Shane McClanahan

P Tampa Bay Rays

Age 30 LHP 6'3" / 210 lbs MLB Svc 5.0 · Ctrl thru 2027 peak 1.4 · 2027 ILForty Man (40M)

Overview

MLBSP40M40-MANArb-3FA 2028

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2023	26	MLBTB	21	21	115	3.29	3.76	25.8%	8.7%	2.3
2025	28	MIX2 levels	3	3	3	10.80	9.70	26.3%	10.5%	—	K 26.3% · BB 10.5% · FIP 7.99
2026	29	MIX2 levels	25	25	121	3.27	3.36	21.8%	7.9%	3.0	K 21.8% · BB 8.0% · FIP 3.44
2027PROJ	30	MLBTB	13	13	79	3.90	3.91	23.1%	8.0%	1.4
2028PROJ	31	MLBTB	14	14	84	4.00	4.10	22.4%	8.4%	1.3
2029PROJ	32	MLBTB	11	11	68	4.21	4.36	21.6%	8.8%	0.8

Last 3 seasons WAR 5.3 · Next 3 projected WAR 3.5Projected rows: MLB playing time only, park and league context applied.

ContractESTIMATED

Control thru2027Service5.919First FA2028

2027Arb-3$7M

Skills · percentileStatcast 2026

FB Velo65

K%47

xwOBA vs44

Form4.50 ERA (proj 3.90) · K 20.0% (proj 23.1%) · BB 6.7% (proj 8.0%) · last 90d · 22 IP through Oct 27

CompsJorge Castillo (age 33) · Ryan Bollinger (age 27) · Tomas Solis (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 92100vR 108

ERA3.90

FIP3.91

K%23.1%

BB%8.0%

K-BB%15.1%

Proj IP79

Value2027 · WAR

Runs saved vs league avg · 79 IP

Grades · Statcast · Contract

Scouting Grades

STUF6565

CTRL5555

CMD6060

K†5555

Statcast Percentiles

FB Velo

p6595.6

Whiff%

p6026.8%

p4721.8%

xwOBA vs

p440.318

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

Status Arb-3

MLB Debut 2021

Service 5.919 yrs.days

Team Control Through 2027

First FA Year 2028

Year	Status	Salary	Proj WAR	Value	Surplus
2027	Arb-3	$7M	+1.4	$11M	+$4M
Totals		$7M		$11M	+$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 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)
2018	21	ROK MLE	Princeton Rays	4	4	7	24	13	1	0	100%	1.8	54.2%	4.2%	50.0%	0.0%	0.00	-0.95	—
2018	21	ROK RAW	Princeton Rays	4	4	7	24	13	1	0	100%	1.8	54.2%	4.2%	50.0%	0.0%	0.00	-0.19	—
2019	22	MIX MLE	3 levels	24	22	121	504	154	45	7	92%	5.0	23.3%	10.4%	12.9%	1.7%	3.36	3.36	—
2019	22	MIX RAW	3 levels	24	22	121	504	154	45	7	92%	5.0	30.6%	8.9%	21.6%	1.4%	3.36	2.42	—
2021	24	MLB MLE	Tampa Bay Rays	25	25	123	517	141	37	14	100%	4.9	27.3%	7.2%	20.1%	2.8%	3.43	3.23	+3.3
2021	24	MLB RAW	Tampa Bay Rays	25	25	123	517	141	37	14	100%	4.9	27.3%	7.2%	20.1%	2.7%	3.43	3.19	+3.4
2022	25	MLB MLE	Tampa Bay Rays	28	28	166	641	194	37	19	100%	5.9	30.3%	5.8%	24.5%	3.0%	2.54	2.95	+5.1
2022	25	MLB RAW	Tampa Bay Rays	28	28	166	641	194	37	19	100%	5.9	30.3%	5.8%	24.5%	3.0%	2.54	2.92	+5.2
2023	26	MLB MLE	Tampa Bay Rays	21	21	115	469	121	41	15	100%	5.5	25.8%	8.7%	17.1%	3.3%	3.29	3.83	+2.2
2023	26	MLB RAW	Tampa Bay Rays	21	21	115	469	121	41	15	100%	5.5	25.8%	8.7%	17.1%	3.2%	3.29	3.76	+2.3
2025	28	MIX MLE	2 levels	3	3	3	19	5	2	2	100%	1.1	26.3%	10.5%	15.8%	10.5%	10.80	7.99	—
2025	28	MIX MLE	2 levels	3	3	3	19	5	2	2	100%	1.1	26.3%	10.5%	15.8%	10.5%	10.80	7.99	—
2025	28	MIX RAW	2 levels	3	3	3	19	5	2	2	100%	1.1	26.3%	10.5%	15.8%	10.5%	10.80	9.70	—
2026	29	MIX MLE	2 levels	25	25	121	496	108	39	10	100%	4.8	21.8%	8.0%	13.8%	2.1%	3.27	3.44	+2.9
2026	29	MIX MLE	2 levels	25	25	121	496	108	39	10	100%	4.8	21.8%	8.0%	13.8%	2.1%	3.27	3.44	+2.9
2026	29	MIX RAW	2 levels	25	25	121	496	108	39	10	100%	4.8	21.8%	7.9%	13.9%	2.0%	3.27	3.36	+3.0
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			98	98	523	2114	562	154	58	100%	5.3	26.6%	7.3%	19.3%	2.7%	3.10	3.28	+13.7
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	30	MLB	TB	13	13	79	334	77	27	8	100%	6.1	23.1%	8.0%	15.1%	2.5%	3.90	3.91	+1.4
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	31	MLB MLE	TB	14	14	84	353	79	30	10	100%	6.0	22.4%	8.4%	14.0%	2.7%	4.04	4.14	+1.2
2029	32	MLB MLE	TB	11	11	68	289	62	25	9	100%	6.2	21.6%	8.8%	12.8%	3.0%	4.25	4.40	+0.8
2030	33	MLB MLE	TB	9	9	53	222	46	20	7	100%	5.8	20.7%	9.2%	11.5%	3.2%	4.51	4.68	+0.4
2031	34	MLB MLE	TB	6	6	37	155	31	15	5	100%	6.1	19.8%	9.7%	10.1%	3.5%	4.79	4.98	+0.2
2028	31	MLB CTX	TB	14	14	84	355	79	30	9	100%	6.0	22.4%	8.4%	14.0%	2.6%	4.00	4.10	+1.3
2029	32	MLB CTX	TB	11	11	68	287	62	25	8	100%	6.2	21.6%	8.8%	12.8%	2.9%	4.21	4.36	+0.8
2030	33	MLB CTX	TB	9	9	53	224	46	21	7	100%	5.9	20.7%	9.2%	11.5%	3.1%	4.46	4.63	+0.4
2031	34	MLB CTX	TB	6	6	37	156	31	15	5	100%	6.2	19.8%	9.7%	10.1%	3.4%	4.74	4.93	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		138	138	764	3133	780	245	88	100%	5.5	24.9%	7.8%	17.1%	2.8%	3.47	3.53	+17.5
/ 200 IP	—	RAW		36	36	200	820	204	64	23	100%	5.5	24.9%	7.8%	17.1%	2.8%	3.47	3.53	+4.6
Career	—	MLE		130	128	657	2670	699	210	70	98%	5.1	26.2%	7.9%	18.3%	2.6%	3.14	3.33	+16.2
/ 200 IP	—	MLE		40	39	200	813	213	64	21	98%	5.1	26.2%	7.9%	18.3%	2.6%	3.14	3.33	+4.2

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.

2019 ABowling Green Hot Rods · 53 IPFIP 2.80 → 3.86 (+1.06)K% 33.2% → 24.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.18%	—	×0.740	24.56%
BB% (unintentional) /BF	13.90%	—	×1.180	16.40%
HR / BF /BF	1.35%	÷1.270	×1.300	1.38%

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 154).

Result: FIP 2.80 → 3.86, 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+Charlotte Stone Crabs · 49 IPFIP 1.31 → 2.08 (+0.77)K% 30.9% → 23.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	30.89%	—	×0.770	23.79%
BB% (unintentional) /BF	4.19%	—	×1.150	4.82%
HR / BF /BF	0.52%	÷0.939	×1.250	0.70%

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 88).

Result: FIP 1.31 → 2.08, 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 AAMontgomery Biscuits · 18 IPFIP 3.80 → 4.82 (+1.02)K% 23.3% → 18.9%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.33%	—	×0.810	18.90%
BB% (unintentional) /BF	6.67%	—	×1.100	7.33%
HR / BF /BF	3.33%	÷0.920	×1.200	4.35%

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 84).

Result: FIP 3.80 → 4.82, 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).

2018 ROKPrinceton Rays · 7 IPFIP -0.95 → 0.65 (+1.60)K% 54.2% → 36.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	54.17%	—	×0.680	36.83%
BB% (unintentional) /BF	4.17%	—	×1.250	5.21%
HR / BF /BF	0.00%	÷1.000	×1.400	0.00%

Factors used: pitcher ROK level factors — K ×0.68, BB ×1.25, HR ×1.40. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 100).

Result: FIP -0.95 → 0.65, 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
Shane McClanahan (OGILVIE)	—	—	3.91	23.1%	8.0%	2.5%	—	4.37	21.7%	13.0%	205	+0.46	—	—	—
Jorge Castillo L 2015 · 4.50 FIP	33	SP	4.50	16.8%	9.2%	3.0%	.292	4.95	12.4%	7.2%	186	+0.45	4.50	408	72
Ryan Bollinger L 2018 · 3.56 FIP	27	SP	3.56	17.1%	7.5%	1.7%	.290	—	—	—	—	—	3.56	112	70
Tomas Solis L 2015 · 4.20 FIP	32	SP	4.20	15.0%	6.2%	2.9%	.264	5.09	12.0%	3.7%	159	+0.89	4.20	327	69
Brandon Mann L 2016 · 4.72 FIP	32	SP	4.72	19.4%	7.9%	4.1%	.320	3.97	19.0%	7.6%	128	-0.75	3.59	190	68
Alejandro Soto L 2016 · 3.96 FIP	30	SP	3.96	14.9%	6.4%	2.4%	.367	4.15	15.9%	10.3%	97	+0.19	3.96	280	67
Paul Oseguera L 2015 · 3.83 FIP	31	SP	3.83	17.6%	8.5%	2.1%	.297	5.62	5.6%	-6.9%	28	+1.79	3.83	162	67
Yusei Kikuchi L 2021 · 4.49 FIP	30	SP	4.49	24.5%	9.3%	4.2%	.285	4.00	27.0%	19.2%	444	-0.49	3.23	1,056	66
Arturo Lopez L 2015 · 4.80 FIP	32	SP	4.80	13.7%	6.2%	3.8%	.301	4.80	10.9%	4.2%	217	+0.00	4.34	445	65
Alejandro Astorga L 2017 · 4.01 FIP	30	SP	4.01	14.4%	8.2%	2.0%	.306	—	—	—	—	—	3.72	311	65
Orlando Lara L 2015 · 4.29 FIP	30	SP	4.29	15.2%	10.3%	2.1%	.348	4.08	14.2%	7.2%	230	-0.21	3.85	426	65
Jose De Paula L 2019 · 3.31 FIP	31	SP	3.31	19.0%	7.6%	1.6%	.394	—	—	—	—	—	3.31	118	63
John Bale L 2003 · 4.12 FIP	29	SP	4.12	19.0%	5.1%	3.6%	.305	—	—	—	—	—	2.49	168	62
Tsuyoshi Wada L 2014 · 3.60 FIP	33	SP	3.60	19.7%	6.2%	2.5%	.290	3.66	16.8%	9.7%	119	+0.06	3.60	188	61
Marlon Arias L 2015 · 4.32 FIP	30	SP	4.32	16.8%	12.2%	2.0%	.330	3.73	17.2%	9.5%	22	-0.59	3.73	154	61
Kramer Sneed L 2016 · 4.21 FIP	27	SP	4.21	13.2%	8.2%	2.2%	.265	—	—	—	—	—	4.21	116	60
Juan Pablo Oramas L 2019 · 3.60 FIP	29	SP	3.60	21.2%	8.0%	2.3%	.337	—	—	—	—	—	3.46	440	60
James Gillheeney L 2015 · 3.79 FIP	27	SP-	3.79	14.4%	8.0%	1.6%	.300	—	—	—	—	—	3.79	129	59
Chris Narveson L 2011 · 4.01 FIP	29	SP	4.01	18.0%	9.2%	2.3%	.291	—	—	—	—	—	4.00	625	59
Carlos Hernandez L 2017 · 3.07 FIP	30	SP	3.07	14.7%	4.0%	1.3%	.295	2.83	17.9%	12.4%	73	-0.24	2.83	331	59
Santiago Gutierrez L 2016 · 3.90 FIP	30	SP	3.90	14.8%	9.2%	1.6%	.350	4.94	15.8%	5.6%	121	+1.04	3.90	341	59

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	4.2	94	24.7%	7.9%	1.08	3.52
Eric Gagne ('08)	3.2	80	27.0%	8.5%	1.06	3.47
Alejandro Peña ('81-'96, 15 WAR*)	5.3	81	24.7%*	7.5%*	0.96*	3.61*
Joe Hesketh ('84-'94, 10 WAR*)	4.8	87	23.2%*	8.8%*	1.07*	3.95*
Doug Corbett ('80-'87, 9 WAR*)	2.8	79	22.5%*	8.7%*	1.03*	3.44*
Daniel Hudson ('24)	4.3	71	22.8%	7.7%	1.01	3.74
Héctor Rondón ('20)	2.2	54	24.2%	7.4%	1.03	3.49