Inspiration

Many teams still take too many low-value mid-range shots. We wanted a quick way to see which court zones actually score best and how many points are lost by poor shot selection.

What it does

ShotSense takes shot-level data (player, x, y, made) and:

  • Classifies every shot into 5 zones: rim, paint, mid-range, corner 3, above-the-break 3
  • Computes FG% and points per shot for each zone
  • Draws a shot chart (makes in green, misses in red)
  • Simulates how many points a player would gain by moving 10% of their shots from mid-range to their most efficient zone

How we built it

Pure HTML, CSS and JavaScript. Everything runs in the browser, with no backend and no install. Zones are computed from NBA court coordinates, and the chart is drawn on a canvas.

Challenges

Defining zones correctly from raw coordinates (the corner 3 vs. the arc), and building the project within the hackathon's time limit.

What we learned

Points per shot is a much clearer way to compare zones than FG% alone.

What's next

Real NBA data via nba_api, defender-distance adjustment, team comparisons, and exporting reports.

Note: the built-in demo data is randomly generated, not real. Upload a real CSV to analyze real players.

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