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Sport Suitability Prediction Based on Physical Fitness Components Using k-Nearest Neighbors Algorithm

  • Muhammad Nabil Fikri JamaluddinEmail author
  • Mohd Syafiq Miswan
  • Shukor Sanim Mohd Fauzi
  • Ray Adderley JM Gining
  • Noor Fadlyana Raman
  • Mohd Zaid Mohd Ghazali
Conference paper

Abstract

Various type of sport requires different levels of physical fitness capability to achieve optimal performance. Physical fitness components such as endurance and physical characteristics shown to have great influence in performance of athlete. Data collected from Physical Fitness Test (PFT) by trainers are usually for record keeping and monitoring, it also consists rich of data attributes of athletes and sports they play. However, the relationship between these components and type of sports are poorly understood. Analysis such as cross tabulation for under-standing the relationships have not been explored. In this project, 16 attributes from PFT have been recognized to contribute to the type of sport they play. These data are used to predict suitable sports type for athletes based on their physical fitness score. The development begins with data preparations, digitization and cleaning and three data sets are prepared for this purpose. Data sets divided into male, female and combination male and female athletes, the results shown male athlete data sets outperform others with 81.3% accuracy. Overall, the physical fitness components influence to the type of sport athletes play.

Keywords

Sport suitability prediction Physical fitness k-Nearest neighbors Athlete development Physical fitness components 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Muhammad Nabil Fikri Jamaluddin
    • 1
    Email author
  • Mohd Syafiq Miswan
    • 2
  • Shukor Sanim Mohd Fauzi
    • 1
  • Ray Adderley JM Gining
    • 1
  • Noor Fadlyana Raman
    • 1
  • Mohd Zaid Mohd Ghazali
    • 3
  1. 1.Faculty of Computer and Mathematical SciencesUniversiti Teknologi MARA, Perlis BranchArauMalaysia
  2. 2.Faculty of Sports Science and RecreationUniversiti Teknologi MARA, Perlis BranchArauMalaysia
  3. 3.Professional Education, Research and Education DivisionNational Sports Institute of MalaysiaBukit JalilMalaysia

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