Apex Analytics: F1 Circuit DNA Dashboard — An Interactive Web-Based Formula 1 Analytics Platform with Circuit DNA, Telemetry Visualisation, and Machine Learning Win Prediction

Abstract- This paper presents Apex Analytics, an
interactive web-based Formula 1 analytics dashboard
integrating the Rohan Rao Kaggle Dataset (1950–2024)
with the FastF1 Python library (2018–2025) to deliver
circuit-level insights unavailable in any existing public
tool. The system’s central feature, Circuit DNA, provides
a multi-layered analytical fingerprint for each Grand
Prix circuit, covering constructor dominance trends, lap
record progression, tyre strategy patterns, and driver
telemetry including speed traces, throttle/brake profiles,
and G-force data. Built on a Python FastAPI backend
with eleven RESTful endpoints and a React.js 18
frontend using Chart.js, Three.js, and D3.js, the system
includes an ML win-probability engine achieving 95.1%
accuracy via Gradient Boosting. Validated across five
circuits—Monaco, Silverstone, Monza, SpaFrancorchamps, and Suzuka—the system achieved
100% endpoint pass rates, sub-50ms simulation latency,
and a user satisfaction score of 4.2/5.0. Apex Analytics is
open-source, freely deployable, and requires no
installation.