Predictive Analytics

iSportConnect and Paper.Li brought me two predictive analytics stories this morning.

The iSportConnect link shared news of the Rugby Football Union’s partnership with IBM.

IBM has become the Official Analytics Partner for the RFU and  “will implement an analytics solution to provide fans with real-time insights into the game, including information about individual performance by players – the IBM TryTracker”.

IBM’s Predictive Analytics software “will analyse historic and current rugby data provided by Opta” and aims to “give viewers access to insights that will heighten their understanding of what to watch for in each game and explain what needs to be done to increase the likelihood of a team win against specific opponents”.

K2G

The IBM TryTracker will include the ‘Keys to the Game’,  that will “provide play-by-play insights during the game, and predict three crucial areas of performance specific to each team ahead of match day”. The data for the Tracker will be collected by Opta for all England internationals and will be analysed by IBM, before being hosted on RFU.com.

The platform will also:

  • Visualise ‘Momentum’
  • Identify ‘Key Influencers’

IBM’ service builds on work developed in tennis tournaments. (I posted about the Wimbledon SlamTracker last year.)

Paper.Li brought news that “researchers have created software that predicts when and where disease outbreaks might occur based on two decades of New York Times articles and other online data”. An MIT Technology Review post by Tom Simonite provided details of the prototype software.

  • It uses 22 years of New York Times archives (1986-2007)
  • Draws on data from the Web to learn about what leads up to major news events (including DBpedia, WordNet, and OpenCyc)

This blend of resources supports the development of general rules for what events precede others.

The post highlights another a startup company, Recorded Future that makes predictions about future events “harvested from forward-looking statements online and other sources”. In a post about the company last December, Tom Simonite reported that search results “are compiled using a constantly updated index of ‘streaming data’, including news articles, filings with government regulators, Twitter updates, and transcripts from earnings calls or political and economic speeches”.

Recorded Future uses linguistic algorithms to identify specific types of events and can track the overall tone that news coverage and blog entries take.  (A video about Recorded Future.)

RF

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