Publication:
A Software Engineering Approach in Netball Performance Analysis: Training and Activities Features for Automatic Players Position Selection

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dc.citedby1
dc.contributor.authorMohamad A.H.en_US
dc.contributor.authorRamli R.en_US
dc.contributor.authorRamli A.F.en_US
dc.contributor.authorid57207888993en_US
dc.contributor.authorid57191413657en_US
dc.contributor.authorid57220806277en_US
dc.date.accessioned2023-05-29T08:08:01Z
dc.date.available2023-05-29T08:08:01Z
dc.date.issued2020
dc.descriptionAir navigation; Feature extraction; Software engineering; Sports; Automatic selection; Computer-based system; Critical activities; Making decision; Mixed approach; Performance analysis; Physical performance; Recent researches; Quality controlen_US
dc.description.abstractPlayer performance analysis and player selection are two critical activities that should be carried out by coaches to form sports teams. In netball, testing, training, and activities will be performed by coaches to collect player performance for analysis and player selection. Albeit its importance, coaches are still recording this data on paper-based sheets. The time-consuming and tedious manual evaluation process will be then conducted based on predefined criteria which likely leading to improper team formation, lack of transparency, and favouritism. Recent research in literature has led to player classification and physical performance evaluation using match data. While this is highly depending on coach experience, problems may occur which coaches expressed the demands of having a more systematic and guided approach to assist in player selection. In giving some guidance for performance evaluation and player selection, this study highlighted computer-based system features represented in flowcharts, considering inputs from practitioners and researchers using a mixed approach of data gathering. While algorithms are proposed to evaluate time and distance achieved by each player for team selection, two key factors in measuring player performance and quality are determined to assist computer system in analysing and making decisions for automatic selection. The results show that on average, around 35 per cent of errors are found upon pilot path testing. A systematic fixing is performed to improve the processes, and optimum results are achieved consequently. Initial findings obtained in this study may lead to further investigation of the algorithms in actual sports settings and environment. � 2020 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo9243476
dc.identifier.doi10.1109/ICIMU49871.2020.9243476
dc.identifier.epage377
dc.identifier.scopus2-s2.0-85097651288
dc.identifier.spage371
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85097651288&doi=10.1109%2fICIMU49871.2020.9243476&partnerID=40&md5=4ca69beb999683261b19ce5089d04fa6
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/25307
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitle2020 8th International Conference on Information Technology and Multimedia, ICIMU 2020
dc.titleA Software Engineering Approach in Netball Performance Analysis: Training and Activities Features for Automatic Players Position Selectionen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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