Chris Paddack

P Texas Rangers

Age 31 RHP 6'5" / 217 lbs MLB peak 0.2 · 2027

Overview

MLBSP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR
2024	28	MLBMIN	17	17	88	4.99	4.08	20.6%	5.5%	1.4
2025	29	MLBDET	33	28	158	5.35	4.94	16.7%	5.5%	0.8
2026	30	MLBTEX	14	9	57	6.79	4.75	15.0%	7.1%	0.4
2027PROJ	31	MLBTEX	7	7	41	5.00	4.95	16.6%	6.2%	0.2
2028PROJ	32	MLBTEX	7	7	43	5.12	5.20	15.8%	6.7%	0.1
2029PROJ	33	MLBTEX	6	6	33	5.34	5.48	14.9%	7.1%	-0.0

Last 3 seasons WAR 2.6 · Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo27

xwOBA vs24

K%10

CompsDaisuke Matsuzaka (age 31) · Hideki Irabu (age 31) · Brian Tollberg (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127119vR 110

ERA5.00

FIP4.95

K%16.6%

BB%6.2%

K-BB%10.3%

Proj IP41

Value2027 · WAR

Runs saved vs league avg · 41 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2792.9

Whiff%

p2221.4%

p1015.0%

xwOBA vs

p240.342

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	19	ROK MLE	GCL Marlins	11	7	45	180	39	7	1	64%	4.1	14.7%	4.9%	9.9%	0.8%	2.18	2.90	—
2015	19	ROK RAW	GCL Marlins	11	7	45	180	39	7	1	64%	4.1	21.7%	3.9%	17.8%	0.6%	2.18	2.13	—
2016	20	A MLE	Fort Wayne TinCaps	9	9	42	153	71	5	2	100%	4.7	34.3%	3.9%	30.5%	1.9%	0.85	1.74	—
2016	20	A RAW	Fort Wayne TinCaps	9	9	42	153	71	5	2	100%	4.7	46.4%	3.3%	43.1%	1.3%	0.85	0.71	—
2018	22	MIX MLE	2 levels	17	17	90	340	120	7	4	100%	5.3	27.6%	2.3%	25.3%	1.7%	2.10	2.02	—
2018	22	MIX RAW	2 levels	17	17	90	340	120	7	4	100%	5.3	35.3%	2.1%	33.2%	1.2%	2.10	1.24	—
2019	23	MLB MLE	San Diego Padres	26	26	141	568	153	30	23	100%	5.4	26.9%	5.3%	21.7%	4.0%	3.33	3.66	+3.0
2019	23	MLB RAW	San Diego Padres	26	26	141	568	153	30	23	100%	5.4	26.9%	5.3%	21.7%	4.0%	3.33	3.69	+2.9
2020	24	MLB MLE	San Diego Padres	12	12	59	245	58	12	14	100%	4.9	23.7%	4.9%	18.8%	5.6%	4.73	4.78	+0.4
2020	24	MLB RAW	San Diego Padres	12	12	59	245	58	12	14	100%	4.9	23.7%	4.9%	18.8%	5.7%	4.73	4.83	+0.4
2021	25	MLB MLE	San Diego Padres	23	22	108	459	99	21	15	96%	4.7	21.6%	4.6%	17.0%	3.2%	5.07	3.61	+2.3
2021	25	MLB RAW	San Diego Padres	23	22	108	459	99	21	15	96%	4.7	21.6%	4.6%	17.0%	3.3%	5.07	3.65	+2.3
2022	26	MLB MLE	Minnesota Twins	5	5	22	93	20	2	0	100%	4.5	21.5%	2.2%	19.4%	0.0%	4.03	1.56	+1.1
2022	26	MLB RAW	Minnesota Twins	5	5	22	93	20	2	0	100%	4.5	21.5%	2.2%	19.4%	0.0%	4.03	1.58	+1.1
2023	27	MIX MLE	4 levels	5	2	15	61	23	4	2	40%	2.9	37.7%	6.6%	31.1%	3.3%	4.30	2.55	+0.4
2023	27	MIX RAW	4 levels	5	2	15	61	23	4	2	40%	2.9	37.7%	6.6%	31.1%	3.3%	4.30	2.55	+0.4
2024	28	MLB MLE	Minnesota Twins	17	17	88	384	79	21	14	100%	5.2	20.6%	5.5%	15.1%	3.6%	4.99	4.05	+1.4
2024	28	MLB MLE	Minnesota Twins	17	17	88	384	79	21	14	100%	5.2	20.6%	5.5%	15.1%	3.6%	4.99	4.05	+1.4
2024	28	MLB RAW	Minnesota Twins	17	17	88	384	79	21	14	100%	5.2	20.6%	5.5%	15.1%	3.6%	4.99	4.08	+1.4
2025	29	MLB MLE	Detroit Tigers	33	28	158	670	112	37	31	85%	4.8	16.7%	5.5%	11.2%	4.8%	5.35	5.04	+0.6
2025	29	MLB MLE	Detroit Tigers	33	28	158	670	112	37	31	85%	4.8	16.7%	5.5%	11.2%	4.8%	5.35	5.04	+0.6
2025	29	MLB RAW	Detroit Tigers	33	28	158	670	112	37	31	85%	4.8	16.7%	5.5%	11.2%	4.6%	5.35	4.94	+0.8
2026	30	MLB MLE	Texas Rangers	14	9	57	267	40	19	9	64%	4.1	15.0%	7.1%	7.9%	3.1%	6.79	4.46	+0.6
2026	30	MLB MLE	Texas Rangers	14	9	57	267	40	19	9	64%	4.1	15.0%	7.1%	7.9%	3.1%	6.79	4.46	+0.6
2026	30	MLB RAW	Texas Rangers	14	9	57	267	40	19	9	64%	4.1	15.0%	7.1%	7.9%	3.4%	6.79	4.75	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			132	119	639	2708	569	143	107	90%	4.8	21.0%	5.3%	15.7%	4.0%	4.83	4.17	+9.3
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	TEX	7	7	41	173	29	11	7	100%	5.9	16.6%	6.2%	10.3%	3.8%	5.00	4.95	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	TEX	7	7	43	182	29	12	7	100%	6.2	15.8%	6.7%	9.1%	4.0%	5.12	5.20	+0.1
2029	33	MLB MLE	TEX	6	6	33	139	21	10	6	100%	5.5	14.9%	7.1%	7.8%	4.3%	5.34	5.48	-0.0
2028	32	MLB CTX	TEX	7	7	43	182	29	12	7	100%	6.1	15.8%	6.7%	9.1%	4.0%	5.12	5.20	+0.1
2029	33	MLB CTX	TEX	6	6	33	139	21	10	6	100%	5.5	14.9%	7.1%	7.8%	4.3%	5.34	5.48	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		145	132	715	3029	618	165	120	91%	4.9	20.4%	5.4%	15.0%	4.0%	4.87	4.25	+9.7
/ 200 IP	—	RAW		40	37	200	848	173	46	34	91%	4.9	20.4%	5.4%	15.0%	4.0%	4.87	4.25	+2.7
Career	—	MLE		172	154	826	3420	757	169	118	90%	4.8	22.1%	4.9%	17.2%	3.4%	4.17	3.74	+9.3
/ 200 IP	—	MLE		42	37	200	828	183	41	28	90%	4.8	22.1%	4.9%	17.2%	3.4%	4.17	3.74	+2.6

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.

2018 A+Lake Elsinore Storm · 52 IPFIP 0.71 → 1.94 (+1.23)K% 40.9% → 31.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	40.89%	—	×0.770	31.48%
BB% (unintentional) /BF	1.97%	—	×1.150	2.27%
HR / BF /BF	1.48%	÷0.839	×1.250	2.20%

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 68).

Result: FIP 0.71 → 1.94, 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 AASan Antonio Missions · 38 IPFIP 1.50 → 2.14 (+0.64)K% 27.0% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.01%	—	×0.810	21.88%
BB% (unintentional) /BF	2.19%	—	×1.100	2.41%
HR / BF /BF	0.73%	÷0.824	×1.200	1.06%

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 65).

Result: FIP 1.50 → 2.14, 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 AFort Wayne TinCaps · 42 IPFIP 0.31 → 1.74 (+1.43)K% 46.4% → 34.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	46.41%	—	×0.740	34.34%
BB% (unintentional) /BF	3.27%	—	×1.180	3.86%
HR / BF /BF	1.31%	÷0.888	×1.300	1.91%

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 78).

Result: FIP 0.31 → 1.74, 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).

2015 ROKGCL Marlins · 45 IPFIP 2.07 → 2.90 (+0.83)K% 21.7% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.67%	—	×0.680	14.73%
BB% (unintentional) /BF	3.89%	—	×1.250	4.86%
HR / BF /BF	0.56%	÷1.000	×1.400	0.78%

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 2.07 → 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
Chris Paddack (OGILVIE)	—	—	—	—	—	3.8%	—	5.32	15.4%	8.5%	76	+0.37	—	—	—
Daisuke Matsuzaka R 2012 · 5.55 FIP	31	SP	5.55	19.1%	9.3%	5.2%	.329	3.83	21.1%	9.5%	122	-1.72	3.77	790	66
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	64
Brian Tollberg R 2002 · 4.98 FIP	29	SP	4.98	11.5%	5.9%	3.8%	.339	—	—	—	—	—	4.02	297	61
Zack Segovia R 2015 · 4.78 FIP	32	SP	4.78	15.0%	8.3%	3.4%	.314	3.33	20.2%	14.3%	39	-1.45	3.33	144	60
Scott Carroll R 2016 · 4.94 FIP	31	SP	4.94	10.5%	8.6%	3.0%	.289	5.71	14.4%	5.8%	22	+0.77	3.92	377	58
Chris Heston R 2017 · 5.88 FIP	29	SP-	5.88	13.6%	10.0%	4.9%	.368	—	—	—	—	—	3.81	321	58
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	57
Stan Spencer R 2000 · 4.42 FIP	30	SP	4.42	19.2%	8.7%	3.4%	.259	—	—	—	—	—	3.61	119	57
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	57
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	57
Erik Hiljus R 2002 · 6.07 FIP	29	SP	6.07	14.1%	9.7%	5.3%	.281	—	—	—	—	—	3.35	112	56
Tyler Herron R 2017 · 4.02 FIP	30	SP	4.02	16.4%	8.7%	2.2%	.377	—	—	—	—	—	4.02	117	56
Jeremy Hefner R 2016 · 4.64 FIP	30	SP	4.64	16.8%	9.1%	3.3%	.305	—	—	—	—	—	3.56	322	55
Miguel González R 2015 · 4.53 FIP	31	SP	4.53	17.5%	7.9%	3.5%	.289	4.23	15.9%	9.0%	325	-0.30	3.72	905	55
Brian Lawrence R 2007 · 4.68 FIP	31	SP	4.68	12.9%	8.6%	2.9%	.371	—	—	—	—	—	3.33	963	55
Chien-Ming Wang R 2011 · 4.59 FIP	31	SP	4.59	9.5%	4.9%	3.0%	.271	5.27	10.4%	1.9%	59	+0.68	3.53	976	54
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	54
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
Manny Barreda R 2019 · 5.21 FIP	30	SP	5.21	18.1%	9.5%	4.4%	.317	3.34	20.1%	12.9%	40	-1.87	3.30	376	54
Robert Ellis R 2001 · 4.84 FIP	30	SP	4.84	9.9%	7.7%	2.9%	.287	8.08	9.0%	-2.2%	18	+3.24	4.84	110	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	3.8	76	20.2%	5.6%	1.53	4.88
Matt Andriese ('24)	2.6	74	21.8%	6.7%	1.36	4.65
Doug Bird ('73-'83, 10 WAR*)	6.1	110	20.3%*	5.8%*	1.41*	4.43*
Matt Wisler ('22)	2.5	63	20.1%	7.6%	1.40	4.59
Tommy Milone ('23)	4.8	95	17.4%	5.7%	1.53	4.58
Willie Blair ('90-'01, 1 WAR*)	6.4	106	16.4%*	7.2%*	1.32*	4.86*
Pat Underwood ('79-'83, 1 WAR*)	1.7	115	20.9%*	6.3%*	1.57*	4.52*