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IAmTomShaw/f1-race-replay

An interactive Formula 1 race visualisation and data analysis tool built with Python! 🏎️

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Summary Information

Updated 18 minutes ago
Added to GitGenius on September 10th, 2026
Created on November 21st, 2025
Open Issues & Pull Requests: 153 (+0)
GitHub issues: Enabled
Number of forks: 824
Total Stargazers: 6,246 (+0)
Total Subscribers: 65 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 16.3 hours
Mean response time: 21.2 days
90th percentile: 62.1 days
Tracked items: 61

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How this project is maintained

Around half of the issues opened in the past year never receive a reply. 98% of open issues come from outside the core team, so the backlog reflects real-world use rather than internal planning. 75% of tracked open issues have had no activity in three months, so the open count overstates what is actively being worked. Only 10% of issues opened in the past year have been closed. Three people close 62% of everything that gets resolved.

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Issue Activity (beta)

Open issues: 40
New in 7 days: 3
Closed in 7 days: 0
Avg open age: 175 days
Stale 30+ days: 36
Stale 90+ days: 28

Recent activity

Opened in 7 days: 2
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

Top labels

  • enhancement (7)
  • bug (4)

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Detailed Description

F1 Race Replay is an interactive Formula 1 race visualisation and data analysis tool built in Python.

It enables users to interactively explore race data, track driver positions and performance metrics over time, and gain insights into how races unfolded through both visualisation and structured data analysis.

It works well for projects requiring detailed examination of driver performance, position changes, lap times, or other telemetry-related insights. The Python foundation makes it accessible for data science workflows and integration into larger analytical pipelines.

The project shows active development with regular commits addressing bug fixes and feature enhancements. Work spans multiple areas including core visualisation logic, data processing improvements, and user interface refinements. The codebase receives ongoing attention to both functionality and code quality.