Connor Schultz

P Knoxville Smokies

Age 28 RHP 6'4" / 225 lbs AA peak 0.5 · 2027

Overview

AAPROSPECT

ETA2029MLB%2%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	25	MIX2 levels	14	2	47	1.91	2.59	27.5%	4.4%	—	K 19.7% · BB 5.3% · FIP 3.88
2025	26	MIX2 levels	27	13	89	3.53	2.83	23.7%	5.6%	—	K 18.5% · BB 6.4% · FIP 3.53
2026	27	MIX2 levels	20	17	75	4.58	3.68	24.6%	9.0%	—	K 19.1% · BB 10.9% · FIP 4.67
2027PROJ	28	MLBCHC	1	1	1	4.66	4.66	18.0%	8.4%	0.0
2028PROJ31% MLB	29	MLBCHC	3	3	19	4.71	4.76	18.3%	8.7%	0.1
2029PROJ51% MLB	30	MLBCHC	4	4	27	4.81	4.90	18.3%	9.1%	0.2

Next 3 projected WAR 0.3Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Scouting grades · 20-80

Stuff40Control60Command50

Career WAR0.0 WAR median (P10 -0.2 / P90 0.4, comp-based) · star 0% · didn't stick 98%

CompsFabio Castillo (age 28) · Dustin Nippert (age 28) · Patrick Johnson (age 27)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 122114vR 105

ERA4.66

FIP4.66

K%18.0%

BB%8.4%

K-BB%9.5%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF4040

CTRL6060

CMD5050

K†4045

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 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)
2024	25	MIX MLE	2 levels	14	2	47	182	50	8	4	14%	3.4	19.7%	5.3%	14.3%	3.2%	1.91	3.88	—
2024	25	MIX MLE	2 levels	14	2	47	182	50	8	4	14%	3.4	19.7%	5.3%	14.3%	3.2%	1.91	3.88	—
2024	25	MIX RAW	2 levels	14	2	47	182	50	8	4	14%	3.4	27.5%	4.4%	23.1%	2.2%	1.91	2.59	—
2025	26	MIX MLE	2 levels	27	13	89	375	89	21	7	48%	3.3	18.5%	6.4%	12.1%	2.2%	3.53	3.53	—
2025	26	MIX MLE	2 levels	27	13	89	375	89	21	7	48%	3.3	18.5%	6.4%	12.1%	2.2%	3.53	3.53	—
2025	26	MIX RAW	2 levels	27	13	89	375	89	21	7	48%	3.3	23.7%	5.6%	18.1%	1.9%	3.53	2.83	—
2026	27	MIX MLE	2 levels	20	17	75	333	82	30	9	85%	3.7	19.1%	10.9%	8.2%	3.3%	4.58	4.67	—
2026	27	MIX MLE	2 levels	20	17	75	333	82	30	9	85%	3.7	19.1%	10.9%	8.2%	3.3%	4.58	4.67	—
2026	27	MIX RAW	2 levels	20	17	75	333	82	30	9	85%	3.7	24.6%	9.0%	15.6%	2.7%	4.58	3.68	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	28	MLB	CHC	1	1	1	4	1	0	0	100%	1.0	18.0%	8.4%	9.5%	3.0%	4.66	4.66	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	29	MLB MLE	CHC	10	10	60	252	46	22	8	100%	6.0	18.3%	8.7%	9.5%	3.1%	4.71	4.76	+0.4
2029	30	MLB MLE	CHC	9	9	52	220	40	20	7	100%	5.8	18.3%	9.1%	9.2%	3.3%	4.81	4.90	+0.3
2028	29	MLB CTX	CHC	3	3	19	80	15	7	3	100%	6.3	18.3%	8.7%	9.5%	3.1%	4.71	4.76	+0.1
2029	30	MLB CTX	CHC	4	4	27	114	21	10	4	100%	6.8	18.3%	9.1%	9.2%	3.3%	4.81	4.90	+0.2
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		8	8	45	192	35	17	6	100%	5.7	18.3%	8.9%	9.4%	3.2%	4.77	4.46	+0.5
/ 200 IP	—	RAW		33	33	200	844	154	75	26	100%	6.0	18.3%	8.9%	9.4%	3.2%	4.77	4.46	+2.2
Career	—	MLE		61	32	211	890	169	70	25	52%	3.5	18.9%	7.9%	11.1%	2.8%	3.54	4.03	+0.7
/ 200 IP	—	MLE		58	30	200	844	160	66	24	52%	3.5	18.9%	7.9%	11.1%	2.8%	3.54	4.03	+1.3

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.

2026 AAKnoxville Smokies · 66 IPFIP 3.86 → 4.67 (+0.80)K% 23.5% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.55%	—	×0.810	19.08%
BB% (unintentional) /BF	9.90%	—	×1.100	10.89%
HR / BF /BF	2.73%	÷1.000	×1.200	3.28%

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 100).

Result: FIP 3.86 → 4.67, 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).

2026 ROKACL Cubs · 8 IPFIP 2.04 → 3.55 (+1.51)K% 32.5% → 22.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	32.50%	—	×0.680	22.10%
BB% (unintentional) /BF	2.50%	—	×1.250	3.12%
HR / BF /BF	2.50%	÷1.000	×1.400	3.50%

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 2.04 → 3.55, 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).

2025 A+South Bend Cubs · 71 IPFIP 2.92 → 3.62 (+0.69)K% 23.1% → 17.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.13%	—	×0.770	17.81%
BB% (unintentional) /BF	5.54%	—	×1.150	6.37%
HR / BF /BF	1.95%	÷1.106	×1.250	2.21%

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 121).

Result: FIP 2.92 → 3.62, 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).

2025 AAKnoxville Smokies · 18 IPFIP 2.42 → 3.17 (+0.76)K% 26.5% → 21.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.47%	—	×0.810	21.44%
BB% (unintentional) /BF	5.88%	—	×1.100	6.47%
HR / BF /BF	1.47%	÷0.911	×1.200	1.94%

Result: FIP 2.42 → 3.17, 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).

2024 AMyrtle Beach Pelicans · 30 IPFIP 2.28 → 3.36 (+1.08)K% 26.5% → 19.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	26.55%	—	×0.740	19.65%
BB% (unintentional) /BF	3.54%	—	×1.180	4.18%
HR / BF /BF	1.77%	÷0.908	×1.300	2.53%

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 82).

Result: FIP 2.28 → 3.36, 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).

2024 ROKACL Cubs · 17 IPFIP 2.98 → 4.74 (+1.76)K% 29.0% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.99%	—	×0.680	19.71%
BB% (unintentional) /BF	5.80%	—	×1.250	7.25%
HR / BF /BF	2.90%	÷0.935	×1.400	4.34%

Result: FIP 2.98 → 4.74, 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
Connor Schultz (OGILVIE)	—	—	4.66	18.0%	8.4%	3.0%	—	4.83	18.3%	9.4%	112	+0.17	—	—	—
Fabio Castillo R 2017 · 3.98 FIP	28	SP-	3.98	20.9%	8.8%	2.8%	.291	—	—	—	—	—	3.13	195	83
Dustin Nippert R 2009 · 4.09 FIP	28	SP-	4.09	18.0%	9.7%	2.3%	.271	4.49	17.9%	6.1%	57	+0.40	3.83	268	77
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	77
Zach Stewart R 2015 · 4.43 FIP	28	SP-	4.43	14.4%	8.3%	2.7%	.322	5.17	11.7%	2.1%	51	+0.74	4.27	194	77
Scott McGregor R 2015 · 4.37 FIP	28	SP-	4.37	11.8%	7.6%	2.4%	.293	—	—	—	—	—	4.37	107	77
Clay Condrey R 2003 · 5.41 FIP	27	SP-	5.41	14.9%	10.1%	4.2%	.303	4.07	13.1%	7.4%	29	-1.34	3.18	250	76
Nolan Sanburn R 2017 · 4.55 FIP	26	SW	4.55	15.0%	10.4%	2.5%	.310	—	—	—	—	—	3.82	169	75
Jorge Martinez R 2016 · 3.53 FIP	31	SP-	3.53	12.9%	5.3%	1.6%	.266	3.71	16.5%	11.5%	154	+0.18	3.53	214	75
Josh Roeder R 2019 · 4.71 FIP	26	SW	4.71	15.1%	8.7%	3.3%	.264	—	—	—	—	—	4.71	175	75
David Griffin R 2023 · 5.83 FIP	27	SP-	5.83	14.2%	9.2%	5.0%	.306	—	—	—	—	—	4.43	239	74
Lisalverto Bonilla R 2017 · 4.61 FIP	27	SW	4.61	18.2%	10.5%	3.1%	.304	4.70	15.8%	3.2%	11	+0.09	3.22	242	74
Aldo Montes R 2017 · 4.96 FIP	27	SP-	4.96	12.4%	8.5%	3.3%	.322	4.69	18.2%	7.6%	75	-0.27	4.69	210	74
Mike Connolly R 2018 · 5.13 FIP	26	SW	5.13	13.2%	9.4%	3.5%	.321	—	—	—	—	—	3.94	328	74
Omar Bencomo R 2017 · 4.50 FIP	28	SP-	4.50	18.9%	6.3%	4.0%	.333	4.48	14.9%	10.1%	186	-0.02	3.70	381	73
Ramon Delgado R 2016 · 4.60 FIP	29	SW	4.60	13.8%	5.9%	3.5%	.332	4.31	11.2%	7.2%	74	-0.29	4.31	135	73
Eddie Bonine R 2009 · 5.60 FIP	28	SW	5.60	13.1%	7.6%	4.8%	.306	4.54	8.6%	2.0%	68	-1.06	4.40	129	73
Colin Bates R 2015 · 4.57 FIP	27	SP-	4.57	10.5%	6.5%	2.8%	.301	—	—	—	—	—	4.57	111	73
Shawn Haviland R 2015 · 3.95 FIP	29	SP-	3.95	14.6%	6.0%	2.4%	.303	4.67	16.1%	8.8%	169	+0.72	3.69	283	72
Mikey O'Brien R 2015 · 3.57 FIP	25	SP-	3.57	13.5%	8.1%	1.1%	.292	—	—	—	—	—	3.57	110	72
Casey Sadler R 2018 · 3.95 FIP	28	SW	3.95	16.0%	7.8%	2.2%	.298	3.35	23.2%	16.5%	145	-0.60	2.21	385	72

Career Comps

Completed MLB careers (no pro action in 2+ yrs) whose totals — actual + projected — most resemble this player's. Pool: 1,234 reliever careers (754 from 1990-2025 + 480 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	0.9	60	18.2%	8.7%	1.21	4.72
Juan Gutierrez ('14)	1.4	57	19.4%	8.4%	1.04	4.49
J. C. Gutierrez ('07-'14, -0 WAR*)	1.4	57	19.8%*	8.5%*	1.19*	4.72*
Bob Macdonald ('90-'96, 1 WAR*)	1.2	59	18.3%*	9.8%*	1.20*	4.32*
Trevor Gott ('15-'23, -1 WAR*)	1.2	61	18.5%*	8.4%*	1.01*	4.85*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*
Gary Wayne ('89-'94, 2 WAR*)	1.2	62	19.9%*	9.4%*	1.05*	3.88*