James Kaprielian

P Buffalo Bisons

Age 33 RHP 6'3" / 225 lbs AAA peak 0.5 · 2027

Overview

AAASP

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2022	28	MIX3 levels	29	29	148	4.51	4.57	17.4%	10.0%	1.4	K 17.0% · BB 10.2% · FIP 4.63
2023	29	MIX2 levels	16	13	69	5.71	4.33	20.4%	10.2%	0.9	K 20.4% · BB 10.7% · FIP 4.68
2024	30	MIX3 levels	14	14	57	6.59	6.38	17.8%	14.2%	—	K 14.2% · BB 12.6% · FIP 6.78
2025	31	No MLB games played
2026	32	No MLB games played
2027PROJ	33	MLBTOR	1	1	5	4.69	4.70	21.6%	9.9%	0.0
2028PROJ6% MLB	34	MLBTOR	1	1	3	4.88	5.01	20.6%	10.4%	0.0
2029PROJMLE	35	MLBTOR	—	—	0	5.16	5.34	19.7%	11.0%	—

Last 3 seasons WAR 2.3 · Next 3 projected WAR 0.1Projected rows: MLB playing time only, park and league context applied.

Contract

No contract data on file.

Skills · percentileStatcast 2023

K%38

xwOBA vs26

FB Velo19

CompsJuan Delgadillo (age 32) · Manuel Flores (age 33) · Andres Ivan Meza (age 32)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 123115vR 107

ERA4.69

FIP4.70

K%21.6%

BB%9.9%

K-BB%11.6%

Proj IP54

Value2027 · WAR

Runs saved vs league avg · 54 IP

Grades · Statcast · Contract

Scouting Grades

STUF5050

CTRL4545

CMD4545

K†5050

Statcast Percentiles

FB Velo

p1992.3

Whiff%

p4825.0%

p3820.4%

xwOBA vs

p260.340

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)
2015	21	ROK MLE	GCL Yankees2	2	0	2	11	2	2	0	0%	1.2	18.2%	18.2%	0.0%	0.0%	11.57	3.87	—
2015	21	ROK RAW	GCL Yankees2	2	0	2	11	2	2	0	0%	1.2	18.2%	18.2%	0.0%	0.0%	11.57	3.96	—
2016	22	A+ MLE	Tampa Yankees	3	3	18	65	22	3	1	100%	6.0	26.1%	5.3%	20.8%	2.2%	1.50	2.80	—
2016	22	A+ RAW	Tampa Yankees	3	3	18	65	22	3	1	100%	6.0	33.8%	4.6%	29.2%	1.5%	1.50	1.88	—
2019	25	MIX MLE	3 levels	19	16	68	277	75	16	8	84%	3.6	20.9%	6.9%	14.0%	3.6%	3.18	4.17	—
2019	25	MIX RAW	3 levels	19	16	68	277	75	16	8	84%	3.6	27.1%	5.8%	21.3%	2.9%	3.18	3.13	—
2020	26	MLB MLE	Oakland Athletics	2	0	4	17	4	2	2	0%	1.8	23.5%	11.8%	11.8%	11.8%	7.36	9.06	-0.2
2020	26	MLB RAW	Oakland Athletics	2	0	4	17	4	2	2	0%	1.8	23.5%	11.8%	11.8%	11.8%	7.36	9.65	-0.2
2021	27	MIX MLE	2 levels	25	22	124	523	128	42	19	88%	5.0	24.5%	8.2%	16.3%	4.2%	4.06	4.35	+1.5
2021	27	MIX RAW	2 levels	25	22	124	523	128	42	19	88%	5.0	24.5%	8.0%	16.4%	3.6%	4.06	4.04	+2.0
2022	28	MIX MLE	3 levels	29	29	148	637	111	64	19	100%	5.1	17.0%	10.2%	6.8%	3.0%	4.51	4.63	+1.3
2022	28	MIX RAW	3 levels	29	29	148	637	111	64	19	100%	5.1	17.4%	10.0%	7.4%	3.0%	4.51	4.57	+1.4
2023	29	MIX MLE	2 levels	16	13	69	313	64	32	9	81%	4.3	20.4%	10.7%	9.6%	3.5%	5.71	4.68	+0.6
2023	29	MIX RAW	2 levels	16	13	69	313	64	32	9	81%	4.3	20.4%	10.2%	10.2%	2.9%	5.71	4.33	+0.9
2024	30	MIX MLE	3 levels	14	14	57	275	49	39	13	100%	4.1	14.2%	12.6%	1.6%	6.0%	6.59	6.78	—
2024	30	MIX MLE	3 levels	14	14	57	275	49	39	13	100%	4.1	14.2%	12.6%	1.6%	6.0%	6.59	6.78	—
2024	30	MIX RAW	3 levels	14	14	57	275	49	39	13	100%	4.1	17.8%	14.2%	3.6%	4.7%	6.59	6.38	—
▸ Career totals (raw MLB only — as recorded)
MLB Career	—			66	58	318	1376	282	132	46	88%	4.8	20.5%	9.6%	10.9%	3.3%	4.61	4.45	+3.5
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	33	MLB	TOR	1	1	5	21	5	2	1	100%	5.0	21.6%	9.9%	11.6%	3.2%	4.69	4.70	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	34	MLB MLE	TOR	8	8	47	197	41	21	7	100%	5.8	20.6%	10.4%	10.2%	3.5%	4.88	5.01	+0.2
2029	35	MLB MLE	TOR	6	6	37	156	31	17	6	100%	6.1	19.7%	11.0%	8.7%	3.9%	5.16	5.34	+0.0
2028	34	MLB CTX	TOR	1	1	3	13	3	1	0	100%	3.0	20.6%	10.4%	10.2%	3.5%	4.88	5.01	+0.0
2029	35	MLB CTX	TOR	—	—	0	—	—	—	—	—	—	19.7%	11.0%	8.7%	3.9%	5.16	5.34	—
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		66	58	321	1388	285	133	46	88%	4.9	20.5%	9.6%	10.9%	3.3%	4.62	4.42	+3.7
/ 200 IP	—	RAW		41	36	200	865	178	83	29	88%	4.8	20.5%	9.6%	10.9%	3.3%	4.62	4.42	+2.3
Career	—	MLE		110	97	490	2118	420	203	82	88%	4.5	19.8%	9.6%	10.3%	3.9%	4.57	4.76	+3.7
/ 200 IP	—	MLE		45	40	200	864	171	83	33	88%	4.5	19.8%	9.6%	10.3%	3.9%	4.57	4.76	+1.9

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.

2024 AAABuffalo Bisons · 49 IPFIP 6.43 → 6.78 (+0.35)K% 16.5% → 14.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.53%	—	×0.860	14.21%
BB% (unintentional) /BF	14.05%	—	×0.900	12.64%
HR / BF /BF	5.37%	÷0.990	×1.100	5.97%

Factors used: pitcher AAA level factors (Triple-A 2023+ robo-zone set: walks improve on promotion) — K ×0.86, BB ×0.90, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 98).

Result: FIP 6.43 → 6.78, 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).

2023 AAALas Vegas Aviators · 8 IPFIP 2.08 → 2.25 (+0.17)K% 21.2% → 18.2%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.21%	—	×0.860	18.24%
BB% (unintentional) /BF	6.06%	—	×0.900	5.45%
HR / BF /BF	0.00%	÷0.996	×1.100	0.00%

Result: FIP 2.08 → 2.25, 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).

2022 AAALas Vegas Aviators · 9 IPFIP 4.51 → 4.78 (+0.27)K% 16.7% → 14.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.67%	—	×0.880	14.67%
BB% (unintentional) /BF	11.90%	—	×1.050	12.50%
HR / BF /BF	2.38%	÷1.075	×1.100	2.44%

Factors used: pitcher AAA level factors — K ×0.88, BB ×1.05, HR ×1.10. Pitcher translation is level-wide (no per-league rows, no age adjustment); HR/BF is park-adjusted at half strength (park HR factor 115).

Result: FIP 4.51 → 4.78, 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).

2021 AAALas Vegas Aviators · 5 IPFIP 1.69 → 1.96 (+0.27)K% 23.8% → 21.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	23.81%	—	×0.880	20.95%
BB% (unintentional) /BF	4.76%	—	×1.050	5.00%
HR / BF /BF	0.00%	÷0.941	×1.100	0.00%

Result: FIP 1.69 → 1.96, 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+Stockton Ports · 36 IPFIP 3.54 → 4.46 (+0.92)K% 28.3% → 21.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	28.29%	—	×0.770	21.78%
BB% (unintentional) /BF	5.26%	—	×1.150	6.05%
HR / BF /BF	3.95%	÷1.114	×1.250	4.43%

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 123).

Result: FIP 3.54 → 4.46, 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 AAMidland RockHounds · 28 IPFIP 3.02 → 3.77 (+0.75)K% 24.3% → 19.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	24.30%	—	×0.810	19.68%
BB% (unintentional) /BF	7.48%	—	×1.100	8.22%
HR / BF /BF	1.87%	÷0.954	×1.200	2.35%

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 91).

Result: FIP 3.02 → 3.77, 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).

2016 A+Tampa Yankees · 18 IPFIP 1.67 → 2.80 (+1.12)K% 33.8% → 26.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	33.85%	—	×0.770	26.06%
BB% (unintentional) /BF	4.62%	—	×1.150	5.31%
HR / BF /BF	1.54%	÷0.862	×1.250	2.23%

Result: FIP 1.67 → 2.80, 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
James Kaprielian (OGILVIE)	—	—	4.70	21.6%	9.9%	3.2%	—	5.16	20.2%	9.5%	84	+0.46	—	—	—
Juan Delgadillo R 2015 · 4.54 FIP	32	SP	4.54	15.5%	7.2%	3.3%	.316	4.47	10.9%	4.7%	39	-0.07	4.47	143	70
Manuel Flores R 2019 · 4.32 FIP	33	SP	4.32	17.1%	7.4%	3.1%	.291	—	—	—	—	—	3.46	515	66
Andres Ivan Meza R 2019 · 4.33 FIP	32	SP	4.33	11.7%	7.7%	2.3%	.349	—	—	—	—	—	4.14	275	64
Deck McGuire R 2022 · 5.12 FIP	33	SP-	5.12	15.7%	13.1%	3.1%	.279	—	—	—	—	—	3.41	622	62
Elih Villanueva R 2017 · 5.48 FIP	31	SP	5.48	14.1%	6.0%	5.1%	.365	—	—	—	—	—	3.83	225	62
Miguel Ruiz R 2017 · 5.60 FIP	31	SP	5.60	10.6%	11.0%	3.6%	.279	—	—	—	—	—	5.60	117	62
Diego Moreno R 2019 · 4.08 FIP	32	SP	4.08	12.4%	6.9%	2.1%	.376	4.75	18.6%	9.2%	30	+0.67	2.29	187	61
Chuck Smith R 2001 · 3.99 FIP	31	SP	3.99	18.4%	8.1%	2.6%	.289	—	—	—	—	—	3.08	211	61
Jonathan Castellanos R 2015 · 3.63 FIP	33	SP	3.63	12.2%	6.5%	1.3%	.313	4.15	11.8%	3.5%	216	+0.52	3.40	394	60
Sergio Valenzuela R 2017 · 5.66 FIP	32	SP	5.66	10.6%	6.5%	4.8%	.355	—	—	—	—	—	3.66	244	60
Salvador Valdez R 2016 · 3.60 FIP	33	SP	3.60	12.8%	7.5%	1.1%	.310	3.99	11.5%	4.9%	138	+0.39	3.60	326	60
Hector Ambriz R 2016 · 3.63 FIP	32	SP	3.63	16.0%	6.4%	2.0%	.273	6.40	10.4%	2.9%	91	+2.77	2.24	259	60
Leo Medrano R 2016 · 4.34 FIP	33	SP	4.34	11.0%	7.3%	2.3%	.312	—	—	—	—	—	3.76	222	59
Jarrett Grube R 2015 · 3.75 FIP	33	SP	3.75	18.7%	4.2%	3.1%	.285	4.57	17.3%	9.6%	253	+0.82	3.75	393	58
Austin Bibens-Dirkx R 2018 · 4.89 FIP	33	SP-	4.89	17.9%	7.6%	4.3%	.322	4.82	15.9%	9.5%	147	-0.07	3.97	567	58
Shawn Haviland R 2017 · 5.00 FIP	31	SP-	5.00	16.3%	8.1%	4.1%	.261	—	—	—	—	—	3.69	283	58
Jason Simontacchi R 2007 · 4.96 FIP	33	SP	4.96	13.0%	5.9%	4.0%	.331	—	—	—	—	—	4.79	356	58
Kenshin Kawakami R 2009 · 3.97 FIP	34	SP-	3.97	15.7%	7.6%	2.2%	.277	4.06	15.1%	9.5%	87	+0.09	3.97	244	58
Koji Uehara R 2009 · 3.52 FIP	34	SP	3.52	17.2%	3.9%	2.5%	.300	2.55	33.5%	30.6%	145	-0.97	1.28	481	58
Rolando Valdez R 2019 · 5.36 FIP	33	SP-	5.36	11.7%	7.6%	4.2%	.360	—	—	—	—	—	3.06	258	58

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	2.3	76	20.6%	9.9%	1.31	4.69
Vicente Palacios ('87-'00, 1 WAR*)	1.9	62	21.0%*	10.0%*	1.41*	4.86*
Roansy Contreras ('25)	1.2	82	19.3%	9.8%	1.38	4.77
Jake Faria ('23)	1.0	68	20.9%	10.3%	1.32	4.87
Adam Conley ('21)	2.2	87	19.8%	9.4%	1.16	4.71
Shawn Hillegas ('87-'93, -0 WAR*)	2.6	86	19.6%*	10.2%*	1.24*	5.03*
Rich Folkers ('70-'77, -0 WAR*)	2.1	85	19.1%*	8.8%*	1.35*	4.91*