Kelvis Salcedo

P Lakeland Flying Tigers

Age 21 RHP 6'0" / 180 lbs A Svc 0.0 · Ctrl thru 2033 peak 1.2 · 2030

Overview

APROSPECTMiLBFA 2034

OGV OFP50OGV rank#42ETA2028MLB%0%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	18	ROKDSL Tigers 2	12	11	50	3.93	2.52	28.9%	8.5%	—	K 19.7% · BB 10.7% · FIP 3.89
2025	19	MIX2 levels	18	10	69	1.83	2.28	33.5%	9.8%	—	K 23.5% · BB 12.1% · FIP 3.65
2026	20	MIX2 levels	13	11	37	3.44	1.87	36.8%	6.5%	—	K 26.3% · BB 7.8% · FIP 3.27
2027PROJ	21	MLBDET	—	—	0	4.19	4.19	26.0%	10.3%	—
2028PROJ49% MLB	22	MLBDET	10	10	52	4.02	3.94	26.5%	9.4%	0.9
2029PROJ73% MLB	23	MLBDET	17	17	93	3.91	3.82	26.9%	8.9%	1.7

Next 3 projected WAR 2.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2033Service0.0First FA2034

2027MiLB2028Pre-Arb$0.8M2029Pre-Arb$0.8M2030Pre-Arb$0.8M2031Arb-1$5M2032Arb-2$9M2033Arb-3$13M

Career WAR0.0 WAR median (P10 -0.5 / P90 20, comp-based) · star 2% · didn't stick 71%

CompsBrandon Bailey (age 22) · Anderson Brito (age 20) · Javi Rivera (age 22)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 113105vR 97

ERA4.19

FIP4.19

K%26.0%

BB%10.3%

K-BB%15.7%

Proj IP81

Value2027 · WAR

Runs saved vs league avg · 81 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$64M ctrl surplus

Contract

Contract ESTIMATED · service-time + WAR-based estimator (needs verification)

Status MiLB

MLB Debut 2028

Service 0 yrs (est)

Team Control Through 2033

First FA Year 2034

Year	Status	Salary	Proj WAR	Value	Surplus
2027	MiLB	still in minors · estimated debut 2028
2028	Pre-Arb	$0.8M	+0.9	$3M	+$3M
2029	Pre-Arb	$0.8M	+1.7	$12M	+$11M
2030	Pre-Arb	$0.8M	+2.1	$13M	+$13M
2031	Arb-1	$5M	+2.3	$14M	+$10M
2032	Arb-2	$9M	+2.4	$13M	+$8M
2033	Arb-3	$13M	+2.4	$12M	+$5M
Totals		$31M		$67M	+$49M

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)
2023	17	ROK MLE	DSL Tigers 2	14	2	25	117	32	12	0	14%	1.8	18.6%	12.8%	5.8%	0.0%	6.20	3.15	—
2023	17	ROK RAW	DSL Tigers 2	14	2	25	117	32	12	0	14%	1.8	27.4%	10.3%	17.1%	0.0%	6.20	1.96	—
2024	18	ROK MLE	DSL Tigers 2	12	11	50	211	61	18	3	92%	4.2	19.7%	10.7%	9.0%	2.0%	3.93	3.89	—
2024	18	ROK MLE	DSL Tigers 2	12	11	50	211	61	18	3	92%	4.2	19.7%	10.7%	9.0%	2.0%	3.93	3.89	—
2024	18	ROK RAW	DSL Tigers 2	12	11	50	211	61	18	3	92%	4.2	28.9%	8.5%	20.4%	1.4%	3.93	2.52	—
2025	19	MIX MLE	2 levels	18	10	69	254	85	25	3	56%	3.8	23.5%	12.1%	11.4%	1.8%	1.83	3.65	—
2025	19	MIX MLE	2 levels	18	10	69	254	85	25	3	56%	3.8	23.5%	12.1%	11.4%	1.8%	1.83	3.65	—
2025	19	MIX RAW	2 levels	18	10	69	254	85	25	3	56%	3.8	33.5%	9.8%	23.6%	1.2%	1.83	2.28	—
2026	20	MIX MLE	2 levels	13	11	37	155	57	10	3	85%	2.8	26.3%	7.8%	18.5%	2.6%	3.44	3.27	—
2026	20	MIX MLE	2 levels	13	11	37	155	57	10	3	85%	2.8	26.3%	7.8%	18.5%	2.6%	3.44	3.27	—
2026	20	MIX RAW	2 levels	13	11	37	155	57	10	3	85%	2.8	36.8%	6.5%	30.3%	1.9%	3.44	1.87	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	21	MLB	DET	—	—	0	—	—	—	—	—	—	26.0%	10.3%	15.7%	2.9%	4.19	4.19	—
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	22	MLB MLE	DET	21	21	105	444	118	42	13	100%	5.0	26.5%	9.4%	17.1%	2.9%	4.09	4.01	+1.7
2029	23	MLB MLE	DET	24	24	127	538	145	48	15	100%	5.3	26.9%	8.9%	18.0%	2.8%	3.98	3.89	+2.3
2030	24	MLB MLE	DET	24	24	135	569	155	49	16	100%	5.6	27.3%	8.6%	18.6%	2.8%	3.89	3.82	+2.6
2031	25	MLB MLE	DET	23	23	134	564	155	48	16	100%	5.8	27.5%	8.5%	19.0%	2.8%	3.82	3.77	+2.6
2032	26	MLB MLE	DET	22	22	134	566	157	48	16	100%	6.1	27.7%	8.4%	19.3%	2.8%	3.78	3.75	+2.7
2033	27	MLB MLE	DET	22	22	132	555	154	47	16	100%	6.0	27.7%	8.5%	19.2%	2.9%	3.78	3.79	+2.5
2034	28	MLB MLE	DET	21	21	126	532	147	46	16	100%	6.0	27.6%	8.7%	18.9%	3.0%	3.84	3.87	+2.3
2035	29	MLB MLE	DET	20	20	118	499	136	44	15	100%	5.9	27.4%	8.9%	18.5%	3.1%	3.94	4.00	+2.0
2036	30	MLB MLE	DET	18	18	108	454	123	42	15	100%	6.0	27.0%	9.2%	17.8%	3.3%	4.08	4.18	+1.6
2037	31	MLB MLE	DET	16	16	96	407	108	39	14	100%	6.0	26.6%	9.6%	17.1%	3.5%	4.26	4.38	+1.1
2038	32	MLB MLE	DET	14	14	85	358	94	36	14	100%	6.0	26.2%	10.0%	16.2%	3.8%	4.47	4.61	+0.8
2039	33	MLB MLE	DET	12	12	74	311	80	32	13	100%	6.1	25.7%	10.4%	15.3%	4.1%	4.70	4.86	+0.5
2040	34	MLB MLE	DET	11	11	64	268	67	29	12	100%	5.8	25.1%	10.9%	14.2%	4.4%	4.96	5.13	+0.2
2028	22	MLB CTX	DET	10	10	52	220	58	21	6	100%	5.2	26.5%	9.4%	17.1%	2.8%	4.02	3.94	+0.9
2029	23	MLB CTX	DET	17	17	93	393	106	35	11	100%	5.5	26.9%	8.9%	18.0%	2.7%	3.91	3.82	+1.7
2030	24	MLB CTX	DET	20	20	112	473	129	41	13	100%	5.6	27.3%	8.6%	18.6%	2.7%	3.82	3.75	+2.1
2031	25	MLB CTX	DET	20	20	118	498	137	42	13	100%	5.9	27.5%	8.5%	19.0%	2.7%	3.75	3.70	+2.3
2032	26	MLB CTX	DET	20	20	122	515	143	43	14	100%	6.1	27.7%	8.4%	19.3%	2.7%	3.71	3.68	+2.4
2033	27	MLB CTX	DET	20	20	122	515	143	44	14	100%	6.1	27.7%	8.5%	19.2%	2.7%	3.71	3.72	+2.4
2034	28	MLB CTX	DET	20	20	118	498	137	43	14	100%	5.9	27.6%	8.7%	18.9%	2.8%	3.77	3.80	+2.2
2035	29	MLB CTX	DET	19	19	112	473	129	42	14	100%	5.9	27.4%	8.9%	18.5%	3.0%	3.87	3.93	+1.9
2036	30	MLB CTX	DET	17	17	102	431	116	40	14	100%	6.0	27.0%	9.2%	17.8%	3.2%	4.00	4.10	+1.5
2037	31	MLB CTX	DET	15	15	91	384	102	37	13	100%	6.1	26.6%	9.6%	17.1%	3.4%	4.18	4.30	+1.1
2038	32	MLB CTX	DET	13	13	80	338	88	34	12	100%	6.2	26.2%	10.0%	16.2%	3.6%	4.38	4.52	+0.7
2039	33	MLB CTX	DET	12	12	70	296	76	31	11	100%	5.8	25.7%	10.4%	15.3%	3.9%	4.61	4.77	+0.4
2040	34	MLB CTX	DET	10	10	57	241	60	26	10	100%	5.7	25.1%	10.9%	14.2%	4.2%	4.86	5.03	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		214	214	1250	5279	1427	479	160	100%	5.8	27.0%	9.1%	18.0%	3.0%	3.98	3.63	+27.0
/ 200 IP	—	RAW		34	34	200	844	228	77	26	100%	5.9	27.0%	9.1%	18.0%	3.0%	3.98	3.63	+4.3
Career	—	MLE		57	34	180	737	164	80	13	60%	3.2	22.2%	10.9%	11.3%	1.7%	3.34	3.56	+22.7
/ 200 IP	—	MLE		63	38	200	817	182	89	14	60%	3.2	22.2%	10.9%	11.3%	1.7%	3.34	3.56	+3.2

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 ALakeland Flying Tigers · 36 IPFIP 2.02 → 3.27 (+1.26)K% 35.5% → 26.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.53%	—	×0.740	26.29%
BB% (unintentional) /BF	6.58%	—	×1.180	7.76%
HR / BF /BF	1.97%	÷1.000	×1.300	2.57%

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 100).

Result: FIP 2.02 → 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).

2025 ROKFCL Tigers · 45 IPFIP 2.22 → 3.59 (+1.37)K% 30.8% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.81%	—	×0.680	20.95%
BB% (unintentional) /BF	11.05%	—	×1.250	13.81%
HR / BF /BF	0.58%	÷0.880	×1.400	0.92%

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 76).

Result: FIP 2.22 → 3.59, 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 ALakeland Flying Tigers · 23 IPFIP 2.07 → 3.77 (+1.70)K% 39.0% → 28.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	39.02%	—	×0.740	28.88%
BB% (unintentional) /BF	7.32%	—	×1.180	8.63%
HR / BF /BF	2.44%	÷0.864	×1.300	3.67%

Result: FIP 2.07 → 3.77, 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 ROKDSL Tigers 2 · 50 IPFIP 2.52 → 3.89 (+1.37)K% 28.9% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.91%	—	×0.680	19.66%
BB% (unintentional) /BF	8.53%	—	×1.250	10.66%
HR / BF /BF	1.42%	÷0.995	×1.400	2.00%

Result: FIP 2.52 → 3.89, 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 ROKDSL Tigers 2 · 25 IPFIP 2.09 → 3.15 (+1.06)K% 27.4% → 18.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	27.35%	—	×0.680	18.60%
BB% (unintentional) /BF	10.26%	—	×1.250	12.82%
HR / BF /BF	0.00%	÷1.009	×1.400	0.00%

Result: FIP 2.09 → 3.15, 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
Kelvis Salcedo (OGILVIE)	—	—	—	—	—	2.9%	—	3.90	26.9%	18.0%	367	-0.29	—	—	—
Brandon Bailey R 2017 · 3.54 FIP	22	SP-	3.54	24.6%	9.9%	2.3%	.290	4.44	21.2%	9.6%	215	+0.90	3.54	306	87
Anderson Brito R 2024 · 3.50 FIP	20	SP-	3.50	27.5%	11.9%	2.2%	.231	3.85	23.2%	7.4%	82	+0.35	3.28	135	83
Javi Rivera R 2022 · 3.78 FIP	22	SP-	3.78	22.3%	7.9%	2.9%	.259	3.72	18.6%	9.0%	93	-0.06	2.81	274	82
Connor Cooke R 2022 · 3.35 FIP	22	SP-	3.35	23.7%	8.4%	2.2%	.350	4.10	24.4%	11.8%	56	+0.75	2.93	103	82
Logan Hofmann R 2021 · 4.57 FIP	21	SP-	4.57	22.1%	11.3%	3.5%	.239	6.80	9.7%	-12.0%	47	+2.23	4.57	129	81
Vince Velasquez R 2015 · 3.26 FIP	23	SW	3.26	26.2%	9.8%	2.1%	.290	3.87	25.5%	16.5%	350	+0.61	3.26	964	81
Michael Knorr R 2023 · 4.30 FIP	23	SP-	4.30	23.6%	11.1%	3.3%	.312	5.15	22.0%	9.5%	123	+0.85	4.30	181	81
Tyler Guilfoil R 2023 · 3.18 FIP	23	SP-	3.18	26.0%	12.3%	1.3%	.305	5.52	17.8%	4.4%	190	+2.34	3.18	274	81
J.C. Flowers R 2021 · 3.59 FIP	23	SP-	3.59	21.3%	8.7%	2.1%	.330	4.84	16.4%	2.8%	184	+1.25	3.59	281	80
Ian Bedell R 2023 · 3.73 FIP	23	SP-	3.73	21.0%	10.1%	2.1%	.285	5.56	18.8%	9.0%	178	+1.83	3.73	274	80
Sam Benschoter R 2022 · 3.71 FIP	24	SP-	3.71	26.3%	9.2%	3.0%	.344	4.96	18.7%	8.6%	306	+1.25	3.61	441	80
Casey Legumina R 2021 · 4.08 FIP	24	SP-	4.08	23.3%	9.3%	3.2%	.260	4.33	20.2%	11.3%	189	+0.25	3.54	355	79
Michael Forret R 2024 · 4.00 FIP	20	SP-	4.00	21.8%	11.8%	2.3%	.302	3.45	22.8%	12.9%	190	-0.55	2.65	289	79
Moisés Chace R 2024 · 4.01 FIP	21	SP-	4.01	29.0%	13.7%	3.0%	.302	6.14	20.5%	2.9%	17	+2.13	3.77	247	79
Zach Peek R 2021 · 3.62 FIP	23	SP-	3.62	22.8%	10.1%	2.1%	.339	3.51	17.5%	9.8%	45	-0.11	3.51	256	79
Ryan Lobus R 2024 · 3.68 FIP	23	SP-	3.68	27.0%	7.2%	3.5%	.277	3.65	22.1%	13.2%	128	-0.03	3.59	216	78
Chris Campos R 2023 · 4.91 FIP	22	SP-	4.91	21.0%	11.8%	3.8%	.364	4.57	18.6%	11.6%	249	-0.34	4.54	318	78
Dualvert Gutierrez R 2021 · 3.22 FIP	20	SP-	3.22	23.5%	9.1%	1.7%	.352	4.29	15.9%	2.2%	78	+1.07	3.22	130	78
Brandon Young R 2021 · 4.13 FIP	22	SP	4.13	24.5%	12.3%	2.8%	.297	3.48	22.2%	14.6%	150	-0.65	3.03	492	78
Landen Roupp R 2022 · 3.02 FIP	23	SP-	3.02	26.9%	9.8%	1.7%	.274	3.42	23.2%	13.0%	209	+0.40	2.36	472	77

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 927 starter careers (497 from 1990-2025 + 430 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	7.6	108	27.0%	9.1%	1.21	4.06
Rich Hill ('25)	7.1	101	23.9%	9.2%	1.12	4.02
Jose DeLeon ('83-'95, 22 WAR*)	9.5	146	25.8%*	10.4%*	1.01*	4.17*
Frankie Montas ('25)	3.9	98	23.6%	8.2%	1.20	4.20
Kenta Maeda ('25)	4.9	123	25.8%	7.0%	1.30	4.20
Bob Johnson ('69-'77, 6 WAR*)	3.5	115	23.4%*	8.9%*	1.49*	4.12*
Woodie Fryman ('66-'83, 21 WAR*)	12.1	142	21.1%*	8.8%*	1.09*	4.43*