000			02928cam a2200517M 4500
001			9780429470615
003			FlBoTFG
005			20220531132533.0
006			m o d
007			cr |n|||||||||
008			200116s2020 nyu o 000 0 eng d
040			_aOCoLC-P _beng _cOCoLC-P
020			_a9780429894251 _q(electronic bk.)
020			_a0429894252 _q(electronic bk.)
020			_a9780429470615 _q(electronic bk.)
020			_a0429470614 _q(electronic bk.)
020			_a9780429894268 _q(electronic bk. : PDF)
020			_a0429894260 _q(electronic bk. : PDF)
020			_z1138600792
020			_z9781138600799
020			_z1138600814
020			_z9781138600812
035			_a(OCoLC)1135386043
035			_a(OCoLC-P)1135386043
050		4	_aGV885.49.N37
072		7	_aBUS _x061000 _2bisacsh
072		7	_aCOM _x021030 _2bisacsh
072		7	_aMAT _x025000 _2bisacsh
072		7	_aWS _2bicssc
082	0	4	_a796.323630973 _223
100	1		_aZuccolotto, Paola.
245	1	0	_aBASKETBALL DATA SCIENCE _h[electronic resource] : _bwith applications in R.
260			_aNEW YORK : _bCRC PRESS, _c2020.
300			_a1 online resource
490	1		_aChapman & Hall/CRC data science series
520			_aUsing data from one season of NBA games, Basketball Data Science: With Applications in R is the perfect book for anyone interested in learning and applying data analytics in basketball. Whether assessing the spatial performance of an MBA players shots or doing an analysis of the impact of high pressure game situations on the probability of scoring, this book discusses a variety of case studies and hands-on examples using a custom R package. The codes are supplied so readers can reproduce the analyses themselves or create their own. Assuming a basic statistical knowledge, Basketball Data Science with R is suitable for students, technicians, coaches, data analysts and applied researchers. Features: One of the first books to provide statistical and data mining methods for the growing field of analytics in basketball. Presents tools for modelling graphs and figures to visualize the data. Includes real world case studies and examples, such as estimations of scoring probability using the Golden State Warriors as a test case. Provides the source code and data so readers can do their own analyses on NBA teams and players.
588			_aOCLC-licensed vendor bibliographic record.
650		7	_aBUSINESS & ECONOMICS / Statistics _2bisacsh
650		7	_aCOMPUTERS / Database Management / Data Mining _2bisacsh
650		7	_aMATHEMATICS / Recreations & Games _2bisacsh
650		0	_aBasketball _vStatistics.
650		0	_aBasketball _xGraphic methods.
700	1		_aManisera, Marica.
856	4	0	_3Taylor & Francis _uhttps://www.taylorfrancis.com/books/9780429470615
856	4	2	_3OCLC metadata license agreement _uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
999			_c73676 _d73676