Javi Rivera

P Chattanooga Lookouts

Age 27 RHP 6'1" / 195 lbs AA

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	23	A+CIN	10	9	43	4.01	3.90	19.4%	9.7%	—	K 14.9% · BB 11.1% · FIP 4.80
2024	24	A+CIN	12	12	51	4.09	2.11	28.2%	7.3%	—	K 21.7% · BB 8.4% · FIP 2.81
2026	26	MIX2 levels	22	22	94	6.63	6.82	17.2%	11.2%	—	K 14.1% · BB 12.4% · FIP 7.67
2027PROJ	27	MLBCIN	1	1	1	6.14	6.14	15.5%	11.8%	-0.0
2028PROJ38% MLB	28	MLBCIN	3	3	17	6.01	6.04	16.2%	11.7%	-0.1
2029PROJ56% MLB	29	MLBCIN	4	4	22	5.98	6.05	16.5%	11.7%	-0.2

Next 3 projected WAR -0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Career WAR0.0 WAR median (P10 0.0 / P90 0.0, comp-based) · star 0% · didn't stick 98%

CompsTravis Smith (age 29) · Jake Bockenstedt (age 24) · Clay Condrey (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 150142vR 134

ERA6.14

FIP6.14

K%15.5%

BB%11.8%

K-BB%3.7%

Proj IP58

Value2027 · WAR

Runs saved vs league avg · 58 IP

Grades · Contract

Scouting Grades

K†3040

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)
2022	22	MIX MLE	2 levels	24	16	93	372	111	25	8	67%	3.9	22.3%	7.9%	14.4%	2.9%	3.29	3.78	—
2022	22	MIX RAW	2 levels	24	16	93	372	111	25	8	67%	3.9	29.8%	6.7%	23.1%	2.2%	3.29	2.64	—
2023	23	A+ MLE	Dayton Dragons	10	9	43	186	36	18	4	90%	4.3	14.9%	11.1%	3.8%	2.8%	4.01	4.80	—
2023	23	A+ RAW	Dayton Dragons	10	9	43	186	36	18	4	90%	4.3	19.4%	9.7%	9.7%	2.2%	4.01	3.90	—
2024	24	A+ MLE	Dayton Dragons	12	12	51	220	62	16	2	100%	4.2	21.7%	8.4%	13.3%	0.9%	4.09	2.81	—
2024	24	A+ MLE	Dayton Dragons	12	12	51	220	62	16	2	100%	4.2	21.7%	8.4%	13.3%	0.9%	4.09	2.81	—
2024	24	A+ RAW	Dayton Dragons	12	12	51	220	62	16	2	100%	4.2	28.2%	7.3%	20.9%	0.9%	4.09	2.11	—
2026	26	MIX MLE	2 levels	22	22	94	437	75	49	27	100%	4.3	14.1%	12.4%	1.7%	7.6%	6.63	7.67	—
2026	26	MIX MLE	2 levels	22	22	94	437	75	49	27	100%	4.3	14.1%	12.4%	1.7%	7.6%	6.63	7.67	—
2026	26	MIX RAW	2 levels	22	22	94	437	75	49	27	100%	4.3	17.2%	11.2%	5.9%	6.2%	6.63	6.82	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	CIN	1	1	1	4	1	0	0	100%	1.0	15.5%	11.8%	3.7%	4.5%	6.14	6.14	-0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	CIN	8	8	45	191	31	22	9	100%	5.7	16.2%	11.7%	4.5%	4.5%	6.01	6.04	-0.3
2029	29	MLB MLE	CIN	6	6	39	165	27	19	7	100%	6.5	16.5%	11.7%	4.8%	4.5%	5.98	6.05	-0.3
2028	28	MLB CTX	CIN	3	3	17	72	12	8	3	100%	5.7	16.2%	11.7%	4.5%	4.5%	6.01	6.04	-0.1
2029	29	MLB CTX	CIN	4	4	22	93	15	11	4	100%	5.5	16.5%	11.7%	4.8%	4.5%	5.98	6.05	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		6	6	39	164	27	19	7	100%	6.5	16.3%	11.7%	4.7%	4.5%	5.99	5.66	-0.1
/ 200 IP	—	RAW		33	33	200	844	139	98	36	100%	6.0	16.3%	11.7%	4.7%	4.5%	5.99	5.66	-0.6
Career	—	MLE		68	59	280	1215	220	122	51	87%	4.1	18.1%	10.1%	8.0%	4.2%	4.66	5.16	-0.6
/ 200 IP	—	MLE		49	42	200	868	157	87	37	87%	4.1	18.1%	10.1%	8.0%	4.2%	4.66	5.16	-1.4

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.

2026 AAChattanooga Lookouts · 88 IPFIP 6.55 → 7.67 (+1.12)K% 17.4% → 14.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.36%	—	×0.810	14.06%
BB% (unintentional) /BF	11.25%	—	×1.100	12.37%
HR / BF /BF	6.36%	÷1.000	×1.200	7.63%

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 6.55 → 7.67, 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).

2026 ROKACL Reds · 6 IPFIP 5.21 → 6.72 (+1.51)K% 14.3% → 9.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.29%	—	×0.680	9.71%
BB% (unintentional) /BF	10.71%	—	×1.250	13.39%
HR / BF /BF	3.57%	÷1.000	×1.400	5.00%

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 5.21 → 6.72, 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).

2024 A+Dayton Dragons · 51 IPFIP 2.14 → 2.81 (+0.67)K% 28.2% → 21.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.18%	—	×0.770	21.70%
BB% (unintentional) /BF	7.27%	—	×1.150	8.36%
HR / BF /BF	0.91%	÷1.285	×1.250	0.88%

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 157).

Result: FIP 2.14 → 2.81, 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+Dayton Dragons · 43 IPFIP 3.87 → 4.80 (+0.93)K% 19.4% → 14.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.35%	—	×0.770	14.90%
BB% (unintentional) /BF	9.68%	—	×1.150	11.13%
HR / BF /BF	2.15%	÷0.951	×1.250	2.83%

Result: FIP 3.87 → 4.80, 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 ADaytona Tortugas · 74 IPFIP 2.08 → 3.25 (+1.16)K% 30.2% → 22.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.24%	—	×0.740	22.38%
BB% (unintentional) /BF	6.19%	—	×1.180	7.30%
HR / BF /BF	1.37%	÷0.883	×1.300	2.02%

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 77).

Result: FIP 2.08 → 3.25, 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 A+Dayton Dragons · 19 IPFIP 4.51 → 5.72 (+1.21)K% 28.4% → 21.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.40%	—	×0.770	21.86%
BB% (unintentional) /BF	8.64%	—	×1.150	9.94%
HR / BF /BF	4.94%	÷1.058	×1.250	5.83%

Result: FIP 4.51 → 5.72, 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
Javi Rivera (OGILVIE)	—	—	6.14	15.5%	11.8%	4.5%	—	6.04	16.3%	4.6%	84	-0.10	—	—	—
Travis Smith R 2002 · 5.28 FIP	29	SP	5.28	13.1%	8.2%	4.1%	.324	5.71	15.0%	9.0%	51	+0.43	3.67	105	82
Jake Bockenstedt R 2024 · 6.05 FIP	24	SP	6.05	17.0%	13.1%	5.0%	.322	4.35	16.8%	5.4%	126	-1.70	3.74	218	81
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	80
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	78
Kohei Arihara R 2021 · 6.04 FIP	28	SP	6.04	13.5%	7.3%	5.8%	.262	4.58	16.4%	9.2%	94	-1.46	4.58	135	76
Noah Song R 2023 · 6.06 FIP	26	SP	6.06	12.0%	13.2%	4.2%	.239	3.80	19.8%	8.3%	116	-2.26	3.68	138	75
Seth Shuman R 2024 · 5.47 FIP	26	SP	5.47	14.1%	8.0%	4.7%	.273	4.61	17.0%	11.3%	157	-0.86	3.16	357	75
Miguel Ruiz R 2015 · 5.77 FIP	29	SP-	5.77	8.8%	8.0%	4.4%	.346	5.60	10.6%	-0.4%	53	-0.17	5.60	117	75
Alex Blackford R 2017 · 5.59 FIP	26	SP	5.59	14.9%	12.5%	4.0%	.289	—	—	—	—	—	3.48	229	74
Blair Henley R 2024 · 5.41 FIP	27	SP	5.41	17.2%	12.4%	4.0%	.318	—	—	—	—	—	3.97	187	73
Asher Wojciechowski R 2016 · 5.40 FIP	27	SP	5.40	13.5%	11.0%	3.7%	.315	4.71	22.2%	14.4%	379	-0.69	3.15	678	73
Justin Miller R 2004 · 5.41 FIP	26	SP-	5.41	12.5%	10.4%	3.7%	.316	2.63	28.6%	21.7%	62	-2.78	2.63	373	73
Edgar Alberto Garcia R 2015 · 5.24 FIP	27	SP-	5.24	11.6%	9.8%	3.4%	.263	4.28	15.3%	5.2%	167	-0.96	4.01	272	73
Paul Rigdon R 2001 · 5.34 FIP	25	SP	5.34	13.6%	11.1%	3.6%	.283	—	—	—	—	—	5.29	167	72
David Fletcher R 2024 · 5.67 FIP	30	SP-	5.67	7.5%	10.3%	3.5%	.294	—	—	—	—	—	5.67	100	72
Jackson Tetreault R 2022 · 5.30 FIP	26	SP	5.30	15.9%	10.2%	4.1%	.254	—	—	—	—	—	4.02	404	71
Kevin McGowan R 2019 · 5.41 FIP	27	SP	5.41	15.4%	10.7%	4.1%	.259	—	—	—	—	—	2.94	426	71
Bryan Mitchell R 2018 · 6.03 FIP	27	SP-	6.03	13.0%	12.2%	4.5%	.282	5.36	17.2%	4.6%	115	-0.67	2.72	481	71
Jordan Cooper R 2015 · 5.01 FIP	26	SP	5.01	9.2%	10.2%	2.5%	.305	—	—	—	—	—	5.01	106	71
Noah Bremer R 2023 · 5.82 FIP	27	SP	5.82	13.1%	11.9%	4.2%	.303	—	—	—	—	—	3.19	271	70

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	0.7	47	16.0%	11.7%	1.74	6.05
Dave Stevens ('00)	1.3	50	14.6%	11.3%	1.76	6.02
Scott Proctor ('11)	1.7	57	19.0%	10.9%	1.52	4.78
Matt Perisho ('05)	1.4	69	15.2%	12.2%	1.37	6.39
Darrel Akerfelds ('86-'91, -3 WAR*)	1.2	78	15.8%*	11.9%*	1.61*	5.40*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Steve Shields ('85-'89, -3 WAR*)	1.1	55	17.0%*	9.0%*	1.61*	5.49*