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PeriodicalsArtificial Intelligence & Machine Learning

Cognitive analysis in sports: Supporting match analysis and scouting through artificial intelligence

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Abstract & Overview

Abstract In elite sports, there is an opportunity to take advantage of rich and detailed datasets generated across multiple threads of the sporting business. Challenges currently exist due to time constraints to analyse the data, as well as the quantity and variety of data available to assess. Artificial Intelligence (AI) techniques can be a valuable asset in assisting decision makers in tackling such challenges, but deep AI skills are generally not held by those with rich experience in sporting domains. Here, we describe how certain commonly available AI services can be used to provide analytic assistance to sports experts in exploring, and gaining insights from, typical data sources. In particular, we focus on the use of Natural Language Processing and Conversational Interfaces to provide users with an intuitive and time‐saving toolkit to explore their datasets and the conclusions arising from analytics performed on them. We show the benefit of presenting powerful AI and analytic techniques to domain experts, showing the potential for impact not only at the elite level of sports, where AI and analytic capabilities may be more available, but also at a more grass‐roots level where there is generally little access to specialist resources. The work described in this paper was trialled with Leatherhead Football Club, a semi‐professional team that, at the time, were based in the English 7th tier of football.

Cite this record

Joe Pavitt, Dave Braines, Richard Tomsett (2021). Cognitive analysis in sports: Supporting match analysis and scouting through artificial intelligence. Applied AI Letters, 2(1). https://doi.org/10.1002/ail2.21

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Pavitt, J., Braines, D., & Tomsett, R. (2021). Cognitive analysis in sports: Supporting match analysis and scouting through artificial intelligence. Applied AI Letters, 2(1). https://doi.org/10.1002/ail2.21
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