Joey Cantillo

P Cleveland Guardians

Age 27 LHP 6'4" / 225 lbs MLB Svc 1.0 · Ctrl thru 2031 peak 1.6 · 2027

Overview

MLBSP40-MANPre-ArbFA 2032

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	24	MIX3 levels	20	18	78	4.60	3.89	28.3%	12.2%	1.4	K 26.3% · BB 11.2% · FIP 3.97
2025	25	MIX2 levels	40	19	117	3.55	3.52	27.6%	10.2%	1.4	K 26.8% · BB 10.0% · FIP 3.57
2026	26	MLBCLE	33	30	159	3.62	3.87	24.9%	11.8%	2.9
2027PROJ	27	MLBCLE	20	20	121	4.04	4.32	24.6%	11.3%	1.5
2028PROJ95% MLB	28	MLBCLE	16	16	94	4.26	4.40	24.5%	11.5%	1.1
2029PROJ95% MLB	29	MLBCLE	13	13	77	4.44	4.56	23.9%	11.7%	0.8

Last 3 seasons WAR 5.8 · Next 3 projected WAR 3.4Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2031Service1.942First FA2032

2027Pre-Arb$0.8M2028Pre-Arb$0.8M2029Arb-1$2M2030Arb-2$2M2031Arb-3$2M

Skills · percentileStatcast 2026

K%65

xwOBA vs54

FB Velo18

Form3.18 ERA (proj 4.04) · K 26.5% (proj 24.6%) · BB 11.2% (proj 11.3%) · last 60d · 23 IP through Oct 27

CompsJorge De La Rosa (age 27) · David Peterson (age 27) · Steven Brault (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 95103vR 111

ERA4.04

FIP4.32

K%24.6%

BB%11.3%

K-BB%13.3%

Proj IP121

Value2027 · WAR

Runs saved vs league avg · 121 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$25M ctrl surplus

Statcast · Contract

Statcast Percentiles

FB Velo

p1892.2

Whiff%

p7429.1%

p6524.9%

xwOBA vs

p540.308

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

Status Pre-Arb

MLB Debut 2024

Service 1.942 yrs.days

Team Control Through 2031

First FA Year 2032

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Pre-Arb	$0.8M	+1.5	$12M	+$11M
2028	Pre-Arb	$0.8M	+1.1	$8M	+$7M
2029	Arb-1	$2M	+0.8	$3M	+$1M
2030	Arb-2	$2M	+0.4	$1M	+$0.0M (cut)
2031	Arb-3	$2M	+0.2	$0.6M	+$0.0M (cut)
Totals		$3M		$25M	+$20M

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)
2017	17	ROK MLE	AZL Padres 2	7	0	8	37	14	6	0	0%	1.1	37.8%	16.2%	21.6%	0.0%	4.50	1.96	—
2017	17	ROK RAW	AZL Padres 2	7	0	8	37	14	6	0	0%	1.1	37.8%	16.2%	21.6%	0.0%	4.50	1.85	—
2018	18	MIX MLE	2 levels	12	10	49	201	63	15	0	83%	4.1	21.6%	8.2%	13.4%	0.0%	2.76	2.32	—
2018	18	MIX RAW	2 levels	12	10	49	201	63	15	0	83%	4.1	31.3%	7.5%	23.9%	0.0%	2.76	1.45	—
2019	19	MIX MLE	2 levels	22	22	112	432	144	34	5	100%	5.1	24.8%	9.2%	15.5%	1.4%	2.26	2.96	—
2019	19	MIX RAW	2 levels	22	22	112	432	144	34	5	100%	5.1	33.3%	7.9%	25.5%	1.2%	2.26	2.02	—
2021	21	MIX MLE	2 levels	7	2	13	58	19	11	0	29%	1.9	32.8%	19.0%	13.8%	0.0%	2.77	2.74	—
2021	21	MIX RAW	2 levels	7	2	13	58	19	11	0	29%	1.9	32.8%	19.0%	13.8%	0.0%	2.77	2.72	—
2022	22	AA MLE	Akron RubberDucks	14	13	61	245	87	28	2	93%	4.3	28.8%	12.6%	16.2%	1.0%	1.93	2.79	—
2022	22	AA RAW	Akron RubberDucks	14	13	61	245	87	28	2	93%	4.3	35.5%	11.4%	24.1%	0.8%	1.93	2.05	—
2023	23	MIX MLE	2 levels	26	24	119	522	146	69	18	92%	4.6	23.7%	12.4%	11.3%	3.8%	4.07	4.73	—
2023	23	MIX RAW	2 levels	26	24	119	522	146	69	18	92%	4.6	28.0%	13.2%	14.8%	3.4%	4.07	4.35	—
2024	24	MIX MLE	3 levels	20	18	78	343	97	42	10	90%	3.9	26.3%	11.2%	15.1%	3.0%	4.60	3.97	+1.3
2024	24	MIX MLE	3 levels	20	18	78	343	97	42	10	90%	3.9	26.3%	11.2%	15.1%	3.0%	4.60	3.97	+1.3
2024	24	MIX RAW	3 levels	20	18	78	343	97	42	10	90%	3.9	28.3%	12.2%	16.0%	2.9%	4.60	3.89	+1.4
2025	25	MIX MLE	2 levels	40	19	117	490	135	50	13	48%	2.9	26.8%	10.0%	16.7%	2.7%	3.55	3.57	+1.4
2025	25	MIX MLE	2 levels	40	19	117	490	135	50	13	48%	2.9	26.8%	10.0%	16.7%	2.7%	3.55	3.57	+1.4
2025	25	MIX RAW	2 levels	40	19	117	490	135	50	13	48%	2.9	27.6%	10.2%	17.3%	2.7%	3.55	3.52	+1.4
2026	26	MLB MLE	Cleveland Guardians	33	30	159	687	171	81	17	91%	4.8	24.9%	11.8%	13.1%	2.5%	3.62	3.85	+2.9
2026	26	MLB MLE	Cleveland Guardians	33	30	159	687	171	81	17	91%	4.8	24.9%	11.8%	13.1%	2.5%	3.62	3.85	+2.9
2026	26	MLB RAW	Cleveland Guardians	33	30	159	687	171	81	17	91%	4.8	24.9%	11.8%	13.1%	2.5%	3.62	3.87	+2.9
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			76	51	293	1251	323	138	33	67%	3.9	25.8%	11.0%	14.8%	2.6%	3.66	3.77	+5.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	27	MLB	CLE	20	20	121	511	126	58	14	100%	6.0	24.6%	11.3%	13.3%	2.7%	4.04	4.32	+1.5
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	28	MLB MLE	CLE	16	16	99	417	102	48	12	100%	6.2	24.5%	11.5%	13.0%	2.8%	4.26	4.40	+1.2
2029	29	MLB MLE	CLE	13	13	81	341	81	40	10	100%	6.2	23.9%	11.7%	12.2%	2.9%	4.44	4.56	+0.8
2030	30	MLB MLE	CLE	11	11	66	277	64	33	9	100%	6.0	23.2%	12.0%	11.2%	3.1%	4.64	4.77	+0.5
2031	31	MLB MLE	CLE	9	9	51	216	48	27	7	100%	5.7	22.4%	12.3%	10.1%	3.4%	4.86	5.00	+0.2
2032	32	MLB MLE	CLE	6	6	37	157	34	20	6	100%	6.2	21.6%	12.7%	8.9%	3.6%	5.10	5.26	+0.1
2028	28	MLB CTX	CLE	16	16	94	397	97	46	11	100%	5.9	24.5%	11.5%	13.0%	2.8%	4.26	4.40	+1.1
2029	29	MLB CTX	CLE	13	13	77	325	78	38	10	100%	5.9	23.9%	11.7%	12.2%	2.9%	4.44	4.56	+0.8
2030	30	MLB CTX	CLE	10	10	62	262	61	31	8	100%	6.2	23.2%	12.0%	11.2%	3.1%	4.64	4.77	+0.4
2031	31	MLB CTX	CLE	8	8	49	207	46	26	7	100%	6.1	22.4%	12.3%	10.1%	3.4%	4.86	5.00	+0.2
2032	32	MLB CTX	CLE	6	6	35	148	32	19	5	100%	5.8	21.6%	12.7%	8.9%	3.6%	5.10	5.26	+0.1
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		129	104	610	2588	636	297	74	81%	4.7	24.6%	11.5%	13.1%	2.9%	4.12	4.05	+9.8
/ 200 IP	—	RAW		42	34	200	849	209	97	24	81%	4.7	24.6%	11.5%	13.1%	2.9%	4.12	4.05	+3.2
Career	—	MLE		181	138	716	3015	770	338	69	76%	4.0	25.5%	11.2%	14.3%	2.3%	3.37	3.61	+8.4
/ 200 IP	—	MLE		51	39	200	843	215	94	19	76%	4.0	25.5%	11.2%	14.3%	2.3%	3.37	3.61	+2.7

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 AAAColumbus Clippers · 21 IPFIP 3.53 → 3.78 (+0.26)K% 30.3% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.34%	—	×0.860	26.09%
BB% (unintentional) /BF	8.99%	—	×0.900	8.09%
HR / BF /BF	3.37%	÷1.093	×1.100	3.39%

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 118).

Result: FIP 3.53 → 3.78, 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 AAAColumbus Clippers · 38 IPFIP 3.72 → 3.93 (+0.22)K% 29.8% → 25.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.82%	—	×0.860	25.65%
BB% (unintentional) /BF	14.62%	—	×0.900	13.16%
HR / BF /BF	2.34%	÷1.060	×1.100	2.43%

Result: FIP 3.72 → 3.93, 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 AAAColumbus Clippers · 95 IPFIP 4.60 → 4.87 (+0.27)K% 26.1% → 22.5%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.12%	—	×0.860	22.46%
BB% (unintentional) /BF	12.94%	—	×0.900	11.65%
HR / BF /BF	3.76%	÷1.037	×1.100	3.99%

Result: FIP 4.60 → 4.87, 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).

2023 AAAkron RubberDucks · 24 IPFIP 3.01 → 4.14 (+1.12)K% 36.1% → 29.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	36.08%	—	×0.810	29.23%
BB% (unintentional) /BF	14.43%	—	×1.100	15.88%
HR / BF /BF	2.06%	÷0.909	×1.200	2.72%

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 82).

Result: FIP 3.01 → 4.14, 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 AAAkron RubberDucks · 61 IPFIP 2.00 → 2.79 (+0.80)K% 35.5% → 28.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	35.51%	—	×0.810	28.76%
BB% (unintentional) /BF	11.43%	—	×1.100	12.57%
HR / BF /BF	0.82%	÷1.014	×1.200	0.97%

Result: FIP 2.00 → 2.79, 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 AAAkron RubberDucks · 8 IPFIP 3.72 → 4.50 (+0.78)K% 29.3% → 23.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	29.27%	—	×0.810	23.71%
BB% (unintentional) /BF	24.39%	—	×1.100	26.83%
HR / BF /BF	0.00%	÷0.893	×1.200	0.00%

Result: FIP 3.72 → 4.50, 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 AFort Wayne TinCaps · 98 IPFIP 1.54 → 2.53 (+0.99)K% 34.7% → 25.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	34.69%	—	×0.740	25.67%
BB% (unintentional) /BF	7.32%	—	×1.180	8.63%
HR / BF /BF	0.81%	÷1.151	×1.300	0.92%

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 130).

Result: FIP 1.54 → 2.53, 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+Lake Elsinore Storm · 14 IPFIP 4.11 → 5.49 (+1.38)K% 25.4% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	25.40%	—	×0.770	19.56%
BB% (unintentional) /BF	11.11%	—	×1.150	12.78%
HR / BF /BF	3.17%	÷0.900	×1.250	4.41%

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 80).

Result: FIP 4.11 → 5.49, 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
Joey Cantillo (OGILVIE)	—	—	—	—	—	2.7%	—	4.55	23.9%	12.2%	245	+0.23	—	—	—
Jorge De La Rosa L 2008 · 3.77 FIP	27	SP-	3.77	22.4%	10.3%	2.3%	.310	3.70	23.0%	13.2%	366	-0.07	3.24	1,537	75
David Peterson L 2023 · 4.14 FIP	27	SP-	4.14	25.1%	10.7%	3.3%	.356	3.54	20.5%	11.2%	438	-0.60	2.81	1,078	72
Steven Brault L 2019 · 4.47 FIP	27	SP-	4.47	19.8%	10.1%	3.2%	.301	3.81	18.8%	8.2%	70	-0.66	3.12	691	65
Casey Fossum L 2005 · 4.19 FIP	27	SP-	4.19	17.7%	7.9%	2.9%	.287	4.77	14.9%	5.8%	247	+0.58	3.50	782	65
Alex Wood L 2018 · 3.16 FIP	27	SP-	3.16	21.2%	5.5%	2.1%	.285	3.70	24.6%	18.1%	187	+0.54	2.66	1,258	65
Patrick Corbin L 2016 · 4.54 FIP	27	SP-	4.54	18.7%	9.1%	3.4%	.317	3.12	27.0%	20.3%	592	-1.42	2.30	2,144	64
Wandy Rodriguez L 2006 · 4.43 FIP	27	SP-	4.43	16.0%	9.2%	2.8%	.311	3.58	21.7%	14.6%	526	-0.85	3.37	1,572	62
Matthew Boyd L 2018 · 4.30 FIP	27	SP	4.30	22.4%	7.2%	4.0%	.252	4.32	26.2%	19.5%	324	+0.02	2.22	1,457	62
Hogan Harris L 2024 · 4.46 FIP	27	SP-	4.46	20.3%	11.8%	2.9%	.312	3.42	26.7%	15.1%	150	-1.04	3.09	501	62
Ken Waldichuk L 2023 · 5.01 FIP	25	SP-	5.01	20.7%	11.0%	4.1%	.303	5.78	21.8%	6.9%	51	+0.77	3.51	432	61
Manny Banuelos L 2018 · 3.48 FIP	27	SP-	3.48	23.8%	8.9%	2.3%	.338	5.89	18.7%	5.9%	51	+2.41	2.95	486	59
Héctor Santiago L 2015 · 4.43 FIP	27	SP	4.43	20.9%	8.5%	3.7%	.245	5.13	19.2%	8.1%	378	+0.70	4.07	1,059	59
Manny Parra L 2010 · 4.19 FIP	27	SW	4.19	23.0%	10.7%	3.1%	.331	3.16	25.6%	15.3%	105	-1.03	2.43	710	58
Tommy Henry L 2024 · 4.36 FIP	27	SP	4.36	19.6%	10.2%	3.0%	.333	5.16	14.7%	5.5%	143	+0.80	4.36	676	58
Tyler Anderson L 2017 · 4.02 FIP	27	SP-	4.02	22.4%	7.3%	3.4%	.315	4.35	20.7%	12.2%	256	+0.33	3.10	1,288	58
Ben Shields L 2024 · 3.23 FIP	25	SP-	3.23	25.3%	8.2%	2.2%	.273	3.02	23.5%	13.3%	43	-0.21	3.02	147	58
Felix Doubront L 2015 · 3.92 FIP	27	SP	3.92	18.0%	8.4%	2.3%	.304	4.12	23.7%	14.7%	42	+0.20	3.44	719	57
Steven Matz L 2018 · 4.33 FIP	27	SP	4.33	23.2%	8.6%	3.8%	.259	4.21	22.5%	15.9%	342	-0.12	3.19	1,226	57
Daniel Lynch IV L 2024 · 4.14 FIP	27	SP-	4.14	18.1%	6.4%	3.2%	.268	4.53	15.7%	7.7%	154	+0.39	2.21	764	57
Eric Lauer L 2022 · 4.36 FIP	27	SP	4.36	23.8%	8.9%	3.9%	.258	4.45	22.7%	14.8%	294	+0.09	3.74	1,097	56

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 2,161 pitcher careers (1,251 from 1990-2025 + 910 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	3.7	83	24.6%	11.5%	1.10	4.12
Bobby Castillo ('77-'85, 5 WAR*)	3.4	86	22.3%*	11.3%*	1.23*	4.27*
Danny Frisella ('67-'76, 4 WAR*)	3.0	68	24.8%*	11.0%*	1.25*	3.99*
Dick Selma ('65-'74, 6 WAR*)	4.2	93	24.5%*	11.1%*	1.12*	4.28*
Brandon Morrow ('18)	4.3	78	24.0%	10.1%	0.92	3.96
Darren Dreifort ('04)	4.4	97	21.2%	10.3%	0.93	4.36
Junior Guerra ('21)	2.5	85	21.2%	10.9%	1.17	4.06