Yerry De los Santos

P Scranton/Wilkes-Barre RailRiders

Age 29 RHP 6'3" / 230 lbs AAA peak 0.3 · 2027

Overview

AAARP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	AAAScranton/Wilk…	51	1	59	4.12	4.18	21.3%	7.4%	—	K 18.3% · BB 6.6% · FIP 4.41
2025	27	MIX3 levels	43	0	53	3.04	3.51	20.3%	9.3%	0.7	K 18.9% · BB 9.3% · FIP 3.40
2026	28	MIX2 levels	52	2	70	3.36	3.14	23.4%	7.1%	1.2	K 20.9% · BB 6.6% · FIP 3.28
2027PROJ	29	MLBNYY	61	0	64	4.22	4.35	19.7%	9.0%	0.1
2028PROJ92% MLB	30	MLBNYY	35	0	37	4.42	4.56	19.0%	9.3%	-0.0
2029PROJ93% MLB	31	MLBNYY	22	0	23	4.64	4.79	18.2%	9.7%	-0.1

Last 3 seasons WAR 1.8 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

FB Velo54

xwOBA vs31

K%22

CompsNeil Wagner (age 29) · Diego Moreno (age 29) · Mark Serrano (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 116108vR 100

ERA4.22

FIP4.35

K%19.7%

BB%9.0%

K-BB%10.7%

Proj IP71

Value2027 · WAR

Runs saved vs league avg · 71 IP

Grades · Statcast · Contract

Scouting Grades

STUF4545

CTRL4040

CMD3535

K†4545

Statcast Percentiles

FB Velo

p5494.8

Whiff%

p1016.0%

p2218.1%

xwOBA vs

p310.334

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	17	ROK MLE	DSL Pirates	14	14	59	265	28	17	1	100%	4.2	7.2%	8.0%	-0.8%	0.5%	4.73	3.80	—
2015	17	ROK RAW	DSL Pirates	14	14	59	265	28	17	1	100%	4.2	10.6%	6.4%	4.2%	0.4%	4.73	3.24	—
2017	19	ROK MLE	DSL Pirates	5	0	9	35	4	3	0	0%	1.7	11.4%	8.6%	2.9%	0.0%	1.04	3.22	—
2017	19	ROK RAW	DSL Pirates	5	0	9	35	4	3	0	0%	1.7	11.4%	8.6%	2.9%	0.0%	1.04	3.22	—
2018	20	ROK MLE	Bristol Pirates	12	0	18	76	24	8	0	0%	1.5	21.5%	13.2%	8.3%	0.0%	2.45	2.95	—
2018	20	ROK RAW	Bristol Pirates	12	0	18	76	24	8	0	0%	1.5	31.6%	10.5%	21.1%	0.0%	2.45	1.79	—
2019	21	A MLE	Greensboro Grasshoppers	37	0	50	192	73	12	3	0%	1.4	28.1%	7.4%	20.8%	2.0%	1.44	2.76	—
2019	21	A RAW	Greensboro Grasshoppers	37	0	50	192	73	12	3	0%	1.4	38.0%	6.2%	31.8%	1.6%	1.44	1.68	—
2021	23	MIX MLE	2 levels	16	0	24	92	25	6	2	0%	1.5	21.4%	7.6%	13.7%	3.5%	1.52	4.19	—
2021	23	MIX RAW	2 levels	16	0	24	92	25	6	2	0%	1.5	27.2%	6.5%	20.7%	2.2%	1.52	2.85	—
2022	24	MIX MLE	2 levels	38	0	41	170	46	12	4	0%	1.1	25.6%	7.1%	18.5%	2.5%	3.70	3.23	+0.6
2022	24	MIX RAW	2 levels	38	0	41	170	46	12	4	0%	1.1	27.1%	7.1%	20.0%	2.4%	3.70	3.00	+0.8
2023	25	MIX MLE	2 levels	45	0	49	233	46	24	5	0%	1.1	18.1%	9.7%	8.4%	2.2%	4.74	4.00	+0.3
2023	25	MIX RAW	2 levels	45	0	49	233	46	24	5	0%	1.1	19.7%	10.3%	9.4%	2.1%	4.74	4.01	+0.3
2024	26	AAA MLE	Scranton/Wilkes-Barre RailRiders	51	1	59	258	55	19	9	2%	1.2	18.3%	6.6%	11.7%	3.7%	4.12	4.41	—
2024	26	AAA MLE	Scranton/Wilkes-Barre RailRiders	51	1	59	258	55	19	9	2%	1.2	18.3%	6.6%	11.7%	3.7%	4.12	4.41	—
2024	26	AAA RAW	Scranton/Wilkes-Barre RailRiders	51	1	59	258	55	19	9	2%	1.2	21.3%	7.4%	14.0%	3.5%	4.12	4.18	—
2025	27	MIX MLE	3 levels	43	0	53	236	48	22	4	0%	1.2	18.9%	9.3%	9.6%	1.3%	3.04	3.40	+0.7
2025	27	MIX MLE	3 levels	43	0	53	236	48	22	4	0%	1.2	18.9%	9.3%	9.6%	1.3%	3.04	3.40	+0.7
2025	27	MIX RAW	3 levels	43	0	53	236	48	22	4	0%	1.2	20.3%	9.3%	11.0%	1.7%	3.04	3.51	+0.7
2026	28	MIX MLE	2 levels	52	2	70	295	69	21	6	4%	1.3	20.9%	6.6%	14.3%	2.0%	3.36	3.28	+1.1
2026	28	MIX MLE	2 levels	52	2	70	295	69	21	6	4%	1.3	20.9%	6.6%	14.3%	2.0%	3.36	3.28	+1.1
2026	28	MIX RAW	2 levels	52	2	70	295	69	21	6	4%	1.3	23.4%	7.1%	16.3%	2.0%	3.36	3.14	+1.2
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			89	0	108	470	89	44	9	0%	1.2	18.9%	9.4%	9.6%	1.9%	3.43	3.76	+1.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	NYY	61	0	64	270	53	24	7	0%	1.0	19.7%	9.0%	10.7%	2.5%	4.22	4.35	+0.1
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	NYY	38	0	40	170	32	16	5	0%	1.1	19.0%	9.3%	9.7%	2.7%	4.42	4.56	-0.0
2029	31	MLB MLE	NYY	23	0	25	104	19	10	3	0%	1.1	18.2%	9.7%	8.6%	3.0%	4.64	4.79	-0.1
2028	30	MLB CTX	NYY	35	0	37	156	30	15	4	0%	1.1	19.0%	9.3%	9.7%	2.7%	4.42	4.56	-0.0
2029	31	MLB CTX	NYY	22	0	23	97	18	9	3	0%	1.0	18.2%	9.7%	8.6%	3.0%	4.64	4.79	-0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		146	0	167	722	136	68	16	0%	1.1	18.9%	9.4%	9.5%	2.2%	3.81	3.92	+1.2
/ 200 IP	—	RAW		174	0	200	863	162	81	19	0%	1.1	18.9%	9.4%	9.5%	2.2%	3.81	3.92	+1.5
Career	—	MLE		313	17	432	1852	352	149	36	5%	1.4	19.0%	8.0%	11.0%	2.0%	3.39	3.59	+0.9
/ 200 IP	—	MLE		145	8	200	857	163	69	17	5%	1.4	19.0%	8.0%	11.0%	2.0%	3.39	3.59	+1.1

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 AAAScranton/Wilkes-Barre RailRiders · 48 IPFIP 2.34 → 2.62 (+0.27)K% 25.9% → 22.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.87%	—	×0.860	22.25%
BB% (unintentional) /BF	6.97%	—	×0.900	6.27%
HR / BF /BF	1.00%	÷1.000	×1.100	1.09%

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 2.34 → 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).

2025 AAAScranton/Wilkes-Barre RailRiders · 17 IPFIP 3.40 → 3.66 (+0.26)K% 25.7% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.71%	—	×0.860	22.11%
BB% (unintentional) /BF	7.14%	—	×0.900	6.43%
HR / BF /BF	2.86%	÷1.070	×1.100	2.94%

Result: FIP 3.40 → 3.66, 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 AAAScranton/Wilkes-Barre RailRiders · 59 IPFIP 4.15 → 4.41 (+0.26)K% 21.3% → 18.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.32%	—	×0.860	18.33%
BB% (unintentional) /BF	7.36%	—	×0.900	6.63%
HR / BF /BF	3.49%	÷1.045	×1.100	3.67%

Result: FIP 4.15 → 4.41, 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 AAAIndianapolis Indians · 25 IPFIP 4.34 → 4.47 (+0.13)K% 21.7% → 18.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.71%	—	×0.860	18.67%
BB% (unintentional) /BF	10.85%	—	×0.900	9.77%
HR / BF /BF	3.10%	÷1.095	×1.100	3.12%

Result: FIP 4.34 → 4.47, 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 AAAIndianapolis Indians · 16 IPFIP 1.57 → 2.02 (+0.45)K% 34.5% → 30.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.48%	—	×0.880	30.34%
BB% (unintentional) /BF	3.45%	—	×1.050	3.62%
HR / BF /BF	1.72%	÷1.013	×1.100	1.87%

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 103).

Result: FIP 1.57 → 2.02, 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).

2021 AAAltoona Curve · 18 IPFIP 3.28 → 4.19 (+0.92)K% 26.4% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.39%	—	×0.810	21.38%
BB% (unintentional) /BF	6.94%	—	×1.100	7.64%
HR / BF /BF	2.78%	÷0.947	×1.200	3.52%

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 89).

Result: FIP 3.28 → 4.19, 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 AAAIndianapolis Indians · 6 IPFIP 1.20 → 1.54 (+0.34)K% 30.0% → 26.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.00%	—	×0.880	26.40%
BB% (unintentional) /BF	5.00%	—	×1.050	5.25%
HR / BF /BF	0.00%	÷1.096	×1.100	0.00%

Result: FIP 1.20 → 1.54, 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).

2019 AGreensboro Grasshoppers · 50 IPFIP 1.54 → 2.76 (+1.22)K% 38.0% → 28.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.02%	—	×0.740	28.14%
BB% (unintentional) /BF	6.25%	—	×1.180	7.38%
HR / BF /BF	1.56%	÷1.009	×1.300	2.01%

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 102).

Result: FIP 1.54 → 2.76, 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).

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
Yerry De los Santos (OGILVIE)	—	—	4.35	19.7%	9.0%	2.5%	—	4.65	18.7%	9.3%	65	+0.30	—	—	—
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	86
Diego Moreno R 2016 · 3.75 FIP	29	SU	3.75	21.0%	8.2%	2.5%	.347	3.13	17.8%	11.9%	54	-0.62	2.29	187	84
Mark Serrano R 2016 · 3.16 FIP	30	SU	3.16	17.7%	6.5%	1.3%	.290	4.36	21.1%	14.0%	88	+1.20	3.16	120	83
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	83
Tyler Walker R 2005 · 4.19 FIP	29	SU	4.19	19.4%	7.5%	3.2%	.303	3.61	19.7%	11.3%	93	-0.58	2.38	289	83
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	83
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	82
Kevin Gryboski R 2003 · 3.67 FIP	29	SU	3.67	16.8%	8.9%	1.6%	.295	3.92	9.4%	0.2%	82	+0.25	3.67	178	82
Gerardo Sanchez R 2017 · 3.47 FIP	28	SU	3.47	21.6%	8.4%	2.1%	.355	3.58	20.5%	15.1%	56	+0.11	2.65	137	82
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	82
Carlos Fisher R 2011 · 4.33 FIP	28	SU	4.33	15.5%	9.1%	2.5%	.275	—	—	—	—	—	2.48	245	81
Brian Sanches R 2008 · 4.74 FIP	29	SU	4.74	18.5%	9.3%	3.7%	.378	4.01	20.5%	10.8%	182	-0.73	3.39	229	80
Matt Lindstrom R 2009 · 4.12 FIP	29	SU	4.12	17.8%	10.0%	2.3%	.320	3.16	17.7%	11.7%	154	-0.96	2.40	443	80
Tyler Sturdevant R 2015 · 4.37 FIP	29	SU	4.37	21.3%	8.5%	3.6%	.241	3.97	18.5%	11.9%	118	-0.40	3.44	149	80
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	80
Francisco Mendoza R 2016 · 3.81 FIP	28	SU	3.81	17.9%	7.7%	2.3%	.344	—	—	—	—	—	3.13	120	80
Bo Schultz R 2015 · 4.30 FIP	29	SU	4.30	18.3%	7.9%	3.2%	.218	3.49	15.1%	8.9%	77	-0.81	2.73	141	79
Santiago Casilla R 2009 · 4.44 FIP	29	SU	4.44	15.0%	9.4%	2.6%	.324	3.29	22.1%	13.0%	170	-1.15	2.76	647	79
Jhan Mariñez R 2018 · 4.09 FIP	29	SU	4.09	21.2%	7.9%	3.2%	.331	—	—	—	—	—	3.16	253	79
Marc Magliaro R 2018 · 3.94 FIP	28	SU	3.94	19.6%	7.3%	2.9%	.307	—	—	—	—	—	3.94	125	79

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	1.2	35	19.1%	9.7%	0.90	3.95
Mark Dewey ('90-'96, 3 WAR*)	1.2	42	18.7%*	9.6%*	0.80*	3.89*
Javy Guerra ('21)	1.5	50	18.5%	9.1%	0.86	3.98
Ray Searage ('81-'90, 4 WAR*)	1.4	41	21.0%*	10.8%*	0.84*	3.70*
Ed Vosberg ('86-'02, 1 WAR*)	1.2	47	21.0%*	9.6%*	0.86*	4.06*
Manny Acosta ('12)	1.2	41	20.5%	10.9%	1.09	3.99
Scott Oberg ('19)	1.3	51	21.5%	9.3%	0.91	3.85