杰出教练员评定讨论杰出教练员评定讨论 Abstract：In this paper， I propose three mathematical models to study coaches clustering， ranking of coaches in the same cluster， and the quantification of time line. Then I tackle two sub-problems， coach evaluation without the factor of time line， coach evaluation considering the influence of time line， the extension of our model for all genders and sports. Problem one deals with coach evaluation without the factor of time line. I select four time-independent metrics， namely， coaching time， winning percentage， total coaching sessions， and championships. I can divide the coaches into three groups using k-means methods. Through comparison of the centroid in each group， I determine the coaching level. I score the first-class coaches by using analytical hierarchy process （AHP）. Since coaches of the same group have common characteristics， I strengthen three parameters to determine the criteria layer， and construct a comparison matrix. Then I obtain the weight of the evaluation metrics， and rank the coaches. Finally I get a list of “the outstanding coach in the 20th century”. Problem two takes time line into consideration. I build a regression model to quantify the growth of the teams participated， and get a simplified indicator of competitive level. Through analyzing the four strengthened parameters， I get a more scientific ranking of coaches. 一、Problem （一）Clustering Model I extract the date of the coaching time， winning percentage， total number of coaching sessions and championships by the obtained coaches’ data， which is used to form a primary database. This database will be classified according to the similarity of the data， that is to say， t...
