Tyler Ivey

P Sugar Land Space Cowboys

Age 31 RHP 6'4" / 195 lbs AAA peak 0.2 · 2027

Overview

AAASPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2021	25	MIX3 levels	6	5	18	5.09	4.85	23.5%	12.3%	0.1	K 21.2% · BB 15.6% · FIP 5.67
2022	26	AAAHOU	5	2	13	10.38	5.10	26.2%	10.8%	—	K 23.0% · BB 11.3% · FIP 5.63
2025	29	AAAHOU	27	25	122	5.83	4.97	18.4%	11.9%	—	K 15.8% · BB 10.7% · FIP 5.16
2026	30	No MLB games played
2027PROJ	31	MLBHOU	1	1	8	5.57	5.57	15.0%	12.4%	-0.0
2028PROJ37% MLB	32	MLBHOU	4	4	21	5.58	5.67	15.4%	12.4%	-0.1
2029PROJ55% MLB	33	MLBHOU	4	4	25	5.68	5.81	15.5%	12.7%	-0.1

Last 3 seasons WAR 0.1 · Next 3 projected WAR -0.2Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control40Command35

CompsMiguel Ruiz (age 31) · Daniel Guerrero (age 31) · David Fletcher (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 139131vR 123

ERA5.57

FIP5.57

K%15.0%

BB%12.4%

K-BB%2.7%

Proj IP79

Value2027 · WAR

Runs saved vs league avg · 79 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL4040

CMD3535

K†3030

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)
2017	21	ROK MLE	GCL Astros	1	1	2	8	3	2	0	100%	2.0	37.5%	25.0%	12.5%	0.0%	0.00	3.10	—
2017	21	ROK RAW	GCL Astros	1	1	2	8	3	2	0	100%	2.0	37.5%	25.0%	12.5%	0.0%	0.00	3.10	—
2018	22	MIX MLE	2 levels	24	18	112	455	135	29	5	75%	4.7	22.5%	7.4%	15.1%	1.4%	2.97	2.93	—
2018	22	MIX RAW	2 levels	24	18	112	455	135	29	5	75%	4.7	29.7%	6.4%	23.3%	1.1%	2.97	2.05	—
2019	23	MIX MLE	3 levels	14	11	52	205	68	20	5	79%	3.7	26.9%	9.6%	17.3%	3.1%	1.38	3.72	—
2019	23	MIX RAW	3 levels	14	11	52	205	68	20	5	79%	3.7	33.2%	9.8%	23.4%	2.4%	1.38	2.89	—
2021	25	MIX MLE	3 levels	6	5	18	81	19	10	3	83%	2.9	21.2%	15.6%	5.6%	4.4%	5.09	5.67	-0.1
2021	25	MIX RAW	3 levels	6	5	18	81	19	10	3	83%	2.9	23.5%	12.3%	11.1%	3.7%	5.09	4.85	+0.1
2022	26	AAA MLE	Sugar Land Space Cowboys	5	2	13	65	17	7	3	40%	2.6	23.0%	11.3%	11.7%	5.5%	10.38	5.63	—
2022	26	AAA RAW	Sugar Land Space Cowboys	5	2	13	65	17	7	3	40%	2.6	26.2%	10.8%	15.4%	4.6%	10.38	5.10	—
2025	29	AAA MLE	Sugar Land Space Cowboys	27	25	122	554	102	66	18	93%	4.5	15.8%	10.7%	5.1%	3.7%	5.83	5.16	—
2025	29	AAA MLE	Sugar Land Space Cowboys	27	25	122	554	102	66	18	93%	4.5	15.8%	10.7%	5.1%	3.7%	5.83	5.16	—
2025	29	AAA RAW	Sugar Land Space Cowboys	27	25	122	554	102	66	18	93%	4.5	18.4%	11.9%	6.5%	3.2%	5.83	4.97	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			1	1	5	20	3	1	1	100%	4.7	15.0%	5.0%	10.0%	5.0%	7.71	5.24	+0.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	31	MLB	HOU	1	1	8	34	5	4	1	100%	8.0	15.0%	12.4%	2.7%	3.3%	5.57	5.57	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	32	MLB MLE	HOU	10	10	57	242	37	30	8	100%	5.7	15.4%	12.4%	3.0%	3.5%	5.58	5.67	-0.2
2029	33	MLB MLE	HOU	8	8	46	193	30	24	7	100%	5.7	15.5%	12.7%	2.8%	3.7%	5.68	5.81	-0.2
2028	32	MLB CTX	HOU	4	4	21	89	14	11	3	100%	5.2	15.4%	12.4%	3.0%	3.5%	5.58	5.67	-0.1
2029	33	MLB CTX	HOU	4	4	25	106	16	13	4	100%	6.2	15.5%	12.7%	2.8%	3.7%	5.68	5.81	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		9	9	51	215	33	25	8	100%	5.6	15.4%	11.9%	3.6%	3.7%	5.83	5.35	+0.0
/ 200 IP	—	RAW		34	34	200	846	130	98	31	100%	5.8	15.4%	11.9%	3.6%	3.7%	5.83	5.35	+0.1
Career	—	MLE		77	62	319	1368	280	135	41	81%	4.1	20.5%	9.8%	10.7%	3.0%	4.21	4.24	-0.4
/ 200 IP	—	MLE		48	39	200	859	176	84	25	81%	4.1	20.5%	9.8%	10.7%	3.0%	4.21	4.24	-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.

2025 AAASugar Land Space Cowboys · 122 IPFIP 4.84 → 5.16 (+0.32)K% 18.4% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.41%	—	×0.860	15.83%
BB% (unintentional) /BF	11.91%	—	×0.900	10.72%
HR / BF /BF	3.25%	÷0.961	×1.100	3.72%

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 92).

Result: FIP 4.84 → 5.16, 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 AAASugar Land Space Cowboys · 13 IPFIP 4.79 → 5.63 (+0.84)K% 26.2% → 23.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.15%	—	×0.880	23.02%
BB% (unintentional) /BF	10.77%	—	×1.050	11.31%
HR / BF /BF	4.62%	÷0.917	×1.100	5.54%

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 83).

Result: FIP 4.79 → 5.63, 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 AAASugar Land Skeeters · 11 IPFIP 4.98 → 5.67 (+0.70)K% 24.1% → 21.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.07%	—	×0.880	21.19%
BB% (unintentional) /BF	14.81%	—	×1.050	15.56%
HR / BF /BF	3.70%	÷0.935	×1.100	4.36%

Result: FIP 4.98 → 5.67, 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 AACorpus Christi Hooks · 46 IPFIP 2.89 → 3.72 (+0.83)K% 33.2% → 26.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.15%	—	×0.810	26.85%
BB% (unintentional) /BF	8.70%	—	×1.100	9.57%
HR / BF /BF	2.72%	÷1.067	×1.200	3.06%

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 113).

Result: FIP 2.89 → 3.72, 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 A+Buies Creek Astros · 70 IPFIP 2.18 → 3.05 (+0.87)K% 28.9% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.87%	—	×0.770	22.23%
BB% (unintentional) /BF	7.39%	—	×1.150	8.50%
HR / BF /BF	1.06%	÷0.962	×1.250	1.37%

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 92).

Result: FIP 2.18 → 3.05, 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).

2018 AQuad Cities River Bandits · 42 IPFIP 1.72 → 2.72 (+1.00)K% 31.0% → 22.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.99%	—	×0.740	22.94%
BB% (unintentional) /BF	4.68%	—	×1.180	5.52%
HR / BF /BF	1.17%	÷0.973	×1.300	1.56%

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 95).

Result: FIP 1.72 → 2.72, 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
Tyler Ivey (OGILVIE)	—	—	5.57	15.0%	12.4%	3.3%	—	5.73	15.4%	2.9%	103	+0.16	—	—	—
Miguel Ruiz R 2017 · 5.60 FIP	31	SP	5.60	10.6%	11.0%	3.6%	.279	—	—	—	—	—	5.60	117	80
Daniel Guerrero R 2016 · 4.81 FIP	31	SP	4.81	12.4%	11.6%	2.3%	.328	4.93	11.7%	2.0%	175	+0.12	4.61	269	78
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	78
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
Hector Galvan R 2019 · 4.84 FIP	31	SP-	4.84	14.3%	12.2%	2.6%	.357	—	—	—	—	—	3.59	406	75
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	74
Alex Caldera R 2016 · 4.54 FIP	30	SP	4.54	11.9%	11.1%	1.9%	.280	—	—	—	—	—	4.54	120	72
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	70
Walter Silva R 2009 · 5.72 FIP	32	SP	5.72	9.1%	12.4%	3.3%	.330	—	—	—	—	—	3.67	453	70
Reinier Roibal R 2019 · 4.91 FIP	30	SP	4.91	17.5%	11.8%	3.3%	.426	—	—	—	—	—	3.11	133	70
Scott Copeland R 2019 · 5.62 FIP	31	SP-	5.62	17.1%	12.4%	4.4%	.311	—	—	—	—	—	3.55	569	69
Luis Mateo R 2019 · 5.55 FIP	29	SP-	5.55	8.6%	13.4%	2.7%	.303	—	—	—	—	—	3.48	160	68
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	68
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	68
Nate Long R 2015 · 4.67 FIP	29	SP	4.67	14.8%	10.6%	2.7%	.285	—	—	—	—	—	4.67	151	66
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	65
Derek Eitel R 2017 · 4.72 FIP	29	SP-	4.72	17.2%	16.0%	1.9%	.273	—	—	—	—	—	3.96	138	65
Cody Mincey R 2022 · 5.56 FIP	30	SP	5.56	13.9%	8.4%	4.7%	.297	—	—	—	—	—	2.49	147	65
Erik Hiljus R 2002 · 6.07 FIP	29	SP	6.07	14.1%	9.7%	5.3%	.281	—	—	—	—	—	3.35	112	64
Kohei Arihara R 2022 · 4.58 FIP	29	SP-	4.58	16.4%	7.2%	3.5%	.333	—	—	—	—	—	4.58	135	63

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	62	15.2%	12.3%	1.35	5.65
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Matt Perisho ('05)	1.4	69	15.2%	12.2%	1.37	6.39
Luther Hackman ('03)	1.1	71	13.3%	10.9%	1.10	5.09
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*
Bill Wilson ('69-'73, -0 WAR*)	1.3	52	20.3%*	11.5%*	1.13*	4.84*