This project presents a comparative study of three node ranking metrics – in-degree, PageRank, and Zermelo’s strength – in competitive directed networks. Through numerical simulations on different synthetic networks, the study evaluated their mutual correlations with respect to the predefined intrinsic strength of the nodes. Correlation analyses using Pearson and Spearman coefficients reveal that Zermelo’s strength provides the most accurate estimates across all network configurations, particularly in networks where participation is unequal. In-degree shows high sensitivity to network density and participation bias, while PageRank exhibits moderate performance with limited dependence on its teleportation probability parameter. This work is a basis for future analysis of real-world competitive data in professional tennis rankings.