Framber Valdez

P Detroit Tigers

Age 33 LHP 5'11" / 230 lbs MLB Svc 7.0 · Ctrl thru 2026 peak 2.0 · 2027

Overview

MLBSP40-MANFA 2027

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	30	MLBHOU	28	28	176	2.91	3.08	24.0%	7.8%	5.2
2025	31	MLBHOU	31	31	192	3.66	3.23	23.3%	8.5%	5.2
2026	32	MLBDET	31	31	174	4.03	3.90	17.8%	8.8%	3.1
2027PROJ	33	MLBDET	19	19	122	3.95	4.07	20.6%	8.6%	1.9
2028PROJ	34	MLBDET	13	13	85	4.14	4.31	19.7%	9.1%	1.0
2029PROJ	35	MLBDET	9	9	56	4.44	4.64	18.7%	9.7%	0.4

Last 3 seasons WAR 13.5 · Next 3 projected WAR 3.4Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2026Service7.948First FA2027

Skills · percentileStatcast 2026

FB Velo52

xwOBA vs42

K%20

Form2.45 ERA (proj 3.95) · K 20.2% (proj 20.6%) · BB 9.2% (proj 8.6%) · last 60d · 29 IP through Oct 27

CompsYusei Kikuchi (age 33) · Mark Hendrickson (age 33) · Jorge Castillo (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 95103vR 111

ERA3.95

FIP4.07

K%20.6%

BB%8.6%

K-BB%11.9%

Proj IP122

Value2027 · WAR

Runs saved vs league avg · 122 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5294.7

Whiff%

p1720.6%

p2017.8%

xwOBA vs

p420.321

Contract CONFIRMED · hand-curated extension

Status FA

MLB Debut 2018

Service 7.948 yrs.days

Team Control Through 2026

First FA Year 2027

Year	Status	Salary	Proj WAR	Value	Surplus
Totals		$0.0M		$0.0M	+$0.0M

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	21	ROK MLE	DSL Astros Blue	16	0	37	161	36	17	1	0%	2.3	15.2%	13.2%	2.0%	0.9%	3.68	3.97	—
2015	21	ROK RAW	DSL Astros Blue	16	0	37	161	36	17	1	0%	2.3	22.4%	10.6%	11.8%	0.6%	3.68	2.88	—
2016	22	MIX MLE	3 levels	9	9	52	212	51	16	1	100%	5.7	18.1%	9.1%	9.0%	1.0%	2.96	3.27	—
2016	22	MIX RAW	3 levels	9	9	52	212	51	16	1	100%	5.7	24.1%	7.5%	16.5%	0.5%	2.96	2.31	—
2017	23	MIX MLE	2 levels	25	18	110	484	126	52	7	72%	4.4	20.5%	12.1%	8.4%	1.7%	4.16	3.85	—
2017	23	MIX RAW	2 levels	25	18	110	484	126	52	7	72%	4.4	26.0%	10.7%	15.3%	1.4%	4.16	3.05	—
2018	24	MIX MLE	3 levels	30	19	140	584	163	56	10	63%	4.7	23.9%	10.2%	13.7%	2.0%	3.60	3.47	+3.3
2018	24	MIX RAW	3 levels	30	19	140	584	163	56	10	63%	4.7	27.9%	9.6%	18.3%	1.7%	3.60	2.90	+4.4
2019	25	MIX MLE	2 levels	36	15	115	509	137	61	12	42%	3.2	25.3%	12.2%	13.1%	2.5%	4.85	3.88	+0.9
2019	25	MIX RAW	2 levels	36	15	115	509	137	61	12	42%	3.2	26.9%	12.0%	14.9%	2.4%	4.85	3.67	+1.2
2020	26	MLB MLE	Houston Astros	11	10	71	288	76	16	5	91%	6.4	26.4%	5.6%	20.8%	1.8%	3.57	2.56	+2.6
2020	26	MLB RAW	Houston Astros	11	10	71	288	76	16	5	91%	6.4	26.4%	5.6%	20.8%	1.7%	3.57	2.55	+2.6
2021	27	MIX MLE	2 levels	24	24	142	605	130	59	12	100%	5.9	21.9%	10.0%	11.9%	2.2%	3.05	3.70	+2.9
2021	27	MIX RAW	2 levels	24	24	142	605	130	59	12	100%	5.9	21.5%	9.8%	11.7%	2.0%	3.05	3.62	+3.1
2022	28	MLB MLE	Houston Astros	31	31	201	827	194	67	11	100%	6.5	23.5%	8.1%	15.4%	1.4%	2.82	2.90	+6.4
2022	28	MLB RAW	Houston Astros	31	31	201	827	194	67	11	100%	6.5	23.5%	8.1%	15.4%	1.3%	2.82	2.88	+6.5
2023	29	MLB MLE	Houston Astros	31	31	198	808	200	57	19	100%	6.4	24.8%	7.1%	17.7%	2.4%	3.45	3.23	+5.4
2023	29	MLB RAW	Houston Astros	31	31	198	808	200	57	19	100%	6.4	24.8%	7.1%	17.7%	2.4%	3.45	3.19	+5.5
2024	30	MLB MLE	Houston Astros	28	28	176	703	169	55	13	100%	6.3	24.0%	7.8%	16.2%	1.9%	2.91	3.10	+5.1
2024	30	MLB MLE	Houston Astros	28	28	176	703	169	55	13	100%	6.3	24.0%	7.8%	16.2%	1.9%	2.91	3.10	+5.1
2024	30	MLB RAW	Houston Astros	28	28	176	703	169	55	13	100%	6.3	24.0%	7.8%	16.2%	1.8%	2.91	3.08	+5.2
2025	31	MLB MLE	Houston Astros	31	31	192	802	187	68	15	100%	6.2	23.3%	8.5%	14.8%	1.9%	3.66	3.26	+5.1
2025	31	MLB MLE	Houston Astros	31	31	192	802	187	68	15	100%	6.2	23.3%	8.5%	14.8%	1.9%	3.66	3.26	+5.1
2025	31	MLB RAW	Houston Astros	31	31	192	802	187	68	15	100%	6.2	23.3%	8.5%	14.8%	1.9%	3.66	3.23	+5.2
2026	32	MLB MLE	Detroit Tigers	31	31	174	758	135	67	16	100%	5.6	17.8%	8.8%	9.0%	2.2%	4.03	3.93	+3.1
2026	32	MLB MLE	Detroit Tigers	31	31	174	758	135	67	16	100%	5.6	17.8%	8.8%	9.0%	2.2%	4.03	3.93	+3.1
2026	32	MLB RAW	Detroit Tigers	31	31	174	758	135	67	16	100%	5.6	17.8%	8.8%	9.0%	2.1%	4.03	3.90	+3.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			219	197	1255	5241	1188	455	103	90%	5.7	22.7%	8.7%	14.0%	2.0%	3.46	3.36	+31.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	DET	19	19	122	515	106	45	12	100%	6.4	20.6%	8.6%	11.9%	2.2%	3.95	4.07	+1.9
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	DET	13	13	85	360	71	33	9	100%	6.6	19.7%	9.1%	10.5%	2.5%	4.20	4.37	+1.0
2029	35	MLB MLE	DET	9	9	56	234	44	23	7	100%	6.2	18.7%	9.7%	9.0%	2.9%	4.51	4.71	+0.4
2030	36	MLB MLE	DET	5	5	33	139	25	14	5	100%	6.6	17.7%	10.3%	7.4%	3.3%	4.85	5.08	+0.1
2028	34	MLB CTX	DET	13	13	85	359	71	33	9	100%	6.5	19.7%	9.1%	10.5%	2.4%	4.14	4.31	+1.0
2029	35	MLB CTX	DET	9	9	56	236	44	23	7	100%	6.2	18.7%	9.7%	9.0%	2.8%	4.44	4.64	+0.4
2030	36	MLB CTX	DET	5	5	33	139	25	14	4	100%	6.6	17.7%	10.3%	7.4%	3.1%	4.77	5.00	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		246	224	1428	5974	1327	525	123	91%	5.8	22.2%	8.8%	13.4%	2.1%	3.57	3.46	+33.9
/ 200 IP	—	RAW		34	31	200	837	186	74	17	91%	5.8	22.2%	8.8%	13.4%	2.1%	3.57	3.46	+4.7
Career	—	MLE		303	247	1608	6741	1524	611	131	82%	5.3	22.6%	9.1%	13.5%	1.9%	3.52	3.40	+32.8
/ 200 IP	—	MLE		38	31	200	839	190	76	16	82%	5.3	22.6%	9.1%	13.5%	1.9%	3.52	3.40	+4.6

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.

2021 AAASugar Land Skeeters · 7 IPFIP 2.59 → 2.78 (+0.19)K% 15.2% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.15%	—	×0.880	13.33%
BB% (unintentional) /BF	6.06%	—	×1.050	6.36%
HR / BF /BF	0.00%	÷0.935	×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 87).

Result: FIP 2.59 → 2.78, 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 AAARound Rock Express · 44 IPFIP 1.97 → 2.57 (+0.59)K% 38.3% → 33.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.33%	—	×0.880	33.73%
BB% (unintentional) /BF	9.44%	—	×1.050	9.92%
HR / BF /BF	1.67%	÷0.948	×1.100	1.93%

Result: FIP 1.97 → 2.57, 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).

2018 AACorpus Christi Hooks · 94 IPFIP 2.44 → 3.15 (+0.71)K% 30.5% → 24.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.46%	—	×0.810	24.67%
BB% (unintentional) /BF	7.36%	—	×1.100	8.10%
HR / BF /BF	1.78%	÷1.059	×1.200	2.01%

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 112).

Result: FIP 2.44 → 3.15, 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 AAAFresno Grizzlies · 9 IPFIP 2.04 → 2.35 (+0.31)K% 25.0% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.880	22.00%
BB% (unintentional) /BF	8.33%	—	×1.050	8.75%
HR / BF /BF	0.00%	÷0.951	×1.100	0.00%

Result: FIP 2.04 → 2.35, 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+Buies Creek Astros · 61 IPFIP 2.77 → 3.70 (+0.92)K% 28.5% → 22.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.52%	—	×0.770	21.96%
BB% (unintentional) /BF	11.33%	—	×1.150	13.03%
HR / BF /BF	1.17%	÷1.006	×1.250	1.46%

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 101).

Result: FIP 2.77 → 3.70, 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).

2017 AACorpus Christi Hooks · 49 IPFIP 3.38 → 4.03 (+0.65)K% 23.2% → 18.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.25%	—	×0.810	18.83%
BB% (unintentional) /BF	10.09%	—	×1.100	11.10%
HR / BF /BF	1.75%	÷1.035	×1.200	2.03%

Result: FIP 3.38 → 4.03, 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).

2016 AQuad Cities River Bandits · 35 IPFIP 2.39 → 3.27 (+0.88)K% 24.5% → 18.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.48%	—	×0.740	18.11%
BB% (unintentional) /BF	7.69%	—	×1.180	9.08%
HR / BF /BF	0.70%	÷0.911	×1.300	1.00%

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 82).

Result: FIP 2.39 → 3.27, 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 ROKGreeneville Astros · 11 IPFIP 1.04 → 2.20 (+1.16)K% 34.9% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.88%	—	×0.680	23.72%
BB% (unintentional) /BF	6.98%	—	×1.250	8.72%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

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 1.04 → 2.20, 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
Framber Valdez (OGILVIE)	—	—	—	—	—	2.2%	—	4.61	19.0%	9.5%	174	+0.54	—	—	—
Yusei Kikuchi L 2024 · 3.41 FIP	33	SP	3.41	28.0%	6.0%	3.5%	.308	3.93	22.4%	13.1%	246	+0.52	3.23	1,056	62
Mark Hendrickson L 2007 · 3.78 FIP	33	SW	3.78	17.3%	4.7%	2.8%	.318	4.32	14.2%	8.0%	314	+0.54	3.04	1,169	39
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	33
Miguel González R 2017 · 4.54 FIP	33	SP	4.54	14.6%	7.7%	3.1%	.285	6.88	7.6%	-1.5%	12	+2.34	3.72	905	33
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	33
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	33
Roy Merritt L 2017 · 3.95 FIP	31	SP	3.95	16.2%	5.8%	2.7%	.339	—	—	—	—	—	3.93	129	31
Daniel Rodriguez L 2017 · 3.87 FIP	32	SP	3.87	13.1%	9.7%	1.2%	.335	4.77	20.8%	13.0%	112	+0.90	2.89	391	30
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	30
Tomas Solis L 2016 · 4.86 FIP	33	SP	4.86	12.4%	8.5%	3.1%	.273	5.95	10.1%	2.4%	117	+1.09	4.20	327	29
Arturo Lopez L 2016 · 5.26 FIP	33	SP	5.26	11.5%	7.9%	3.9%	.341	4.92	11.3%	5.2%	224	-0.34	4.34	445	28
Orlando Lara L 2017 · 4.39 FIP	32	SP	4.39	14.7%	6.5%	3.1%	.346	4.09	22.0%	14.2%	104	-0.30	3.85	426	28
Merrill Kelly R 2022 · 3.69 FIP	33	SP	3.69	22.0%	7.3%	2.8%	.267	3.76	23.5%	15.9%	435	+0.07	3.60	1,170	27
Kwang Hyun Kim L 2021 · 4.21 FIP	33	SP-	4.21	17.7%	8.2%	2.9%	.266	—	—	—	—	—	3.76	146	27
Junior Guerra R 2018 · 3.99 FIP	33	SP	3.99	22.3%	9.0%	3.0%	.309	4.12	21.2%	9.1%	173	+0.13	3.18	646	27
Jose De Paula L 2019 · 3.31 FIP	31	SP	3.31	19.0%	7.6%	1.6%	.394	—	—	—	—	—	3.31	118	26
Jose Contreras R 2005 · 4.13 FIP	33	SP	4.13	18.0%	8.5%	2.7%	.254	4.04	14.4%	7.8%	506	-0.09	2.43	1,279	25
Alfredo Simon R 2014 · 3.91 FIP	33	SP	3.91	15.5%	6.0%	2.5%	.256	4.88	13.7%	5.1%	261	+0.97	2.83	784	25
Kenta Maeda R 2021 · 3.79 FIP	33	SP	3.79	24.9%	6.8%	3.5%	.307	4.26	23.6%	17.1%	230	+0.47	2.87	1,092	25
Tsuyoshi Wada L 2014 · 3.60 FIP	33	SP	3.60	19.7%	6.2%	2.5%	.290	3.66	16.8%	9.7%	119	+0.06	3.60	188	24

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	7.8	119	22.1%	8.8%	0.81	3.60
Alex Wood ('24)	6.3	114	22.1%	7.1%	0.91	3.78
Jose Rijo ('84-'02, 33 WAR*)	9.4	145	25.9%*	8.4%*	0.93*	3.56*
Erik Bedard ('14)	6.5	130	22.2%	9.5%	0.90	3.99
Francisco Liriano ('19)	9.1	130	23.3%	10.5%	0.91	4.15
Bob Moose ('67-'76, 14 WAR*)	6.5	145	20.0%*	7.0%*	0.80*	4.31*
Pete Vuckovich ('75-'86, 17 WAR*)	7.3	162	21.4%*	8.8%*	0.95*	4.11*