Transforming the access to value in gaming: Linius transforms access to valuable event structure in video for analysis and sports betting or performance
E-sports: what the market is worth
The e-sports audience boasts a very valuable demographic, skewing towards consumers with a full-time job and relatively high income. The report shows that they are also big spenders on digital media subscriptions, hardware and mobile content including games.
There are 400 million players of multiplayer online games in the world. This compares to 500 million fans for Formula 1, the #2 worldwide sport (behind soccer).
There is US$500 million of secondary market activity in the multiplayer world (buying and selling of accounts and in-game services). You’ll find a great example below of what helps to drive that interest.
The “League of Legends” 2012 championship prize pool was US$5 million. In golf, the US Masters had a prize pool of $8 million in 2013.
The average gamer plays 22 hours per week, while the average American watches TV 28 hours/week. The average gamer only watches TV 7.7 hours/week. Contrary to stereotype, 40% of all gamers are female. In this space, the US online betting industry is currently worth around US$45 billion.
The traffic flows through a number of sites, from Sony and Xbox owned properties to Twitch and YouTube. The game streaming site Twitch accounts for 43% of all live video streaming traffic.
Imagine the value to professional gamblers and gamers if you could instantly search, isolate or assemble scenes of in-game video, or sports events such as horse racing, to analyse player/team/horse performance prior to betting on an outcome.
Video games are increasingly long and complex, and the ability to isolate specific parts of the game to understand skills and strengths with certain weapons and skills is rare.
With the growth and traffic of e-sports, being able to identify event structure and repurpose it fast and simply brings immense value to the entire industry.
Linius uses a single video file for all edits as opposed to multiple files for every scene of edit. The company’s technology permits the integration of machine-to-machine intelligence in assembling, editing and presenting relevant media.