Prediction from regional angst – A study of NFL sentiment in Twitter using technical stock market charting

摘要

To predict NFL game outcomes, we examine the application of technical stock market techniques to sentiment gathered from social media. From our analysis we found a $14.84 average return per sentiment-based wager compared to a $12.21 average return loss on the entire 256 games of the 2015–2016 regular season if using an odds-only approach. We further noted that wagers on underdogs (i.e., the less favored teams) that exhibit a “golden cross” pattern in sentiment (e.g., the most recent sentiment signal crosses the longer baseline sentiment), netted a $48.18 return per wager on 41 wagers. These results show promise of cross-domain research and we believe that applying stock market techniques to sports wagering may open an entire new research area.