Sports Performance Analysis Web Application

Performance data was being recorded manually on paper and then transferred into spreadsheets for analysis.

This created a number of limitations:

• Time-consuming, repetitive and error prone data entry
• Limited ability to capture detailed shot-level data
• Inconsistent and unstructured data capture
• Difficult to consistently analyse trends over time
• Difficulty identifying specific areas for improvement in a timely manner

The existing approach worked, but restricted the usefulness of the data and made ongoing analysis inefficient.

A bespoke web application was designed and developed to replace the manual and spreadsheet-based process.

The system was built around a structured data model reflecting the key aspects of play and performance metrics relevant to the athlete.

Key features included:

Mobile-friendly data input for use at the course

• Consistent and structured capture of performance data
• Automated statistical analysis
• Graphical reporting to visualise trends and results
• Centralised data storage, removing the need for spreadsheets

The application was developed using a Python/Django-based stack, with a focus on simplicity, reliability, and ease of use.

• Improved efficiency
  Data entry became significantly faster and more consistent, reducing the time required to enter a typical round from around an hour to 15–20 minutes
• Better performance insight
  Immediate access to statistics and trends, enabling performance to be reviewed at the course immediately after a round, rather than requiring later spreadsheet entry and analysis
• More detailed and granular data capture
  The system enabled recording of precise shot outcomes (for example, exact position on the green rather than simply “on the green”), providing a much richer dataset for analysis
• Clear visual identification of improvement areas
  Data-driven understanding of strengths and weaknesses
• More reliable system
  Replacement of error-prone paper-based and spreadsheet processes with a single, consistent system, eliminating duplication and lowering the risk of data loss and manual error
• Appropriate technical solution
  A lightweight SQLite database was used, reflecting the needs of a single-user system without unnecessary complexity