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Artificial intelligence for team sports: a survey

Artificial intelligence for team sports: a survey
Artificial intelligence for team sports: a survey
The sports domain presents a number of significant computational challenges for artificial intelligence and machine learning. In this paper we explore the techniques that have been applied to the challenges within team sports thus far. We focus on a number of different areas, these include: match outcome prediction, tactical decision making, player investments, fantasy sports and injury prediction. By assessing the work in these areas we explore how AI is used in the predict match outcomes, and to help sports teams improve their strategic and tactical decision making. In particular, we describe the main directions in which research efforts have been focused to date. This highlights a number of strengths, but also weaknesses of the models and techniques that have been employed. Finally, we discuss the research questions that exist in order to further the use of AI and machine learning in team sports.
Beal, Ryan
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Norman, Timothy J.
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Ramchurn, Sarvapali D.
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Beal, Ryan
d9874cb0-bd92-4a16-8576-78d769b41ff7
Norman, Timothy J.
663e522f-807c-4569-9201-dc141c8eb50d
Ramchurn, Sarvapali D.
1d62ae2a-a498-444e-912d-a6082d3aaea3

Beal, Ryan, Norman, Timothy J. and Ramchurn, Sarvapali D. (2019) Artificial intelligence for team sports: a survey. Knowledge Engineering Review, 34, [e28]. (doi:10.1017/S0269888919000225).

Record type: Article

Abstract

The sports domain presents a number of significant computational challenges for artificial intelligence and machine learning. In this paper we explore the techniques that have been applied to the challenges within team sports thus far. We focus on a number of different areas, these include: match outcome prediction, tactical decision making, player investments, fantasy sports and injury prediction. By assessing the work in these areas we explore how AI is used in the predict match outcomes, and to help sports teams improve their strategic and tactical decision making. In particular, we describe the main directions in which research efforts have been focused to date. This highlights a number of strengths, but also weaknesses of the models and techniques that have been employed. Finally, we discuss the research questions that exist in order to further the use of AI and machine learning in team sports.

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Artificial Intelligence for Team Sports: A Survey - Accepted Manuscript
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Accepted/In Press date: 2 October 2019
e-pub ahead of print date: 20 December 2019
Published date: 2019

Identifiers

Local EPrints ID: 436900
URI: http://eprints.soton.ac.uk/id/eprint/436900
PURE UUID: 355f1558-cac8-4ab0-99b9-20acbaf77629
ORCID for Timothy J. Norman: ORCID iD orcid.org/0000-0002-6387-4034
ORCID for Sarvapali D. Ramchurn: ORCID iD orcid.org/0000-0001-9686-4302

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Date deposited: 13 Jan 2020 17:33
Last modified: 17 Mar 2024 05:06

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Contributors

Author: Ryan Beal
Author: Sarvapali D. Ramchurn ORCID iD

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