Bike Race GPS Data Comparison

I want to capture and analyse two simultaneous data streams from separate bikes during the same run. Each stream must include speed, GPS coordinates and bike lean-angle, and I also need the script to calculate the on-track gap, cumulative distance difference and instant gain or loss between the riders at any point of the lap.

Input may arrive as NMEA, GPX, CSV or any other common logger format; accurate time alignment is essential because the two recorders will not start at exactly the same moment. Once synced, I expect a merged dataset that lets me replay or inspect the race: overlays of both trajectories on a map, speed-against-distance graphs, and lean-angle trends. From that, the code should output real-time or post-processed indicators such as “+0.34 s at turn 7”, distance delta curves, and a per-section gain/loss table.

Preferred toolchain is Python with pandas for cleaning and resampling, NumPy for calculations and a visual layer in Matplotlib or Plotly, but I’m open to other languages if they reach the same end result. Deliverables:

• well-documented source code
• a sample merged CSV (one line per timestamp holding both bikes’ speed, lat/long, angle, gap, distance, gain/loss)
• at least one visual dashboard or notebook that demonstrates the comparisons

The solution must run offline on Windows or macOS without paid dependencies; open-source libraries are fine.