SV Darmstadt 98 - Bundesliga club

Player analysis with AI technology

Starting point

  • Increased analysis times
    The coaching staff and scouts at Darmstadt 98 needed several days to access the performance data of players from the "Impect" dataset.
  • Manual queries
    The IT department conducted manual queries, leading to bottlenecks and delays in decision-making regarding player acquisitions and game strategies.
  • Real-time data access
    The club was looking for a more efficient solution to independently access data in real-time without IT support.
 

Approach

  • By implementing an AI-powered solution with Amazon Bedrock and Amazon Athena, the "Impect" dataset can now be accessed in real-time.
  • The newly developed generative AI agent allows the coaching staff and scouts to enter natural language queries such as "Who is the best substitute for an injured player?".
  • The automation of data ingestion with AWS Lambda and the integrated performance monitoring ensure a fast response time while simultaneously increasing the system's reliability.

Features/Project outcome

  • The data query time has been reduced from several days to less than 5 minutes, significantly improving efficiency and decision-making.
  • The new, intuitive user interface enables even non-technical staff to independently and easily query complex datasets.
  • The scalable architecture supports future expansions, such as predictive analysis of player performance, enabling continuous development.

Customer benefits

  • Increase in operational efficiency
    By eliminating IT bottlenecks, decisions can be made faster and more agilely.
  • Optimized decision accuracy
    Real-time insights enable more precise decisions and enhance success in player acquisition.
  • High acceptance rate among scouts and the coaching staff
    This promotes strategic agility and optimizes the overall performance of the team.
Lars Ritter | Senior Manager