Adaptive Lineup Recommendation System for Basketball Coaching Using Multi Linear Regression and Decision Support Techniques

Data-driven analytics are rarely used in basketball coaching, leading to ineffective strategies and poor player selection. As a result, the HoopMaster, mobile Android application, is developed to address these challenges, wherein it utilizes advanced data analytics with interactive simulations to improve basketball coaching effectiveness. It uses Multi Linear Regression (MLR) to assess player performance metrics and determine the optimal starting lineup, equipping coaches with the insights necessary for making informed decisions. Additionally, it uses Decision Tree Algorithm to suggest play recommendations matching each player's strength and weakness, allowing for better strategic preparation. To further enhance the coaching experience, HoopMaster has an integrated animated digital court board on which basketball plays can be designed, animated and simulated for teaching or training purposes. This function allows for efficient collaboration and communication during practice and games. HoopMaster seeks to transform and revolutionize the manner of basketball coaching by applying technology in the basketball scene through the integration of Multi Linear Regression for lineup optimization, Decision Tree for strategic insights, and dynamic animation for visual play presentation. The system was applied and evaluated by basketball coaches, players and Information Technology professionals to check its adherence to the requirements set by the standards outlined in ISO 25010.