Predicting the NFL using Twitter
Abstract
We study the relationship between social media output and National Football League (NFL) games, using a dataset containing messages from Twitter and NFL game statistics. Specifically, we consider tweets pertaining to specific teams and games in the NFL season and use them alongside statistical game data to build predictive models for future game outcomes (which team will win?) and sports betting outcomes (which team will win with the point spread? will the total points be over/under the line?). We experiment with several feature sets and find that simple features using large volumes of tweets can match or exceed the performance of more traditional features that use game statistics.
Keywords
Cite
@article{arxiv.1310.6998,
title = {Predicting the NFL using Twitter},
author = {Shiladitya Sinha and Chris Dyer and Kevin Gimpel and Noah A. Smith},
journal= {arXiv preprint arXiv:1310.6998},
year = {2013}
}
Comments
Presented at ECML/PKDD 2013 Workshop on Machine Learning and Data Mining for Sports Analytics