001451242 000__ 05334cam\a2200601\i\4500 001451242 001__ 1451242 001451242 003__ OCoLC 001451242 005__ 20230310004650.0 001451242 006__ m\\\\\o\\d\\\\\\\\ 001451242 007__ cr\cn\nnnunnun 001451242 008__ 221116s2022\\\\si\\\\\\ob\\\\000\0\eng\d 001451242 019__ $$a1350632629$$a1350689282 001451242 020__ $$a9789811970498$$q(electronic bk.) 001451242 020__ $$a9811970491$$q(electronic bk.) 001451242 020__ $$z9789811970481 001451242 020__ $$z9811970483 001451242 0247_ $$a10.1007/978-981-19-7049-8$$2doi 001451242 035__ $$aSP(OCoLC)1350844350 001451242 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dEBLCP$$dYDX$$dN$T$$dSFB$$dOCLCF$$dUKAHL$$dOCLCQ 001451242 043__ $$ae------ 001451242 049__ $$aISEA 001451242 050_4 $$aGV943.9.R43 001451242 08204 $$a796.3343028563$$223/eng/20221116 001451242 1001_ $$aMusa, Rabiu Muazu,$$eauthor.$$1https://isni.org/isni/0000000497019292 001451242 24510 $$aData mining and machine learning in high-performance sport :$$bperformance analysis of on-field and video assistant referees in European soccer leagues /$$cRabiu Muazu Musa, Anwar P.P. Abdul Majeed, Mohamad Razali Abdullah, Garry Kuan Ern, Mohd Azraai Mohd Razman. 001451242 264_1 $$aSingapore :$$bSpringer,$$c2022. 001451242 300__ $$a1 online resource. 001451242 336__ $$atext$$btxt$$2rdacontent 001451242 337__ $$acomputer$$bc$$2rdamedia 001451242 338__ $$aonline resource$$bcr$$2rdacarrier 001451242 4901_ $$aSpringerBriefs in applied sciences and technology 001451242 504__ $$aIncludes bibliographical references. 001451242 5050_ $$aCurrent Trend of Analysis in High-Performance Sport, and the Recent Updates in Data Mining and Machine Learning Application in Sports -- Pattern Recognition of Misconducts Offences and Bookings of Top-European Soccer Leagues Referees -- Tactical and Misconduct Actions leading to VAR Interventions in Top-Flights European Soccer Leagues -- Positional Events Incidences Leading to VAR Intervention in European Soccer Leagues Games -- Decisions Error of Top European Leagues Soccer Leagues Referees at Specific Time of Match Play -- Prevalence and Differences of Decisions Error in Top-Class European Soccer Leagues -- Relationship Between match loading and Decisions Error among top-class European Soccer Leagues Referees -- Summary, Conclusion, Current Status and Future Direction for Referees' Performance in European Soccer Leagues. 001451242 506__ $$aAccess limited to authorized users. 001451242 520__ $$aThis book explores the application of data mining and machine learning techniques in studying the activity pattern, decision-making skills, misconducts, and actions resulting in the intervention of VAR in European soccer leagues referees. The game of soccer at the elite level is characterised by intense competitions, a high level of intensity, technical, and tactical skills coupled with a long duration of play. Referees are required to officiate the game and deliver correct and indisputable decisions throughout the duration of play. The increase in the spatial and temporal task demands of the game necessitates that the referees must respond and cope with the physiological and psychological loads inherent in the game. The referees are also required to deliver an accurate decision and uphold the rules and regulations of the game during a match. These demands and attributes make the work of referees highly complex. The increasing pace and complexity of the game resulted in the introduction of the Video Assistant Referee (VAR) to assist and improve the decision-making of on-field referees. Despite the integration of VAR into the current refereeing system, the performances of the referees are yet to be error-free. Machine learning coupled with data mining techniques has shown to be vital in providing insights from a large dataset which could be used to draw important inferences that can aid decision-making for diagnostics purposes and overall performance improvement. A total of 6232 matches from 5 consecutive seasons officiated across the English Premier League, Spanish LaLiga, Italian Serie A as well as the German Bundesliga was studied. It is envisioned that the findings in this book could be useful in recognising the activity pattern of top-class referees, that is non-trivial for the stakeholders in devising strategies to further enhance the performances of referees as well as empower talent identification experts with pertinent information for mapping out future high-performance referees. 001451242 588__ $$aDescription based on print version record. 001451242 650_0 $$aSoccer$$xRefereeing$$xTechnological innovations. 001451242 650_0 $$aSoccer$$xTournaments$$zEurope. 001451242 650_0 $$aMachine learning. 001451242 650_0 $$aData mining. 001451242 655_0 $$aElectronic books. 001451242 7001_ $$aMajeed, Anwar P. P. Abdul,$$eauthor. 001451242 7001_ $$aAbdullah, Mohamad Razali,$$eauthor.$$1https://isni.org/isni/0000000497020023 001451242 7001_ $$aErn, Garry Kuan,$$eauthor. 001451242 7000_ $$aMohd Azraai Mohd Razman,$$eauthor. 001451242 77608 $$iPrint version:$$aMusa, Rabiu Muazu.$$tData mining and machine learning in high-performance sport.$$dSingapore : Springer Nature Singapore, 2022$$z9789811970481$$w(OCoLC)1346949112 001451242 830_0 $$aSpringerBriefs in applied sciences and technology. 001451242 852__ $$bebk 001451242 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-981-19-7049-8$$zOnline Access$$91397441.1 001451242 909CO $$ooai:library.usi.edu:1451242$$pGLOBAL_SET 001451242 980__ $$aBIB 001451242 980__ $$aEBOOK 001451242 982__ $$aEbook 001451242 983__ $$aOnline 001451242 994__ $$a92$$bISE