The scientific literature lacks consensus on classification of middle- and long-distance runners. This creates situations where the sample studied may not represent the target population and could produce misleading conclusions. Thus, we present an approach for a data-driven classification of middle- and long-distance runners according to their competition results. The best annual results of middle- and long-distance track runners participating at major (Olympics, World and European Championships) and national championships (Denmark, Sweden, Finland, Norway) were gathered for the 2012-2018 period. Overall, 1920 men`s and 1808 women`s performance results were gathered. The results were grouped accordingly. Quadratic discriminant analysis was applied to define the limits between the groups. Three basic categories could be proposed for classification: world class, international and national. Classification provides a realistic overview of performance standards and the number of athletes for different categories in middle- and long-distance track running in real-world settings. The performance-based classification provides data-driven and unified criteria for reporting standards on athletes` proficiency levels. It allows for more consistent reporting practices on the target population in research. In addition to scientific research, the classification could also be employed for a variety of practical purposes.
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