John Michael Bertrand

P Sacramento River Cats

Age 29 LHP 6'3" / 238 lbs AAA peak 0.3 · 2027

Overview

AAAPROSPECT

ETA2029MLB%10%

Year	Age	Lvl / Team	G	GS	IP	ERA	FIP	K%	BB%	WAR	MLE rates
2024	26	MIX2 levels	30	29	156	4.15	3.53	19.1%	6.9%	—	K 15.8% · BB 7.2% · FIP 4.10
2025	27	MIX2 levels	27	26	144	2.82	3.78	17.0%	8.8%	—	K 13.4% · BB 10.2% · FIP 4.38
2026	28	AAASF	15	13	67	5.37	4.73	14.4%	11.5%	—	K 12.4% · BB 10.4% · FIP 4.72
2027PROJ	29	MLBSF	1	1	7	5.36	5.36	11.6%	11.1%	0.0
2028PROJ37% MLB	30	MLBSF	3	3	19	5.36	5.43	12.4%	11.2%	-0.0
2029PROJ55% MLB	31	MLBSF	4	4	23	5.44	5.55	12.8%	11.4%	-0.0

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

Stuff35Control50Command35

Career WAR0.0 WAR median (P10 -0.1 / P90 0.1, comp-based) · star 0% · didn't stick 100%

CompsEdgar Osuna (age 29) · Carlos Teller (age 29) · Marlon Arias (age 30)

2027 FULL-SEASON PROJECTIONrates below = full-season projection

showingPROJ

wRC+ AGAINSTvL 119127vR 135

ERA5.36

FIP5.36

K%11.6%

BB%11.1%

K-BB%0.5%

Proj IP69

Value2027 · WAR

Runs saved vs league avg · 69 IP

Grades · Contract

Scouting Grades

STUF3535

CTRL5050

CMD3535

K†3030

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)
2022	24	ROK MLE	ACL Giants Black	5	1	8	28	8	0	0	20%	1.6	28.6%	0.0%	28.6%	0.0%	0.00	0.69	—
2022	24	ROK RAW	ACL Giants Black	5	1	8	28	8	0	0	20%	1.6	28.6%	0.0%	28.6%	0.0%	0.00	1.10	—
2023	25	MIX MLE	3 levels	27	19	118	487	92	35	6	70%	4.4	14.8%	8.1%	6.7%	1.5%	3.65	3.71	—
2023	25	MIX RAW	3 levels	27	19	118	487	92	35	6	70%	4.4	18.9%	7.2%	11.7%	1.2%	3.65	3.09	—
2024	26	MIX MLE	2 levels	30	29	156	653	125	45	14	97%	5.2	15.8%	7.2%	8.6%	2.6%	4.15	4.10	—
2024	26	MIX MLE	2 levels	30	29	156	653	125	45	14	97%	5.2	15.8%	7.2%	8.6%	2.6%	4.15	4.10	—
2024	26	MIX RAW	2 levels	30	29	156	653	125	45	14	97%	5.2	19.1%	6.9%	12.3%	2.1%	4.15	3.53	—
2025	27	MIX MLE	2 levels	27	26	144	594	101	52	11	96%	5.3	13.4%	10.2%	3.2%	2.0%	2.82	4.38	—
2025	27	MIX MLE	2 levels	27	26	144	594	101	52	11	96%	5.3	13.4%	10.2%	3.2%	2.0%	2.82	4.38	—
2025	27	MIX RAW	2 levels	27	26	144	594	101	52	11	96%	5.3	17.0%	8.8%	8.2%	1.9%	2.82	3.78	—
2026	28	AAA MLE	Sacramento River Cats	15	13	67	313	45	36	7	87%	4.5	12.4%	10.4%	2.0%	2.5%	5.37	4.72	—
2026	28	AAA MLE	Sacramento River Cats	15	13	67	313	45	36	7	87%	4.5	12.4%	10.4%	2.0%	2.5%	5.37	4.72	—
2026	28	AAA RAW	Sacramento River Cats	15	13	67	313	45	36	7	87%	4.5	14.4%	11.5%	2.9%	2.2%	5.37	4.73	—
▸ 2027 season — projected remainder (no 2027 stats recorded)
2027	29	MLB	SF	1	1	7	30	3	3	1	100%	7.0	11.6%	11.1%	0.5%	2.7%	5.36	5.36	+0.0
▸ Career projection (2028+) — MLB context, MLB playing time (IP × MLB%)
2028	30	MLB MLE	SF	8	8	50	213	26	24	6	100%	6.3	12.4%	11.2%	1.2%	2.9%	5.36	5.43	-0.0
2029	31	MLB MLE	SF	7	7	41	175	22	20	5	100%	5.9	12.8%	11.4%	1.5%	3.1%	5.44	5.55	-0.1
2028	30	MLB CTX	SF	3	3	19	80	10	9	2	100%	6.3	12.4%	11.2%	1.2%	2.9%	5.36	5.43	-0.0
2029	31	MLB CTX	SF	4	4	23	97	12	11	3	100%	5.8	12.8%	11.4%	1.5%	3.1%	5.44	5.55	-0.0
▸ Career totals — MLB only (actual + projected)
Career	—	RAW		7	7	41	175	22	20	5	100%	5.9	12.6%	11.3%	1.3%	3.0%	5.40	5.12	+0.1
/ 200 IP	—	RAW		33	33	200	844	106	97	24	100%	6.0	12.6%	11.3%	1.3%	3.0%	5.40	5.12	+0.6
Career	—	MLE		104	88	493	2075	301	179	44	85%	4.7	14.5%	8.6%	5.9%	2.1%	3.74	4.13	-0.1
/ 200 IP	—	MLE		42	36	200	842	122	73	18	85%	4.7	14.5%	8.6%	5.9%	2.1%	3.74	4.13	-0.2

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.

2026 AAASacramento River Cats · 67 IPFIP 4.57 → 4.72 (+0.15)K% 14.4% → 12.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.38%	—	×0.860	12.36%
BB% (unintentional) /BF	11.50%	—	×0.900	10.35%
HR / BF /BF	2.24%	÷1.000	×1.100	2.46%

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 100).

Result: FIP 4.57 → 4.72, 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 AARichmond Flying Squirrels · 132 IPFIP 3.98 → 4.38 (+0.40)K% 16.6% → 13.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	16.58%	—	×0.810	13.43%
BB% (unintentional) /BF	9.29%	—	×1.100	10.22%
HR / BF /BF	2.00%	÷1.183	×1.200	2.03%

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 137).

Result: FIP 3.98 → 4.38, 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 AAASacramento River Cats · 12 IPFIP 1.50 → 1.74 (+0.23)K% 22.2% → 19.1%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	22.22%	—	×0.860	19.11%
BB% (unintentional) /BF	2.22%	—	×0.900	2.00%
HR / BF /BF	0.00%	÷0.938	×1.100	0.00%

Result: FIP 1.50 → 1.74, 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).

2024 AARichmond Flying Squirrels · 146 IPFIP 3.54 → 4.10 (+0.56)K% 19.4% → 15.8%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	19.44%	—	×0.810	15.75%
BB% (unintentional) /BF	6.54%	—	×1.100	7.19%
HR / BF /BF	2.29%	÷1.062	×1.200	2.59%

Result: FIP 3.54 → 4.10, 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 AAASacramento River Cats · 10 IPFIP 3.41 → 3.43 (+0.02)K% 14.6% → 12.6%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	14.63%	—	×0.860	12.59%
BB% (unintentional) /BF	12.20%	—	×0.900	10.98%
HR / BF /BF	0.00%	÷1.010	×1.100	0.00%

Result: FIP 3.41 → 3.43, 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 AARichmond Flying Squirrels · 52 IPFIP 3.06 → 3.54 (+0.48)K% 17.3% → 14.0%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.33%	—	×0.810	14.04%
BB% (unintentional) /BF	9.33%	—	×1.100	10.27%
HR / BF /BF	0.44%	÷0.906	×1.200	0.59%

Result: FIP 3.06 → 3.54, 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 A+Eugene Emeralds · 49 IPFIP 3.23 → 3.95 (+0.72)K% 21.4% → 16.4%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	21.35%	—	×0.770	16.44%
BB% (unintentional) /BF	6.25%	—	×1.150	7.19%
HR / BF /BF	2.08%	÷1.076	×1.250	2.42%

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 115).

Result: FIP 3.23 → 3.95, 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 ASan Jose Giants · 17 IPFIP 2.80 → 3.60 (+0.80)K% 17.1% → 12.7%

Component	Raw	Park ÷	Level factor ×	= MLE
K% /BF	17.14%	—	×0.740	12.69%
BB% (unintentional) /BF	2.86%	—	×1.180	3.37%
HR / BF /BF	1.43%	÷0.890	×1.300	2.09%

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 78).

Result: FIP 2.80 → 3.60, 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
John Michael Bertrand (OGILVIE)	—	—	5.36	11.6%	11.1%	2.7%	—	5.48	12.6%	1.3%	92	+0.12	—	—	—
Edgar Osuna L 2017 · 5.05 FIP	29	SP	5.05	10.6%	8.2%	3.3%	.345	5.09	10.0%	2.8%	83	+0.04	5.05	175	85
Carlos Teller L 2016 · 4.86 FIP	29	SP-	4.86	14.3%	10.7%	2.9%	.297	4.74	12.6%	1.1%	148	-0.12	3.75	333	82
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	79
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	79
Amilcar Gaxiola L 2019 · 4.61 FIP	28	SP-	4.61	11.8%	10.0%	2.3%	.316	—	—	—	—	—	4.58	321	77
Alejandro Soto L 2015 · 4.41 FIP	29	SP	4.41	12.8%	7.0%	2.7%	.367	4.07	14.6%	9.1%	128	-0.34	3.96	280	76
Kramer Sneed L 2016 · 4.21 FIP	27	SP	4.21	13.2%	8.2%	2.2%	.265	—	—	—	—	—	4.21	116	74
Darin Gorski L 2016 · 4.50 FIP	28	SP	4.50	15.0%	9.8%	2.6%	.299	—	—	—	—	—	4.50	206	73
Kyle Hald L 2015 · 4.33 FIP	26	SP	4.33	12.1%	7.4%	2.4%	.313	—	—	—	—	—	4.33	124	73
Jack Snodgrass L 2016 · 5.01 FIP	28	SP-	5.01	15.7%	10.1%	3.6%	.305	—	—	—	—	—	4.66	118	73
Santiago Gutierrez L 2015 · 4.29 FIP	29	SP	4.29	11.0%	7.9%	2.0%	.314	3.92	14.9%	6.1%	169	-0.37	3.90	341	71
Henry Garcia L 2017 · 4.68 FIP	27	SP	4.68	9.2%	10.2%	1.9%	.342	—	—	—	—	—	4.47	114	70
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	70
Mike Belfiore L 2015 · 4.63 FIP	26	SP	4.63	12.0%	9.2%	2.5%	.305	—	—	—	—	—	4.63	135	69
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
John Anderson L 2016 · 4.23 FIP	27	SP-	4.23	14.3%	8.7%	2.2%	.367	—	—	—	—	—	4.12	235	68
Enrique Lechuga L 2015 · 4.70 FIP	29	SP-	4.70	10.0%	10.5%	2.0%	.354	3.78	10.5%	4.4%	59	-0.92	3.78	137	68
Matt Lujan L 2017 · 4.69 FIP	28	SP-	4.69	14.3%	6.4%	3.6%	.348	—	—	—	—	—	4.06	227	68
Marco Tovar L 2017 · 5.04 FIP	28	SP-	5.04	16.1%	11.3%	3.4%	.317	4.78	12.6%	7.0%	82	-0.26	3.78	327	67
Danny Wirchansky L 2024 · 4.47 FIP	27	SP-	4.47	16.2%	7.4%	3.3%	.246	5.88	13.0%	0.2%	68	+1.41	4.47	179	66

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	0.8	53	12.1%	11.2%	1.10	5.38
Brian Stokes ('10)	1.0	52	14.5%	10.1%	1.22	5.27
Rodney Myers ('04)	1.2	60	15.0%	10.3%	1.05	5.07
Luther Hackman ('03)	1.1	71	13.3%	10.9%	1.10	5.09
Greg Booker ('83-'90, -1 WAR*)	1.3	53	13.3%*	10.2%*	1.07*	4.51*
Daryl Patterson ('68-'74, -1 WAR*)	1.2	46	18.3%*	11.2%*	1.27*	5.03*
Kevin Hickey ('81-'91, 0 WAR*)	1.2	47	17.7%*	10.2%*	1.10*	4.27*