PENERAPAN ALGORITMA BRANCH AND BOUND DENGAN STATISTIK EXPECTED GOALS UNTUK MENENTUKAN KOMBINASI PASSING OPTIMAL DALAM SEPAK BOLA

Abstract

This study proposes a new approach in football tactical analysis by utilizing Branch and Bound (B&B) algorithm and Expected Goals (xG) statistics to determine the optimal passing combination that maximizes goal-scoring chances. By modeling the game as a decision tree, each node represents a game state and each branch represents a possible passing action. The B&B method is used to eliminate non-optimal paths based on cumulative xG values. A dataset from professional matches is used for evaluation, showing that this approach can identify passing patterns that generate higher goal-scoring chances than conventional strategies.