Andrew Abbott

P Cincinnati Reds

Age 28 LHP 6'0" / 192 lbs MLB peak 0.9 · 2027

Overview

MLBSP40-MAN

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MLBCIN	25	25	138	3.72	4.91	19.5%	8.7%	0.8
2025	26	MIX2 levels	31	31	176	2.91	3.76	21.6%	6.6%	3.5	K 21.8% · BB 6.3% · FIP 3.47
2026	27	MLBCIN	32	32	166	4.61	4.93	18.0%	10.4%	0.9
2027PROJ	28	MLBCIN	20	20	117	4.36	4.76	18.9%	9.1%	0.9
2028PROJ	29	MLBCIN	14	14	82	4.70	4.92	18.3%	9.3%	0.4
2029PROJ	30	MLBCIN	10	10	60	4.96	5.13	17.6%	9.6%	0.2

Last 3 seasons WAR 5.1 · Next 3 projected WAR 1.5Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2026

xwOBA vs28

FB Velo21

K%21

Form7.84 ERA (proj 4.36) · K 17.2% (proj 18.9%) · BB 8.1% (proj 9.1%) · last 60d · 21 IP through Oct 27

CompsHéctor Santiago (age 28) · Steven Matz (age 28) · Joe Saunders (age 28)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 107115vR 123

ERA4.36

FIP4.76

K%18.9%

BB%9.1%

K-BB%9.8%

Proj IP117

Value2027 · WAR

Runs saved vs league avg · 117 IP

Statcast · Contract

Statcast Percentiles

FB Velo

p2192.4

Whiff%

p2922.4%

p2118.0%

xwOBA vs

p280.338

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)
2021	22	MIX MLE	2 levels	6	5	13	56	22	4	2	83%	2.2	39.3%	7.1%	32.1%	3.6%	4.15	2.65	—
2021	22	MIX RAW	2 levels	6	5	13	56	22	4	2	83%	2.2	39.3%	7.1%	32.1%	3.6%	4.15	2.64	—
2022	23	MIX MLE	2 levels	25	24	118	489	159	48	8	96%	4.7	26.0%	10.9%	15.1%	2.0%	3.81	3.36	—
2022	23	MIX RAW	2 levels	25	24	118	489	159	48	8	96%	4.7	32.5%	9.8%	22.7%	1.6%	3.81	2.51	—
2023	24	MIX MLE	3 levels	31	31	163	670	210	61	24	100%	5.3	29.2%	8.9%	20.3%	3.5%	3.42	3.67	+3.4
2023	24	MIX RAW	3 levels	31	31	163	670	210	61	24	100%	5.3	31.3%	9.1%	22.2%	3.6%	3.42	3.56	+3.7
2024	25	MLB MLE	Cincinnati Reds	25	25	138	586	114	51	25	100%	5.5	19.5%	8.7%	10.8%	4.0%	3.72	4.73	+1.1
2024	25	MLB MLE	Cincinnati Reds	25	25	138	586	114	51	25	100%	5.5	19.5%	8.7%	10.8%	4.0%	3.72	4.73	+1.1
2024	25	MLB RAW	Cincinnati Reds	25	25	138	586	114	51	25	100%	5.5	19.5%	8.7%	10.8%	4.3%	3.72	4.91	+0.8
2025	26	MIX MLE	2 levels	31	31	176	727	157	48	22	100%	5.7	21.8%	6.3%	15.5%	2.6%	2.91	3.47	+4.2
2025	26	MIX MLE	2 levels	31	31	176	727	157	48	22	100%	5.7	21.8%	6.3%	15.5%	2.6%	2.91	3.47	+4.2
2025	26	MIX RAW	2 levels	31	31	176	727	157	48	22	100%	5.7	21.6%	6.6%	15.0%	3.0%	2.91	3.76	+3.5
2026	27	MLB MLE	Cincinnati Reds	32	32	166	729	131	76	26	100%	5.2	18.0%	10.4%	7.5%	3.3%	4.61	4.72	+1.3
2026	27	MLB MLE	Cincinnati Reds	32	32	166	729	131	76	26	100%	5.2	18.0%	10.4%	7.5%	3.3%	4.61	4.72	+1.3
2026	27	MLB RAW	Cincinnati Reds	32	32	166	729	131	76	26	100%	5.2	18.0%	10.4%	7.5%	3.6%	4.61	4.93	+0.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			107	107	580	2458	514	214	86	100%	5.4	20.9%	8.7%	12.2%	3.5%	3.76	4.36	+7.0
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CIN	20	20	117	494	93	45	16	100%	5.8	18.9%	9.1%	9.8%	3.1%	4.36	4.76	+0.9
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CIN	14	14	82	347	64	32	11	100%	5.9	18.3%	9.3%	9.0%	3.3%	4.70	4.92	+0.5
2029	30	MLB MLE	CIN	10	10	60	253	44	24	9	100%	6.0	17.6%	9.6%	8.0%	3.5%	4.96	5.13	+0.2
2028	29	MLB CTX	CIN	14	14	82	346	63	32	11	100%	5.9	18.3%	9.3%	9.0%	3.3%	4.70	4.92	+0.4
2029	30	MLB CTX	CIN	10	10	60	253	45	24	9	100%	6.0	17.6%	9.6%	8.0%	3.5%	4.96	5.13	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		131	131	722	3058	622	271	106	100%	5.5	20.3%	8.8%	11.5%	3.5%	3.96	4.41	+8.3
/ 200 IP	—	RAW		36	36	200	847	172	75	29	100%	5.5	20.3%	8.8%	11.5%	3.5%	3.96	4.41	+2.3
Career	—	MLE		150	148	775	3257	748	290	101	99%	5.2	23.0%	8.9%	14.1%	3.1%	3.68	3.99	+7.6
/ 200 IP	—	MLE		39	38	200	841	193	75	26	99%	5.2	23.0%	8.9%	14.1%	3.1%	3.68	3.99	+2.1

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.

2025 AAALouisville Bats · 10 IPFIP 6.83 → 7.75 (+0.92)K% 18.6% → 16.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	18.60%	—	×0.860	16.00%
BB% (unintentional) /BF	11.63%	—	×0.900	10.47%
HR / BF /BF	6.98%	÷0.901	×1.100	8.51%

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 80).

Result: FIP 6.83 → 7.75, 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 · 38 IPFIP 4.14 → 4.56 (+0.42)K% 34.8% → 30.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.84%	—	×0.860	29.96%
BB% (unintentional) /BF	9.03%	—	×0.900	8.13%
HR / BF /BF	5.16%	÷1.054	×1.100	5.39%

Result: FIP 4.14 → 4.56, 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 AAChattanooga Lookouts · 16 IPFIP -1.65 → -0.55 (+1.10)K% 64.3% → 52.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	64.29%	—	×0.810	52.07%
BB% (unintentional) /BF	5.36%	—	×1.100	5.89%
HR / BF /BF	0.00%	÷1.017	×1.200	0.00%

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 103).

Result: FIP -1.65 → -0.55, 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 AAChattanooga Lookouts · 91 IPFIP 2.84 → 3.68 (+0.84)K% 30.8% → 25.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.83%	—	×0.810	24.97%
BB% (unintentional) /BF	10.62%	—	×1.100	11.68%
HR / BF /BF	1.81%	÷0.990	×1.200	2.20%

Result: FIP 2.84 → 3.68, 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 · 27 IPFIP 1.21 → 2.19 (+0.98)K% 38.8% → 29.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.83%	—	×0.770	29.90%
BB% (unintentional) /BF	6.80%	—	×1.150	7.82%
HR / BF /BF	0.97%	÷1.058	×1.250	1.15%

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 1.21 → 2.19, 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 ADaytona Tortugas · 11 IPFIP 3.10 → 4.90 (+1.80)K% 38.8% → 28.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	38.78%	—	×0.740	28.69%
BB% (unintentional) /BF	8.16%	—	×1.180	9.63%
HR / BF /BF	4.08%	÷0.969	×1.300	5.48%

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 94).

Result: FIP 3.10 → 4.90, 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 Abbott (OGILVIE)	—	—	—	—	—	3.1%	—	5.01	18.0%	8.5%	142	+0.25	—	—	—
Héctor Santiago L 2016 · 5.12 FIP	28	SP	5.12	18.3%	10.1%	4.2%	.257	5.09	20.1%	8.4%	310	-0.03	4.07	1,059	78
Steven Matz L 2019 · 4.21 FIP	28	SP	4.21	22.1%	6.5%	3.9%	.292	4.03	23.9%	17.6%	244	-0.18	3.19	1,226	70
Joe Saunders L 2009 · 4.99 FIP	28	SP	4.99	12.5%	7.7%	3.6%	.282	4.39	13.4%	6.8%	590	-0.60	3.86	1,378	69
Nate Robertson L 2006 · 4.53 FIP	28	SP	4.53	15.6%	7.4%	3.3%	.272	4.47	14.7%	6.8%	396	-0.06	4.13	1,144	69
Ted Lilly L 2004 · 4.41 FIP	28	SP	4.41	19.9%	10.3%	3.1%	.257	4.46	19.5%	11.2%	515	+0.05	3.61	1,975	67
Chris Capuano L 2007 · 4.06 FIP	28	SP	4.06	19.7%	7.8%	3.0%	.323	4.06	19.4%	12.2%	66	+0.00	3.40	1,458	66
Wade Miley L 2015 · 3.73 FIP	28	SP	3.73	17.7%	7.7%	2.1%	.305	4.15	18.7%	9.8%	429	+0.42	3.12	1,805	65
Paul Maholm L 2010 · 4.04 FIP	28	SP	4.04	12.1%	7.1%	1.9%	.321	3.89	16.0%	9.5%	504	-0.15	3.67	1,556	64
Tom Gorzelanny L 2010 · 3.82 FIP	28	SP-	3.82	19.7%	10.6%	1.9%	.305	3.87	21.7%	13.8%	262	+0.05	2.67	899	63
J.A. Happ L 2011 · 4.59 FIP	28	SP	4.59	19.2%	11.2%	3.1%	.292	4.11	20.7%	11.9%	395	-0.48	3.37	1,890	63
Casey Fossum L 2006 · 4.79 FIP	28	SP	4.79	14.8%	10.1%	3.0%	.276	4.75	15.0%	7.0%	117	-0.04	3.50	782	63
Jarrod Washburn L 2003 · 4.82 FIP	28	SP	4.82	13.5%	5.7%	3.9%	.254	4.44	12.9%	6.3%	514	-0.38	3.81	1,864	63
Jorge De La Rosa L 2009 · 3.70 FIP	28	SP	3.70	24.2%	10.0%	2.5%	.300	3.89	21.2%	11.9%	191	+0.19	3.24	1,537	62
John Halama L 2000 · 4.48 FIP	28	SP	4.48	11.8%	7.6%	2.6%	.326	4.62	12.2%	5.9%	320	+0.14	3.01	911	62
Brian Duensing L 2011 · 4.22 FIP	28	SP	4.22	16.2%	6.9%	2.9%	.327	3.64	16.3%	10.1%	224	-0.58	2.57	799	62
Ty Blach L 2019 · 5.32 FIP	28	SP	5.32	13.9%	7.7%	4.4%	.374	3.36	14.1%	9.5%	95	-1.96	1.83	1,176	62
Wandy Rodriguez L 2007 · 3.91 FIP	28	SP	3.91	20.2%	7.7%	2.8%	.290	3.39	22.2%	15.0%	538	-0.52	3.37	1,572	62
Ricky Romero L 2012 · 4.82 FIP	27	SP	4.82	15.0%	12.5%	2.5%	.305	—	—	—	—	—	3.50	824	61
Matt Moore L 2017 · 4.57 FIP	28	SP	4.57	18.7%	8.1%	3.7%	.314	4.76	18.3%	9.8%	102	+0.19	2.80	1,191	61
Andy Pettitte L 2000 · 4.03 FIP	28	SP	4.03	13.8%	8.4%	1.9%	.295	3.09	19.0%	14.0%	544	-0.94	2.90	3,316	60

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	4.2	120	20.1%	8.9%	1.33	4.02
Dick Woodson ('69-'74, 5 WAR*)	2.9	118	17.4%*	9.8%*	1.25*	4.15*
Pat Zachry ('76-'85, 10 WAR*)	5.9	131	19.1%*	9.8%*	1.10*	4.18*
Luis Ortiz ('25)	1.6	109	19.8%	10.1%	1.16	4.05
Mike Mason ('82-'88, 4 WAR*)	3.0	121	19.2%*	9.3%*	1.10*	4.57*
Chris Capuano ('16)	7.1	119	19.5%	7.5%	1.23	4.38
Derek Holland ('21)	7.3	113	19.7%	8.4%	1.35	4.62