Published Paper Details:

Formula 1 (F1) motorsport operates at the intersec- tion of high-speed engineering and data-driven decision making, where fractions of a second determine competitive outcomes. Despite the existence of publicly accessible telemetry libraries such as FastF1 and structured APIs like the Ergast Developer API, the raw data they expose remains largely inaccessible to students, independent analysts, and motorsport enthusiasts due to the technical complexity involved in extraction and interpretation. This paper presents the design and development of an interactive web-based platform that consolidates F1 telemetry and race data into a structured analytical dashboard. The system integrates data pipelines built on FastF1 and Ergast, performs preprocessing to normalize lap times, telemetry channels, and sector timings, and exposes processed results through a responsive frontend built with ReactJS. Core analytical features include lap-time differential computation, multi-driver telemetry overlays, speed- versus-distance profiles, sector performance comparisons, and consistency metrics derived from statistical measures of lap- time variance. The architecture follows a modular layered design encompassing an API controller, data processor, database storage layer, and visualization module. Evaluation confirms that the platform accurately renders historical race sessions and provides meaningful performance insights in an intuitive visual format. The work demonstrates practical application of data engineering, dynamic visualization, and web application development within the domain of real-world motorsport analytics.