The paper constructs a Kabaddi network based on player participation in the Indian Pro Kabaddi League (PKL) over the past 10 seasons. The network has 863 nodes (players) and 17,195 edges, indicating that on average, each player has played with around 19 other players during their PKL career.
Key insights from the network analysis:
The Kabaddi network exhibits small-world properties, with a high clustering coefficient of 0.728 and an average shortest path length of 2.349. This suggests a highly clustered network with short paths between players.
The degree analysis identifies the most highly connected players, with PO Surjeet Singh having the highest degree of 159, indicating he has played with the most number of teammates.
The PageRank analysis is used to rank the players based on their centrality and importance within the network. The top-ranked players include Girish Maruti Ernak, K Prapanjan, and PO Surjeet Singh.
The study compares the PageRank scores of the top 40 players with their average strike rates, revealing an inverse relationship. Players with higher PageRank scores tend to have lower strike rates, suggesting that their frequent team changes may have impacted their performance.
The network analysis provides insights into the connectivity patterns, player influence, and performance dynamics within the Indian Pro Kabaddi League, which can be valuable for team management, player recruitment, and strategic decision-making.
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by Arjab Sengup... pada arxiv.org 05-06-2024
https://arxiv.org/pdf/2405.01596.pdfPertanyaan yang Lebih Dalam