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dc.contributor.authorNimmagadda, Shastri
dc.contributor.authorMullins, Antony
dc.contributor.authorReiners, Torsten
dc.contributor.authorMani, Neel
dc.date.accessioned2020-07-10T05:20:21Z
dc.date.available2020-07-10T05:20:21Z
dc.date.issued2020
dc.identifier.citationNimmagadda, S. and Mullins, A. and Reiners, T. and Mani, N. 2020. Design Science Guided Sports Information System Framework Development for Sports Data Analytics, in Americas Conference on Information Systems, Aug 10 2020. Salt Lake City, Utah: AMCIS.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/79991
dc.description.abstract

We identify various sports-related challenges pertinent to teams, player selections, and event management. We examine both technical and managerial decisions made during player promotion, and various factors influenced the matches. We conceptualize that the game strategies, player and team selections, performance-based sports ecology management entities can blend into an informatics paradigm for which sports data modelling and analytics are required. In addition, reviews of players in social media have significance in weighing the economic value of players. With a motivation to systematize and franchise the branded teams and players to generate revenues, we aim at articulating a logical Sports Information System (SIS), for which various design-science guided artefacts are proposed. The research evaluates game strategies, the promotion of promising players, team-based performance, and economic indicators. Documentation of sports facts and logical storage models are vital to generate metadata and assess how players performed and what factors can motivate future matches.

dc.publisherAssociation for Information Systems
dc.relation.urihttps://aisel.aisnet.org/amcis2020/data_science_analytics_for_decision_support/
dc.titleDesign Science Guided Sports Information System Framework Development for Sports Data Analytics
dc.typeConference Paper
dcterms.source.startPage1
dcterms.source.endPage10
dcterms.source.titleAMCIS 2020 Proceedings - Data Science and Analytics for Decision Support (SIGDSA)
dcterms.source.conferenceAmericas Conference on Information Systems
dcterms.source.conference-start-date10 Aug 2020
dcterms.source.conferencelocationSalt Lake City, Utah
dc.date.updated2020-07-10T05:20:21Z
curtin.departmentSchool of Management
curtin.accessStatusOpen access via publisher
curtin.facultyFaculty of Business and Law
curtin.contributor.orcidMullins, Antony [0000-0002-8485-290X]
dcterms.source.conference-end-date15 Aug 2020
curtin.contributor.scopusauthoridMullins, Antony [57211398415]


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