Tony Santillan

P Cincinnati Reds

Age 30 RHP 6'3" / 285 lbs MLB

Overview

MLBRP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	27	MIX2 levels	67	1	69	3.28	2.90	33.4%	10.5%	1.4	K 30.9% · BB 9.7% · FIP 2.96
2025	28	MLBCIN	80	0	74	2.44	3.48	24.9%	9.6%	0.9
2026	29	MIX2 levels	47	1	44	5.98	6.28	20.5%	13.0%	-0.9	K 18.8% · BB 13.6% · FIP 6.16
2027PROJ	30	MLBCIN	37	0	39	4.45	4.74	24.2%	10.9%	-0.1
2028PROJ95% MLB	31	MLBCIN	27	0	28	4.76	4.97	23.4%	11.2%	-0.1
2029PROJ95% MLB	32	MLBCIN	19	0	20	5.04	5.23	22.7%	11.6%	-0.1

Last 3 seasons WAR 1.4 · Next 3 projected WAR -0.4Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo50

K%27

xwOBA vs10

CompsHirokazu Sawamura (age 33) · Jim Miller (age 30) · Bryan Mitchell (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 134126vR 118

ERA4.45

FIP4.74

K%24.2%

BB%10.9%

K-BB%13.3%

Proj IP39

Value2027 · WAR

Runs saved vs league avg · 39 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p5094.5

Whiff%

p3322.9%

p2718.8%

xwOBA vs

p100.385

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	18	ROK MLE	AZL Reds	8	7	20	85	19	11	1	88%	2.5	15.2%	16.2%	-1.0%	1.6%	5.03	4.77	—
2015	18	ROK RAW	AZL Reds	8	7	20	85	19	11	1	88%	2.5	22.4%	12.9%	9.4%	1.2%	5.03	3.51	—
2016	19	MIX MLE	2 levels	15	15	69	302	84	40	7	100%	4.6	19.7%	16.0%	3.7%	3.0%	5.19	5.10	—
2016	19	MIX RAW	2 levels	15	15	69	302	84	40	7	100%	4.6	27.8%	13.2%	14.6%	2.3%	5.19	3.72	—
2017	20	A MLE	Dayton Dragons	25	24	128	533	128	56	9	96%	5.1	17.8%	12.4%	5.4%	1.9%	3.38	4.20	—
2017	20	A RAW	Dayton Dragons	25	24	128	533	128	56	9	96%	5.1	24.0%	10.5%	13.5%	1.7%	3.38	3.33	—
2018	21	MIX MLE	2 levels	26	26	149	629	134	38	13	100%	5.7	16.8%	6.8%	10.0%	2.6%	3.08	3.98	—
2018	21	MIX RAW	2 levels	26	26	149	629	134	38	13	100%	5.7	21.3%	6.0%	15.3%	2.1%	3.08	3.20	—
2019	22	AA MLE	Chattanooga Lookouts	21	21	102	465	92	54	8	100%	4.9	16.0%	12.8%	3.3%	2.1%	4.84	4.52	—
2019	22	AA RAW	Chattanooga Lookouts	21	21	102	465	92	54	8	100%	4.9	19.8%	11.6%	8.2%	1.7%	4.84	3.90	—
2021	24	MIX MLE	2 levels	39	10	81	342	107	36	12	26%	2.1	29.5%	10.7%	18.8%	3.4%	2.55	3.82	+0.7
2021	24	MIX RAW	2 levels	39	10	81	342	107	36	12	26%	2.1	31.3%	10.5%	20.8%	3.5%	2.55	3.71	+0.8
2022	25	MLB MLE	Cincinnati Reds	21	0	20	96	21	11	1	0%	0.9	21.9%	11.5%	10.4%	1.0%	5.49	3.23	+0.3
2022	25	MLB RAW	Cincinnati Reds	21	0	20	96	21	11	1	0%	0.9	21.9%	11.5%	10.4%	1.0%	5.49	3.30	+0.3
2023	26	MIX MLE	2 levels	38	0	35	178	41	32	5	0%	0.9	21.5%	15.8%	5.8%	3.3%	7.39	5.07	-0.2
2023	26	MIX RAW	2 levels	38	0	35	178	41	32	5	0%	0.9	23.0%	18.0%	5.1%	2.8%	7.39	5.34	-0.3
2024	27	MIX MLE	2 levels	67	1	69	296	99	31	7	1%	1.0	30.9%	9.7%	21.2%	2.3%	3.28	2.96	+1.3
2024	27	MIX MLE	2 levels	67	1	69	296	99	31	7	1%	1.0	30.9%	9.7%	21.2%	2.3%	3.28	2.96	+1.3
2024	27	MIX RAW	2 levels	67	1	69	296	99	31	7	1%	1.0	33.4%	10.5%	23.0%	2.4%	3.28	2.90	+1.4
2025	28	MLB MLE	Cincinnati Reds	80	0	74	301	75	29	7	0%	0.9	24.9%	9.6%	15.3%	2.2%	2.44	3.40	+1.0
2025	28	MLB MLE	Cincinnati Reds	80	0	74	301	75	29	7	0%	0.9	24.9%	9.6%	15.3%	2.2%	2.44	3.40	+1.0
2025	28	MLB RAW	Cincinnati Reds	80	0	74	301	75	29	7	0%	0.9	24.9%	9.6%	15.3%	2.3%	2.44	3.48	+0.9
2026	29	MIX MLE	2 levels	47	1	44	200	41	26	11	2%	0.9	18.8%	13.6%	5.2%	5.3%	5.98	6.16	-0.8
2026	29	MIX MLE	2 levels	47	1	44	200	41	26	11	2%	0.9	18.8%	13.6%	5.2%	5.3%	5.98	6.16	-0.8
2026	29	MIX RAW	2 levels	47	1	44	200	41	26	11	2%	0.9	20.5%	13.0%	7.5%	5.5%	5.98	6.28	-0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			203	5	211	918	235	100	30	2%	1.0	25.6%	10.9%	14.7%	3.3%	3.67	4.14	+1.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	CIN	37	0	39	165	40	18	6	0%	1.1	24.2%	10.9%	13.3%	3.5%	4.45	4.74	-0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	CIN	29	0	30	127	30	14	5	0%	1.0	23.4%	11.2%	12.2%	3.7%	4.76	4.97	-0.1
2029	32	MLB MLE	CIN	20	0	21	90	20	10	4	0%	1.1	22.7%	11.6%	11.0%	4.0%	5.04	5.23	-0.2
2030	33	MLB MLE	CIN	13	0	14	60	13	7	3	0%	1.1	21.8%	12.1%	9.7%	4.3%	5.32	5.51	-0.1
2028	31	MLB CTX	CIN	27	0	28	118	28	13	4	0%	1.0	23.4%	11.2%	12.2%	3.7%	4.76	4.97	-0.1
2029	32	MLB CTX	CIN	19	0	20	84	19	10	3	0%	1.1	22.7%	11.6%	11.0%	4.0%	5.04	5.23	-0.1
2030	33	MLB CTX	CIN	12	0	13	55	12	7	2	0%	1.1	21.8%	12.1%	9.7%	4.3%	5.32	5.51	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		262	5	273	1180	295	130	40	2%	1.0	25.0%	11.0%	13.9%	3.4%	3.97	4.26	+0.9
/ 200 IP	—	RAW		192	4	200	865	216	95	29	2%	1.0	25.0%	11.0%	13.9%	3.4%	3.97	4.26	+0.7
Career	—	MLE		387	105	791	3427	712	391	89	27%	2.0	20.8%	11.4%	9.3%	2.6%	3.90	4.21	+0.5
/ 200 IP	—	MLE		98	27	200	867	180	99	22	27%	2.0	20.8%	11.4%	9.3%	2.6%	3.90	4.21	+0.4

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.

2024 AAALouisville Bats · 39 IPFIP 3.08 → 3.27 (+0.19)K% 30.5% → 26.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.46%	—	×0.860	26.20%
BB% (unintentional) /BF	12.64%	—	×0.900	11.38%
HR / BF /BF	1.72%	÷1.111	×1.100	1.71%

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 122).

Result: FIP 3.08 → 3.27, 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 AAALouisville Bats · 32 IPFIP 4.92 → 5.07 (+0.15)K% 25.0% → 21.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.00%	—	×0.860	21.50%
BB% (unintentional) /BF	17.50%	—	×0.900	15.75%
HR / BF /BF	3.12%	÷1.054	×1.100	3.26%

Result: FIP 4.92 → 5.07, 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).

2021 AAALouisville Bats · 38 IPFIP 3.32 → 3.74 (+0.42)K% 33.6% → 29.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.55%	—	×0.880	29.53%
BB% (unintentional) /BF	9.87%	—	×1.050	10.36%
HR / BF /BF	3.29%	÷1.088	×1.100	3.33%

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 118).

Result: FIP 3.32 → 3.74, 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).

2019 AAChattanooga Lookouts · 102 IPFIP 3.84 → 4.52 (+0.68)K% 19.8% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.78%	—	×0.810	16.03%
BB% (unintentional) /BF	11.61%	—	×1.100	12.77%
HR / BF /BF	1.72%	÷0.979	×1.200	2.11%

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 96).

Result: FIP 3.84 → 4.52, 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+Daytona Tortugas · 87 IPFIP 2.92 → 3.57 (+0.65)K% 20.2% → 15.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.22%	—	×0.770	15.57%
BB% (unintentional) /BF	6.09%	—	×1.150	7.01%
HR / BF /BF	1.39%	÷1.058	×1.250	1.64%

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 112).

Result: FIP 2.92 → 3.57, 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 AAPensacola Blue Wahoos · 62 IPFIP 3.57 → 4.54 (+0.96)K% 22.8% → 18.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.76%	—	×0.810	18.44%
BB% (unintentional) /BF	5.97%	—	×1.100	6.57%
HR / BF /BF	2.99%	÷0.909	×1.200	3.94%

Result: FIP 3.57 → 4.54, 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).

2017 ADayton Dragons · 128 IPFIP 3.33 → 4.20 (+0.87)K% 24.0% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.02%	—	×0.740	17.77%
BB% (unintentional) /BF	10.51%	—	×1.180	12.40%
HR / BF /BF	1.69%	÷1.168	×1.300	1.88%

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 134).

Result: FIP 3.33 → 4.20, 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 ROKBillings Mustangs · 39 IPFIP 3.31 → 4.91 (+1.60)K% 28.0% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.05%	—	×0.680	19.07%
BB% (unintentional) /BF	9.76%	—	×1.250	12.20%
HR / BF /BF	2.44%	÷1.000	×1.400	3.41%

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 3.31 → 4.91, 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).

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
Tony Santillan (OGILVIE)	—	—	—	—	—	3.5%	—	5.17	22.8%	11.3%	65	+0.43	—	—	—
Hirokazu Sawamura R 2021 · 4.48 FIP	33	SU	4.48	26.2%	11.2%	4.0%	.263	4.02	18.1%	6.8%	51	-0.46	4.02	104	71
Jim Miller R 2012 · 4.56 FIP	30	SU	4.56	20.9%	11.8%	3.1%	.243	3.95	18.8%	14.7%	74	-0.61	3.95	140	68
Bryan Mitchell R 2021 · 4.29 FIP	30	SU	4.29	20.6%	12.0%	2.5%	.305	5.07	14.4%	3.9%	39	+0.78	2.72	481	68
Joe Nelson R 2006 · 3.91 FIP	31	SU	3.91	22.8%	10.4%	2.6%	.258	4.05	23.4%	12.8%	94	+0.14	3.08	139	68
Dustin Molleken R 2015 · 3.74 FIP	30	SU	3.74	20.4%	11.7%	1.6%	.287	3.90	20.6%	8.4%	77	+0.16	3.38	129	67
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	67
John Axford R 2013 · 4.25 FIP	30	SU	4.25	22.5%	8.0%	3.7%	.330	3.73	23.6%	12.2%	176	-0.52	1.90	518	67
Britt Reames R 2002 · 3.76 FIP	28	SU	3.76	24.7%	10.4%	2.6%	.323	—	—	—	—	—	3.76	204	67
Mike Broadway R 2017 · 4.73 FIP	30	SU	4.73	18.3%	10.2%	3.4%	.245	4.65	23.0%	12.4%	49	-0.08	1.74	195	66
Erik Davis R 2017 · 4.25 FIP	30	SU	4.25	22.2%	11.1%	3.0%	.349	3.52	17.4%	8.5%	65	-0.73	3.05	227	66
Neil Wagner R 2013 · 4.02 FIP	29	SU	4.02	20.5%	7.5%	3.1%	.306	4.05	19.8%	7.5%	43	+0.03	3.11	135	65
Manny Acosta R 2011 · 3.75 FIP	30	SU	3.75	22.5%	7.4%	2.9%	.321	4.49	21.3%	10.2%	47	+0.74	3.08	350	65
Jeremy Fikac R 2004 · 4.91 FIP	29	SU	4.91	19.6%	8.0%	4.5%	.276	—	—	—	—	—	3.10	136	65
Heath Hembree R 2019 · 4.30 FIP	30	SU	4.30	26.6%	9.2%	4.2%	.260	5.30	27.8%	17.4%	99	+1.00	2.52	382	65
Wirfin Obispo R 2015 · 4.80 FIP	30	SU	4.80	18.6%	12.2%	3.1%	.292	1.31	28.6%	24.5%	126	-3.49	1.30	218	65
Hector Velázquez R 2019 · 4.82 FIP	30	SW	4.82	19.6%	12.3%	3.3%	.292	3.81	19.2%	10.9%	25	-1.01	2.75	536	64
Ryan Tepera R 2018 · 3.90 FIP	30	SU	3.90	25.9%	8.7%	3.4%	.282	3.20	28.4%	19.9%	104	-0.70	2.35	445	64
Guillermo Moscoso R 2013 · 5.15 FIP	29	SU	5.15	24.2%	14.1%	4.2%	.203	—	—	—	—	—	3.56	486	64
Troy Percival R 2000 · 4.46 FIP	30	SU	4.46	22.2%	11.8%	3.2%	.252	3.15	28.2%	18.8%	163	-1.31	2.15	709	64
Blake Smith R 2016 · 3.59 FIP	28	SU	3.59	22.4%	8.6%	2.4%	.307	—	—	—	—	—	3.17	124	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	1.6	39	24.9%	11.3%	1.33	4.04
Chasen Shreve ('24)	1.8	45	25.2%	10.8%	1.54	3.96
Dominic Leone ('24)	2.1	54	23.9%	10.4%	1.26	3.94
Louis Coleman ('18)	1.4	46	23.4%	10.8%	1.17	3.51
Alberto Reyes ('95-'08, 5 WAR*)	2.1	54	27.1%*	10.2%*	1.18*	3.66*
Mac Scarce ('72-'78, 1 WAR*)	1.0	52	25.9%*	12.4%*	1.27*	4.17*
Bill Scherrer ('82-'88, 1 WAR*)	1.6	62	20.7%*	10.2%*	1.19*	4.44*