Ty Blach

P Iowa Cubs

Age 36 LHP 6'1" / 215 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	33	MIX2 levels	32	21	112	5.93	5.45	12.1%	4.8%	-0.1	K 11.4% · BB 4.7% · FIP 5.18
2025	34	MIX2 levels	12	12	56	3.54	3.24	19.9%	5.4%	—	K 15.4% · BB 5.2% · FIP 3.94
2026	35	MIX2 levels	16	9	61	6.05	4.54	15.7%	8.5%	0.6	K 13.3% · BB 7.9% · FIP 4.76
2027PROJ	36	MLBCHC	26	26	163	5.22	5.17	12.2%	7.4%	0.4
2028PROJ	37	MLBCHC	16	16	100	5.35	5.49	11.1%	8.0%	-0.2
2029PROJ	38	MLBCHC	12	12	72	5.69	5.92	10.0%	8.7%	-0.5

Last 3 seasons WAR 0.5 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2024

FB Velo10

K%10

xwOBA vs10

CompsChris Michalak (age 35) · Francisley Bueno (age 36) · Juan Antonio Pena (age 37)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 127135vR 144

ERA5.22

FIP5.17

K%12.2%

BB%7.4%

K-BB%4.8%

Proj IP163

Value2027 · WAR

Runs saved vs league avg · 163 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p1089.1

Whiff%

p1014.8%

p1010.9%

xwOBA vs

p100.402

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	24	AAA MLE	Sacramento River Cats	27	27	165	699	93	31	16	100%	6.1	11.7%	4.7%	7.1%	2.6%	4.46	4.11	—
2015	24	AAA RAW	Sacramento River Cats	27	27	165	699	93	31	16	100%	6.1	13.3%	4.4%	8.9%	2.3%	4.46	3.80	—
2016	25	MIX MLE	2 levels	30	28	180	717	123	43	10	93%	6.0	15.3%	6.3%	9.0%	1.4%	3.21	3.39	+4.5
2016	25	MIX RAW	2 levels	30	28	180	717	123	43	10	93%	6.0	17.2%	6.0%	11.2%	1.4%	3.21	3.17	+5.0
2017	26	MLB MLE	San Francisco Giants	34	24	164	692	73	41	17	71%	4.8	10.5%	5.9%	4.6%	2.7%	4.78	4.42	+1.9
2017	26	MLB RAW	San Francisco Giants	34	24	164	692	73	41	17	71%	4.8	10.5%	5.9%	4.6%	2.5%	4.78	4.31	+2.1
2018	27	MLB MLE	San Francisco Giants	47	13	119	512	75	37	8	28%	2.5	14.6%	7.2%	7.4%	1.7%	4.25	3.71	+1.2
2018	27	MLB RAW	San Francisco Giants	47	13	119	512	75	37	8	28%	2.5	14.6%	7.2%	7.4%	1.6%	4.25	3.65	+1.3
2019	28	MIX MLE	2 levels	26	22	123	587	90	44	23	85%	4.7	13.9%	7.7%	6.2%	4.4%	7.74	5.32	+0.1
2019	28	MIX RAW	2 levels	26	22	123	587	90	44	23	85%	4.7	15.3%	7.5%	7.8%	3.9%	7.74	5.14	+0.4
2021	30	MIX MLE	2 levels	16	15	22	81	23	1	0	94%	1.4	18.2%	2.1%	16.1%	0.0%	1.23	1.83	—
2021	30	MIX RAW	2 levels	16	15	22	81	23	1	0	94%	1.4	28.4%	1.2%	27.2%	0.0%	1.23	1.15	—
2022	31	MIX MLE	2 levels	39	2	80	351	49	17	7	5%	2.1	13.3%	5.0%	8.3%	1.9%	5.27	3.65	+0.9
2022	31	MIX RAW	2 levels	39	2	80	351	49	17	7	5%	2.1	14.0%	4.8%	9.1%	2.0%	5.27	3.65	+0.9
2023	32	MIX MLE	2 levels	31	18	109	485	77	32	17	58%	3.5	15.1%	6.4%	8.7%	3.2%	5.22	4.38	+1.3
2023	32	MIX RAW	2 levels	31	18	109	485	77	32	17	58%	3.5	15.9%	6.6%	9.3%	3.5%	5.22	4.60	+1.0
2024	33	MIX MLE	2 levels	32	21	112	496	60	24	24	66%	3.5	11.4%	4.7%	6.7%	4.5%	5.93	5.18	+0.3
2024	33	MIX MLE	2 levels	32	21	112	496	60	24	24	66%	3.5	11.4%	4.7%	6.7%	4.5%	5.93	5.18	+0.3
2024	33	MIX RAW	2 levels	32	21	112	496	60	24	24	66%	3.5	12.1%	4.8%	7.3%	4.8%	5.93	5.45	-0.1
2025	34	MIX MLE	2 levels	12	12	56	241	48	13	5	100%	4.7	15.4%	5.2%	10.1%	2.7%	3.54	3.94	—
2025	34	MIX MLE	2 levels	12	12	56	241	48	13	5	100%	4.7	15.4%	5.2%	10.1%	2.7%	3.54	3.94	—
2025	34	MIX RAW	2 levels	12	12	56	241	48	13	5	100%	4.7	19.9%	5.4%	14.5%	2.1%	3.54	3.24	—
2026	35	MIX MLE	2 levels	16	9	61	281	44	24	8	56%	3.8	13.3%	7.9%	5.3%	3.2%	6.05	4.76	+0.5
2026	35	MIX MLE	2 levels	16	9	61	281	44	24	8	56%	3.8	13.3%	7.9%	5.3%	3.2%	6.05	4.76	+0.5
2026	35	MIX RAW	2 levels	16	9	61	281	44	24	8	56%	3.8	15.7%	8.5%	7.1%	2.8%	6.05	4.54	+0.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			157	70	523	2289	295	151	70	45%	3.3	12.9%	6.6%	6.3%	3.1%	5.39	4.58	-0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	36	MLB	CHC	26	26	163	688	84	51	22	100%	6.3	12.2%	7.4%	4.8%	3.3%	5.22	5.17	+0.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	37	MLB MLE	CHC	16	16	100	420	46	34	15	100%	6.2	11.1%	8.0%	3.0%	3.7%	5.43	5.57	-0.2
2029	38	MLB MLE	CHC	12	12	72	304	30	26	13	100%	6.0	10.0%	8.7%	1.3%	4.1%	5.77	6.00	-0.5
2028	37	MLB CTX	CHC	16	16	100	422	47	34	15	100%	6.2	11.1%	8.0%	3.0%	3.5%	5.35	5.49	-0.2
2029	38	MLB CTX	CHC	12	12	72	304	30	26	12	100%	6.0	10.0%	8.7%	1.3%	4.0%	5.69	5.92	-0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		184	97	694	3013	372	211	97	53%	3.8	12.3%	7.0%	5.3%	3.2%	5.41	4.71	+5.6
/ 200 IP	—	RAW		53	28	200	868	107	61	28	53%	3.8	12.3%	7.0%	5.3%	3.2%	5.41	4.71	+1.6
Career	—	MLE		310	191	1191	5142	686	309	141	62%	3.8	13.3%	6.0%	7.3%	2.7%	4.87	4.24	+4.3
/ 200 IP	—	MLE		52	32	200	863	115	52	24	62%	3.8	13.3%	6.0%	7.3%	2.7%	4.87	4.24	+1.2

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.

2026 AAAIowa Cubs · 58 IPFIP 4.53 → 4.76 (+0.23)K% 15.4% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.44%	—	×0.860	13.28%
BB% (unintentional) /BF	8.82%	—	×0.900	7.94%
HR / BF /BF	2.94%	÷1.000	×1.100	3.24%

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 100).

Result: FIP 4.53 → 4.76, 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).

2025 AAARound Rock Express · 51 IPFIP 3.55 → 3.94 (+0.39)K% 17.9% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.86%	—	×0.860	15.36%
BB% (unintentional) /BF	5.80%	—	×0.900	5.22%
HR / BF /BF	2.23%	÷0.913	×1.100	2.69%

Result: FIP 3.55 → 3.94, 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).

2024 AAAAlbuquerque Isotopes · 41 IPFIP 4.65 → 4.79 (+0.13)K% 14.5% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.46%	—	×0.860	12.43%
BB% (unintentional) /BF	3.61%	—	×0.900	3.25%
HR / BF /BF	4.22%	÷1.096	×1.100	4.23%

Result: FIP 4.65 → 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).

2023 AAAAlbuquerque Isotopes · 31 IPFIP 2.97 → 3.17 (+0.19)K% 20.3% → 17.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.30%	—	×0.860	17.46%
BB% (unintentional) /BF	6.02%	—	×0.900	5.41%
HR / BF /BF	1.50%	÷1.062	×1.100	1.56%

Result: FIP 2.97 → 3.17, 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 AAAAlbuquerque Isotopes · 36 IPFIP 3.71 → 3.91 (+0.20)K% 12.7% → 11.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	12.66%	—	×0.880	11.14%
BB% (unintentional) /BF	5.06%	—	×1.050	5.32%
HR / BF /BF	1.90%	÷1.061	×1.100	1.97%

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 112).

Result: FIP 3.71 → 3.91, 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 ADelmarva Shorebirds · 15 IPFIP 1.25 → 1.83 (+0.58)K% 24.6% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.56%	—	×0.740	18.18%
BB% (unintentional) /BF	1.75%	—	×1.180	2.07%
HR / BF /BF	0.00%	÷1.035	×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 107).

Result: FIP 1.25 → 1.83, 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 ROKFCL Orioles Orange · 7 IPFIP -0.07 → 0.95 (+1.01)K% 37.5% → 25.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	37.50%	—	×0.680	25.50%
BB% (unintentional) /BF	0.00%	—	×1.250	0.00%
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 -0.07 → 0.95, 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 AAANorfolk Tides · 96 IPFIP 4.38 → 5.02 (+0.63)K% 15.6% → 13.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.62%	—	×0.880	13.75%
BB% (unintentional) /BF	6.03%	—	×1.050	6.33%
HR / BF /BF	3.35%	÷0.889	×1.100	4.15%

Result: FIP 4.38 → 5.02, 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
Ty Blach (OGILVIE)	—	—	—	—	—	3.3%	—	5.75	10.6%	2.3%	172	+0.58	—	—	—
Chris Michalak L 2006 · 5.71 FIP	35	SP-	5.71	6.2%	8.6%	3.7%	.273	—	—	—	—	—	4.71	186	66
Francisley Bueno L 2017 · 4.44 FIP	36	SP	4.44	11.7%	8.4%	2.3%	.351	—	—	—	—	—	2.43	188	60
Juan Antonio Pena L 2015 · 4.20 FIP	37	SP-	4.20	13.6%	9.9%	1.8%	.287	—	—	—	—	—	4.20	149	55
Oscar Rivera L 2017 · 5.80 FIP	36	SP	5.80	9.8%	7.8%	4.6%	.252	—	—	—	—	—	3.68	237	53
Jorge Castillo L 2017 · 4.97 FIP	35	SP	4.97	11.2%	6.7%	3.6%	.337	4.91	19.6%	11.5%	119	-0.06	4.50	408	51
Marlon Arias L 2019 · 4.83 FIP	34	SP	4.83	19.8%	11.2%	3.6%	.273	—	—	—	—	—	3.73	154	41
Arturo Lopez L 2019 · 5.46 FIP	36	SP	5.46	12.2%	6.8%	4.6%	.320	—	—	—	—	—	4.34	445	41
Jesse Estrada R 2019 · 4.34 FIP	35	SP-	4.34	14.4%	6.6%	2.9%	.312	—	—	—	—	—	3.80	257	33
Juan Delgadillo R 2017 · 4.47 FIP	34	SP	4.47	10.9%	6.2%	2.7%	.311	—	—	—	—	—	4.47	143	32
Austin Bibens-Dirkx R 2021 · 4.20 FIP	36	SP-	4.20	15.8%	5.6%	3.1%	.333	—	—	—	—	—	3.97	567	26
Kenshin Kawakami R 2010 · 4.06 FIP	35	SP	4.06	15.1%	5.6%	2.8%	.293	—	—	—	—	—	3.97	244	24
Francisco Rodriguez R 2019 · 5.18 FIP	36	SP	5.18	10.7%	9.3%	3.3%	.339	—	—	—	—	—	3.16	334	22
David Buchanan R 2024 · 4.26 FIP	35	SP-	4.26	14.7%	6.5%	2.9%	.337	5.56	12.2%	4.1%	29	+1.30	3.88	560	21
Jason Lane L 2015 · 5.56 FIP	38	SP	5.56	8.4%	6.2%	4.3%	.307	—	—	—	—	—	5.56	164	21
Jose Oyervides R 2017 · 5.38 FIP	35	SP	5.38	18.0%	6.3%	5.5%	.254	5.66	16.3%	5.1%	115	+0.28	3.01	407	21
Chris Smith R 2017 · 5.08 FIP	36	SP-	5.08	15.6%	7.5%	4.3%	.286	—	—	—	—	—	3.79	477	20
Walter Silva R 2015 · 4.15 FIP	38	SP	4.15	14.8%	7.4%	2.5%	.311	3.91	10.4%	3.7%	209	-0.24	3.67	453	20
Frankie De La Cruz R 2019 · 4.38 FIP	35	SP-	4.38	16.2%	8.0%	3.0%	.322	—	—	—	—	—	2.87	262	19
Jonathan Castellanos R 2017 · 4.91 FIP	35	SP	4.91	8.4%	9.2%	2.5%	.314	5.24	11.0%	2.0%	67	+0.33	3.40	394	18
Ivan Maldonado R 2016 · 5.41 FIP	36	SP	5.41	6.4%	9.7%	3.0%	.325	—	—	—	—	—	4.60	172	17

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	4.3	95	12.3%	7.3%	1.26	5.39
David Huff ('16)	2.0	66	13.3%	7.5%	1.35	5.17
Shawn Boskie ('98)	4.4	109	12.8%	7.6%	1.38	5.14
Sean Bergman ('00)	3.8	107	13.5%	8.1%	1.19	5.28
Jeff Ballard ('87-'94, -2 WAR*)	3.9	110	9.7%*	6.7%*	1.36*	5.09*
Dave Otto ('87-'94, -1 WAR*)	1.6	80	13.4%*	8.5%*	1.17*	5.29*
John O'Donoghue ('63-'71, 1 WAR*)	3.8	107	14.5%*	7.9%*	1.19*	4.86*