB% (unintentional) /BF	21.79%	—	×1.150	25.06%
HR / BF /BF	1.12%	÷0.909	×1.250	1.54%

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 82).

Result: FIP 3.45 → 4.79, 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).

2021 AANew Hampshire Fisher Cats · 36 IPFIP 3.83 → 4.85 (+1.02)K% 31.5% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	31.48%	—	×0.810	25.50%
BB% (unintentional) /BF	16.05%	—	×1.100	17.65%
HR / BF /BF	2.47%	÷0.973	×1.200	3.04%

Result: FIP 3.83 → 4.85, 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
Luis Quiñones (OGILVIE)	—	—	5.06	25.3%	17.1%	2.8%	—	5.18	24.7%	8.0%	16	+0.12	—	—	—
Cody Hall R 2018 · 3.92 FIP	30	SU	3.92	25.9%	17.5%	1.5%	.244	—	—	—	—	—	3.51	134	65
Jared Mortensen R 2016 · 4.99 FIP	28	SU	4.99	20.9%	18.8%	2.3%	.250	—	—	—	—	—	4.42	200	60
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	60
Guillermo Moscoso R 2013 · 5.15 FIP	29	SU	5.15	24.2%	14.1%	4.2%	.203	—	—	—	—	—	3.56	486	60
Derek Eitel R 2017 · 4.72 FIP	29	SP-	4.72	17.2%	16.0%	1.9%	.273	—	—	—	—	—	3.96	138	59
Edgar Alberto Garcia R 2017 · 4.01 FIP	29	SP-	4.01	17.3%	10.9%	1.8%	.305	—	—	—	—	—	4.01	272	58
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	58
Hector Velázquez R 2019 · 4.82 FIP	30	SW	4.82	19.6%	12.3%	3.3%	.292	3.81	19.2%	10.9%	25	-1.01	2.75	536	58
Edwar Ramirez R 2010 · 4.76 FIP	29	SU	4.76	18.5%	16.7%	2.0%	.235	—	—	—	—	—	3.66	109	57
Javy Guerra R 2016 · 4.29 FIP	30	SU	4.29	21.3%	13.9%	2.3%	.303	3.95	19.5%	13.0%	193	-0.34	2.94	409	56
Jon Duplantier R 2024 · 3.94 FIP	30	SW	3.94	24.0%	15.5%	1.6%	.331	—	—	—	—	—	3.10	435	56
Bryan Mitchell R 2021 · 4.29 FIP	30	SU	4.29	20.6%	12.0%	2.5%	.305	5.07	14.4%	3.9%	39	+0.78	2.72	481	56
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	55
Jordan Jankowski R 2018 · 4.76 FIP	29	SU	4.76	21.8%	16.9%	2.5%	.396	—	—	—	—	—	2.57	196	55
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	55
Deck McGuire R 2018 · 5.28 FIP	29	SW	5.28	18.4%	13.2%	3.8%	.262	—	—	—	—	—	3.41	622	55
Aldo Montes R 2019 · 4.69 FIP	29	SW	4.69	18.2%	10.6%	3.3%	.336	—	—	—	—	—	4.69	210	55
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	55
Mitchell Osnowitz R 2021 · 5.48 FIP	30	SU	5.48	19.6%	19.2%	2.9%	.337	—	—	—	—	—	4.54	132	54
Wil Browning R 2017 · 4.44 FIP	28	SU	4.44	17.9%	13.1%	2.2%	.359	—	—	—	—	—	2.14	162	54