NASCAR Project

Through our ongoing collaboration with Asphalt Analytics, we support data-driven operations within professional motorsports environments, including the NASCAR Cup Series.Our work spans multiple operational areas, all centered around real-time data collection, processing, and analysis in high-pressure, performance-driven environments.

1. Live Race Analysis (NASCAR Cup Series)

During the NASCAR Cup Series season (from mid-February to mid-November), our team performs real-time pit stop analysis for every race.This involves a detailed breakdown of each pit stop by capturing precise timestamps for all critical actions, including:
  • vehicle entry into the pit stall
  • vehicle stop
  • removal and installation of each tire
  • fueling start and completion
  • vehicle exit
All data is recorded using a specialized application developed by Asphalt Analytics. Video footage is captured via specific cameras positioned above each pit stall, automatically recording each stop from entry to exit. Once uploaded to the system, our team processes the footage and performs the breakdown in real time.Before analysis, each pit stop is classified based on the actions performed (e.g., full tire change, partial tire change, fuel-only stops). We also identify and flag non-standard stops, such as those involving repairs or irregular procedures, which are not considered competitive.In addition to data entry, we conduct real-time auditing using automated scripts that detect anomalies based on predefined performance parameters.All processed data becomes immediately available to clients through the Asphalt Analytics platform, enabling real-time performance insights and decision-making.

2. Live Practice Sessions

In addition to race events, we support live analysis during practice sessions conducted within team facilities.These sessions take place throughout the year, typically several times per week, and follow the same structured approach as race-day analysis, ensuring consistency and continuous performance monitoring.

3. Data Labeling & AI Training Support

We also contribute to data labeling projects focused on training AI models for automated recognition and analysis.This involves frame-by-frame annotation of video data, where specific elements such as tires, tools, and pit crew members, are precisely identified and labeled.

These datasets are used to train machine learning models to automatically detect and analyze similar elements in future scenarios.This work is performed using specialized annotation tools such as CVAT and requires a high level of accuracy, consistency, and attention to detail.

Through this collaboration, we have developed strong capabilities in handling real-time operations, structured data workflows, and high-volume, high-precision environments-skills that translate across industries where reliability and performance are critical