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Erschienen in:
2017 | OriginalPaper | Buchkapitel
Hierarchical Ranking of Cricket Teams Incorporating Player Composition
verfasst von : Abhinav Agarwalla, Madhav Mantri, Vishal Singh
Erschienen in: Pattern Recognition and Machine Intelligence
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Abstract
We analyze the performance of international ODI cricket teams through a hierarchical ranking scheme. Players are represented as the nodes of a graph with batsmen as authorities, and bowlers as hubs. Low level player ratings determined using weighted HITS algorithm, are fed into a higher level Elo rating system to rank teams. Strike rate, economy rate, number of boundaries, etc. determine the edge weights for player graph. Match characteristics like margin of victory, winning style and player rankings determine the K-factor in Elo ratings. We show that player composition along with match characteristics is also an important aspect of team ranking, which has not explored previously. We report significant improvements in predicting match outcomes against other ranking schemes.