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The days of relying on a single broadcaster for sports events are long gone. With the emergence of various sports-focused over-the-top (OTT) platforms, broadcasters have recognized that sports remain one of the few genres for which audiences are willing to pay extra. Recent studies reveal that 63% of sports enthusiasts are open to subscribing to an OTT service, while half of this audience engages with additional sports content. However, for those without exclusive rights to major events like the Super Bowl, the challenge lies in finding ways to stand out and captivate viewers. Enter machine learning, a potential game-changer in the realm of sports broadcasting. In this article, we’ll delve into how machine learning can enhance viewer engagement and experience—something you might not have realized you needed.
Enhancing Personalization and Accessibility
At its core, machine learning has the capacity to automate labor-intensive tasks, streamline workflows, and reduce costs. A pertinent example is in the realm of captioning and translation. Currently, the process of generating captions for live events often involves third-party service providers. However, solutions like Amazon Transcribe Live can accomplish this more cost-effectively and with the scalability of cloud technology. Further, once captions are generated, translating them into various languages becomes effortless with Amazon Translate. Following that, a text-to-speech service such as Amazon Polly can create a foreign audio track in real-time. This means viewers watching the Olympics in multiple countries no longer have to wait for translated broadcasts; they can enjoy the event in their preferred language simultaneously.
Igniting Fan Engagement
During the 2018 Royal Wedding, Sky News in the UK introduced a “Who’s Who” feature that highlighted celebrities as they appeared on screen, offering insights into their connections with the royal family. Similarly, using a combination of Amazon Rekognition, AWS Elemental MediaConvert, and other services, a Media Analysis solution can employ facial recognition to identify players in real-time. This technology allows sports enthusiasts to instantly jump to scenes featuring their favorite athletes.
Visuals can also include player and game statistics, keeping fans informed and engaged throughout the broadcast.
Automated Highlight Creation
Imagine automating the creation of highlight reels during a game for post-event recaps. Traditionally, this process requires staff to mark clip start and end points, cut the video, store it, and tag it with metadata. Machine learning can streamline this entire workflow. For instance, using Amazon Rekognition to monitor scoreboard changes can help identify scoring moments, enabling live video clipping from various angles for viewers to watch later.
Delivering In-Depth Stats
For those who enjoy diving into statistics, the NFL and MLB have employed AWS’s machine learning capabilities to provide fans with deeper insights into gameplay. The NFL’s Next Gen Stats, which utilizes RFID technology, tracks player movements and performance in real-time. In the future, machine learning will enhance this system by predicting formations and key game events.
Similarly, MLB Advanced Media’s Statcast employs machine vision and radar to analyze player and ball movements, providing a comprehensive understanding of Major League Baseball dynamics in real-time—generating approximately 7 terabytes of data per game!
Embracing Machine Learning for Sports
The application of artificial intelligence in sports can range from personalized content recommendations based on user interests to immersive virtual reality experiences. Many of these innovations rely on machine learning. By leveraging this technology, live sports broadcasters can significantly enhance viewer engagement without incurring substantial costs or needing to overhaul existing workflows.
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