Text clustering is a technique used to group documents based on their topics. In a study comparing different clustering methods on sports articles, hierarchical clustering was found to be the most stable and effective. K-medoids clustering performed poorly, while k-means clustering was sensitive to common words. This research shows that hierarchical clustering is the best method for accurately categorizing documents based on their content.