The recruiting process in the National Football League (NFL) and in university athletic programs consumes a lot of time and resources. There is thus a need to streamline the process with the help of a sophisticated dashboard that provides data-driven information about prospective athletes and their performance. Participants in this project were tasked with creating a dashboard – preferably with the support of machine learning (ML) and artificial intelligence (AI) – to suggest similar athletes within a discipline. Specifically, this means that participants should use data to create player profiles, which in turn can provide coaches with suggestions for players similar to the ones they have currently selected.
Willis Sports Organization (WSO) provides data and recruitment analytics to professional sports coaches, colleges, and teams to support and simplify the player recruiting process.
Potential business value and background
The recruiting process in the National Football League (NFL) takes up a lot of time and resources. The idea, therefore, is to create a sophisticated dashboard that displays athletes’ performance metrics. Additionally, there is a need for a performance measurement system that can match a player with a preferred athlete.
Approach to the solution
The matching system uses athlete characteristics to identify players most similar to the selected one by using datapoint distances, which are then visualized in the Plotly Library.
Potential next steps
- Implement the function into the current demo dashboard
- Include college, high school, and international players in the database
- WSO American football data provided (Excel)
- NFL combine data provided (Excel)
- Data scraping of current and former NFL player statistics