Pixellot’s David Shapiro explains how AI-automated production tools are democratizing sports broadcasting
Solution Brings Automated Capture and Distribution to High School and Small College Sports
Since its inception in 2013, Pixellot has helped pave the way for automated sports production. The company’s AI-powered production systems automate the live sports capture, distribution and production of more than 150,000 games per month in 67 countries around the world.
And Pixellot continues to grow. Last month, the Israel-based company announced a $161 million Series D funding round — the largest funding round in Israeli sports tech history. PSG, a Boston-based growth equity fund, led the round.
SVG sat with David Shapiro, President, North America, Pixellot, to discuss some recent AI-automated productions, how Pixellot’s broadcast solutions have opened up a whole new world for underserved sports properties; where AI automation is seen on high profile sports productions; how these tools can help athletes grow their fan base and develop their own name, image and likeness (NIL) businesses; and what Pixellot’s technology roadmap looks like.
Pixellot has been busier than ever lately. What recent productions you’ve been involved in have helped advance AI-automated production?
The MLB Draft League and the MLB Appalachian League are two leagues that take place at approximately 20 different venues. College-aged athletes that MLB has identified as potential draft picks are playing in these two leagues. Our technology gives them the ability to produce 100% of those games. This summer, between May and August, we will produce around 500 games in both leagues. The games will be broadcast on the OTT platforms that we have designed for both leagues, and then MLB will select certain games that will also be available on the MLB network.
The largest example of Pixellot in the United States is PlayOn Sports, where the technology is installed in approximately 15,000 high school fields and courts across the country and will produce nearly one million games per year for the NFHS network.
We have another company we’re working on to bring even more access and games to other parts of North America, so stay tuned.
How has AI-powered production opened up live streaming to underserved sports properties in recent years?
The biggest opening was in the high school market. Typically, five years ago, high school games were not produced except for championship games or games between very large schools. Now, most high school games are produced and streamed, with Pixellot producing the majority of games for the NFHS network.
Also, the smaller colleges, below the Power Five schools like Texas A&M or Stanford, didn’t produce games, but Pixellot technology enabled those colleges to have production. With our newest product, Pixellot Air, we’re enabling production right into youth sports, so everything from 5-year-olds to high school sports.
How has the sports production industry’s perspective on AI-automated production evolved? Do you see more companies adopting this technology beyond smaller/lower profile events?
Yes, production companies are starting to look at how they can make productions more cost-effectively. There are companies like Rush Media, which produce all the games for the Big East, which FloSports has the rights to. They use our solution as part of the production solution. They add additional camera angles, using us as traditional camera 1 and adding the other camera angles and running it through a mixer to mix those different angles. I think we’re starting to see more innovation in the industry to find a way to produce high-profile games more cost-effectively, and Rush Media is the best example of that.
How can AI-based approaches help athletes grow their fan base and grow their own NIL businesses?
NIL is the big topic right now in college sports. It becomes a recruiting advantage if you are able to provide opportunities for your athletes and open doors for them to generate income because a scholarship only goes so far. Many sports, like baseball, only give partial scholarships, so NIL is seen as a way to supplement that.
For a university to maximize the NIL for its athletes, it needs every practice and game to be filmed so the athletes have all the high-level content. Then they can use the content on their own social media marketing channels. AI-automated production will – and does – play an important role in the growth of NIL and the academic industry.
What are some of the latest enhancements to the Pixellot platform that allow live sports producers to deliver even better live streams?
The end-to-end solution and service proposition certainly plays a major role in our growth. Now, in addition to simple automated production, we also offer a white label OTT solution so that if a rights holder – which may be a league, university, tournament organizer or even a sports venue – needs to a way to distribute content, we have a white label OTT designed for them.
Major League Baseball uses Pixellot’s white label OTT for the Draft League and Appalachian League. Cooperstown All Star Village, which is a large facility near the Baseball Hall of Fame in Cooperstown, NY, uses it, as do several other partners. They use it as an enhancement, [providing] the ability to charge a subscription or charge a la carte, know who your users are, cut clips and monetize content. In many different ways, we do turnkey things for their partners.
Another improvement is the Pixellot Prime upgrade. This is Pixellot’s highest end solution where we have 1080p 60 fps which is broadcast quality output.
Has the explosion of streaming and OTT channels increased the demand for AI-automated production in recent years? How has Pixellot adapted to meet this increased demand?
Pixellot has certainly increased the demand for automated solutions. Just look at the cost of doing general business around the world. Pixellot has seen incredible increases, in terms of labor, materials, shipping, etc. Businesses need to find a way to produce more efficiently, and Pixellot is the answer to that.
Also, with all the growing channels and OTT, there is more demand for more content. Content is increasingly localized and personalized, and the way you capture a lot more content is through automated production. It doesn’t become effective if you have to increase the number of people and the amount of equipment you need to meet those needs. That’s why so many Pixellot partners have embraced our technology.
How do you see the use of Pixellot and automated production tools like it evolving in the years to come? What are the potential high growth areas? How will the technology continue to mature and become even more efficient/high quality?
Our DoublePlay baseball solution is a good example of the evolution of Pixellot. For the first time, Pixellot has multiple cameras with automated switching. The basic solution right now, for all other sports, including rectangular sports, is that you have multiple cameras, but they’re all coming from one angle. In baseball, softball and cricket, Pixellot realized that it didn’t work to be one-sided. The baseball solution started as just behind home plate, but evolved to have one camera behind home plate and one camera behind center field.
Pixellot built an AI to tell the computer when to switch between camera angles based on the state of the game. An example would be, when the pitcher is on the mound and the batter is in the batter’s box, the view is from center field, where you see 80% of MLB’s broadcasts. Once the camera determines that the ball has been batted and is in play, the production switches from center to the home plate camera. Here you see a wider angle of home plate zooming in on where the action is on the court.
Pixellot has received amazing feedback and a lot of demand in baseball and softball for this product because no one else has anything like it. We believe that the logic that has been built could also be used for rectangular sports – football, basketball, soccer, etc. – adding goal line cameras in soccer or behind the hoop cameras in basketball, while creating logic to tell the cameras when to change angles to give the production a more personalized feel, as if you had a director in the booth who decides, even if the AI makes the decision.
Youth sports are a huge opportunity for growth. The number of athletes increases as you go down, and often those athletes care about their content: being able to share it with friends and family, but also use it for recruiting so that they can be recruited from a college or a professional team in Europe. As mentioned earlier, All Star Village in Cooperstown [has] incredible audience and interest in Pixellot technology.
Another great thing is that it has to be mobile, which is why we created the Pixellot Air: so that mom, dad or coach can take the sidelines and be able to produce a game.
Do you have any other great news or messages from Pixellot that you would like to share with SVG readers? Do you see any big business or technology trends that you think will have a significant impact on the industry in the next 12-18 months?
The big news is that Pixellot recently raised $161 million, which is a significant increase for us and for the industry. This amount of funding will give us the ability to conquer this market in an even bigger way. Much of the growth we will see will be in the amateur sports we talked about earlier. They are a great opportunity, [along with] growth in new geographies around the world. Currently, most of Pixellot’s business is in North America and Europe. We are exploring growth in other parts of the world, such as China, India and other parts of Asia.