Andrew Bellatti

P El Paso Chihuahuas

Age 35 RHP 6'1" / 190 lbs AAA

Overview

AAARP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	31	MIX3 levels	56	0	53	3.59	3.92	24.8%	11.5%	0.4	K 22.1% · BB 10.9% · FIP 4.04
2024	32	AAAPHI	46	0	43	5.48	4.67	20.8%	16.3%	—	K 17.9% · BB 14.7% · FIP 4.66
2025	33	AAASD	5	0	5	11.57	4.17	17.9%	17.9%	—	K 17.9% · BB 17.9% · FIP 3.85
2026	34	No MLB games played
2027PROJ	35	MLBSD	5	0	5	4.31	4.33	25.8%	10.1%	0.0
2028PROJMLE	36	MLBSD	—	—	0	4.54	4.70	24.8%	10.7%	—
2029PROJMLE	37	MLBSD	—	—	0	4.87	5.10	23.7%	11.3%	—

Last 3 seasons WAR 0.4 · Next 3 projected WAR 0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2023

K%50

FB Velo44

xwOBA vs25

CompsMark Serrano (age 33) · Toby Borland (age 35) · Brendan Donnelly (age 35)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 115107vR 99

ERA4.31

FIP4.33

K%25.8%

BB%10.1%

K-BB%15.7%

Proj IP52

Value2027 · WAR

Runs saved vs league avg · 52 IP

Grades · Statcast · Contract

Scouting Grades

STUF7070

CTRL4040

CMD5555

K†6060

Statcast Percentiles

FB Velo

p4494.1

Whiff%

p9033.9%

p5022.1%

xwOBA vs

p250.341

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	23	MIX MLE	3 levels	39	6	74	316	63	25	11	15%	1.9	19.3%	8.8%	10.5%	3.2%	4.48	4.34	+0.2
2015	23	MIX RAW	3 levels	39	6	74	316	63	25	11	15%	1.9	19.9%	7.9%	12.0%	3.5%	4.48	4.34	+0.2
2016	24	MIX MLE	3 levels	13	0	14	71	21	9	1	0%	1.1	29.6%	12.7%	16.9%	1.4%	6.91	2.98	—
2016	24	MIX RAW	3 levels	13	0	14	71	21	9	1	0%	1.1	29.6%	12.7%	16.9%	1.4%	6.91	2.96	—
2019	27	MIX MLE	2 levels	25	0	38	164	35	11	4	0%	1.5	16.4%	6.6%	9.8%	3.8%	5.50	4.61	—
2019	27	MIX RAW	2 levels	25	0	38	164	35	11	4	0%	1.5	21.3%	6.7%	14.6%	2.4%	5.50	3.50	—
2021	29	MIX MLE	3 levels	33	0	36	148	46	13	2	0%	1.1	29.1%	8.2%	20.9%	2.2%	2.48	2.87	+0.7
2021	29	MIX RAW	3 levels	33	0	36	148	46	13	2	0%	1.1	31.1%	8.8%	22.3%	1.4%	2.48	2.36	+1.0
2022	30	MIX MLE	2 levels	61	1	56	236	81	24	5	2%	0.9	33.9%	10.4%	23.5%	2.0%	3.23	2.67	+1.3
2022	30	MIX RAW	2 levels	61	1	56	236	81	24	5	2%	0.9	34.3%	10.2%	24.2%	2.1%	3.23	2.65	+1.3
2023	31	MIX MLE	3 levels	56	0	53	234	58	27	6	0%	0.9	22.1%	10.9%	11.2%	2.6%	3.59	4.04	+0.3
2023	31	MIX RAW	3 levels	56	0	53	234	58	27	6	0%	0.9	24.8%	11.5%	13.2%	2.6%	3.59	3.92	+0.4
2024	32	AAA MLE	Lehigh Valley IronPigs	46	0	43	202	42	33	4	0%	0.9	17.9%	14.7%	3.2%	2.2%	5.48	4.66	—
2024	32	AAA MLE	Lehigh Valley IronPigs	46	0	43	202	42	33	4	0%	0.9	17.9%	14.7%	3.2%	2.2%	5.48	4.66	—
2024	32	AAA RAW	Lehigh Valley IronPigs	46	0	43	202	42	33	4	0%	0.9	20.8%	16.3%	4.5%	2.0%	5.48	4.67	—
2025	33	AAA MLE	El Paso Chihuahuas	5	0	5	28	5	5	0	0%	0.9	17.9%	17.9%	0.0%	0.0%	11.57	3.85	—
2025	33	AAA MLE	El Paso Chihuahuas	5	0	5	28	5	5	0	0%	0.9	17.9%	17.9%	0.0%	0.0%	11.57	3.85	—
2025	33	AAA RAW	El Paso Chihuahuas	5	0	5	28	5	5	0	0%	0.9	17.9%	17.9%	0.0%	0.0%	11.57	4.17	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			106	1	106	457	125	48	13	1%	1.0	27.4%	10.5%	16.8%	2.8%	3.83	3.70	+1.1
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	35	MLB	SD	5	0	5	21	5	2	1	0%	1.0	25.8%	10.1%	15.7%	3.2%	4.31	4.33	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	36	MLB MLE	SD	37	0	39	163	40	17	6	0%	1.0	24.8%	10.7%	14.1%	3.6%	4.54	4.70	-0.1
2029	37	MLB MLE	SD	27	0	28	120	28	14	5	0%	1.1	23.7%	11.3%	12.3%	4.0%	4.87	5.10	-0.2
2028	36	MLB CTX	SD	—	—	0	—	—	—	—	—	—	24.8%	10.7%	14.1%	3.6%	4.54	4.70	—
2029	37	MLB CTX	SD	—	—	0	—	—	—	—	—	—	23.7%	11.3%	12.3%	4.0%	4.87	5.10	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		106	1	106	459	125	48	13	1%	1.0	27.3%	10.5%	16.8%	2.8%	3.84	3.68	+1.1
/ 200 IP	—	RAW		201	2	200	865	236	91	25	1%	1.0	27.3%	10.5%	16.8%	2.8%	3.84	3.68	+2.1
Career	—	MLE		278	7	318	1399	325	144	36	3%	1.1	23.2%	10.3%	12.9%	2.6%	4.35	3.85	+0.8
/ 200 IP	—	MLE		175	4	200	879	204	91	22	3%	1.1	23.2%	10.3%	12.9%	2.6%	4.35	3.85	+0.9

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.

2025 AAAEl Paso Chihuahuas · 5 IPFIP 3.85 → 3.84 (−0.02)K% 17.9% → 15.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.86%	—	×0.860	15.36%
BB% (unintentional) /BF	17.86%	—	×0.900	16.07%
HR / BF /BF	0.00%	÷0.981	×1.100	0.00%

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 96).

Result: FIP 3.85 → 3.84, 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 AAALehigh Valley IronPigs · 43 IPFIP 4.50 → 4.66 (+0.16)K% 20.8% → 17.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.79%	—	×0.860	17.88%
BB% (unintentional) /BF	16.34%	—	×0.900	14.70%
HR / BF /BF	1.98%	÷0.989	×1.100	2.20%

Result: FIP 4.50 → 4.66, 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).

2023 AAALehigh Valley IronPigs · 26 IPFIP 3.47 → 3.69 (+0.21)K% 25.7% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.66%	—	×0.860	22.07%
BB% (unintentional) /BF	12.39%	—	×0.900	11.15%
HR / BF /BF	1.77%	÷1.028	×1.100	1.89%

Result: FIP 3.47 → 3.69, 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).

2021 AAAJacksonville Jumbo Shrimp · 30 IPFIP 2.26 → 2.87 (+0.61)K% 33.0% → 29.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.04%	—	×0.880	29.08%
BB% (unintentional) /BF	7.83%	—	×1.050	8.22%
HR / BF /BF	1.74%	÷0.886	×1.100	2.16%

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 77).

Result: FIP 2.26 → 2.87, 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 AATrenton Thunder · 31 IPFIP 3.80 → 4.61 (+0.81)K% 20.3% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	20.30%	—	×0.810	16.44%
BB% (unintentional) /BF	6.02%	—	×1.100	6.62%
HR / BF /BF	3.01%	÷0.960	×1.200	3.76%

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 92).

Result: FIP 3.80 → 4.61, 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 A+Tampa Tarpons · 7 IPFIP 2.15 → 2.83 (+0.69)K% 25.8% → 19.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.81%	—	×0.770	19.87%
BB% (unintentional) /BF	9.68%	—	×1.150	11.13%
HR / BF /BF	0.00%	÷0.960	×1.250	0.00%

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 92).

Result: FIP 2.15 → 2.83, 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 AAADurham Bulls · 5 IPFIP 2.37 → 2.83 (+0.46)K% 34.5% → 30.3%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.48%	—	×0.880	30.34%
BB% (unintentional) /BF	17.24%	—	×1.050	18.10%
HR / BF /BF	0.00%	÷1.167	×1.100	0.00%

Result: FIP 2.37 → 2.83, 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 AAMontgomery Biscuits · 5 IPFIP 4.35 → 5.13 (+0.78)K% 25.9% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.93%	—	×0.810	21.00%
BB% (unintentional) /BF	11.11%	—	×1.100	12.22%
HR / BF /BF	3.70%	÷1.081	×1.200	4.11%

Result: FIP 4.35 → 5.13, 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
Andrew Bellatti (OGILVIE)	—	—	4.33	25.8%	10.1%	3.2%	—	4.87	24.3%	13.4%	67	+0.54	—	—	—
Mark Serrano R 2019 · 5.25 FIP	33	SU	5.25	20.2%	7.9%	5.2%	.289	—	—	—	—	—	3.16	120	75
Toby Borland R 2004 · 4.28 FIP	35	SU	4.28	20.9%	8.1%	3.5%	.259	—	—	—	—	—	2.92	248	71
Brendan Donnelly R 2006 · 4.21 FIP	35	SU	4.21	19.1%	9.0%	2.9%	.260	3.19	18.6%	10.1%	60	-1.02	2.23	385	70
Jean Machi R 2017 · 4.12 FIP	35	SU	4.12	18.6%	6.6%	3.2%	.285	—	—	—	—	—	2.16	306	70
Keiichi Yabu R 2005 · 4.05 FIP	36	SU	4.05	16.8%	8.8%	2.3%	.307	3.48	15.9%	6.6%	68	-0.57	3.48	126	70
Juan Sandoval R 2016 · 3.24 FIP	35	SU	3.24	18.2%	10.2%	0.7%	.288	4.40	16.3%	9.1%	116	+1.16	3.24	225	68
Leo Rosales R 2015 · 3.99 FIP	34	SU	3.99	18.1%	10.8%	1.9%	.261	4.24	7.8%	-0.4%	22	+0.25	3.85	130	67
Rafael Martín R 2019 · 4.71 FIP	35	SU	4.71	22.5%	6.0%	5.0%	.333	—	—	—	—	—	2.94	227	67
Spencer Patton R 2023 · 4.33 FIP	35	SU	4.33	18.9%	9.7%	2.9%	.295	—	—	—	—	—	2.79	239	67
Fernando Rodriguez Jr. R 2019 · 5.11 FIP	35	SW	5.11	25.0%	11.2%	4.9%	.312	—	—	—	—	—	3.34	335	66
Joe Nelson R 2009 · 5.35 FIP	34	SU	5.35	19.8%	14.3%	3.9%	.221	—	—	—	—	—	3.08	139	66
Hector Navarro R 2015 · 4.35 FIP	35	SU	4.35	15.0%	5.4%	3.3%	.281	3.00	15.2%	9.0%	81	-1.35	2.30	126	64
Hirokazu Sawamura R 2022 · 4.02 FIP	34	SU	4.02	18.1%	11.3%	1.9%	.270	—	—	—	—	—	4.02	104	63
Zack Segovia R 2019 · 4.55 FIP	36	SU	4.55	17.6%	13.6%	2.2%	.353	—	—	—	—	—	3.33	144	63
Brian Schlitter R 2021 · 4.70 FIP	35	SU	4.70	14.9%	9.1%	3.1%	.318	—	—	—	—	—	3.27	300	63
Matt Miller R 2006 · 4.98 FIP	34	SU	4.98	18.5%	13.8%	3.1%	.214	—	—	—	—	—	2.13	101	63
Rodolfo Aguirre R 2019 · 4.50 FIP	34	SU	4.50	21.3%	5.1%	4.7%	.244	—	—	—	—	—	3.39	212	63
Matt Bush R 2022 · 3.73 FIP	36	SU	3.73	30.3%	6.6%	4.3%	.224	3.79	26.2%	17.5%	36	+0.06	2.87	249	62
Jim Miller R 2016 · 5.43 FIP	34	SU	5.43	20.4%	14.1%	4.1%	.347	—	—	—	—	—	3.95	140	62
Yoshihisa Hirano R 2019 · 3.72 FIP	35	SU	3.72	26.2%	8.6%	3.2%	.303	5.02	17.5%	4.8%	12	+1.30	3.45	132	62

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	1.1	37	26.1%	10.7%	1.23	4.20
Colin Poche ('25)	1.1	54	26.7%	10.2%	1.32	4.01
José Cisnero ('24)	1.4	46	24.0%	11.3%	1.01	4.16
Yency Almonte ('24)	1.1	45	22.5%	9.9%	1.13	4.44
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*
Buddy Schultz ('75-'79, 2 WAR*)	1.2	60	27.4%*	8.5%*	1.21*	4.14*