Cristopher Sánchez

P Philadelphia Phillies

Age 30 LHP 6'6" / 200 lbs MLB Svc 4.0 · Ctrl thru 2033 peak 5.1 · 2027

Overview

MLBSP40-MANExtFA 2034

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	27	MLBPHI	31	31	182	3.32	2.93	20.3%	5.8%	5.7
2025	28	MLBPHI	32	32	202	2.50	2.43	26.3%	5.5%	7.9
2026	29	MLBPHI	33	33	207	2.91	2.71	27.0%	5.3%	7.1
2027PROJ	30	MLBPHI	28	28	170	3.11	3.05	26.4%	5.4%	5.0
2028PROJ	31	MLBPHI	24	24	142	3.30	3.37	25.6%	5.8%	3.7
2029PROJ	32	MLBPHI	20	20	123	3.50	3.63	24.8%	6.2%	2.8

Last 3 seasons WAR 20.7 · Next 3 projected WAR 11.6Projected rows: MLB playing time only, park and league context applied.

ContractCONFIRMED

Control thru2033Service4.483First FA2034

2027Ext$6M2028Ext$9M2029Ext$14M2030Ext$15M2031Ext$27M2032Ext$12M2033Ext$11M

Skills · percentileStatcast 2026

xwOBA vs78

K%76

FB Velo58

Form4.19 ERA (proj 3.11) · K 23.7% (proj 26.4%) · BB 4.5% (proj 5.4%) · last 60d · 39 IP through Oct 27

CompsWei-Yin Chen (age 30) · Wandy Rodriguez (age 30) · Erik Bedard (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 7482vR 90

ERA3.11

FIP3.05

K%26.4%

BB%5.4%

K-BB%21.0%

Proj IP170

Value2027 · WAR

Runs saved vs league avg · 170 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit+$32M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p5895.1

Whiff%

p8831.3%

p7627.0%

xwOBA vs

p780.285

Contract CONFIRMED · hand-curated extension

Status Arb-2

MLB Debut 2021

Service 4.483 yrs.days

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Ext	$6M	+5.0	$60M	+$54M
2028	Ext	$9M	+3.7	$36M	+$28M
2029	Ext	$14M	+2.8	$21M	+$9M
2030	Ext	$15M	+2.0	$13M	+$2M
2031	Ext	$27M	+1.3	$8M	-$10M
2032	Ext	$12M	+0.7	$2M	-$5M
2033	Ext	$11M	+0.3	$0.8M	-$5M
Totals		$94M		$139M	+$72M

Why some years run red
On long-term deals the salary is locked in regardless of how the player ages. Late years are red whenever projected production drops below the AAV — that's expected, not a sign the deal is bad. The honest scorecard is the Net Surplus over the whole contract, not any single year.

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	18	ROK MLE	DSL Rays	15	0	20	89	16	16	0	0%	1.4	12.2%	22.5%	-10.2%	0.0%	3.54	4.91	—
2015	18	ROK RAW	DSL Rays	15	0	20	89	16	16	0	0%	1.4	18.0%	18.0%	0.0%	0.0%	3.54	3.89	—
2016	19	ROK MLE	DSL Rays 1	13	11	62	257	42	12	0	85%	4.7	11.1%	5.8%	5.3%	0.0%	3.06	2.90	—
2016	19	ROK RAW	DSL Rays 1	13	11	62	257	42	12	0	85%	4.7	16.3%	4.7%	11.7%	0.0%	3.06	2.32	—
2017	20	ROK MLE	Princeton Rays	13	7	39	198	30	16	8	54%	3.0	10.3%	10.1%	0.2%	5.7%	10.01	6.61	—
2017	20	ROK RAW	Princeton Rays	13	7	39	198	30	16	8	54%	3.0	15.2%	8.1%	7.1%	4.0%	10.01	5.48	—
2018	21	ROK MLE	Princeton Rays	10	10	43	197	34	22	3	100%	4.3	11.7%	14.0%	-2.2%	2.1%	4.60	5.05	—
2018	21	ROK RAW	Princeton Rays	10	10	43	197	34	22	3	100%	4.3	17.3%	11.2%	6.1%	1.5%	4.60	3.96	—
2019	22	MIX MLE	3 levels	24	10	76	308	73	25	3	42%	3.2	18.3%	8.9%	9.4%	1.0%	2.26	3.24	—
2019	22	MIX RAW	3 levels	24	10	76	308	73	25	3	42%	3.2	23.7%	8.1%	15.6%	1.0%	2.26	2.68	—
2021	24	MIX MLE	2 levels	26	18	86	384	102	55	5	69%	3.3	23.8%	14.9%	8.8%	1.4%	4.73	3.78	+1.7
2021	24	MIX RAW	2 levels	26	18	86	384	102	55	5	69%	3.3	26.6%	14.3%	12.2%	1.3%	4.73	3.40	+2.1
2022	25	MIX MLE	2 levels	30	17	97	415	93	36	6	57%	3.2	20.7%	8.9%	11.8%	1.4%	4.16	3.24	+2.6
2022	25	MIX RAW	2 levels	30	17	97	415	93	36	6	57%	3.2	22.4%	8.7%	13.7%	1.4%	4.16	3.10	+2.7
2023	26	MIX MLE	2 levels	29	26	149	618	140	45	22	90%	5.1	21.7%	6.8%	14.8%	3.5%	3.74	4.03	+2.4
2023	26	MIX RAW	2 levels	29	26	149	618	140	45	22	90%	5.1	22.7%	7.3%	15.4%	3.6%	3.74	4.05	+2.4
2024	27	MLB MLE	Philadelphia Phillies	31	31	182	754	153	44	11	100%	5.9	20.3%	5.8%	14.5%	1.4%	3.32	2.87	+5.8
2024	27	MLB MLE	Philadelphia Phillies	31	31	182	754	153	44	11	100%	5.9	20.3%	5.8%	14.5%	1.4%	3.32	2.87	+5.8
2024	27	MLB RAW	Philadelphia Phillies	31	31	182	754	153	44	11	100%	5.9	20.3%	5.8%	14.5%	1.5%	3.32	2.93	+5.7
2025	28	MLB MLE	Philadelphia Phillies	32	32	202	807	212	44	12	100%	6.3	26.3%	5.5%	20.8%	1.4%	2.50	2.33	+8.2
2025	28	MLB MLE	Philadelphia Phillies	32	32	202	807	212	44	12	100%	6.3	26.3%	5.5%	20.8%	1.4%	2.50	2.33	+8.2
2025	28	MLB RAW	Philadelphia Phillies	32	32	202	807	212	44	12	100%	6.3	26.3%	5.5%	20.8%	1.5%	2.50	2.43	+7.9
2026	29	MLB MLE	Philadelphia Phillies	33	33	207	857	231	45	19	100%	6.3	27.0%	5.3%	21.7%	2.1%	2.91	2.62	+7.4
2026	29	MLB MLE	Philadelphia Phillies	33	33	207	857	231	45	19	100%	6.3	27.0%	5.3%	21.7%	2.1%	2.91	2.62	+7.4
2026	29	MLB RAW	Philadelphia Phillies	33	33	207	857	231	45	19	100%	6.3	27.0%	5.3%	21.7%	2.2%	2.91	2.71	+7.1
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			137	118	743	3050	740	172	64	86%	5.4	24.3%	5.6%	18.6%	2.1%	3.15	2.92	+23.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	PHI	28	28	170	718	189	39	14	100%	6.1	26.4%	5.4%	21.0%	2.0%	3.11	3.05	+5.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	PHI	24	24	142	601	154	35	13	100%	5.9	25.6%	5.8%	19.9%	2.2%	3.21	3.28	+3.7
2029	32	MLB MLE	PHI	20	20	123	519	129	32	13	100%	6.1	24.8%	6.2%	18.7%	2.5%	3.40	3.53	+2.8
2030	33	MLB MLE	PHI	17	17	104	441	106	29	12	100%	6.1	24.0%	6.6%	17.4%	2.8%	3.65	3.81	+2.0
2031	34	MLB MLE	PHI	14	14	84	354	82	25	11	100%	6.0	23.1%	7.1%	16.0%	3.1%	3.93	4.12	+1.3
2032	35	MLB MLE	PHI	10	10	61	256	57	20	9	100%	6.1	22.1%	7.7%	14.5%	3.4%	4.24	4.45	+0.7
2033	36	MLB MLE	PHI	6	6	38	163	34	13	6	100%	6.4	21.1%	8.3%	12.8%	3.8%	4.59	4.82	+0.3
2028	31	MLB CTX	PHI	24	24	142	600	154	35	14	100%	5.9	25.6%	5.8%	19.9%	2.4%	3.30	3.37	+3.7
2029	32	MLB CTX	PHI	20	20	123	519	129	32	14	100%	6.2	24.8%	6.2%	18.7%	2.7%	3.50	3.63	+2.8
2030	33	MLB CTX	PHI	17	17	104	439	105	29	13	100%	6.1	24.0%	6.6%	17.4%	3.0%	3.76	3.92	+2.0
2031	34	MLB CTX	PHI	14	14	84	355	82	25	12	100%	6.0	23.1%	7.1%	16.0%	3.3%	4.05	4.24	+1.3
2032	35	MLB CTX	PHI	10	10	61	258	57	20	9	100%	6.1	22.1%	7.7%	14.5%	3.7%	4.38	4.59	+0.7
2033	36	MLB CTX	PHI	6	6	38	160	34	13	7	100%	6.3	21.1%	8.3%	12.8%	4.1%	4.74	4.97	+0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		229	210	1295	5384	1302	326	133	92%	5.7	24.2%	6.1%	18.1%	2.5%	3.41	3.18	+35.7
/ 200 IP	—	RAW		35	32	200	831	201	50	21	92%	5.7	24.2%	6.1%	18.1%	2.5%	3.41	3.18	+5.5
Career	—	MLE		256	195	1162	4884	1047	379	90	76%	4.5	21.4%	7.8%	13.7%	1.8%	3.52	3.29	+33.4
/ 200 IP	—	MLE		44	34	200	841	180	65	16	76%	4.5	21.4%	7.8%	13.7%	1.8%	3.52	3.29	+5.2

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.

2023 AAALehigh Valley IronPigs · 50 IPFIP 4.56 → 4.74 (+0.17)K% 19.8% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.82%	—	×0.860	17.05%
BB% (unintentional) /BF	13.06%	—	×0.900	11.76%
HR / BF /BF	2.70%	÷1.028	×1.100	2.89%

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 106).

Result: FIP 4.56 → 4.74, 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 AAALehigh Valley IronPigs · 57 IPFIP 2.34 → 2.65 (+0.31)K% 24.4% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.37%	—	×0.880	21.45%
BB% (unintentional) /BF	8.40%	—	×1.050	8.82%
HR / BF /BF	0.42%	÷1.039	×1.100	0.44%

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 108).

Result: FIP 2.34 → 2.65, 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 AAALehigh Valley IronPigs · 73 IPFIP 3.33 → 3.81 (+0.47)K% 27.4% → 24.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.38%	—	×0.880	24.10%
BB% (unintentional) /BF	14.77%	—	×1.050	15.51%
HR / BF /BF	1.23%	÷0.957	×1.100	1.41%

Result: FIP 3.33 → 3.81, 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 ABowling Green Hot Rods · 40 IPFIP 2.97 → 3.64 (+0.67)K% 22.8% → 16.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.84%	—	×0.740	16.90%
BB% (unintentional) /BF	6.17%	—	×1.180	7.28%
HR / BF /BF	1.85%	÷1.270	×1.300	1.90%

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 154).

Result: FIP 2.97 → 3.64, 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).

2019 A+Charlotte Stone Crabs · 34 IPFIP 2.10 → 2.78 (+0.68)K% 25.9% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.90%	—	×0.770	19.94%
BB% (unintentional) /BF	9.35%	—	×1.150	10.76%
HR / BF /BF	0.00%	÷0.939	×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 88).

Result: FIP 2.10 → 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).

2018 ROKPrinceton Rays · 43 IPFIP 3.89 → 5.05 (+1.15)K% 17.3% → 11.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.26%	—	×0.680	11.74%
BB% (unintentional) /BF	11.17%	—	×1.250	13.96%
HR / BF /BF	1.52%	÷1.000	×1.400	2.13%

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 3.89 → 5.05, 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).

2017 ROKPrinceton Rays · 39 IPFIP 5.06 → 6.61 (+1.55)K% 15.2% → 10.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.15%	—	×0.680	10.30%
BB% (unintentional) /BF	8.08%	—	×1.250	10.10%
HR / BF /BF	4.04%	÷1.000	×1.400	5.66%

Result: FIP 5.06 → 6.61, 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 ROKDSL Rays 1 · 62 IPFIP 2.31 → 2.90 (+0.59)K% 16.3% → 11.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.34%	—	×0.680	11.11%
BB% (unintentional) /BF	4.67%	—	×1.250	5.84%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Result: FIP 2.31 → 2.90, 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
Cristopher Sánchez (OGILVIE)	—	—	—	—	—	2.0%	—	3.51	24.9%	18.8%	370	+0.46	—	—	—
Wei-Yin Chen L 2015 · 3.88 FIP	30	SP	3.88	19.3%	5.2%	3.2%	.288	4.31	19.3%	13.2%	290	+0.43	3.63	1,065	58
Wandy Rodriguez L 2009 · 3.40 FIP	30	SP	3.40	22.7%	6.8%	2.5%	.296	3.80	19.3%	12.2%	592	+0.40	3.37	1,572	49
Erik Bedard L 2009 · 3.42 FIP	30	SP	3.42	25.9%	9.8%	2.3%	.264	3.88	22.2%	12.9%	255	+0.46	2.96	1,317	41
Chris Narveson L 2011 · 4.01 FIP	29	SP	4.01	18.0%	9.2%	2.3%	.291	—	—	—	—	—	4.00	625	36
Shota Imanaga L 2024 · 3.71 FIP	30	SP	3.71	25.1%	4.0%	4.0%	.262	4.76	22.8%	17.9%	319	+1.05	3.71	492	28
Masahiro Tanaka R 2019 · 4.01 FIP	30	SP	4.01	19.6%	5.3%	3.5%	.292	4.08	22.3%	18.2%	48	+0.07	2.82	1,054	27
Corey Kluber R 2016 · 3.10 FIP	30	SP	3.10	26.4%	6.5%	2.6%	.267	2.73	29.6%	25.0%	454	-0.37	2.16	1,636	27
J.A. Happ L 2013 · 4.23 FIP	30	SP	4.23	18.6%	10.8%	2.4%	.286	3.79	20.5%	13.5%	525	-0.44	3.37	1,890	26
Tanner Roark R 2017 · 3.88 FIP	30	SP	3.88	21.4%	7.6%	3.0%	.294	4.48	20.3%	13.2%	393	+0.60	2.40	1,194	26
Kyle Gibson R 2018 · 3.97 FIP	30	SP	3.97	21.7%	9.3%	2.8%	.282	3.91	21.2%	12.9%	409	-0.06	3.56	1,920	24
Scott Diamond L 2016 · 3.46 FIP	30	SP	3.46	12.7%	4.8%	1.5%	.326	—	—	—	—	—	3.46	659	24
Matt Tomshaw L 2019 · 3.09 FIP	30	SP-	3.09	21.6%	4.5%	2.3%	.297	8.67	18.4%	13.6%	53	+5.58	3.04	681	22
Kenta Maeda R 2018 · 2.89 FIP	30	SP-	2.89	28.8%	7.3%	2.3%	.312	3.55	27.4%	20.7%	327	+0.66	2.87	1,092	21
Yu Darvish R 2017 · 3.59 FIP	30	SP	3.59	27.3%	7.4%	3.4%	.279	3.53	30.7%	23.5%	295	-0.06	1.97	1,798	20
Christian Friedrich L 2016 · 3.96 FIP	29	SP	3.96	17.6%	8.8%	2.2%	.292	—	—	—	—	—	3.39	297	19
Adam Wainwright R 2012 · 3.04 FIP	30	SP	3.04	22.1%	5.9%	1.9%	.310	2.58	21.3%	17.1%	497	-0.46	2.03	2,666	19
Juan Pablo Oramas L 2019 · 3.60 FIP	29	SP	3.60	21.2%	8.0%	2.3%	.337	—	—	—	—	—	3.46	440	18
Ryan Verdugo L 2017 · 3.36 FIP	30	SP-	3.36	22.7%	5.4%	2.7%	.333	—	—	—	—	—	3.36	153	18
Paul Oseguera L 2015 · 3.83 FIP	31	SP	3.83	17.6%	8.5%	2.1%	.297	5.62	5.6%	-6.9%	28	+1.79	3.83	162	18
Mike Fiers R 2015 · 3.86 FIP	30	SP	3.86	23.7%	7.8%	3.2%	.277	4.73	19.9%	13.3%	494	+0.87	2.83	1,140	18

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	7.3	122	24.4%	6.0%	0.91	3.34
Julio Urías ('23)	3.6	102	24.3%	6.6%	1.05	3.11
Alex Wood ('24)	6.3	114	22.1%	7.1%	0.91	3.78
Roger Nelson ('67-'76, 10 WAR*)	3.2	106	19.5%*	7.1%*	0.98*	3.88*
David Price ('22)	10.7	165	23.6%	6.4%	0.93	3.32
Wilbur Wood ('61-'78, 39 WAR*)	13.4	179	17.8%*	6.3%*	1.04*	3.75*
Jose Rijo ('84-'02, 33 WAR*)	9.4	145	25.9%*	8.4%*	0.93*	3.56*