Abstract
Fantasy Sports are becoming more and more popular these days, hence the race to crack it is more trending than ever. In this paper, we focus on cricket (IPL) and Dream11. Using advanced statistical and graphical models, and new performance metrics for batting and bowling we aim to build a model that can predict the top performing 11 players out of the two teams. This involves predicting the player performance and selecting the best 11 while complying with league constraints. The proposed model on an average predicts 70% of the players from the Dream Team.
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Mohith, S., Guha, R., Khetarpaul, S., Saurabh, S. (2022). Team Selection Using Statistical and Graphical Approaches for Cricket Fantasy Leagues. In: Guizzardi, R., Ralyté, J., Franch, X. (eds) Research Challenges in Information Science. RCIS 2022. Lecture Notes in Business Information Processing, vol 446. Springer, Cham. https://doi.org/10.1007/978-3-031-05760-1_48
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