Forecasting basketball players’ performance using sparse functional data
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Título
Forecasting basketball players’ performance using sparse functional dataFecha de publicación
2019-09Editor
WileyCita bibliográfica
Vinué G, Epifanio I.Forecasting basketball players' performance usingsparse functional data.Stat Anal Data Min: The ASAData Sci Journal. 2019;1–14.Tipo de documento
info:eu-repo/semantics/articleVersión de la editorial
https://onlinelibrary.wiley.com/doi/full/10.1002/sam.11436Versión
info:eu-repo/semantics/submittedVersionPalabras clave / Materias
Resumen
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. [-]
Proyecto de investigación
Ministerio de Ciencia, Innovación y Universidades (AEI/FEDER, UE). Grant Number: DPI2017‐87333‐R ; Universitat Jaume I. Grant Number: UJI‐B2017‐13Derechos de acceso
© 2019 Wiley Periodicals, Inc.
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