Exploring Performance Patterns in Student Athletes: A Hierarchical Clustering Approach with Average Linkage

This study examines the use of hierarchical clustering to identify key factors influencing athletic performance and to enhance coaching strategies at the West Sumatra Student Training Education Center (PPLP). A quantitative approach with total sampling was applied, involving 111 athletes across various sports. Data were collected using a validated questionnaire covering six variables: physical condition, social environment, athlete's character, training environment, coach's influence, and motivation. Reliability and validity were confirmed through exploratory factor analysis and Cronbach's Alpha (α > 0.70). Data analysis included descriptive statistics, assumption testing, and hierarchical clustering with the average linkage method based on Euclidean distance. Results revealed five clusters: Cluster 1 (102 athletes) and Cluster 2 (6 athletes) were dominated by motivation; Cluster 3 (1 athlete) highlighted the coach's influence; Cluster 4 (1 athlete) emphasized the training environment; and Cluster 5 (1 athlete) underscored personal characters such as discipline and responsibility. Physical condition was significant mainly in Clusters 2 and 3. Overall, findings suggest that motivation, continuous coach support, and a conducive training environment are critical for optimizing performance. While physical condition remains important, it tends to interact with other factors rather than serve as the primary determinant.