The Data Gap in Sports Analytics and How to Close It

Peer reviewed: 
No, item is not peer reviewed.
Scholarly level: 
Graduate student (Masters)
Final version published as: 

Harell A., Bajic, I. V., The Data Gap in Sports Analytics and How to Close It, Artificial Intelligence in Team Sports Workshop at The Thirty Fourth AAAI Conference on Artificial Intelligence, NY, USA, 2020, Online Proceedings, available at https://ai-teamsports.weebly.com/uploads/1/2/7/0/127046800/paper9.pdf.

Date created: 
2019-11-19
Abstract: 

As the importance and prevalence of sports analytics grows, so does the inequality in sports data. In this paper we examine two main sources of such disparity - the perceived hierarchy of sports and privatization of data. We argue that such inequality hurts the sports analytics community in the short and long terms, and suggest ways for the deep-learning, AI, and sports analytics communities to help mitigate the issue. Keywords: Sports Analytics; AI; Team Sports; Diversity

Language: 
English
Document type: 
Article
Rights: 
Rights remain with the author.
Statistics: