Pablo López

P Minnesota Twins

Age 31 RHP 6'4" / 225 lbs MLB Svc 8.0 · Ctrl thru 2027 peak 1.5 · 2028 ILInjured 60-Day (D60)

Overview

MLBSPIL-6040-MANExtFA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	27	MLBMIN	32	32	194	3.66	3.02	29.2%	5.9%	5.8
2024	28	MLBMIN	32	32	185	4.08	3.45	25.6%	5.3%	4.4
2025	29	MIX2 levels	18	18	92	2.75	2.97	24.1%	5.8%	2.8	K 23.5% · BB 5.8% · FIP 2.98
2026	30	No MLB games played
2027PROJ	31	MLBMIN	10	10	58	3.68	3.68	24.6%	5.9%	1.2
2028PROJ	32	MLBMIN	15	15	89	3.84	3.94	23.8%	6.3%	1.6
2029PROJ	33	MLBMIN	13	13	77	4.07	4.22	22.9%	6.8%	1.1

Last 3 seasons WAR 13.0 · Next 3 projected WAR 3.9Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service8.541First FA2028

2027Ext$18M

Skills · percentileStatcast 2025

K%57

xwOBA vs53

FB Velo50

CompsTim Adleman (age 31) · Matt Shoemaker (age 31) · Stan Spencer (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 10395vR 87

ERA3.68

FIP3.68

K%24.6%

BB%5.9%

K-BB%18.6%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5094.5

Whiff%

p5425.9%

p5723.4%

xwOBA vs

p530.309

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

Status FA

MLB Debut 2018

Service 8.541 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$18M	+1.2	$10M	-$9M
Totals		$18M		$10M	-$9M

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	19	ROK MLE	AZL Mariners	12	3	37	162	26	6	1	25%	3.1	10.9%	4.6%	6.3%	0.9%	3.13	3.24	—
2015	19	ROK RAW	AZL Mariners	12	3	37	162	26	6	1	25%	3.1	16.0%	3.7%	12.3%	0.6%	3.13	2.54	—
2016	20	A MLE	Clinton LumberKings	17	13	84	324	56	9	4	76%	5.0	12.8%	3.3%	9.5%	1.6%	2.13	3.34	—
2016	20	A RAW	Clinton LumberKings	17	13	84	324	56	9	4	76%	5.0	17.3%	2.8%	14.5%	1.2%	2.13	2.71	—
2017	21	A+ MLE	Jupiter Hammerheads	27	24	145	605	121	20	6	89%	5.4	15.4%	3.8%	11.6%	1.3%	4.15	3.00	—
2017	21	A+ RAW	Jupiter Hammerheads	27	24	145	605	121	20	6	89%	5.4	20.0%	3.3%	16.7%	1.0%	4.15	2.38	—
2018	22	MIX MLE	3 levels	22	22	121	500	112	25	14	100%	5.5	20.1%	5.2%	14.9%	3.1%	2.75	3.75	+2.4
2018	22	MIX RAW	3 levels	22	22	121	500	112	25	14	100%	5.5	22.4%	5.0%	17.4%	2.8%	2.75	3.37	+3.0
2019	23	MIX MLE	3 levels	26	26	126	541	111	30	18	100%	4.8	20.3%	5.1%	15.1%	3.4%	5.51	3.89	+2.3
2019	23	MIX RAW	3 levels	26	26	126	541	111	30	18	100%	4.8	20.5%	5.5%	15.0%	3.3%	5.51	3.91	+2.2
2020	24	MLB MLE	Miami Marlins	11	11	57	240	59	17	4	100%	5.2	24.6%	7.1%	17.5%	1.8%	3.61	2.88	+1.8
2020	24	MLB RAW	Miami Marlins	11	11	57	240	59	17	4	100%	5.2	24.6%	7.1%	17.5%	1.7%	3.61	2.84	+1.8
2021	25	MIX MLE	2 levels	22	22	108	434	120	25	11	100%	4.9	27.5%	6.0%	21.5%	2.8%	2.93	3.05	+3.1
2021	25	MIX RAW	2 levels	22	22	108	434	120	25	11	100%	4.9	27.6%	5.8%	21.9%	2.5%	2.93	2.90	+3.4
2022	26	MLB MLE	Miami Marlins	32	32	180	736	174	52	21	100%	5.6	23.6%	7.1%	16.6%	3.0%	3.75	3.65	+3.8
2022	26	MLB RAW	Miami Marlins	32	32	180	736	174	52	21	100%	5.6	23.6%	7.1%	16.6%	2.9%	3.75	3.55	+4.1
2023	27	MLB MLE	Minnesota Twins	32	32	194	801	234	47	24	100%	6.1	29.2%	5.9%	23.3%	3.0%	3.66	3.01	+5.8
2023	27	MLB RAW	Minnesota Twins	32	32	194	801	234	47	24	100%	6.1	29.2%	5.9%	23.3%	3.0%	3.66	3.02	+5.8
2024	28	MLB MLE	Minnesota Twins	32	32	185	772	198	41	26	100%	5.8	25.6%	5.3%	20.3%	3.4%	4.08	3.45	+4.4
2024	28	MLB MLE	Minnesota Twins	32	32	185	772	198	41	26	100%	5.8	25.6%	5.3%	20.3%	3.4%	4.08	3.45	+4.4
2024	28	MLB RAW	Minnesota Twins	32	32	185	772	198	41	26	100%	5.8	25.6%	5.3%	20.3%	3.4%	4.08	3.45	+4.4
2025	29	MIX MLE	2 levels	18	18	92	377	91	22	8	100%	5.1	23.5%	5.8%	17.7%	2.0%	2.75	2.98	+2.8
2025	29	MIX MLE	2 levels	18	18	92	377	91	22	8	100%	5.1	23.5%	5.8%	17.7%	2.0%	2.75	2.98	+2.8
2025	29	MIX RAW	2 levels	18	18	92	377	91	22	8	100%	5.1	24.1%	5.8%	18.3%	2.1%	2.75	2.97	+2.8
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			172	172	965	3995	994	239	115	100%	5.6	24.9%	6.0%	18.9%	2.9%	3.81	3.33	+24.6
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	MIN	10	10	58	245	60	15	7	100%	5.8	24.6%	5.9%	18.6%	2.8%	3.68	3.68	+1.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	MIN	15	15	89	375	89	24	11	100%	5.9	23.8%	6.3%	17.4%	3.0%	3.83	3.93	+1.6
2029	33	MLB MLE	MIN	13	13	77	323	74	22	11	100%	5.9	22.9%	6.8%	16.1%	3.3%	4.06	4.21	+1.1
2030	34	MLB MLE	MIN	12	12	74	311	75	20	11	100%	6.1	24.0%	6.5%	17.5%	3.6%	4.17	4.25	+1.0
2031	35	MLB MLE	MIN	9	9	57	240	55	17	9	100%	6.3	23.1%	7.0%	16.0%	3.9%	4.42	4.58	+0.5
2028	32	MLB CTX	MIN	15	15	89	376	89	24	11	100%	5.9	23.8%	6.3%	17.4%	3.0%	3.84	3.94	+1.6
2029	33	MLB CTX	MIN	13	13	77	325	74	22	11	100%	5.9	22.9%	6.8%	16.1%	3.3%	4.07	4.22	+1.1
2030	34	MLB CTX	MIN	12	12	74	312	75	20	11	100%	6.2	24.0%	6.5%	17.5%	3.6%	4.18	4.26	+1.0
2031	35	MLB CTX	MIN	10	10	57	241	55	17	10	100%	5.7	23.1%	7.0%	16.0%	4.0%	4.43	4.59	+0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		221	221	1261	5244	1287	322	158	100%	5.7	24.5%	6.1%	18.4%	3.0%	3.88	3.46	+30.0
/ 200 IP	—	RAW		35	35	200	832	204	51	25	100%	5.7	24.5%	6.1%	18.4%	3.0%	3.88	3.46	+4.8
Career	—	MLE		251	235	1330	5492	1235	300	144	94%	5.3	22.5%	5.5%	17.0%	2.6%	3.64	3.33	+28.6
/ 200 IP	—	MLE		38	35	200	826	186	45	22	94%	5.3	22.5%	5.5%	17.0%	2.6%	3.64	3.33	+4.5

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.

2025 AAASt. Paul Saints · 16 IPFIP 2.84 → 2.92 (+0.08)K% 27.7% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.69%	—	×0.860	23.82%
BB% (unintentional) /BF	3.08%	—	×0.900	2.77%
HR / BF /BF	3.08%	÷1.253	×1.100	2.70%

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 151).

Result: FIP 2.84 → 2.92, 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 AAANew Orleans Baby Cakes · 9 IPFIP 1.91 → 2.22 (+0.31)K% 25.6% → 22.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.64%	—	×0.880	22.56%
BB% (unintentional) /BF	7.69%	—	×1.050	8.08%
HR / BF /BF	0.00%	÷1.100	×1.100	0.00%

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 120).

Result: FIP 1.91 → 2.22, 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 AAJacksonville Jumbo Shrimp · 5 IPFIP 7.71 → 9.64 (+1.94)K% 18.2% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.18%	—	×0.810	14.73%
BB% (unintentional) /BF	9.09%	—	×1.100	10.00%
HR / BF /BF	9.09%	÷0.918	×1.200	11.88%

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 84).

Result: FIP 7.71 → 9.64, 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 AAJacksonville Jumbo Shrimp · 44 IPFIP 2.15 → 2.82 (+0.68)K% 29.5% → 23.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.48%	—	×0.810	23.88%
BB% (unintentional) /BF	4.62%	—	×1.100	5.09%
HR / BF /BF	1.73%	÷1.041	×1.200	2.00%

Result: FIP 2.15 → 2.82, 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).

2018 AAANew Orleans Baby Cakes · 19 IPFIP 4.21 → 4.75 (+0.54)K% 18.8% → 16.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.75%	—	×0.880	16.50%
BB% (unintentional) /BF	5.00%	—	×1.050	5.25%
HR / BF /BF	3.75%	÷0.952	×1.100	4.33%

Result: FIP 4.21 → 4.75, 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).

2017 A+Jupiter Hammerheads · 145 IPFIP 2.37 → 3.00 (+0.63)K% 20.0% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.770	15.40%
BB% (unintentional) /BF	3.31%	—	×1.150	3.80%
HR / BF /BF	0.99%	÷0.944	×1.250	1.31%

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 89).

Result: FIP 2.37 → 3.00, 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).

2016 AClinton LumberKings · 84 IPFIP 2.67 → 3.34 (+0.67)K% 17.3% → 12.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.28%	—	×0.740	12.79%
BB% (unintentional) /BF	2.78%	—	×1.180	3.28%
HR / BF /BF	1.23%	÷0.976	×1.300	1.64%

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 2.67 → 3.34, 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).

2015 ROKAZL Mariners · 37 IPFIP 2.55 → 3.24 (+0.69)K% 16.0% → 10.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.05%	—	×0.680	10.91%
BB% (unintentional) /BF	3.70%	—	×1.250	4.63%
HR / BF /BF	0.62%	÷1.000	×1.400	0.86%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. 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 2.55 → 3.24, 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).

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
Pablo López (OGILVIE)	—	—	—	—	—	2.8%	—	4.12	23.6%	17.0%	239	+0.44	—	—	—
Tim Adleman R 2019 · 4.30 FIP	31	SP	4.30	22.8%	7.8%	3.9%	.266	4.71	18.5%	11.1%	90	+0.41	3.63	605	66
Matt Shoemaker R 2018 · 3.17 FIP	31	SP	3.17	25.4%	7.7%	2.3%	.310	4.87	19.3%	11.5%	188	+1.70	3.12	728	63
Stan Spencer R 2000 · 4.42 FIP	30	SP	4.42	19.2%	8.7%	3.4%	.259	—	—	—	—	—	3.61	119	62
Jose Oyervides R 2015 · 3.01 FIP	33	SP	3.01	19.1%	6.2%	1.4%	.333	4.09	21.9%	14.5%	184	+1.08	3.01	407	61
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	61
Hideki Irabu R 2000 · 4.38 FIP	31	SP	4.38	17.0%	5.7%	3.6%	.374	5.19	17.2%	11.0%	64	+0.81	3.78	514	61
Merrill Kelly R 2020 · 3.87 FIP	31	SP	3.87	23.2%	3.2%	4.2%	.241	3.79	22.6%	15.0%	536	-0.08	3.60	1,170	60
Jarrett Grube R 2015 · 3.75 FIP	33	SP	3.75	18.7%	4.2%	3.1%	.285	4.57	17.3%	9.6%	253	+0.82	3.75	393	58
Jose Samayoa R 2019 · 4.05 FIP	29	SP	4.05	19.4%	7.0%	3.1%	.314	—	—	—	—	—	3.44	262	58
Yu Darvish R 2018 · 4.50 FIP	31	SP	4.50	27.2%	11.7%	4.0%	.282	3.48	30.5%	24.0%	421	-1.02	1.97	1,798	56
Colin Rea R 2021 · 2.57 FIP	31	SP	2.57	21.7%	3.0%	1.7%	.307	4.32	20.2%	14.0%	310	+1.75	2.57	1,116	56
Bryan Evans R 2018 · 4.87 FIP	31	SP	4.87	18.7%	4.7%	5.0%	.294	3.89	18.7%	8.3%	25	-0.98	3.89	231	55
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	55
Tyler Herron R 2017 · 4.02 FIP	30	SP	4.02	16.4%	8.7%	2.2%	.377	—	—	—	—	—	4.02	117	55
Leo Medrano R 2015 · 3.76 FIP	32	SP	3.76	14.2%	3.9%	2.5%	.354	4.34	11.0%	3.7%	113	+0.58	3.76	222	54
Manuel Flores R 2017 · 3.46 FIP	31	SP	3.46	15.8%	4.7%	2.0%	.305	4.32	17.1%	9.7%	122	+0.86	3.46	515	54
Kevin Herget R 2022 · 3.72 FIP	31	SP-	3.72	21.5%	4.4%	3.4%	.332	3.83	20.9%	14.4%	179	+0.11	2.16	726	54
Chase Anderson R 2019 · 4.39 FIP	31	SP	4.39	20.9%	8.1%	3.7%	.259	5.39	19.2%	10.0%	218	+1.00	3.30	1,260	54
Jeremy Hefner R 2016 · 4.64 FIP	30	SP	4.64	16.8%	9.1%	3.3%	.305	—	—	—	—	—	3.56	322	53
Brad Peacock R 2019 · 4.22 FIP	31	SP-	4.22	25.1%	8.1%	4.0%	.261	4.15	22.8%	12.5%	96	-0.07	2.97	748	53

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	6.6	102	24.5%	6.3%	1.16	3.87
Rick Aguilera ('85-'00, 22 WAR*)	6.5	81	24.3%*	6.1%*	1.18*	3.65*
Collin McHugh ('23)	5.0	90	23.3%	6.7%	0.96	3.72
Alejandro Peña ('81-'96, 15 WAR*)	5.3	81	24.7%*	7.5%*	0.96*	3.61*
Scott Bankhead ('86-'95, 10 WAR*)	4.5	100	21.2%*	7.3%*	1.36*	4.16*
Alex Wood ('24)	6.3	114	22.1%	7.1%	0.91	3.78
Ross Stripling ('24)	4.2	94	20.9%	5.6%	1.32	4.17