Performance and social connection data for baseball and basketball from 2001 to 2020

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.