Researchers at Carnegie Mellon University have promising news for gamblers, economists and impatient sports fans: You can predict the results of major-league football games with Twitter. Better, in many cases, than you could with traditional means.

It’s the latest research in the budding field of Twitter modelling, and as with much in statistics, it sounds a bit like magic. The researchers pulled several million football-related tweets from the Twitter fire hose during the 2010, 2011 and 2012 seasons. They then analyzed and cataloged the sentiment by team, ran the data set through a number of statistical models, and came upon several that either matched or beat traditional forecasts.

Conventional, non-Twitter prediction methods predict the winning team around 58 percent of the time. But by combining conventional methods with Twitter-based models, the researchers were able to predict the game winner with 65.9 percent accuracy. Models that used both Twitter and traditional data also made the most accurate predictions on other sports-betting metrics, like the combined number of points both teams scored.

“We find that simple features of Twitter data can match or exceed the performance of the game statistical features more traditionally used for these tasks,” the researchers conclude. “It is hoped that our approach and dataset may be useful for those who want to use social media to study markets, in sports betting and beyond.”

That, ultimately, might be the coolest takeaway from this research -- the implication that economists could keep plumbing Twitter for insight on a yet-unimagined range of topics and fields. Twitter modelling isn’t exactly new, of course: We’ve already seen the network predict elections, the stock market, box office revenues and the spread of contagious disease. But there’s a suggestion here that we’re just beginning to unlock Twitter’s predictive potential: The network could predict any number of real-life phenomena -- from whether your home team wins its next big game to when hit-and-runs will occur.

In an opinion piece for the Post Sunday, sociologist Fabio Rojas (who has done a bit of work in this field himself) concluded that social media modelling will be the death of the political polling industry -- it’s far more accurate, he argues, to analyze tweets than poll results.

That augurs an intriguing new world where social media-fueled predictions are both more common and accurate. Thanks to Twitter, we could someday guess any number of details about the future ahead of time -- down to the results of football games before they’re even played.