José Soriano — OGILVIE

José Soriano P Toronto Blue Jays

Age 27 RHP 6'3" / 220 lbs MLB Svc 3.0 · Ctrl thru 2028 peak 3.0 · 2026

2026 ROS PROJECTION163 act + 15 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 10698vR 90

ERA3.71

FIP3.64

K%22.7%

BB%10.4%

K-BB%12.3%

ROS IP15

Value2026 · WAR

Runs saved vs league avg · 178 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit━ post-control+$3M ctrl surplus

Grades · Statcast · Arsenal · Contract

Scouting Grades

OFP—55

STUF6565

CTRL3535

CMD3535

K†5555

Statcast Percentiles

FB Velo

p8797.1

Whiff%

p7328.9%

p5222.6%

xwOBA vs

p390.324

FB+8.6 (51%)

SI (29%)

CU (26%)

SL (5%)

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

Status Arb-1

MLB Debut 2023

Service 3.703 yrs.days

Team Control Through 2028

First FA Year 2029

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$0.2M	+0.2	$0.8M	+$0.5M
2027	Arb-2	$9M	+1.5	$11M	+$3M
2028	Arb-3	$10M	+1.1	$8M	+$0.0M (cut)
Totals		$9M		$19M	+$4M

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 industry-standard fWAR.

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 + 2026 so far)
2016	17	ROK MLE	DSL Angels	14	14	57	236	45	30	2	100%	4.1	13.0%	15.9%	-2.9%	1.2%	1.58	4.67	—
2016	17	ROK RAW	DSL Angels	14	14	57	236	45	30	2	100%	4.1	19.1%	12.7%	6.4%	0.8%	1.58	3.56	—
2017	18	ROK MLE	Orem Owlz	13	11	52	218	39	18	2	85%	4.0	12.2%	10.3%	1.8%	1.3%	2.92	4.09	—
2017	18	ROK RAW	Orem Owlz	13	11	52	218	39	18	2	85%	4.0	17.9%	8.3%	9.6%	0.9%	2.92	3.14	—
2018	19	A MLE	Burlington Bees	14	14	46	198	42	35	1	100%	3.3	15.7%	20.9%	-5.2%	0.7%	4.47	4.81	—
2018	19	A RAW	Burlington Bees	14	14	46	198	42	35	1	100%	3.3	21.2%	17.7%	3.5%	0.5%	4.47	3.83	—
2019	20	MIX MLE	2 levels	20	18	82	346	92	51	5	90%	4.1	19.2%	17.5%	1.7%	2.1%	2.51	4.85	—
2019	20	MIX RAW	2 levels	20	18	82	346	92	51	5	90%	4.1	26.6%	14.7%	11.8%	1.4%	2.51	3.51	—
2021	22	A MLE	Bradenton Marauders	2	2	4	20	6	3	0	100%	1.8	30.0%	15.0%	15.0%	0.0%	14.73	2.47	—
2021	22	A RAW	Bradenton Marauders	2	2	4	20	6	3	0	100%	1.8	30.0%	15.0%	15.0%	0.0%	14.73	2.28	—
2022	23	MIX MLE	2 levels	7	7	13	52	17	4	0	100%	1.9	32.7%	7.7%	25.0%	0.0%	2.08	1.31	—
2022	23	MIX RAW	2 levels	7	7	13	52	17	4	0	100%	1.9	32.7%	7.7%	25.0%	0.0%	2.08	1.41	—
2023	24	MIX MLE	2 levels	55	2	65	289	87	37	5	4%	1.2	28.1%	13.4%	14.7%	1.8%	3.86	3.40	+0.9
2023	24	MIX MLE	2 levels	55	2	65	289	87	37	5	4%	1.2	28.1%	13.4%	14.7%	1.8%	3.86	3.40	+0.9
2023	24	MIX RAW	2 levels	55	2	65	289	87	37	5	4%	1.2	30.1%	12.8%	17.3%	1.7%	3.86	3.13	+1.1
2024	25	MLB MLE	Los Angeles Angels	22	20	113	468	97	44	8	91%	5.1	20.7%	9.4%	11.3%	1.7%	3.42	3.46	+2.0
2024	25	MLB MLE	Los Angeles Angels	22	20	113	468	97	44	8	91%	5.1	20.7%	9.4%	11.3%	1.7%	3.42	3.46	+2.0
2024	25	MLB RAW	Los Angeles Angels	22	20	113	468	97	44	8	91%	5.1	20.7%	9.4%	11.3%	1.7%	3.42	3.47	+2.0
2025	26	MLB MLE	Los Angeles Angels	31	31	169	724	152	78	12	100%	5.5	21.0%	10.8%	10.2%	1.6%	4.26	3.58	+2.7
2025	26	MLB MLE	Los Angeles Angels	31	31	169	724	152	78	12	100%	5.5	21.0%	10.8%	10.2%	1.6%	4.26	3.58	+2.7
2025	26	MLB RAW	Los Angeles Angels	31	31	169	724	152	78	12	100%	5.5	21.0%	10.8%	10.2%	1.7%	4.26	3.61	+2.6
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			120	80	487	2058	459	213	40	67%	4.1	22.3%	10.3%	12.0%	1.9%	3.75	3.59	+7.7
▸ 2026 season
YTD	27	MLB MLE	Toronto Blue Jays	29	29	163	681	154	70	16	100%	5.6	22.6%	10.3%	12.3%	2.3%	3.48	3.78	+2.2
YTD	27	MLB MLE	Toronto Blue Jays	29	29	163	681	154	70	16	100%	5.6	22.6%	10.3%	12.3%	2.3%	3.48	3.78	+2.2
▸ 2026 season — so far · projected rest · full
2026	27	MLB RAW	TOR	29	29	163	681	154	70	16	100%	5.6	22.6%	10.3%	12.3%	2.3%	3.48	3.78	+2.2
SO FAR	27	MLB RAW	TOR	29	29	163	681	154	70	16	100%	5.6	22.6%	10.3%	12.3%	2.3%	3.48	3.78	+2.2
ROS	27	MLB MLE	TOR	2	2	15	62	14	6	1	100%	7.4	22.7%	10.4%	12.3%	2.1%	3.71	3.64	+0.2
ROS	27	MLB CTX	TOR	2	2	15	63	14	7	1	100%	7.5	22.7%	10.4%	12.3%	2.1%	3.71	3.64	+0.2
2026 TOT	27	MLB MLE	TOR	—	—	178	743	168	76	17	—	—	22.6%	10.3%	12.3%	2.3%	3.50	3.77	+2.4
FULL	27	MLB A+C	TOR	—	—	178	751	168	76	17	—	—	22.4%	10.2%	12.2%	2.3%	3.50	3.76	+2.4
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	28	MLB MLE	TOR	28	28	166	699	158	73	16	100%	5.9	22.6%	10.5%	12.1%	2.3%	4.16	4.16	+1.4
2028	29	MLB MLE	TOR	26	26	158	668	147	72	16	100%	6.1	22.0%	10.7%	11.3%	2.4%	4.26	4.32	+1.1
2029	30	MLB MLE	TOR	25	25	149	627	134	69	17	100%	5.9	21.3%	11.0%	10.3%	2.6%	4.42	4.53	+0.6
2030	31	MLB MLE	TOR	23	23	139	585	120	67	17	100%	6.0	20.6%	11.4%	9.2%	2.9%	4.63	4.76	+0.2
2031	32	MLB MLE	TOR	21	21	128	541	107	64	17	100%	6.1	19.8%	11.8%	8.0%	3.1%	4.86	5.02	-0.2
2032	33	MLB MLE	TOR	20	20	118	497	94	61	17	100%	5.9	18.9%	12.2%	6.7%	3.4%	5.12	5.30	-0.5
2027	28	MLB CTX	TOR	28	28	166	701	158	74	16	100%	5.9	22.6%	10.5%	12.1%	2.3%	4.16	4.16	+1.5
2028	29	MLB CTX	TOR	26	26	158	667	147	72	16	100%	6.1	22.0%	10.7%	11.3%	2.4%	4.26	4.32	+1.1
2029	30	MLB CTX	TOR	25	25	149	629	134	69	17	100%	6.0	21.3%	11.0%	10.3%	2.6%	4.42	4.53	+0.6
2030	31	MLB CTX	TOR	23	23	139	587	121	67	17	100%	6.0	20.6%	11.4%	9.2%	2.9%	4.63	4.76	+0.2
2031	32	MLB CTX	TOR	21	21	128	540	107	64	17	100%	6.1	19.8%	11.8%	8.0%	3.1%	4.86	5.02	-0.2
2032	33	MLB CTX	TOR	20	20	118	498	94	61	17	100%	5.9	18.9%	12.2%	6.7%	3.4%	5.12	5.30	-0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		265	225	1358	5737	1233	625	141	85%	5.1	21.5%	10.9%	10.6%	2.5%	4.25	4.01	+14.3
/ 200 IP	—	RAW		39	33	200	845	182	92	21	85%	5.1	21.5%	10.9%	10.6%	2.5%	4.25	4.01	+2.1
Career	—	MLE		207	148	765	3232	662	400	55	71%	3.7	20.5%	12.4%	8.1%	1.7%	3.48	3.87	+10.4
/ 200 IP	—	MLE		54	39	200	845	173	104	14	71%	3.7	20.5%	12.4%	8.1%	1.7%	3.48	3.87	+1.5

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
José Soriano (OGILVIE)	—	—	3.96	23.0%	10.5%	2.0%	—	4.33	22.0%	11.3%	472	+0.37	—	—	—
Tyler Chatwood R 2017 · 4.54 FIP	27	SP-	4.54	19.0%	11.9%	2.8%	.279	4.53	20.6%	5.2%	199	-0.01	3.30	537	68
Taylor Jungmann R 2017 · 3.88 FIP	27	SP-	3.88	18.8%	11.1%	1.8%	.279	—	—	—	—	—	3.59	435	59
Mike Foltynewicz R 2019 · 4.20 FIP	27	SP	4.20	20.4%	7.5%	3.4%	.278	5.53	16.6%	10.5%	139	+1.33	3.17	938	59
Aaron Sanchez R 2019 · 4.74 FIP	27	SP	4.74	19.0%	10.9%	3.4%	.309	4.68	14.9%	7.1%	175	-0.06	3.43	924	57
Jon Gray R 2019 · 3.60 FIP	27	SP	3.60	23.5%	8.2%	2.6%	.308	3.75	23.5%	15.5%	315	+0.15	2.93	1,345	57
Louis Varland R 2023 · 4.12 FIP	25	SP-	4.12	22.7%	6.4%	3.9%	.309	3.34	25.0%	18.0%	279	-0.78	1.69	684	56
Daniel Ponce de Leon R 2019 · 4.09 FIP	27	SP	4.09	22.8%	12.0%	2.5%	.246	5.09	22.7%	10.1%	182	+1.00	3.35	768	56
Kevin Gausman R 2018 · 4.13 FIP	27	SP	4.13	19.1%	6.3%	3.4%	.295	3.14	28.6%	22.3%	354	-0.99	2.34	1,930	55
Rafael Montero R 2017 · 3.88 FIP	26	SP-	3.88	22.0%	11.2%	2.2%	.339	3.41	28.7%	22.8%	47	-0.47	2.43	670	55
Mitch Atkins R 2016 · 3.65 FIP	30	SP-	3.65	21.4%	8.2%	2.4%	.341	4.77	14.3%	6.2%	78	+1.12	3.65	205	54
Patrick Johnson R 2016 · 3.82 FIP	27	SP-	3.82	17.3%	6.9%	2.4%	.286	4.14	15.7%	6.4%	120	+0.32	3.82	248	53
Yordano Ventura R 2016 · 4.48 FIP	25	SP	4.48	17.6%	9.4%	3.0%	.292	—	—	—	—	—	3.44	349	53
Jimmy Nelson R 2016 · 4.57 FIP	27	SP	4.57	17.3%	10.4%	2.9%	.289	3.16	27.2%	18.6%	238	-1.41	1.32	650	53
Zach Plesac R 2022 · 4.30 FIP	27	SP	4.30	17.6%	6.7%	3.4%	.285	6.44	13.5%	5.0%	286	+2.14	3.27	965	53
Jared Mortensen R 2015 · 4.42 FIP	27	SP-	4.42	16.9%	7.8%	3.2%	.287	4.99	20.9%	2.1%	72	+0.57	4.42	200	52
Wily Peralta R 2016 · 4.41 FIP	27	SP	4.41	17.1%	7.9%	3.2%	.346	4.70	18.8%	6.6%	183	+0.29	3.98	748	52
Nathan Eovaldi R 2016 · 4.71 FIP	26	SP	4.71	18.5%	7.2%	4.1%	.272	4.29	22.6%	15.6%	179	-0.42	2.44	1,378	52
Jacob Turner R 2018 · 4.48 FIP	27	SP-	4.48	14.9%	8.8%	2.8%	.297	—	—	—	—	—	4.29	340	51
Hiram Burgos R 2015 · 3.40 FIP	27	SP	3.40	19.7%	9.5%	1.4%	.282	4.34	17.2%	8.6%	206	+0.94	3.40	355	51
David Hale R 2015 · 4.15 FIP	27	SP-	4.15	16.2%	6.8%	2.8%	.343	4.11	13.8%	8.1%	251	-0.04	3.30	493	50

Career Comps

Retired MLB careers whose totals most resemble what we're projecting for this player. Pool: 133 completed pitcher careers (2015-2024).

Player	162s	IP/yr	K%	BB%	HR/9	ERA
OGILVIE CAREER PROJECTION	5.1	146	21.3%	11.1%	1.02	4.45
Julio Teheran ('23)	5.2	147	20.4%	8.8%	1.34	4.12
Carlos Martinez ('21)	4.2	121	22.7%	9.1%	0.81	3.67
Aaron Sanchez ('22)	3.3	93	18.1%	10.0%	0.98	4.32
Trevor Bauer ('21)	5.6	159	26.8%	8.7%	1.13	3.68
Zach Davies ('23)	5.2	116	17.5%	8.1%	1.16	4.36
Mike Foltynewicz ('21)	4.0	134	21.4%	7.7%	1.46	4.45