Twitter a better bet for football odds than bookies, research claims
If you want to stay ahead of the game when betting on football matches, turn to Twitter.
A new study has found that Twitter posts provide a better prediction of winners and losers after kick-off than bookies' odds.
Researchers analysed 13.8 million tweets - an average of 5.2 per second - during the 2013/14 English Premier League season as well as in-play betting prices from the online gambling company Betfair.
They found that if the combined tone of supporter tweets at any given second during a match was positive, then the favoured team was more likely to win than the betting odds implied.
The study, said to highlight a "wisdom-of-the-crowds" effect, showed that using Twitter to guide betting could be a money-spinning strategy.
It allowed punters to earn an average return of 2.28% from more than 900,000 bets, the scientists calculated - a success rate they described as "quite striking".
In contrast, combining results from more than four million bets across all 372 matches analysed yielded an average loss of 5.41%.
Lead researcher Dr Alasdair Brown, the Univesity of East Anglia's School of Economics, said: "We find that Twitter activity predicts match outcomes, after controlling for betting market prices.
"Much of the predictive power of social media presents itself just after significant market events, such as goals and red cards, where the tone of tweets can help in the interpretation of information.
"In short, social media activity does not just represent sentiment or misinformation. If sensibly aggregated it can, when combined with a prediction market, help to improve forecast accuracy."
Co-author Dr James Reade, sports economist at the University of Reading, said: "This is a real 'wisdom of crowds' kind of outcome. It says that if we listen to the right parts of the crowd, we can gain more information and make better predictions.
"It's great for football fans, who always want to know what others think of their team. Betting prices, allied with the general mood on Twitter, can give a really accurate picture of where a match is going, in real time."
The findings, published in the journal Economic Inquiry, support recent evidence that social media content can be useful in forecasting.
"For example, there is evidence that social media output, both on Twitter and on financial message boards, predicts future stock returns," said Dr Brown.
"At first glance this may be surprising, as we might think that an individual in possession of valuable information would bet or trade first, and post later. However, if we think that valuable information is dispersed among a number of individuals, then we might understand why social media content leads market prices, as it does in this study and elsewhere."