Forecasting basketball players’ performance using sparse functional data
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comunitat-uji-handle2:10234/7037
comunitat-uji-handle3:10234/8635
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Title
Forecasting basketball players’ performance using sparse functional dataDate
2019-09Publisher
WileyBibliographic citation
Vinué G, Epifanio I.Forecasting basketball players' performance usingsparse functional data.Stat Anal Data Min: The ASAData Sci Journal. 2019;1–14.Type
info:eu-repo/semantics/articlePublisher version
https://onlinelibrary.wiley.com/doi/full/10.1002/sam.11436Version
info:eu-repo/semantics/submittedVersionSubject
Abstract
Statistics and analytic methods are becoming increasingly important in basketball. In particular, predicting players’ performance using past observations is a considerable challenge. The purpose of this study is to ... [+]
Statistics and analytic methods are becoming increasingly important in basketball. In particular, predicting players’ performance using past observations is a considerable challenge. The purpose of this study is to forecast
the future behavior of basketball players. The available data are sparse functional data, which are very common in sports. So far, however, no forecasting method designed for sparse functional data has been used in sports.
A methodology based on two methods to handle sparse and irregular data,
together with the analogous method and functional archetypoid analysis is
proposed. Results in comparison with traditional methods show that our
approach is competitive and additionally provides prediction intervals. The
methodology can also be used in other sports when sparse longitudinal data
are available. [-]
Investigation project
Ministerio de Ciencia, Innovación y Universidades (AEI/FEDER, UE). Grant Number: DPI2017‐87333‐R ; Universitat Jaume I. Grant Number: UJI‐B2017‐13Rights
© 2019 Wiley Periodicals, Inc.
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info:eu-repo/semantics/openAccess
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