An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players

Many approaches have been described ranging from simple checklists to complex mathematical programming models for the benefit of sports improvisation. However, there are very few algorithms or decision engines available that could actually be used by decision-makers to aid in the process of forming a football team. This research constructs a self-generated calculation algorithm as a decision engine in a practical, user-friendly Decision Support System to determine the best team formation and the suitable playing position for players in a football team. A new combined decision model which integrates Analytical Network Process and Case-based Reasoning was developed. The algorithm converts the model to coding, structures the process of entering data, automates the calculations and presents the results in a well-organized and suitable interfaces for the team managerial review purposes. In order to demonstrate the feasibility of the algorithm, the engine was tested in the real application of football team management. The system is organized into two combined components: weight calculation for each player to estimate their strength and simulation for suitable formation when facing opponents. Then, the system will select the appropriate players to be placed in the specified formation. The system was implemented to Kedah Football Association (KFA) where several experimental data were tested. The system can provide the team formation and players, and calculate the strength of the KFA team to justify its winning and loss of 2019 FA Cup and Malaysia Cup final matches respectively. This system can help coaches to solve problem regarding the strong team development with available players and motivate the use of decision technologies in sports able to match the results from the real world implementation