As we are proceeding towards an internet driven world, the impact of internet is increasing in our day to lives. This not only gives impact on the virtual world but also leave a mark in the real world. The social media sites contains huge amount of information, the only thing is to collect the relevant data and analyse the data to form a real world prediction and it can do far more than that. In this paper we study the relationship between the twitter data and the normal data analysis to predict the winning team in the NFL (National Football League).The prediction is based on the data collected on the on-going league which includes performance of each player and their previous statistics. Alongside with the data available online we are combining the twitter data which we extracted by the tweets pertaining to specific teams and games in the NFL season and use them alongside statistical game data to build predictive models for future or the outcome of the game i.e. which team will lose or win depending upon the statistical data available. Specifically the tweets within the 24 hours of match will be considered and the main focus of twitter data will be upon the last hours of tweets i.e. pre-match twitter data and post-match twitter data. We are experimenting on the data and using twitter data we are trying to increase the performance of the existing predictive models that uses only the game stats to predict the future. © Published under licence by IOP Publishing Ltd.