LEADER 03423nam 22005895 450 001 9910485595403321 005 20251107172528.0 010 $a981-16-3192-1 024 7 $a10.1007/978-981-16-3192-4 035 $a(CKB)5590000000487591 035 $a(MiAaPQ)EBC6648175 035 $a(Au-PeEL)EBL6648175 035 $a(PPN)262174332 035 $a(OCoLC)1257550270 035 $a(DE-He213)978-981-16-3192-4 035 $a(EXLCZ)995590000000487591 100 $a20210618d2021 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aMachine Learning in Elite Volleyball $eIntegrating Performance Analysis, Competition and Training Strategies /$fby Rabiu Muazu Musa, Anwar P. P. Abdul Majeed, Muhammad Zuhaili Suhaimi, Mohd Azraai Mohd Razman, Mohamad Razali Abdullah, Noor Azuan Abu Osman 205 $a1st ed. 2021. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2021. 215 $a1 online resource (58 pages) 225 1 $aSpringerBriefs in Applied Sciences and Technology,$x2191-5318 311 08$a981-16-3191-3 327 $aChapter 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. 330 $aThis brief highlights the use of various Machine Learning (ML) algorithms to evaluate training and competitional strategies in Volleyball, as well as to identify high-performance players in the sport. Several psychological elements/strategies coupled with human performance parameters are discussed in view to ascertain their impact on performance in elite Volleyball competitions. It presents key performance indicators as well as human performance parameters that can be used in future evaluation of team performance and players. The details outlined in this brief are vital to coaches, club managers, talent identification experts, performance analysts as well as other important stakeholders in the evaluation of performance and to foster improvement in this sport. 410 0$aSpringerBriefs in Applied Sciences and Technology,$x2191-5318 606 $aMachine learning 606 $aSports sciences 606 $aComputational intelligence 606 $aMachine Learning 606 $aSport Science 606 $aComputational Intelligence 615 0$aMachine learning. 615 0$aSports sciences. 615 0$aComputational intelligence. 615 14$aMachine Learning. 615 24$aSport Science. 615 24$aComputational Intelligence. 676 $a006.31 700 $aMuazu Musa$b Rabiu$0871676 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910485595403321 996 $aMachine learning in elite volleyball$92810257 997 $aUNINA