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Sports Data Management, Mining, and Visualization

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Part of the Lecture Notes in Networks and Systems book series (LNNS,volume 450)

Abstract

Data are everywhere. Examples include sports data. Embedded in these data is implicit, previously unknown and potentially useful information or knowledge to be discovered. In this paper, we present a solution for sports data management, mining and visualization. In particular, we focus on basketball data. Basketball is a culture and is respected by fans around the world. Ever since its birth, basketball has changed drastically. Under such effects, basketball discussion and analysis evolved as well. Our solution adapts three different approaches for predicting the win. Evaluation on real-life basketball data show the effectiveness of our solution.

Keywords

  • Data mining
  • Big data analytics
  • Social networks
  • Sports analytics
  • Basketball

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    http://thegamedesigner.blogspot.com/2012/05/pythagoras-explained.html.

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Acknowledgements

This project is partially supported by (a) Natural Sciences and Engineering Research Council of Canada (NSERC) and (b) University of Manitoba.

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Correspondence to Carson K. Leung .

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Isichei, B.C. et al. (2022). Sports Data Management, Mining, and Visualization. In: Barolli, L., Hussain, F., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2022. Lecture Notes in Networks and Systems, vol 450. Springer, Cham. https://doi.org/10.1007/978-3-030-99587-4_13

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