Jakari

Week 1 vs Holland

Totals

MetricValue
GradeB (82.8)
Snaps37
Targets2
Catches0
Rec Yards0
Rushes0
Rush Yards0
Touchdowns0
Drops0
Missed Assignments0
Loafs1
Key Plays Points55.0

Rates (from totals)

MetricValue
Catch Rate0.0%
Yards per Target0.00
Targets per 30snaps1.62
Key Plays per 30snaps12.97
TDs per 30snaps0.00
Drops Rate0.0%
Missed Assignments per 30snaps0.00
Loafs per 30snaps0.81

Weekly Summary

Jakari had a good performance against Holland with a B grade (82.8). Needs improvement with 0/2 catches (0.0% catch rate). Delivered 8 good blocks in the run game. Dominant blocking with 1 pancake block. Areas for improvement: 1.0 loaf. Limited opportunities with 1.6 targets per 30 snaps. Recommendations: Increase effort level and intensity.

Key Plays

CodeMeaningCount
GBGood Block8
ERelentless Effort6
GRGood Route1
PPancake1
LLoaf (Laziness)1
LFLack of Focus1
TDTouchdown0
ERElite Route0
FDFirst Down0
MAMissed Assignment0
SCSpectacular Catch0
DPDropped Pass0
HHolding0
BRBad Route0
NFSNot Full Speed0
WWhiffed0
BTBroken Tackle0
BBLBad Body Language0
EPExtra Point Conversion0

Performance Insights

Insight
  • Usage profile: short-area/possession (avg 0.0 yds/catch).
  • Chain mover: 0 first downs (0% of catches).
  • Explosiveness (YAC): at-catch production (Broken Tackles: 0).
  • Deep-ball threat: yes (avg 0.0 yds/catch, vertical tags in notes).
  • Ball security: 0 drops.
  • Film tags: vertical routes tagged in notes; in-breaking route volume.

Coach Review

Review
  • Summary: B (82.8). 0 catches on 2 targets for 0 yards and 0 TDs. 0 drops, 0 MA, 1.0 loafs.
  • What stood out: 6 effort plays, 1 pancakes, 8 good blocks
  • Efficiency: 0.0% catch rate and 0.00 yards per target.
  • Improve: Eliminate loafs — sprint off-screen and finish every rep.
  • Next week focus: 0 loafs, 75%+ catch rate, maintain 0 drops, stack effort plays and first downs.
Keep the same intent and finish habits on every snap—your impact is elite when the motor runs hot.

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Updated at 2026-09-13 16:25 · Generated by make_dashboard_html.py