Coaches Ranking: A Time-Irrelevant Data Mining Solution with Flexibility and Objectivity

The ranking of coaches is of great significance for sports teams to find talented coaches. Traditional ranking mechanism is relatively subjective which is usually accomplished by voting. In this paper, we establish a ranking mechanism based on both subjective and objective factors. We use data mining method to classify and analyze the data. The regression tree and the decision tree (CART) are used to narrow down the number of coaches to a reasonable scale. We put forward our AHP model to rank the “candidates” and propose a coach rating analysis system (CRAS) for evaluating the accuracy of system. We verify our ranking system more comprehensive in terms of the evaluation of the coaches through analyzing the result. The proposed mechanism is also significant to find potential coaches.