This dataset examines living and deceased players who have played in the National Basketball Association (debut between 1946 – 2010) and/or the American Basketball Association (1967–1976) using descriptive and Kaplan-Meier and Cox regression analyses. The cut-off date for death data collection was December 11, 2015
Dataset of 2604 National Basketball Association (NBA) players who played more than 1000 minutes in t...
The trends towards Big Data have influenced many business sectors of the economy. Data Analytics wer...
Background: Determining somatic models and profiles in young athletes has recently become a fundamen...
Concerns have been raised recently by players’ associations regarding the risk of death among retire...
Concerns have been raised recently by players’ associations regarding the risk of death among retire...
While factors such as genetics may mediate the relationship between height and mortality, evidence s...
An interesting problem in professional basketball is predicting how long a player remains in the NBA...
International audienceBackground: The purpose of this study was to cross-validate and demonstrate ho...
Phenotypic traits are often influenced by dynamic resource allocation trade-offs which, when occurri...
Researchers interested in changes that occur as people age are faced with a number of methodological...
The aim of this study was: (i) to group basketball players into similar clusters based on a combinat...
The aim–indentify date of birth influence to successful games of elite basketball players. Lot of sc...
This dataset contains statistics per season for each player who played at least one minute that seas...
The aim of the present study was to analyze the changes of game-related statistics in expert players...
Phenotypic traits are often influenced by dynamic resource allocation trade-offs which, when occurri...
Dataset of 2604 National Basketball Association (NBA) players who played more than 1000 minutes in t...
The trends towards Big Data have influenced many business sectors of the economy. Data Analytics wer...
Background: Determining somatic models and profiles in young athletes has recently become a fundamen...
Concerns have been raised recently by players’ associations regarding the risk of death among retire...
Concerns have been raised recently by players’ associations regarding the risk of death among retire...
While factors such as genetics may mediate the relationship between height and mortality, evidence s...
An interesting problem in professional basketball is predicting how long a player remains in the NBA...
International audienceBackground: The purpose of this study was to cross-validate and demonstrate ho...
Phenotypic traits are often influenced by dynamic resource allocation trade-offs which, when occurri...
Researchers interested in changes that occur as people age are faced with a number of methodological...
The aim of this study was: (i) to group basketball players into similar clusters based on a combinat...
The aim–indentify date of birth influence to successful games of elite basketball players. Lot of sc...
This dataset contains statistics per season for each player who played at least one minute that seas...
The aim of the present study was to analyze the changes of game-related statistics in expert players...
Phenotypic traits are often influenced by dynamic resource allocation trade-offs which, when occurri...
Dataset of 2604 National Basketball Association (NBA) players who played more than 1000 minutes in t...
The trends towards Big Data have influenced many business sectors of the economy. Data Analytics wer...
Background: Determining somatic models and profiles in young athletes has recently become a fundamen...
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