How AWS innovation in the world of sports has been game-changing
Before AWS re:Invent opened today, Amazon Web Services Inc. held a Sports In Action Showcase, which included a sports panel with three AWS executives who outlined how the company is working with sports organizations.
The executives were Julie Souza, head of sports for AWS Global Professional Services, Sam Schwartzstein, producer for analytics and insights for Prime Video Live Events, and Andrew Reich, a senior consultant in sports. The panel started with Souza highlighting the five pillars of innovation for AWS in the sports industry. These are:
- Live cloud production and distribution. Leveraging the cloud for production enables flexible, scalable, and sustainable creation and distribution of content.
- Direct to consumer. Delivering high-quality, low latency and interactive sports content directly to fans increases engagement and creates monetization opportunities.
- Smart venues. Reducing the friction with seamless entry, frictionless point of sales for food and merchandising, and sustainable solutions to modernize venues. AWS Just Walk Out stores are an example of improving fan experience using technology to speed up purchasing.
- Fan data and analytics. Analyzing the massive amounts of data created during every game for audience segmentation, persona modeling, marketing, advertising optimization and personalization.
- Performance data and analytics. Using computer vision and tracking data to uncover insights to drive better engagement and monetization and improve player safety and game strategy.
Although the first four bullets are interesting, it’s the final bullet where the panel spent most of its time, as AWS and its sports partners have almost unlimited potential to use data to change almost every aspect of sports. Perhaps the biggest change in sports has been the use of tracking data. This includes analysis at a league level for rules development, analysis of officials, and creating new types of analytics, as well as at a team level for recruiting and game strategy.
Then there’s using the data to attract new fans to the game by using the data to tell stories through a different lens. Schwartzstein referred to this as being able to “show the unseen to the untrained eye” and then mentioned that was a big part of his job. This is done by creating new models and graphics and educating the audience about why they should care.
He explained fan education was the main driver behind Prime Vision with Next Gen Stats on Thursday Night Football. Anyone who has watched it can see right away it’s different than a typical broadcast that looks down the line of scrimmage at just a handful of players. Prime Vision shows all 22 players on the field and will highlight key offensive and defensive players to help fans understand where to focus their attention. This can greatly complement the play-by-play and color commentary on the broadcasts.
It’s important to understand how the data is being collected. Souza mentioned how, at one time, the box score was the only source of information. Today, the different leagues use different techniques to collect data. For example, in the NFL, players have an RFID chip in their shoulder pads.
There’s also a virtual web around the field to understand who is on and off. This lets AWS track player speed, the direction they are moving, acceleration and other information. Initially, this data was used to calculate metrics such as completion percentage and catch rate, but now AWS is using AI to predict things like which player might blitz and then what the offensive coaches should be looking at.
The NHL also uses chips on player shoulder pads but also the puck. Other sports, like basketball and soccer, use optical tracking to capture player and ball movement. Although the data sources might differ, Souza explained that the output is still the same. To get a sense of the volume, Souza mentioned the NFL collects 300M data points per season, and Formula1 captures a staggering 1.1 million data points per second, which makes machine learning and AI-based analysis a must, since people can’t process that much data manually.
Reich then provided examples of how the data has been used to drive change. In NASCAR, pit crews have access to a myriad of information to help them know exactly when to change tires. This was more art than science; a mistimed tire change could cost a driver a race.
In the NHL, there is now an abundance of data on face-offs, which hasn’t been focused on much historically but is a big part of the game. Teams can use the data to create better matchups, but the league can use it for analysts to talk more about it on broadcasts, creating more educated and engaged fans.
Souza did a great job of summing up the importance of analytics by talking about the work AWS is doing with The Bundesliga, the top soccer league in Germany. With that league, AWS shows “Match Facts,” which is live data shown to fans. The league surveyed 1100 fans, and 97% said they improved game viewing, and 90% said it taught them something, which speaks volumes as these are highly educated fans. Souza commented, “When you feel smart about what you are watching, you will watch more of it.”
Like all industries, sports is changing, and every league is trying to improve the experience of their existing fans but also attract new ones. Data is the key to success as it is foundational to new experiences that appeal to both the hardcore fan and casual ones. AWS has been actively using Next Gen Stats to augment fan experience, but as Souza said on the panel, “We are just getting started.” More to come to a broadcast near you.
Image: AWS
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