Creating a Data-driven Recruitment Tool for NAC Breda

Denys Bespalko, a first-year student in the Applied Data Science & Artificial Intelligence programme, built a data-driven recruitment tool for football club NAC Breda.

What it does

The tool helps the club make strategic decisions about acquiring new players and handling emergency transfers. As Denys explains:

“The tool uses data-driven design to customise player selection based on the club’s needs and budget.”

It weighs player characteristics including age, position and performance metrics to guide hiring decisions.

The approach

Rather than reaching for a standard regression or classification model, Denys took a vector-based approach. Each player becomes a point in multidimensional space, described by features such as goals, successful defences, passes and tackles. Cosine similarity then identifies the players who best match the team’s specific requirements.

The project also covered data processing, visualisation, and correlation analysis between performance features. The final deliverable was a report setting out the problem statement, business implications, model specification, ethical considerations and recommendations for the club.

What he’s proud of

“I’m most proud of finding my own unique approach to the project.”

He also built a basic website interface for the tool, and wants to develop the design further and add an API.