Using social networks to improve team transition prediction in professional sports

We examine whether social data can be used to predict how members of Major League Baseball (MLB) and members of the National Basketball Association (NBA) transition between teams during their career. We find that incorporating social data into various machine learning algorithms substantially improv...

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Bibliographic Details
Published in:PloS one 2022-06, Vol.17 (6), p.e0268619-e0268619
Main Authors: Evans, Emily J, Jones, Rebecca, Leung, Joseph, Webb, Benjamin Z
Format: Article
Language:English
Subjects:
Algorithms
Baseball
Biology and Life Sciences
Careers
Computer and Information Sciences
Data
Data mining
Employees
Evaluation
Fitness
Information management
Machine learning
Management
Physical fitness
Physical Sciences
Players
Professional baseball
Professional basketball
Professional sports
Research and Analysis Methods
Social interaction
Social network analysis
Social networks
Social organization
Social Sciences
Sports associations
Sports teams
Teams
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Summary:We examine whether social data can be used to predict how members of Major League Baseball (MLB) and members of the National Basketball Association (NBA) transition between teams during their career. We find that incorporating social data into various machine learning algorithms substantially improves the algorithms’ ability to correctly determine these transitions in the NBA but only marginally in MLB. We also measure the extent to which player performance and team fitness data can be used to predict transitions between teams. This data, however, only slightly improves our predictions for players for both basketball and baseball players. We also consider whether social, performance, and team fitness data can be used to infer past transitions. Here we find that social data significantly improves our inference accuracy in both the NBA and MLB but player performance and team fitness data again does little to improve this score.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0268619