Fusion of a fuzzy rule-based method and other decision-making models in injury prediction problem in football

As injury prevention in football is one of the main aspects of physical preparation, it has also become an important issue addressed by researchers and analysts. They use machine learning methods, rule-based decision systems, or statistical analysis, however, taking into account the complexity of injury prediction, the proposed methods still need to improve the effectiveness and explainability of their operation. This study presents one of the approaches aimed at improving the reliability of the decision model result, namely the creation of an ensemble model based on aggregated results of an expert knowledge rule-based model, a fuzzy model, and a machine learning method (XGBoost algorithm). As the component models are designed to be diverse, the ensemble model combines their features to optimize the decision-making process. This fusion of expert knowledge-based system, fuzzy system, and machine learning model aims to enhance the predictive outcomes.