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Metadata: the game changer for modern sports content

Metadata provides a highly effective way of managing the vast amounts of content that sports broadcasters generate. But it’s about more than just information management. Used well, it can boost fan engagement and help monetize enormous content libraries, too. 

Kelly Messori05.07.245 min read

When the first pro football game was aired in 1939, broadcaster NBC recorded and produced the match with just two cameras. Fast-forward to 2024, and it’s not uncommon for major sports events to have well over 100 cameras capturing the action. Hundreds or even thousands of hours of footage are captured for every single sports game—from major leagues to lower divisions to niche sports.

This is where metadata comes in. Metadata provides a highly effective way of managing the vast amounts of content that sports broadcasters generate. But it’s about more than just information management. Used well, it can boost fan engagement and help monetize enormous content libraries, too. 

What is sports content metadata?

Put simply, metadata refers to ‘data about data’ – it describes qualities or attributes of another piece of data. Several kinds of metadata can be applied to any file, including descriptive metadata (e.g., name, keywords, audio transcripts) or administrative data (e.g., date created, resource type, content owner) - among many others. 

In sports content production, a 10-second clip of a penalty could have dozens of pieces of metadata attached, telling us things like:

  • Which teams were playing
  • Date of the match
  • Time the penalty took place
  • Name of the player who took the penalty
  • Fan reaction (celebration or disappointment)
  • And much, much more

Benefits of sports content metadata

By tagging videos, images, articles, and other media with relevant metadata such as keywords, descriptions, and categories, content creators and managers can categorize, search, and retrieve content quickly and effectively:

  • Find content: Metadata helps logically structure sports content, making it easier for users to navigate a vast library of articles, videos, and other media. For example, every putt on a certain hole in a golf tournament could be tagged with metadata that makes it easy to surface that specific type of moment. 
  • Repurposing: Efficient metadata management systems facilitate content repurposing, where existing content can be easily repackaged and redistributed across different platforms and channels. For example, if you can easily find every time your star quarterback performed a touchdown over the years, it makes it much easier to edit a quick supercut.  
  • Maximize the value of content: As mentioned above, broadcasters generate thousands of hours of content around every single game, with camera operators capturing pitch-side close-ups, stadium views, fan reactions, and more. Yet most of this goes unused during the live broadcast. Metadata allows you to drill down to interesting content again later and repurpose it.
  • Collaboration: Metadata is a common language that fosters collaboration and streamlines remote workflows. By standardizing naming conventions, file structures, and content attributes, metadata allows production teams to work seamlessly across different projects and locations.
  • New opportunities: APIs (Application Programming Interfaces) powered by metadata offer sports content creators the ability to automate tasks, integrate systems, and deliver personalized experiences to their audiences. By leveraging APIs, organizations can streamline content distribution, analytics, and monetization processes by creating processes and automations unique to the sports production workflows.

Example - using sports content metadata

In a recent webinar, Mike Szumlinski, Backlight’s Chief Product Officer, described how content creators can use metadata to generate personalized content for fans. 

For example, say two soccer teams are playing a match. In a traditional highlights video, both teams would get roughly the same amount of exposure. But if you’re a fan of Team A or particularly like Player X, then much of the content is uninteresting to you. Ideally, you’d mainly want highlights of your team’s actions or your favorite player’s moves. And this is where metadata helps. 

Using modern media asset management (MAM) platforms, sports broadcasters can automatically generate videos based on metadata. So, in our soccer game example, metadata of all videos containing Player X could be selected and turned into a separate highlights video that would be most interesting to fans who like that player. This allows for a high level of personalization that highly resonates with today’s audiences. 

Without metadata, finding videos of individual players (or penalties, corners, fouls, footwork skill, etc.) and turning them into separate highlight clips would take an enormous amount of time. 

Challenges of metadata in sports broadcasting

As valuable as metadata can be, generating and applying tags to vast amounts of content has traditionally been very challenging:

  • Quantity: If you are streaming video from over 100 cameras around a stadium over a two or three-hour event, applying frame-by-frame metadata would be prohibitively time-consuming. Most producers only tag major moments in the stream - fouls, goals, penalties, etc. 
  • Cost: It is typically only the biggest broadcasters or leagues that can afford to pay people (or hire willing interns) to tag metadata from a live stream. For smaller leagues, doing anything beyond basic metadata tagging (i.e., date, teams, players) is often impossible. 
  • Practicality: Applying metadata tags to enormous content libraries is only valuable if you can actually use them later to produce more clips and reels. But again, most broadcasters lack the time or resources to go back and produce dozens of new videos from existing content.  

AI-powered sports content metadata solutions

Backlight’s MAM and content creation platforms are primed to help you use metadata to maximize the value of your sports content. Our technologies use machine learning and AI to generate metadata for sports content automatically, then create clips and videos and distribute them for you. 

It starts with iconik. The platform can process all your sports content - including live video streams - and identify and apply a wide range of metadata. Wherever the content is generated and stored (on-prem or the cloud), iconik can create frame-by-frame tags for your entire library. That makes searching through vast content libraries easier to find the moments you need to tell a story. 

You can then connect iconik to Wildmoka, our powerful live and on-demand clip studio. Wildmoka’s algorithm is primed for sports and can identify meaningful events such as celebrations, goals, fouls, and more. It can ‘read’ metadata from iconik and use it to generate all kinds of videos automatically. These can then be distributed to almost any web-based OTT or social media platform (with all the associated monetization opportunities from ads and subscriptions).

Iconik and Wildmoka are already being used by major global sports broadcasters, minor leagues and niche sports to efficiently create metadata and monetize content libraries more effectively. Want to see the solutions in action? Contact us for a demo today

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