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010   $a981-15-1354-6
024 7 $a10.1007/978-981-15-1354-1
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035   $a(MiAaPQ)EBC5986127
035   $a(DE-He213)978-981-15-1354-1
035   $a(PPN)262174901
035   $a(EXLCZ)994100000009939702
100   $a20191126d2019      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aCricket Performance Management $eMathematical Formulation and Analytics /$fby Hemanta Saikia, Dibyojyoti Bhattacharjee, Diganta Mukherjee
205   $a1st ed. 2019.
210  1$aSingapore :$cSpringer Singapore :$cImprint: Springer,$d2019.
215   $a1 online resource (246 pages)
225 1 $aIndian Statistical Institute Series,$x2523-3114
311   $a981-15-1353-8 
327   $aChapter 1. Cricket, Statistics and Data Mining -- Chapter 2. Franchisee Cricket and Cricketer?s Auction -- Chapter 3. Quantifying Performance of Cricketers -- Chapter 4. Fielding Performance Measure: Issues, Concern and Solution -- Chapter 5. Performance Based Market Valuation of Players -- Chapter 6. Impact of Age on Performance of Cricketers -- Chapter 7. Performing Under Difficulty: The Magical Pressure Index -- Chapter 8. Decision Making Approaches to Optimum Team Selection.
330   $aThis book focuses on the application of data mining techniques in cricket. It provides detailed examples of how data mining can be helpful for decision-making in sports with special reference to cricket, particularly the quantitative features related to Twenty20 cricket, the latest and the most popular format of the game. The book highlights the performance quantification of cricketers (batsmen, bowlers, all-rounders, and wicket keepers), determining the market valuation of cricketers based on their on-field performances and the effect of age on the performance of the cricketers. It also provides a comprehensive overview of the different aspects of the game where quantitative techniques are beneficial, and highlights the use of statistical and data mining tools in analysing sports-related data and objective decision-making in sports. The book appeals to a wide readership, including postgraduate students of statistics/mathematics, data analysts, sports management bodies. It also offers data miners, such as researchers in statistics, mathematics, operations research, and computer science ideas for projects.
410  0$aIndian Statistical Institute Series,$x2523-3114
606   $aStatistics
606   $aStatistics
606   $aPopular Science in Statistics$3https://scigraph.springernature.com/ontologies/product-market-codes/Q32000
606   $aStatistics, general$3https://scigraph.springernature.com/ontologies/product-market-codes/S0000X
615  0$aStatistics.
615  0$aStatistics.
615 14$aPopular Science in Statistics.
615 24$aStatistics, general.
676   $a796.358092
700   $aSaikia$b Hemanta$4aut$4http://id.loc.gov/vocabulary/relators/aut$0781847
702   $aBhattacharjee$b Dibyojyoti$4aut$4http://id.loc.gov/vocabulary/relators/aut
702   $aMukherjee$b Diganta$4aut$4http://id.loc.gov/vocabulary/relators/aut
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910733728903321
996   $aCricket Performance Management$93397698
997   $aUNINA