Tanner Tully

P Scranton/Wilkes-Barre RailRiders

Age 32 LHP 6'2" / 205 lbs AAA peak 0.4 · 2027

Overview

AAARPROOKIE

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	27	MIX2 levels	27	20	128	4.78	3.58	17.8%	5.5%	2.0	K 16.2% · BB 5.1% · FIP 3.74
2023	28	AAAScranton/Wilk…	19	19	91	5.64	4.26	18.6%	6.3%	—	K 16.0% · BB 5.7% · FIP 4.48
2024	29	AAAScranton/Wilk…	25	22	100	6.41	5.41	12.9%	6.3%	—	K 11.1% · BB 5.7% · FIP 5.50
2027PROJ	32	MLBNYY	28	28	165	4.79	4.79	15.1%	6.4%	0.2
2028PROJ37% MLB	33	MLBNYY	9	9	56	4.89	4.99	15.3%	7.0%	-0.1
2029PROJ32% MLB	34	MLBNYY	7	7	44	5.06	5.21	15.2%	7.6%	-0.2

Last 3 seasons WAR 2.0 · Next 3 projected WAR -0.0Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff50Control55Command55FB velo50

CompsArturo Lopez (age 32) · Tomas Solis (age 32) · Jorge Castillo (age 33)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 108116vR 124

ERA4.79

FIP4.79

K%15.1%

BB%6.4%

K-BB%8.7%

Proj IP165

Value2027 · WAR

Runs saved vs league avg · 165 IP

Grades · Arsenal · Contract

Scouting Grades

STUF5050

CTRL5555

CMD5555

K†3030

FB-1.2

CH-1.9

Contract

No contract data on file. Pre-MLB players and minor-league free agents do not yet have salary projections — entries are added at first 40-man roster placement.

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 + 2027 so far)
2017	22	MIX MLE	4 levels	25	15	124	523	95	22	14	60%	5.0	13.9%	4.9%	9.0%	3.4%	3.69	4.40	—
2017	22	MIX RAW	4 levels	25	15	124	523	95	22	14	60%	5.0	18.2%	4.2%	14.0%	2.7%	3.69	3.57	—
2018	23	A+ MLE	Lynchburg Hillcats	26	26	147	628	109	19	17	100%	5.7	13.4%	3.5%	9.9%	3.5%	4.47	4.33	—
2018	23	A+ RAW	Lynchburg Hillcats	26	26	147	628	109	19	17	100%	5.7	17.4%	3.0%	14.3%	2.7%	4.47	3.51	—
2019	24	MIX MLE	2 levels	26	26	144	621	89	28	11	100%	5.5	11.8%	4.9%	6.8%	2.4%	4.44	4.04	—
2019	24	MIX RAW	2 levels	26	26	144	621	89	28	11	100%	5.5	14.3%	4.5%	9.8%	1.8%	4.44	3.44	—
2021	26	MIX MLE	2 levels	26	18	113	491	97	32	10	69%	4.3	16.5%	7.0%	9.4%	2.5%	3.50	3.98	—
2021	26	MIX RAW	2 levels	26	18	113	491	97	32	10	69%	4.3	19.8%	6.5%	13.2%	2.0%	3.50	3.38	—
2022	27	MIX MLE	2 levels	27	20	128	561	100	31	13	74%	4.7	16.2%	5.1%	11.1%	2.5%	4.78	3.74	+1.8
2022	27	MIX RAW	2 levels	27	20	128	561	100	31	13	74%	4.7	17.8%	5.5%	12.3%	2.3%	4.78	3.58	+2.0
2023	28	AAA MLE	Scranton/Wilkes-Barre RailRiders	19	19	91	413	77	26	14	100%	4.8	16.0%	5.7%	10.4%	3.7%	5.64	4.48	—
2023	28	AAA RAW	Scranton/Wilkes-Barre RailRiders	19	19	91	413	77	26	14	100%	4.8	18.6%	6.3%	12.3%	3.4%	5.64	4.26	—
2024	29	AAA MLE	Scranton/Wilkes-Barre RailRiders	25	22	100	443	57	28	20	88%	4.0	11.1%	5.7%	5.4%	4.8%	6.41	5.50	—
2024	29	AAA MLE	Scranton/Wilkes-Barre RailRiders	25	22	100	443	57	28	20	88%	4.0	11.1%	5.7%	5.4%	4.8%	6.41	5.50	—
2024	29	AAA RAW	Scranton/Wilkes-Barre RailRiders	25	22	100	443	57	28	20	88%	4.0	12.9%	6.3%	6.5%	4.5%	6.41	5.41	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			3	0	6	30	2	5	1	0%	2.0	6.7%	16.7%	-10.0%	3.3%	6.00	7.10	-0.2
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	32	MLB	NYY	28	28	165	697	105	45	22	100%	5.9	15.1%	6.4%	8.7%	3.2%	4.79	4.79	+0.2
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	33	MLB MLE	NYY	25	25	151	639	98	45	22	100%	6.1	15.3%	7.0%	8.3%	3.5%	4.89	4.99	-0.2
2029	34	MLB MLE	NYY	23	23	138	582	89	44	22	100%	6.0	15.2%	7.6%	7.7%	3.7%	5.06	5.21	-0.5
2028	33	MLB CTX	NYY	9	9	56	236	36	17	8	100%	6.2	15.3%	7.0%	8.3%	3.5%	4.89	4.99	-0.1
2029	34	MLB CTX	NYY	7	7	44	186	28	14	7	100%	6.3	15.2%	7.6%	7.7%	3.7%	5.06	5.21	-0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		20	17	106	453	67	36	16	85%	5.3	14.7%	7.9%	6.8%	3.6%	5.02	4.82	+0.1
/ 200 IP	—	RAW		37	31	200	853	126	68	30	85%	5.4	14.7%	7.9%	6.8%	3.6%	5.02	4.82	+0.2
Career	—	MLE		174	146	847	3680	517	190	117	84%	4.9	14.0%	5.2%	8.9%	3.2%	4.62	4.31	-0.8
/ 200 IP	—	MLE		41	34	200	869	122	45	28	84%	4.9	14.0%	5.2%	8.9%	3.2%	4.62	4.31	-0.5

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
Tanner Tully (OGILVIE)	—	—	4.79	15.1%	6.4%	3.2%	—	5.09	15.3%	8.0%	289	+0.30	—	—	—
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	78
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	78
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	73
Oscar Rivera L 2015 · 3.68 FIP	34	SP	3.68	14.2%	6.9%	1.7%	.298	4.66	10.4%	3.0%	129	+0.98	3.68	237	73
Alejandro Astorga L 2017 · 4.01 FIP	30	SP	4.01	14.4%	8.2%	2.0%	.306	—	—	—	—	—	3.72	311	73
Roy Merritt L 2017 · 3.95 FIP	31	SP	3.95	16.2%	5.8%	2.7%	.339	—	—	—	—	—	3.93	129	68
Orlando Lara L 2017 · 4.39 FIP	32	SP	4.39	14.7%	6.5%	3.1%	.346	4.09	22.0%	14.2%	104	-0.30	3.85	426	67
Daniel Rodriguez L 2017 · 3.87 FIP	32	SP	3.87	13.1%	9.7%	1.2%	.335	4.77	20.8%	13.0%	112	+0.90	2.89	391	65
Everett Teaford L 2015 · 4.42 FIP	31	SP-	4.42	13.9%	7.6%	2.8%	.324	—	—	—	—	—	4.42	208	62
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	58
Kelvin Marte L 2019 · 5.25 FIP	31	SP	5.25	12.0%	10.8%	3.3%	.340	—	—	—	—	—	3.44	360	56
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	56
Eric Stults L 2012 · 3.71 FIP	32	SP-	3.71	13.3%	6.5%	1.7%	.262	4.01	14.8%	9.6%	517	+0.30	3.50	773	56
Enrique Lechuga L 2017 · 3.78 FIP	31	SP	3.78	10.5%	6.1%	1.5%	.390	—	—	—	—	—	3.78	137	53
Santiago Gutierrez L 2017 · 3.95 FIP	31	SP-	3.95	15.0%	8.2%	2.0%	.366	6.54	17.1%	3.7%	46	+2.59	3.90	341	52
Matt Dermody L 2022 · 4.22 FIP	32	SP-	4.22	17.9%	5.5%	3.5%	.302	3.87	20.7%	16.1%	49	-0.35	2.38	348	52
Shota Imanaga L 2024 · 3.71 FIP	30	SP	3.71	25.1%	4.0%	4.0%	.262	4.76	22.8%	17.9%	319	+1.05	3.71	492	52
Kwang Hyun Kim L 2020 · 3.76 FIP	32	SP	3.76	15.6%	6.5%	2.1%	.214	4.21	17.7%	9.5%	107	+0.45	3.76	146	48
Darrell May L 2004 · 5.17 FIP	32	SP	5.17	14.4%	6.1%	4.6%	.315	5.59	11.6%	4.3%	66	+0.42	4.24	657	47
Sean Nolin L 2021 · 4.54 FIP	31	SP-	4.54	20.4%	8.9%	3.7%	.316	5.87	19.3%	12.9%	23	+1.33	3.79	309	42

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,853 starter careers (497 from 1990-2025 + 1,356 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	2.3	153	15.1%	7.2%	1.34	4.92
Don August ('88-'91, 1 WAR*)	2.2	147	12.7%*	8.1%*	1.26*	5.01*
Masato Yoshii ('02)	3.8	151	13.9%	6.9%	1.33	4.62
Bill Steele ('10-'14, -1 WAR*)	3.4	135	15.8%*	7.9%*	1.28*	5.22*
Walt Dickson ('10-'15, 2 WAR*)	3.5	140	13.6%*	8.3%*	1.08*	4.71*
Brandon Claussen ('06)	1.6	105	16.0%	8.5%	1.37	5.04
Chad Ogea ('99)	3.2	127	13.4%	7.8%	1.32	4.88