Chris Bassitt — OGILVIE

Chris Bassitt P Baltimore Orioles

Age 37 RHP 6'5" / 220 lbs MLB Svc 9.0 · Ctrl thru 2026 peak 2.2 · 2026

2026 ROS PROJECTION104 act + 13 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 117109vR 101

ERA3.97

FIP4.12

K%18.2%

BB%8.1%

K-BB%10.1%

ROS IP13

Value2026 · WAR

Runs saved vs league avg · 117 IP

Grades · Statcast · Arsenal · Contract

Scouting Grades

OFP—45

STUF4545

CTRL5050

CMD4540

K†5050

Statcast Percentiles

FB Velo

p1892.2

Whiff%

p2021.1%

p1016.0%

xwOBA vs

p230.344

SL+1.0 (9%)

CT (19%)

SI (38%)

CU (22%)

CH (5%)

FB-9.4 (45%)

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

Status FA

MLB Debut 2015

Service 9.756 yrs.days

Team Control Through 2026

First FA Year 2027

OPT

Year	Status	Salary	Proj WAR	Value	Surplus
2026ROS	Ext	$1M	+0.1	$0.4M	-$1M
Totals		$1M		$0.4M	-$1M

Options · projected decision
2027	MUTUAL OPT	$18.5M / $0.0M buyout	DECLINE
2028	MUTUAL OPT	$19.0M / $0.0M buyout	DECLINE

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)
2015	26	MIX MLE	2 levels	31	23	155	646	134	49	6	74%	5.0	19.4%	7.7%	11.7%	1.1%	3.60	3.02	+3.6
2015	26	MIX RAW	2 levels	31	23	155	646	134	49	6	74%	5.0	20.7%	7.6%	13.2%	0.9%	3.60	2.82	+4.0
2016	27	MLB MLE	Oakland Athletics	5	5	28	133	23	14	5	100%	5.6	17.3%	10.5%	6.8%	4.1%	6.11	5.24	-0.1
2016	27	MLB RAW	Oakland Athletics	5	5	28	133	23	14	5	100%	5.6	17.3%	10.5%	6.8%	3.8%	6.11	5.28	-0.1
2017	28	MIX MLE	2 levels	24	9	51	218	45	20	3	38%	2.1	17.5%	9.8%	7.6%	1.7%	5.33	3.83	—
2017	28	MIX RAW	2 levels	24	9	51	218	45	20	3	38%	2.1	20.6%	9.2%	11.5%	1.4%	5.33	3.28	—
2018	29	MIX MLE	2 levels	29	21	129	556	124	44	10	72%	4.5	20.5%	8.1%	12.4%	2.0%	3.83	3.49	+2.2
2018	29	MIX RAW	2 levels	29	21	129	556	124	44	10	72%	4.5	22.3%	7.9%	14.4%	1.8%	3.83	3.21	+2.7
2019	30	MIX MLE	3 levels	31	28	155	657	157	49	23	90%	5.0	23.0%	7.7%	15.4%	3.8%	3.77	4.20	+1.3
2019	30	MIX RAW	3 levels	31	28	155	657	157	49	23	90%	5.0	23.9%	7.5%	16.4%	3.5%	3.77	3.95	+1.8
2020	31	MLB MLE	Oakland Athletics	11	11	63	261	55	17	6	100%	5.7	21.1%	6.5%	14.6%	2.5%	2.29	3.53	+1.1
2020	31	MLB RAW	Oakland Athletics	11	11	63	261	55	17	6	100%	5.7	21.1%	6.5%	14.6%	2.3%	2.29	3.40	+1.2
2021	32	MLB MLE	Oakland Athletics	27	27	157	637	159	38	15	100%	5.8	25.0%	6.0%	19.0%	2.6%	3.15	3.17	+3.4
2021	32	MLB RAW	Oakland Athletics	27	27	157	637	159	38	15	100%	5.8	25.0%	6.0%	19.0%	2.4%	3.15	3.04	+3.7
2022	33	MLB MLE	New York Mets	30	30	182	745	167	49	19	100%	6.1	22.4%	6.6%	15.8%	2.6%	3.42	3.44	+3.3
2022	33	MLB RAW	New York Mets	30	30	182	745	167	49	19	100%	6.1	22.4%	6.6%	15.8%	2.6%	3.42	3.43	+3.3
2023	34	MLB MLE	Toronto Blue Jays	33	33	200	826	186	57	28	100%	6.1	22.5%	6.9%	15.6%	3.4%	3.60	3.93	+2.3
2023	34	MLB MLE	Toronto Blue Jays	33	33	200	826	186	57	28	100%	6.1	22.5%	6.9%	15.6%	3.4%	3.60	3.93	+2.3
2023	34	MLB RAW	Toronto Blue Jays	33	33	200	826	186	57	28	100%	6.1	22.5%	6.9%	15.6%	3.4%	3.60	3.92	+2.4
2024	35	MLB MLE	Toronto Blue Jays	31	31	171	758	168	68	18	100%	5.5	22.2%	9.0%	13.2%	2.4%	4.16	3.67	+2.6
2024	35	MLB MLE	Toronto Blue Jays	31	31	171	758	168	68	18	100%	5.5	22.2%	9.0%	13.2%	2.4%	4.16	3.67	+2.6
2024	35	MLB RAW	Toronto Blue Jays	31	31	171	758	168	68	18	100%	5.5	22.2%	9.0%	13.2%	2.4%	4.16	3.70	+2.5
2025	36	MLB MLE	Toronto Blue Jays	32	31	170	736	166	52	22	97%	5.3	22.6%	7.1%	15.5%	3.0%	3.96	3.73	+2.4
2025	36	MLB MLE	Toronto Blue Jays	32	31	170	736	166	52	22	97%	5.3	22.6%	7.1%	15.5%	3.0%	3.96	3.73	+2.4
2025	36	MLB RAW	Toronto Blue Jays	32	31	170	736	166	52	22	97%	5.3	22.6%	7.1%	15.5%	3.0%	3.96	3.75	+2.4
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			244	229	1339	5685	1236	427	153	94%	5.5	21.7%	7.5%	14.2%	2.7%	3.72	3.70	+19.5
▸ 2026 season
YTD	37	MLB MLE	Baltimore Orioles	21	19	104	465	78	40	11	90%	5.0	16.3%	8.5%	7.8%	2.3%	4.50	4.06	+1.0
YTD	37	MLB MLE	Baltimore Orioles	21	19	104	465	78	40	11	90%	5.0	16.3%	8.5%	7.8%	2.3%	4.50	4.06	+1.0
▸ 2026 season — so far · projected rest · full
2026	37	AAA RAW	BAL	3	3	14	53	12	4	1	100%	4.6	22.6%	7.5%	15.1%	1.9%	1.98	3.18	—
2026	37	MLB RAW	BAL	18	16	90	412	66	36	10	89%	5.0	16.0%	8.7%	7.3%	2.4%	4.88	4.19	+0.8
SO FAR	37	MLB RAW	BAL	18	16	90	412	66	36	10	89%	5.0	16.0%	8.7%	7.3%	2.4%	4.88	4.19	+0.8
ROS	37	MLB MLE	BAL	2	2	13	54	10	4	2	100%	6.4	18.2%	8.1%	10.1%	2.8%	3.97	4.12	+0.1
ROS	37	MLB CTX	BAL	2	2	13	55	10	4	2	100%	6.5	18.2%	8.1%	10.1%	2.9%	4.04	4.19	+0.1
2026 TOT	37	MLB MLE	BAL	—	—	117	519	88	44	13	—	—	16.9%	8.6%	8.4%	2.4%	4.44	4.07	+1.2
FULL	37	MLB A+C	BAL	—	—	103	435	88	44	13	—	—	20.2%	10.2%	10.0%	2.9%	5.04	4.27	+1.0
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	38	MLB MLE	BAL	22	22	130	549	95	49	17	100%	5.9	17.3%	8.9%	8.3%	3.1%	4.64	4.87	+0.0
2028	39	MLB MLE	BAL	19	19	112	472	76	46	17	100%	5.9	16.1%	9.7%	6.5%	3.6%	5.04	5.31	-0.5
2027	38	MLB CTX	BAL	22	22	130	549	95	49	18	100%	5.9	17.3%	8.9%	8.3%	3.3%	4.72	4.95	+0.0
2028	39	MLB CTX	BAL	19	19	112	473	76	46	18	100%	5.9	16.1%	9.7%	6.5%	3.7%	5.13	5.40	-0.5
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		287	272	1594	6760	1417	526	190	95%	5.6	21.0%	7.8%	13.2%	2.8%	3.90	3.86	+19.9
/ 200 IP	—	RAW		36	34	200	848	178	66	24	95%	5.6	21.0%	7.8%	13.2%	2.8%	3.90	3.86	+2.5
Career	—	MLE		305	268	1565	6638	1429	502	173	88%	5.1	21.5%	7.6%	14.0%	2.6%	3.78	3.67	+18.9
/ 200 IP	—	MLE		39	34	200	848	183	64	22	88%	5.1	21.5%	7.6%	14.0%	2.6%	3.78	3.67	+2.4

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
Chris Bassitt (OGILVIE)	—	—	4.20	21.7%	7.7%	2.9%	—	5.07	16.7%	7.5%	242	+0.87	—	—	—
James Shields R 2018 · 4.85 FIP	36	SP	4.85	17.7%	9.0%	3.8%	.258	—	—	—	—	—	4.15	720	68
Adam Wainwright R 2019 · 4.08 FIP	37	SP	4.08	20.5%	7.7%	3.2%	.310	3.65	19.6%	13.5%	464	-0.43	2.03	1,127	63
John Lackey R 2016 · 3.70 FIP	37	SP	3.70	24.1%	7.0%	3.2%	.249	5.05	20.4%	13.6%	171	+1.35	3.51	577	49
Colby Lewis R 2016 · 4.67 FIP	36	SP	4.67	15.5%	5.9%	3.9%	.239	—	—	—	—	—	3.89	321	47
Jake Peavy R 2016 · 4.35 FIP	35	SP-	4.35	19.6%	6.7%	3.7%	.318	—	—	—	—	—	4.07	262	41
Roberto Hernandez R 2016 · 4.38 FIP	35	SP	4.38	13.8%	7.0%	2.8%	.299	—	—	—	—	—	4.38	171	41
Jeremy Guthrie R 2016 · 4.85 FIP	37	SP	4.85	11.6%	8.6%	3.0%	.359	—	—	—	—	—	4.85	235	40
Jarrett Grube R 2017 · 4.41 FIP	35	SP	4.41	15.8%	8.1%	3.0%	.296	—	—	—	—	—	3.75	393	39
Aaron Harang R 2015 · 4.47 FIP	37	SP	4.47	14.4%	6.4%	3.2%	.288	—	—	—	—	—	4.47	172	39
Frankie De La Cruz R 2019 · 4.38 FIP	35	SP-	4.38	16.2%	8.0%	3.0%	.322	—	—	—	—	—	3.77	240	38
Ryan Vogelsong R 2015 · 4.45 FIP	38	SP-	4.45	18.1%	9.4%	3.1%	.295	4.79	16.7%	6.3%	82	+0.34	4.45	217	38
A.J. Burnett R 2015 · 3.16 FIP	38	SP	3.16	20.5%	6.7%	1.7%	.327	—	—	—	—	—	3.16	164	38
Walter Silva R 2015 · 4.15 FIP	38	SP	4.15	14.8%	7.4%	2.5%	.311	3.91	10.4%	3.7%	209	-0.24	3.67	428	37
Brad Penny R 2015 · 3.68 FIP	37	SP	3.68	12.0%	5.8%	1.6%	.346	—	—	—	—	—	3.68	135	37
Tim Hudson R 2015 · 4.41 FIP	40	SP	4.41	12.2%	6.9%	2.7%	.294	—	—	—	—	—	4.41	124	36
Yasutomo Kubo R 2019 · 3.98 FIP	38	SP	3.98	20.4%	4.7%	3.6%	.327	—	—	—	—	—	3.98	152	36
Edgar Gonzalez R 2019 · 4.58 FIP	36	SP	4.58	12.3%	5.8%	3.2%	.331	—	—	—	—	—	3.19	450	35
Kyle Lohse R 2016 · 4.97 FIP	37	SP	4.97	14.8%	6.0%	4.3%	.287	—	—	—	—	—	4.77	211	35
Pablo Ortega R 2015 · 4.52 FIP	38	SP	4.52	8.6%	7.3%	2.2%	.291	4.24	11.5%	6.0%	236	-0.28	4.01	375	34
Kameron Loe R 2017 · 3.38 FIP	35	SP	3.38	17.1%	8.0%	1.3%	.317	—	—	—	—	—	3.38	201	34

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	2.0	131	18.7%	8.7%	1.22	4.53
James Kaprielian ('23)	1.6	105	20.5%	9.6%	1.26	4.58
Dan Straily ('19)	2.7	136	20.0%	8.9%	1.72	4.54
Mike Foltynewicz ('21)	4.0	134	21.4%	7.7%	1.46	4.45
Kutter Crawford ('24)	2.0	130	23.9%	7.2%	1.45	4.47
Julio Teheran ('23)	5.2	147	20.4%	8.8%	1.34	4.12
Homer Bailey ('19)	1.9	96	18.5%	7.8%	1.34	5.56