DeepAI AI Chat
Log In Sign Up

SMOGS: Social Network Metrics of Game Success

by   Fan Bu, et al.

This paper develops metrics from a social network perspective that are directly translatable to the outcome of a basketball game. We extend a state-of-the-art multi-resolution stochastic process approach to modeling basketball by modeling passes between teammates as directed dynamic relational links on a network and introduce multiplicative latent factors to study higher-order patterns in players' interactions that distinguish a successful game from a loss. Parameters are estimated using a Markov chain Monte Carlo sampler. Results in simulation experiments suggest that the sampling scheme is effective in recovering the parameters. We then apply the model to the first high-resolution optical tracking dataset collected in college basketball games. The learned latent factors demonstrate significant differences between players' passing and receiving tendencies in a loss than those in a win. The model is applicable to team sports other than basketball, as well as other time-varying network observations.


page 1

page 2

page 3

page 4


Learning Continuous-Time Social Network Dynamics

We demonstrate that a number of sociology models for social network dyna...

Modeling Baseball Outcomes as Higher-Order Markov Chains

Baseball is one of the few sports in which each team plays a game nearly...

A Continuous-Time Stochastic Process for High-Resolution Network Data in Sports

Technological advances have paved the way for collecting high-resolution...

Network, Popularity and Social Cohesion: A Game-Theoretic Approach

In studies of social dynamics, cohesion refers to a group's tendency to ...

Identifying World Events in Dynamic International Relations Data Using a Latent Space Model

Dynamic network data have become ubiquitous in social network analysis, ...

A Bayesian Penalized Hidden Markov Model for Ant Interactions

Interactions between social animals provide insights into the exchange a...

Annotated Hypergraphs: Models and Applications

Hypergraphs offer a natural modeling language for studying polyadic inte...