Chase Solesky

P Louisville Bats

Age 29 RHP 6'3" / 201 lbs AAA peak 0.5 · 2027

Overview

AAARP40-MANROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	AAWSH	17	15	83	3.02	3.53	15.0%	5.9%	—	K 12.2% · BB 6.5% · FIP 4.07
2025	27	MIX2 levels	25	24	113	5.03	4.37	19.5%	8.7%	—	K 17.0% · BB 7.9% · FIP 4.74
2026	28	MIX2 levels	33	10	81	5.64	4.15	21.8%	8.0%	0.4	K 18.6% · BB 7.3% · FIP 4.37
2027PROJ	29	MLBTB	8	8	46	4.90	4.90	16.5%	8.0%	0.3
2028PROJ76% MLB	30	MLBTB	7	7	43	4.95	5.02	16.9%	8.4%	0.2
2029PROJ82% MLB	31	MLBTB	7	7	40	5.06	5.17	17.0%	8.8%	0.1

Last 3 seasons WAR 0.4 · Next 3 projected WAR 0.6Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control50Command45

Career WAR0.0 WAR median (P10 -0.2 / P90 0.1, comp-based) · star 0% · didn't stick 98%

CompsZack Segovia (age 32) · Travis Smith (age 29) · Zach Stewart (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 126118vR 110

ERA4.90

FIP4.90

K%16.5%

BB%8.0%

K-BB%8.5%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL5050

CMD4545

K†4040

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)
2021	23	MIX MLE	2 levels	18	18	68	308	88	24	11	100%	3.8	21.3%	9.2%	12.2%	4.9%	5.14	5.15	—
2021	23	MIX RAW	2 levels	18	18	68	308	88	24	11	100%	3.8	28.6%	7.8%	20.8%	3.6%	5.14	3.67	—
2022	24	MIX MLE	2 levels	26	24	116	490	88	34	15	92%	4.5	13.3%	7.7%	5.6%	4.2%	4.10	5.28	—
2022	24	MIX RAW	2 levels	26	24	116	490	88	34	15	92%	4.5	18.0%	6.9%	11.0%	3.1%	4.10	4.14	—
2023	25	MIX MLE	2 levels	26	25	117	520	92	55	16	96%	4.5	14.9%	10.0%	4.9%	3.0%	5.31	4.77	—
2023	25	MIX RAW	2 levels	26	25	117	520	92	55	16	96%	4.5	17.7%	10.6%	7.1%	3.1%	5.31	4.72	—
2024	26	AA MLE	Harrisburg Senators	17	15	83	339	51	20	6	88%	4.9	12.2%	6.5%	5.7%	2.1%	3.02	4.07	—
2024	26	AA MLE	Harrisburg Senators	17	15	83	339	51	20	6	88%	4.9	12.2%	6.5%	5.7%	2.1%	3.02	4.07	—
2024	26	AA RAW	Harrisburg Senators	17	15	83	339	51	20	6	88%	4.9	15.0%	5.9%	9.1%	1.8%	3.02	3.53	—
2025	27	MIX MLE	2 levels	25	24	113	497	97	43	16	96%	4.5	17.0%	7.9%	9.0%	3.8%	5.03	4.74	—
2025	27	MIX MLE	2 levels	25	24	113	497	97	43	16	96%	4.5	17.0%	7.9%	9.0%	3.8%	5.03	4.74	—
2025	27	MIX RAW	2 levels	25	24	113	497	97	43	16	96%	4.5	19.5%	8.7%	10.9%	3.2%	5.03	4.37	—
2026	28	MIX MLE	2 levels	33	10	81	363	79	29	12	30%	2.5	18.6%	7.3%	11.4%	3.5%	5.64	4.37	+0.2
2026	28	MIX MLE	2 levels	33	10	81	363	79	29	12	30%	2.5	18.6%	7.3%	11.4%	3.5%	5.64	4.37	+0.2
2026	28	MIX RAW	2 levels	33	10	81	363	79	29	12	30%	2.5	21.8%	8.0%	13.8%	3.3%	5.64	4.15	+0.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			1	0	3	17	4	1	1	0%	3.0	23.5%	5.9%	17.6%	5.9%	6.00	5.77	-0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	TB	8	8	46	194	32	16	6	100%	5.8	16.5%	8.0%	8.5%	3.3%	4.90	4.90	+0.3
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	TB	10	10	57	242	41	20	8	100%	5.7	16.9%	8.4%	8.5%	3.5%	4.95	5.02	+0.2
2029	31	MLB MLE	TB	8	8	49	207	35	18	8	100%	6.1	17.0%	8.8%	8.1%	3.7%	5.06	5.17	+0.1
2028	30	MLB CTX	TB	7	7	43	182	31	15	6	100%	6.1	16.9%	8.4%	8.5%	3.5%	4.95	5.02	+0.2
2029	31	MLB CTX	TB	7	7	40	169	29	15	6	100%	5.7	17.0%	8.8%	8.1%	3.7%	5.06	5.17	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		15	14	87	370	64	31	14	93%	5.8	17.2%	8.5%	8.7%	3.7%	5.04	4.73	+0.7
/ 200 IP	—	RAW		34	32	200	854	148	72	32	93%	5.8	17.2%	8.5%	8.7%	3.7%	5.04	4.73	+1.5
Career	—	MLE		145	116	579	2517	402	206	90	80%	4.0	16.0%	8.2%	7.8%	3.6%	4.71	4.76	+0.4
/ 200 IP	—	MLE		50	40	200	869	139	71	31	80%	4.0	16.0%	8.2%	7.8%	3.6%	4.71	4.76	+0.7

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 AAALouisville Bats · 78 IPFIP 4.04 → 4.37 (+0.33)K% 21.7% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.68%	—	×0.860	18.64%
BB% (unintentional) /BF	8.09%	—	×0.900	7.28%
HR / BF /BF	3.18%	÷1.000	×1.100	3.50%

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 4.04 → 4.37, 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 AAARochester Red Wings · 110 IPFIP 4.36 → 4.74 (+0.38)K% 19.7% → 17.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.71%	—	×0.860	16.95%
BB% (unintentional) /BF	8.83%	—	×0.900	7.95%
HR / BF /BF	3.29%	÷0.960	×1.100	3.77%

Result: FIP 4.36 → 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).

2024 AAHarrisburg Senators · 83 IPFIP 3.55 → 4.07 (+0.52)K% 15.0% → 12.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	15.04%	—	×0.810	12.19%
BB% (unintentional) /BF	5.90%	—	×1.100	6.49%
HR / BF /BF	1.77%	÷0.990	×1.200	2.15%

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 98).

Result: FIP 3.55 → 4.07, 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 AAACharlotte Knights · 78 IPFIP 5.25 → 5.21 (−0.04)K% 17.6% → 15.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.65%	—	×0.860	15.18%
BB% (unintentional) /BF	11.76%	—	×0.900	10.59%
HR / BF /BF	3.92%	÷1.152	×1.100	3.74%

Result: FIP 5.25 → 5.21, 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 AABirmingham Barons · 39 IPFIP 3.28 → 3.79 (+0.51)K% 17.8% → 14.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.79%	—	×0.810	14.41%
BB% (unintentional) /BF	7.98%	—	×1.100	8.77%
HR / BF /BF	1.23%	÷1.013	×1.200	1.45%

Result: FIP 3.28 → 3.79, 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).

2022 A+Winston-Salem Dash · 110 IPFIP 4.27 → 5.28 (+1.01)K% 17.3% → 13.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.28%	—	×0.770	13.30%
BB% (unintentional) /BF	6.70%	—	×1.150	7.70%
HR / BF /BF	3.24%	÷0.955	×1.250	4.24%

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 91).

Result: FIP 4.27 → 5.28, 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 AABirmingham Barons · 6 IPFIP 2.01 → 2.62 (+0.62)K% 29.6% → 24.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.63%	—	×0.810	24.00%
BB% (unintentional) /BF	11.11%	—	×1.100	12.22%
HR / BF /BF	0.00%	÷1.056	×1.200	0.00%

Result: FIP 2.01 → 2.62, 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 AKannapolis Cannon Ballers · 51 IPFIP 3.26 → 4.81 (+1.55)K% 30.7% → 22.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.74%	—	×0.740	22.74%
BB% (unintentional) /BF	8.66%	—	×1.180	10.22%
HR / BF /BF	3.03%	÷0.925	×1.300	4.26%

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 85).

Result: FIP 3.26 → 4.81, 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).

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
Chase Solesky (OGILVIE)	—	—	4.90	16.5%	8.0%	3.3%	—	5.09	16.9%	8.3%	106	+0.19	—	—	—
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	77
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	75
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	73
Juan Omar Espinoza R 2015 · 4.81 FIP	31	SP-	4.81	8.9%	6.6%	3.0%	.346	4.84	8.4%	-0.8%	52	+0.03	4.81	104	72
Reinier Roibal R 2019 · 4.91 FIP	30	SP	4.91	17.5%	11.8%	3.3%	.426	—	—	—	—	—	3.11	133	70
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	67
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	67
Jon Leicester R 2007 · 4.44 FIP	28	SP-	4.44	11.0%	9.0%	2.1%	.292	—	—	—	—	—	3.76	113	66
Noah Song R 2023 · 6.06 FIP	26	SP	6.06	12.0%	13.2%	4.2%	.239	3.80	19.8%	8.3%	116	-2.26	3.68	138	66
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	65
Edgar Alberto Garcia R 2017 · 4.01 FIP	29	SP-	4.01	17.3%	10.9%	1.8%	.305	—	—	—	—	—	4.01	272	64
Seth Greisinger R 2004 · 5.38 FIP	29	SP-	5.38	15.5%	6.0%	5.1%	.327	—	—	—	—	—	4.53	219	64
Bradin Hagens R 2018 · 4.92 FIP	29	SP-	4.92	14.9%	9.9%	3.3%	.341	5.46	13.2%	0.6%	66	+0.54	3.79	254	64
Rolando Valdez R 2015 · 4.07 FIP	29	SP	4.07	13.3%	5.9%	2.4%	.301	3.78	13.2%	7.9%	176	-0.29	3.06	258	64
Ariel Prieto R 2000 · 4.24 FIP	30	SP-	4.24	12.8%	8.8%	2.0%	.345	—	—	—	—	—	4.05	340	64
Carlos Frías R 2019 · 4.42 FIP	29	SP-	4.42	16.9%	11.1%	2.4%	.369	—	—	—	—	—	3.40	236	64
Kenneth Sigman R 2019 · 4.05 FIP	29	SP-	4.05	13.9%	7.7%	2.1%	.348	—	—	—	—	—	3.56	267	63
Gabriel Arias R 2019 · 4.11 FIP	29	SP-	4.11	13.9%	6.8%	2.4%	.300	—	—	—	—	—	4.11	195	63
Hiram Burgos R 2017 · 4.94 FIP	29	SP	4.94	19.3%	7.5%	4.6%	.351	—	—	—	—	—	3.40	384	62
Orlando Rodriguez R 2023 · 4.67 FIP	27	SW	4.67	13.7%	10.6%	2.5%	.252	—	—	—	—	—	4.40	119	62

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	0.9	59	16.9%	8.3%	1.36	4.98
Carlos Almánzar ('05)	1.2	60	16.3%	7.9%	1.32	4.82
Jose Cabrera ('02)	1.4	68	16.2%	7.9%	1.39	4.95
Ricky Stone ('07)	1.3	64	15.2%	8.0%	1.55	4.68
Steve Kealey ('68-'73, -1 WAR*)	1.1	54	18.5%*	7.2%*	1.32*	5.26*
Randy St. Claire ('84-'94, -0 WAR*)	1.3	50	19.0%*	8.4%*	1.39*	4.61*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*