Tyler Switalski — OGILVIE

Tyler Switalski P Eugene Emeralds

Age 23 LHP 6'4" / 248 lbs A+ Svc 0.0 · Ctrl thru 2034 peak 1.2 · 2028

2026 ROS PROJECTION101 act + 6 ip · rates below = ROS only

showingROS

wRC+ AGAINSTvL 118126vR 135

ERA5.34

FIP5.34

K%14.0%

BB%13.1%

K-BB%0.9%

ROS IP6

Value2026 · WAR

Runs saved vs league avg · 106 IP

━ projected WAR━ paid WAR ($/8M) surplus deficit-$11M ctrl surplus

Grades · Contract

Scouting Grades

STUF3535

CTRL4040

CMD3535

K†3040

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

Status MiLB

MLB Debut 2029

Service 0 yrs (est)

Team Control Through 2034

First FA Year 2035

Year	Status	Salary	Proj WAR	Value	Surplus
2026	MiLB	still in minors · estimated debut 2029
2027	MiLB	still in minors · estimated debut 2029
2028	MiLB	still in minors · estimated debut 2029
2029	Pre-Arb	$0.8M	+0.1	$0.3M	+$0.0M (cut)
2030	Pre-Arb	$0.9M	—	—	—
2031	Pre-Arb	$0.9M	—	—	—
2032	Arb-1	$0.8M	—	—	—
2033	Arb-2	$0.7M	—	—	—
2034	Arb-3	$7M	—	—	—
Totals		$0.0M		$-2M	+$0.0M

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)
2025	22	MIX MLE	2 levels	24	4	97	407	82	40	3	17%	4.0	15.0%	11.5%	3.5%	0.7%	4.00	3.68	—
2025	22	MIX MLE	2 levels	24	4	97	407	82	40	3	17%	4.0	15.0%	11.5%	3.5%	0.7%	4.00	3.68	—
2025	22	MIX RAW	2 levels	24	4	97	407	82	40	3	17%	4.0	20.1%	9.8%	10.3%	0.7%	4.00	3.05	—
▸ 2026 season
YTD	23	AA MLE	Richmond Flying Squirrels	22	21	101	447	119	44	19	95%	4.6	20.7%	11.2%	9.6%	5.2%	5.45	5.64	—
YTD	23	AA MLE	Richmond Flying Squirrels	22	21	101	447	119	44	19	95%	4.6	20.7%	11.2%	9.6%	5.2%	5.45	5.64	—
▸ 2026 season — so far · projected rest · full
2026	23	A+ RAW	SF	16	15	75	316	94	29	13	94%	4.7	29.7%	9.2%	20.6%	4.1%	4.22	4.01	—
2026	23	AA RAW	SF	6	6	26	131	25	15	6	100%	4.3	19.1%	11.5%	7.6%	4.6%	9.00	5.45	—
ROS	23	MLB MLE	SF	1	1	6	24	3	3	1	100%	5.7	14.0%	13.1%	0.9%	2.5%	5.34	5.34	-0.0
2026 TOT	23	MLB MLE	SF	—	—	106	471	122	47	20	—	—	26.0%	10.0%	16.0%	4.2%	5.45	5.63	-0.8
▸ Career projection (2027+) — MLB context, MLB playing time (IP × MLB%)
2027	24	MLB MLE	SF	14	14	101	427	68	51	11	100%	7.2	16.0%	12.0%	3.9%	2.5%	5.12	5.05	-0.2
2028	25	MLB MLE	SF	14	14	102	432	74	49	11	100%	7.3	17.1%	11.4%	5.7%	2.6%	4.96	4.89	+0.0
2029	26	MLB MLE	SF	14	14	102	432	76	48	11	100%	7.3	17.6%	11.2%	6.5%	2.6%	4.86	4.82	+0.1
2030	27	MLB MLE	SF	14	14	101	426	76	48	11	100%	7.2	17.7%	11.2%	6.6%	2.6%	4.85	4.85	+0.1
2031	28	MLB MLE	SF	14	14	98	413	73	47	11	100%	7.0	17.6%	11.3%	6.3%	2.7%	4.90	4.93	-0.0
2032	29	MLB MLE	SF	13	13	94	395	69	46	11	100%	7.2	17.4%	11.5%	5.8%	2.9%	5.00	5.06	-0.2
2033	30	MLB MLE	SF	12	12	88	371	63	44	11	100%	7.3	17.0%	11.8%	5.2%	3.1%	5.14	5.24	-0.3
2027	24	MLB CTX	SF	6	6	43	182	29	22	4	100%	7.2	16.0%	12.0%	3.9%	2.3%	5.02	4.95	-0.1
2028	25	MLB CTX	SF	10	10	68	287	49	33	7	100%	6.8	17.1%	11.4%	5.7%	2.4%	4.85	4.78	+0.0
2029	26	MLB CTX	SF	11	11	81	342	60	38	8	100%	7.4	17.6%	11.2%	6.5%	2.4%	4.75	4.71	+0.1
2030	27	MLB CTX	SF	12	12	86	363	64	41	9	100%	7.2	17.7%	11.2%	6.6%	2.4%	4.74	4.74	+0.0
2031	28	MLB CTX	SF	12	12	87	367	65	42	9	100%	7.2	17.6%	11.3%	6.3%	2.5%	4.79	4.82	-0.0
2032	29	MLB CTX	SF	12	12	85	359	62	41	10	100%	7.1	17.4%	11.5%	5.8%	2.7%	4.88	4.94	-0.2
2033	30	MLB CTX	SF	11	11	81	342	58	40	10	100%	7.4	17.0%	11.8%	5.2%	2.9%	5.01	5.11	-0.3
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		75	75	532	2246	389	257	57	100%	7.1	17.3%	11.5%	5.8%	2.5%	4.85	4.48	+2.6
/ 200 IP	—	RAW		28	28	200	844	146	97	21	100%	7.1	17.3%	11.5%	5.8%	2.5%	4.85	4.48	+1.0
Career	—	MLE		46	25	197	854	154	97	26	54%	4.3	18.0%	11.3%	6.7%	3.1%	4.74	4.71	-0.6
/ 200 IP	—	MLE		47	25	200	866	156	98	27	54%	4.3	18.0%	11.3%	6.7%	3.1%	4.74	4.71	-0.2

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
Tyler Switalski (OGILVIE)	—	—	5.34	14.0%	13.1%	2.5%	—	4.92	16.9%	5.3%	306	-0.42	—	—	—
Cole Kirschsieper L 2023 · 5.07 FIP	22	SP-	5.07	15.2%	12.0%	3.2%	.268	—	—	—	—	—	5.07	105	85
Nate Peterson L 2023 · 4.46 FIP	23	SP-	4.46	18.4%	11.4%	2.7%	.284	5.04	17.2%	5.3%	241	+0.58	4.27	315	83
Pat Peterson L 2015 · 4.17 FIP	22	SP-	4.17	13.5%	10.6%	1.6%	.303	—	—	—	—	—	4.17	108	82
Rolando Gutierrez L 2023 · 4.59 FIP	21	SP-	4.59	12.8%	10.9%	2.2%	.286	3.80	16.2%	-0.1%	18	-0.79	3.53	113	82
Tim Berry L 2015 · 4.46 FIP	24	SP-	4.46	12.0%	9.7%	2.1%	.346	5.03	14.7%	-0.6%	113	+0.57	4.04	196	81
Dominic Perachi L 2023 · 5.19 FIP	22	SP-	5.19	17.5%	13.9%	3.3%	.324	3.80	17.1%	6.8%	186	-1.39	3.33	277	80
Bryan Radziewski L 2015 · 4.15 FIP	23	SP-	4.15	16.4%	10.5%	2.0%	.280	—	—	—	—	—	4.15	106	80
Joe Kemlage L 2022 · 4.42 FIP	23	SW	4.42	19.4%	13.5%	2.3%	.278	5.35	17.6%	5.9%	65	+0.93	4.42	128	79
Wandy Peralta L 2015 · 4.50 FIP	24	SP-	4.50	12.4%	12.6%	1.6%	.324	3.83	17.3%	7.3%	200	-0.67	2.69	725	79
Scott DeCecco L 2015 · 4.55 FIP	24	SP-	4.55	14.5%	11.5%	2.2%	.331	—	—	—	—	—	4.55	125	78
Ian Clarkin L 2018 · 5.33 FIP	23	SP-	5.33	9.3%	11.2%	2.9%	.290	6.01	8.1%	-4.9%	82	+0.68	3.79	335	78
Gabriel Castellanos L 2016 · 4.49 FIP	22	SP	4.49	15.5%	13.7%	1.8%	.348	3.41	15.3%	2.7%	26	-1.08	3.41	108	77
Luis Leroy Cruz L 2015 · 5.03 FIP	24	SP-	5.03	16.0%	10.1%	3.7%	.289	—	—	—	—	—	5.03	116	77
Jake Zokan L 2015 · 4.89 FIP	24	SP	4.89	12.5%	9.9%	2.9%	.292	1.79	24.2%	22.5%	37	-3.10	1.79	120	76
Amilcar Gaxiola L 2015 · 4.58 FIP	24	SP-	4.58	6.3%	8.4%	1.7%	.323	4.99	11.3%	1.8%	148	+0.41	4.58	321	76
Connor Bach L 2015 · 4.48 FIP	23	SP-	4.48	16.4%	17.0%	1.1%	.304	5.82	18.5%	-9.3%	14	+1.34	4.48	124	76
Colin Rodgers L 2017 · 4.56 FIP	23	SP-	4.56	16.2%	11.9%	2.4%	.320	4.36	16.8%	7.1%	68	-0.20	4.02	313	75
Adam Tulloch L 2023 · 4.51 FIP	23	SP-	4.51	20.3%	14.1%	2.4%	.313	4.62	18.1%	1.5%	150	+0.11	4.24	246	75
Evan Grills L 2015 · 5.42 FIP	23	SP-	5.42	13.0%	8.6%	4.2%	.335	4.02	16.1%	11.6%	221	-1.40	3.41	309	74
Kenny Rosenberg L 2018 · 4.70 FIP	23	SP-	4.70	16.1%	10.9%	2.9%	.317	4.25	18.6%	8.1%	165	-0.45	3.44	755	74

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	3.8	94	16.9%	11.6%	1.04	5.01
Chad Kuhl ('24)	3.3	84	20.0%	10.4%	1.31	4.98
Aaron Sanchez ('22)	3.3	93	18.1%	10.0%	0.98	4.32
Dakota Hudson ('24)	2.8	92	15.0%	11.1%	0.91	4.25
Steven Brault ('21)	1.7	57	18.8%	11.3%	1.00	4.77
Tyler Chatwood ('21)	2.6	104	19.2%	13.3%	0.94	4.48
Junior Guerra ('21)	2.5	84	21.3%	11.0%	1.16	4.04