Medium

espnW Hack Day 2012


in Stanford, CA

iSports

Submitted

Watch sports the intelligent way!

This app targets to enhance the video watching experience of a person - especially, women. Many women would love tp learn sports and the stars that dominate each sports. Reading sports online is quite a menace because there is so much information; watching games would be a good alternative but most times - we are clueless even about who the players are.

Websites like ESPN and Youtube have a huge repository of videos viewed by people all across the world - not just sports. These videos do not necessarily answer all questions the viewer wants to know. Our app recognizes the faces of all players in the video and pulls up relevant and even interesting information about those players - women no longer have to ask embarassing questions to their boyfriends or brothers about players in the video who they have no idea about.

We gain players' biographical information from ESPN APIs and transform different statistical data into graphs. We also leverage Mashery APIs to correlate different data fragments. For each player, the top tweets are first fetched and then mined for the context to perform sentiment analysis. Useful youtube recommendations are also given so that related videos can be watched if the user wishes to.

APIs Leveraged:
1. ESPN - Athletes and Statistics
2. Mashery - Clout and Appinion
3. Youtube - Freebase and Youtube
4. Twitter - Timeline ( of a certain player )

Other relevant technology used:
1. Machine Learning using Javafaces
2. Skybiometry
3. SOLR



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