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You searched IISERK - Title: MacClade 4
Tag In 1 In 2 Data
001  vtls000037211
003  IISER-K
005  20220801113100.0
007  cr nn 008mamaa
008  220801s2021 si | s |||| 0|eng d
020  \a 9789811631924 \9 978-981-16-3192-4
035  \a (DE-He213)978-981-16-3192-4
039 9\y 202208011131 \z Siladitya
050 4\a Q325.5-.7
08204\a 006.31 \2 23
1001 \a Muazu Musa, Rabiu. \e author. \4 aut \4 http://id.loc.gov/vocabulary/relators/aut
24510\a Machine Learning in Elite Volleyball \h [electronic resource] : \b Integrating Performance Analysis, Competition and Training Strategies / \c by Rabiu Muazu Musa, Anwar P. P. Abdul Majeed, Muhammad Zuhaili Suhaimi, Mohd Azraai Mohd Razman, Mohamad Razali Abdullah, Noor Azuan Abu Osman.
250  \a 1st ed. 2021.
264 1\a Singapore : \b Springer Nature Singapore : \b Imprint: Springer, \c 2021.
300  \a X, 53 p. 13 illus., 12 illus. in color. \b online resource.
336  \a text \b txt \2 rdacontent
337  \a computer \b c \2 rdamedia
338  \a online resource \b cr \2 rdacarrier
347  \a text file \b PDF \2 rda
4901 \a SpringerBriefs in Applied Sciences and Technology, \x 2191-5318
5050 \a Chapter 1. Nature of Volleyball Sport, Performance Analysis in Volleyball, and the Recent Advances of Machine Learning Application in Sports -- Chapter 2. The Effect of Competition strategies in influencing Volleyball performance -- Chapter 3. Identification of psychological training strategies essential for Volleyball performance -- Chapter 4. The Strategic competitional elements contributing to Volleyball performance -- Chapter 5. Anthropometric variables in the identification of high-performance Volleyball players -- Chapter 6. Performance Indicators predicting medalists and non-medalists in elite men Volleyball competition -- Chapter 7. Summary, Conclusion and Future Direction.
520  \a This brief highlights the use of various Machine Learning (ML) algorithms to evaluate training and competitional strategies in Volleyball, as well as to identify high-performance players in the sport. Several psychological elements/strategies coupled with human performance parameters are discussed in view to ascertain their impact on performance in elite Volleyball competitions. It presents key performance indicators as well as human performance parameters that can be used in future evaluation of team performance and players. The details outlined in this brief are vital to coaches, club managers, talent identification experts, performance analysts as well as other important stakeholders in the evaluation of performance and to foster improvement in this sport.
650 0\a Machine learning.
650 0\a Sports sciences.
650 0\a Computational intelligence.
65014\a Machine Learning.
65024\a Sport Science.
65024\a Computational Intelligence.
7001 \a Abdul Majeed, Anwar P. P. \e author. \4 aut \4 http://id.loc.gov/vocabulary/relators/aut
7001 \a Suhaimi, Muhammad Zuhaili. \e author. \4 aut \4 http://id.loc.gov/vocabulary/relators/aut
7001 \a Mohd Razman, Mohd Azraai. \e author. \4 aut \4 http://id.loc.gov/vocabulary/relators/aut
7001 \a Abdullah, Mohamad Razali. \e author. \4 aut \4 http://id.loc.gov/vocabulary/relators/aut
7001 \a Abu Osman, Noor Azuan. \e author. \4 aut \4 http://id.loc.gov/vocabulary/relators/aut
7102 \a SpringerLink (Online service)
7730 \t Springer Nature eBook
77608\i Printed edition: \z 9789811631917
77608\i Printed edition: \z 9789811631931
830 0\a SpringerBriefs in Applied Sciences and Technology, \x 2191-5318
85640\u https://doi.org/10.1007/978-981-16-3192-4
912  \a ZDB-2-SMA
912  \a ZDB-2-SXMS
950  \a Mathematics and Statistics (SpringerNature-11649)
950  \a Mathematics and Statistics (R0) (SpringerNature-43713)

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