Statistical procedure that magnifies differences between athletes in different groups or clusters while at the same time minimizing differences between athletes that are within the same group.

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The statistical procedure described is cluster analysis, which groups individuals into clusters based on similarities in certain characteristics. By emphasizing differences between athletes in different clusters and minimizing differences within clusters, cluster analysis can help identify distinct groups of athletes with unique characteristics or performance profiles. Meta-analysis is a method of combining data from multiple studies to estimate the overall effect size of a treatment or intervention. Factor analysis and factorial analysis are methods used to identify underlying factors or dimensions that explain patterns of correlations among multiple variables. While these methods can be useful for understanding the relationships among different measures of athlete performance, they do not specifically focus on identifying distinct groups of athletes with similar profiles.

Statistical Procedure That Magnifies Differences Between Athletes in Different Groups