Tyler Santana

P Knoxville Smokies

Age 29 RHP 6'1" / 205 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	32	1	73	5.20	4.45	19.6%	9.8%	—	K 14.8% · BB 11.6% · FIP 5.69
2025	27	AACHC	35	1	64	4.06	3.38	18.2%	8.0%	—	K 14.7% · BB 8.8% · FIP 4.02
2026	28	MIX2 levels	31	0	59	5.61	4.99	18.7%	10.3%	—	K 15.4% · BB 10.0% · FIP 5.30
2027PROJ	29	MLBCHC	1	0	1	5.61	5.61	12.9%	10.7%	-0.0
2028PROJ31% MLB	30	MLBCHC	14	0	15	5.59	5.66	13.6%	10.8%	-0.2
2029PROJ51% MLB	31	MLBCHC	18	0	19	5.65	5.76	13.9%	11.0%	-0.3

Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff35Control50Command40

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 99%

CompsWillie Eyre (age 29) · Grant Black (age 29) · Benjamin Sandoval (age 29)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 140132vR 123

ERA5.61

FIP5.61

K%12.9%

BB%10.7%

K-BB%2.2%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5050

CMD4040

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)
2021	23	MIX MLE	2 levels	9	1	20	83	23	10	1	11%	2.2	20.3%	15.1%	5.1%	1.8%	1.35	4.28	—
2021	23	MIX RAW	2 levels	9	1	20	83	23	10	1	11%	2.2	27.7%	12.0%	15.7%	1.2%	1.35	2.95	—
2022	24	A MLE	Myrtle Beach Pelicans	24	8	99	398	93	31	3	33%	4.1	17.3%	9.2%	8.1%	1.0%	2.28	3.37	—
2022	24	A RAW	Myrtle Beach Pelicans	24	8	99	398	93	31	3	33%	4.1	23.4%	7.8%	15.6%	0.8%	2.28	2.55	—
2023	25	A+ MLE	South Bend Cubs	30	9	91	390	78	35	9	30%	3.0	15.4%	10.3%	5.1%	2.4%	4.07	4.43	—
2023	25	A+ RAW	South Bend Cubs	30	9	91	390	78	35	9	30%	3.0	20.0%	9.0%	11.0%	2.3%	4.07	3.83	—
2024	26	MIX MLE	2 levels	32	1	73	327	64	32	10	3%	2.3	14.8%	11.6%	3.2%	4.3%	5.20	5.69	—
2024	26	MIX MLE	2 levels	32	1	73	327	64	32	10	3%	2.3	14.8%	11.6%	3.2%	4.3%	5.20	5.69	—
2024	26	MIX RAW	2 levels	32	1	73	327	64	32	10	3%	2.3	19.6%	9.8%	9.8%	3.1%	5.20	4.45	—
2025	27	AA MLE	Knoxville Smokies	35	1	64	275	50	22	4	3%	1.8	14.7%	8.8%	5.9%	1.9%	4.06	4.02	—
2025	27	AA MLE	Knoxville Smokies	35	1	64	275	50	22	4	3%	1.8	14.7%	8.8%	5.9%	1.9%	4.06	4.02	—
2025	27	AA RAW	Knoxville Smokies	35	1	64	275	50	22	4	3%	1.8	18.2%	8.0%	10.2%	1.5%	4.06	3.38	—
2026	28	MIX MLE	2 levels	31	0	59	273	51	28	10	0%	1.9	15.4%	10.0%	5.4%	4.1%	5.61	5.30	—
2026	28	MIX MLE	2 levels	31	0	59	273	51	28	10	0%	1.9	15.4%	10.0%	5.4%	4.1%	5.61	5.30	—
2026	28	MIX RAW	2 levels	31	0	59	273	51	28	10	0%	1.9	18.7%	10.3%	8.4%	3.7%	5.61	4.99	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	CHC	1	0	1	4	1	0	0	0%	1.0	12.9%	10.7%	2.2%	3.4%	5.61	5.61	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	CHC	45	0	47	198	27	21	7	0%	1.0	13.6%	10.8%	2.8%	3.6%	5.59	5.66	-0.6
2029	31	MLB MLE	CHC	36	0	38	159	22	18	6	0%	1.0	13.9%	11.0%	2.9%	3.7%	5.65	5.76	-0.5
2028	30	MLB CTX	CHC	14	0	15	63	9	7	2	0%	1.1	13.6%	10.8%	2.8%	3.6%	5.59	5.66	-0.2
2029	31	MLB CTX	CHC	18	0	19	80	11	9	3	0%	1.1	13.9%	11.0%	2.9%	3.7%	5.65	5.76	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		32	0	34	144	20	16	5	0%	1.1	13.8%	10.9%	2.8%	3.7%	5.62	5.34	-0.3
/ 200 IP	—	RAW		190	0	200	844	118	94	29	0%	1.1	13.8%	10.9%	2.8%	3.7%	5.62	5.34	-1.8
Career	—	MLE		161	20	406	1746	277	179	46	12%	2.5	15.8%	10.2%	5.6%	2.6%	3.93	4.49	-1.1
/ 200 IP	—	MLE		79	10	200	861	136	88	22	12%	2.5	15.8%	10.2%	5.6%	2.6%	3.93	4.49	-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.

2026 AAKnoxville Smokies · 33 IPFIP 2.28 → 2.86 (+0.59)K% 25.7% → 20.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.69%	—	×0.810	20.81%
BB% (unintentional) /BF	7.64%	—	×1.100	8.40%
HR / BF /BF	0.69%	÷1.000	×1.200	0.83%

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 100).

Result: FIP 2.28 → 2.86, 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).

2026 AAAIowa Cubs · 26 IPFIP 7.68 → 8.03 (+0.34)K% 10.9% → 9.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	10.85%	—	×0.860	9.33%
BB% (unintentional) /BF	13.18%	—	×0.900	11.86%
HR / BF /BF	6.98%	÷1.000	×1.100	7.67%

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 7.68 → 8.03, 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 AAKnoxville Smokies · 64 IPFIP 3.38 → 4.02 (+0.65)K% 18.2% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.18%	—	×0.810	14.73%
BB% (unintentional) /BF	8.00%	—	×1.100	8.80%
HR / BF /BF	1.45%	÷0.911	×1.200	1.92%

Result: FIP 3.38 → 4.02, 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).

2024 A+South Bend Cubs · 70 IPFIP 4.48 → 5.69 (+1.21)K% 19.2% → 14.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.18%	—	×0.770	14.77%
BB% (unintentional) /BF	10.06%	—	×1.150	11.57%
HR / BF /BF	3.14%	÷0.909	×1.250	4.32%

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 82).

Result: FIP 4.48 → 5.69, 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 A+South Bend Cubs · 91 IPFIP 3.81 → 4.43 (+0.61)K% 20.0% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.00%	—	×0.770	15.40%
BB% (unintentional) /BF	8.97%	—	×1.150	10.32%
HR / BF /BF	2.31%	÷1.197	×1.250	2.41%

Result: FIP 3.81 → 4.43, 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 AMyrtle Beach Pelicans · 99 IPFIP 2.53 → 3.37 (+0.85)K% 23.4% → 17.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.37%	—	×0.740	17.29%
BB% (unintentional) /BF	7.79%	—	×1.180	9.19%
HR / BF /BF	0.75%	÷0.942	×1.300	1.04%

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 88).

Result: FIP 2.53 → 3.37, 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).

2021 A+South Bend Cubs · 18 IPFIP 3.27 → 4.28 (+1.01)K% 26.3% → 20.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.32%	—	×0.770	20.26%
BB% (unintentional) /BF	13.16%	—	×1.150	15.13%
HR / BF /BF	1.32%	÷0.928	×1.250	1.77%

Result: FIP 3.27 → 4.28, 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).

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 Santana (OGILVIE)	—	—	5.61	12.9%	10.7%	3.4%	—	5.70	13.7%	2.8%	84	+0.09	—	—	—
Willie Eyre R 2007 · 4.53 FIP	29	SU	4.53	13.7%	9.1%	2.6%	.306	2.87	11.1%	5.5%	18	-1.66	2.87	164	85
Grant Black R 2023 · 5.49 FIP	29	SU	5.49	15.9%	11.3%	4.2%	.352	—	—	—	—	—	4.46	215	82
Benjamin Sandoval R 2016 · 5.13 FIP	29	SU	5.13	6.7%	11.3%	2.1%	.292	5.51	9.0%	-4.4%	49	+0.38	4.66	146	79
Alex Caldera R 2015 · 5.57 FIP	29	SW	5.57	10.4%	13.1%	3.1%	.333	4.54	11.9%	0.8%	84	-1.03	4.54	120	79
Brian Bass R 2009 · 4.70 FIP	27	SU	4.70	13.5%	9.8%	2.8%	.321	—	—	—	—	—	4.70	176	79
Chris Jakubauskas R 2009 · 4.97 FIP	30	SW	4.97	12.1%	6.2%	3.9%	.250	4.42	15.7%	7.8%	72	-0.55	4.42	165	78
Beck Wheeler R 2017 · 5.40 FIP	28	SU	5.40	15.3%	12.2%	3.7%	.347	—	—	—	—	—	3.46	173	78
Angel Castro R 2015 · 4.50 FIP	32	SU	4.50	15.9%	8.0%	3.1%	.268	4.28	13.6%	5.5%	231	-0.22	3.51	292	78
Fredy Quintero R 2017 · 4.45 FIP	29	SW	4.45	14.0%	8.7%	2.6%	.335	4.62	17.2%	3.5%	43	+0.17	4.29	241	77
Mike Adams R 2022 · 5.36 FIP	27	SU	5.36	17.1%	11.2%	4.2%	.326	—	—	—	—	—	3.65	109	76
Jose Casilla R 2016 · 4.65 FIP	27	SU	4.65	13.0%	8.0%	3.0%	.314	—	—	—	—	—	3.06	104	75
Fernando Villalobos R 2015 · 5.33 FIP	30	SU	5.33	8.3%	13.1%	2.3%	.365	4.36	11.4%	3.1%	109	-0.97	4.00	152	75
Thad Weber R 2013 · 5.18 FIP	28	SU	5.18	16.4%	13.1%	3.3%	.244	4.52	12.2%	6.0%	308	-0.66	4.40	378	75
Eder Llamas R 2015 · 4.84 FIP	29	SU	4.84	12.3%	8.8%	3.0%	.261	3.64	11.3%	4.6%	120	-1.20	3.23	171	75
Tony Fiore R 2000 · 5.61 FIP	28	SU	5.61	10.8%	9.5%	4.0%	.321	4.76	14.3%	3.5%	127	-0.85	4.60	142	74
Kyle McMyne R 2017 · 4.84 FIP	27	SU	4.84	12.5%	12.8%	2.1%	.330	—	—	—	—	—	3.93	181	74
Jose Pina R 2015 · 4.90 FIP	29	SW	4.90	16.9%	9.2%	3.8%	.231	3.66	13.6%	6.9%	246	-1.24	3.63	424	74
Gregory Infante R 2016 · 4.47 FIP	29	SU	4.47	19.0%	12.3%	2.6%	.333	3.43	22.5%	15.8%	120	-1.04	2.97	230	74
Jason Boyd R 2002 · 5.81 FIP	29	SU	5.81	13.7%	10.7%	4.6%	.290	4.74	15.0%	3.7%	65	-1.07	3.68	128	74
Ramon Delgado R 2016 · 4.60 FIP	29	SW	4.60	13.8%	5.9%	3.5%	.332	4.31	11.2%	7.2%	74	-0.29	4.31	135	73

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	0.8	51	13.3%	10.8%	1.37	5.61
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
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*
Dennis Powell ('85-'93, -2 WAR*)	1.7	49	17.6%*	10.1%*	1.18*	5.31*
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*