In a data-driven world, gathering analytics is not enough. They need to be pulled from strategic data sources and, most importantly, to be used correctly depending on each project’s goals and objectives. 

In other words, data is not a one-size-fits-all solution. It is just a starting point, as data input and output have to be thoroughly identified in time for it to be useful. 

This is particularly important when it comes to performance analytics in sports.  

Players, coaches, and sports analysts need access to highly detailed match data in real time or across teams, seasons, and tournaments. 

So, how to get it? For starters, they need ultra-low latency technology to guarantee true real-time streaming. Then, self-healing video that allows for uninterrupted event viewing and analysis. And last but definitely not least, a standardized data model. 

The following performance analytics solutions have these three characteristics as a given. But each one of them offer specific benefits for unique problems:

  • Metrics-backed video: it is a powerful analytics engine that enables teams or stakeholders to quickly define the type of unique insights they need. The engine is integrated with a platform that allows videos to be linked with it. Then, every metric can click through to specific video clip playlists that can be created ad hoc, so it can contextualize data better. It’s a way for referees, medical staff and related stakeholders to contribute live in game decision making 
  • Smart encoder: this device is key for allowing the delivery of ultra-low latency content delivery. It’s a little black box that allows time sync for video, audio, and data. It can handle up to 8 live feeds in-stadium, and is able to transcode and store live content from any device. With a few wires, it can deploy an almost-instant streaming infrastructure that allows a multi-angle, metrics-based video –key for analyzing performance, frame by frame. 
  • An ecosystem: Once they have the metrics-backed video, stakeholders need to connect and collaborate with data-driven insights. Therefore, an empowered ecosystem is needed to boost team analytic processes while working remotely or in-stadium.
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