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BL
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| Record Number
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891601
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| Main Entry
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Musa, Rabiu Muazu
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| Title & Author
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Machine Learning in Sports : : Identifying Potential Archers /\ Rabiu Muazu Musa [and 3 others].
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| Publication Statement
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Singapore :: Springer Nature :: Springer,, 2018.
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| Series Statement
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Springer Briefs in applied sciences and technology
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| Page. NO
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1 online resource
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| ISBN
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9789811325922
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: 9811325928
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9789811325915
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981132591X
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| Contents
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Intro; Acknowledgements; Contents; About the Authors; 1 Introduction; 1.1 Nature ofArchery; 1.2 Performance Parameters Influencing Archery Performance; 1.3 Machine Learning inSporting Activities; 1.4 K-Means Clustering; 1.5 Classification Algorithms; 1.5.1 K-Nearest Neighbour (K-NN); 1.5.2 Support Vector Machine (SVM); 1.5.3 Artificial Neural Network (ANN); 1.5.4 Logistic Regression (LR); 1.5.5 Model Performance Evaluation; 1.6 Study Participants; 1.7 Archery Shooting Test; References; 2 Bio-Physiological Indicators inEvaluating Archery Performance; 2.1 Overview; 2.2 Clustering
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2.3 Classification2.4 Results andDiscussion; 2.5 Summary; References; 3 Psychological Variables inAscertaining Potential Archers; 3.1 Overview; 3.2 Clustering; 3.3 Classification; 3.4 Results andDiscussion; 3.5 Summary; References; 4 Anthropometry Correlation Towards Archery Performance; 4.1 Overview; 4.2 Clustering; 4.3 Classification; 4.4 Results andDiscussion; 4.5 Summary; References; 5 Psycho-Fitness Parameters intheIdentification ofHigh-Potential Archers; 5.1 Overview; 5.2 Clustering; 5.3 Classification; 5.4 Results andDiscussion; 5.5 Summary; References; 6 Concluding Remarks
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| Abstract
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This brief highlights the association of different performance variables that influences archery performance and the employment of different machine learning algorithms in the identification of potential archers. The sport of archery is often associated with a myriad of performance indicators namely bio-physiological, psychological, anthropometric as well as physical fitness. Traditionally, the determination of potential archers is carried out by means of conventional statistical techniques. Nonetheless, such methods often fall short in associating non-linear relationships between the variables. This book explores the notion of machine learning that is capable of mitigating the aforesaid issue. This book is valuable for coaches and managers in identifying potential archers during talent identification programs.
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| Subject
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Archery.
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Machine learning.
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Performance-- Measurement.
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Archery.
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Artificial intelligence.
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Biomedical engineering.
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Computer modelling simulation.
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Machine learning.
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Performance-- Measurement.
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Society social sciences.
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Sports outdoor recreation.
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SPORTS RECREATION-- Field Sports.
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| Subject
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Sports psychology.
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| Dewey Classification
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799.32
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| LC Classification
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GV1185
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| Added Entry
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Abdullah, Mohamad Razali.
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Maje Anwar P. P.Abdul.
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Taha, Zahari.
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