Artificial Intelligence is taking over some of the tasks that we deem tedious.
And many industries may extract a lot of benefit, especially the sports media.The field is overflown with events happening all over the world: games, press conferences, scandals, analytics – no wonder the executives are looking into automation as the way to stay on top of everything sports-related.
But at the same time, the suspicion is growing that some people might lose their jobs over AI.
The short answer to that is: the AI is not that smart.
The longer answer: AI won’t take over your job, but it can become your little helper, saving you time on those tedious things.
Sports broadcasting workflow
Sports broadcasting has gone far beyond announcing the score updates over the radio.
Frankly, it has gone beyond the sporting events as well.
It is a big field after all, with even a bigger fanbase craving for sports-related entertainment all day, every day.
And the media outlets respond to the demand with all things you can imagine, and then some.
Before the events, we get extensive analysis of the situation in the league from people who know their way around athletes’ performance metrics, game strategies, coaching abilities of certain rosters, and so on.
We get the latest news about who’s changing teams, everything going on between the team members, all of the facts, rumors, and quarrels we love.
Then we got the games that producers work very hard on covering. Here, the large team of producers and cameramen keep a sharp eye on everything that’s going on in the field and on the grandstand, doing their best to catch the best plays, fan reactions, quarrels with referees, and so on.
And you cannot forget the post-event content. Interviews with athletes and fans, press conferences, coaches’ impressions, highlight compilations, debates between sports news anchors about the outcome of the game.
All of that needs people to shoot, record, write, produce, and then broadcast and share via TV, radio, podcast platforms, and social media.
How to create sports content: the traditional way
For this particular article, we will focus on the video side of things.
Sports is dominated by video content, with media companies and broadcasters pushing out endless hours of all things sports.
It’s better seeing two anchors fight each other over their favorite teams rather than reading about it.
So, how do we make that content?
We hire a bunch of people. They point cameras and shoot.
Shooting the content involves a whole team of people managing the process. The crew shoot any event from a variety of angles and do their best to capture everything important.
On top of that, producers run the show from the backroom. They decide which camera broadcasts the stream to the viewer at any particular moment. For instance, you can have 5 cameras shooting the soccer field, but the one close to the goal area captures the score in the best way.
So, the producers switch the stream so that the viewers see the footage from that camera on their screens.
The same goes for replays: producers take the footage from the cameras closest to the goal area and compile the clips together.
Then, the team deals with the post-game content. They need to look through the entire game footage, and then find the most memorable moments of the game and cut them into compilations.
The media companies can use those sports highlights in news broadcasts and their pages on social media.
In that scenario, everybody wins: the content promotes the sport itself, the media company that puts the content out, the participating athletes and teams, and the depicted event.
Advertisers get their cut of the traction too if you play it right.
The problem with automated sports broadcasting
Here’s the thing: creating all of that sports content eats up a ton of time.
Don’t get me wrong, generating content that many people enjoy is a very involved and intensive, but overall rewarding process.
Every last person from a reporter writing for a website, and anchor covering the events on camera, to a video production team making those clips and shows as engaging as possible pour their hearts out for what they do.
But that comes with hours of tedious work.
The hours that could be spent on the creative part of the job, improving the speed and efficiency of content production.
But what would people do if we had AI chopping all the clips, moving all those cameras, and writing the scripts?
No, it’s still too soon to pack your things into a cardboard box.
Let’s take a deeper look into automation and see how it can amplify the works of humans instead of taking over their responsibilities.
Automating the sports broadcasting
We’ll spare you the waiting and answer the question right away: AI won’t be able to take over the jobs, because it lacks some cognitive abilities natural to humans.
Those cognitive abilities are the thorough understanding of context and out-of-the-box thinking.
We have seen this happening a lot of times: when encountering a confusing situation, AI can’t figure out a way to deal with it.
That’s when we get this:
And just like any other content, sports-related stuff requires deep knowledge of the subject-matter, as well as the creative thinking that facilitates production.
So content teams of media companies can cover the events in all their glory: it has to sound good, look good, and entertain as many people as possible.
It doesn’t mean that AI is useless in that regard either.
It can take over the more tedious part of work, with humans still running the whole operation.
Here’s some things that automated sports broadcasting can help us with.
Pitching in with game analytics and summaries
Before the game starts, many media outlets can have experts discussing the potential outcomes and predicting which team will come on top.
The same happens after the game: there’s a lot of talk about everything that has happened during the event, the evaluation of certain athletes’ performance, and wondering what’s next for the teams.
AI won’t be able to predict all of that, or make an entertaining conversation. That’s what humans are there for.
We can have AI fetching box-score statistics.
Artificial Intelligence can summarize the game, provide the score, and who the game unfolded: which team took the lead, when the game was overturned, etc.
Artificial Intelligence provides thorough game stats that the analysts can use in their work. The technology has no favorites thus providing accurate information.
And the analysts are free to go off that data, interpreting it and entertaining the audience.
Everybody is happy.
Creating sports highlights clips
Video editors can have Artificial Intelligence cut the best moments of the sporting event, making their work less tedious and time-consuming.
Unlike the human, AI algorithm can sift through the footage in minutes, choosing the most memorable moments of the event and cutting them together into a clip.
With enough polish, the algorithm provides human-like accuracy: with the help of cognitive computing, the technology can make sense of the context, understanding the meaning of everything happening.
It is able to differentiate between own goals, penalties, and last-minute touchdowns, giving the audience the comprehensive summary of the game.
Cropping the footage from landscape to portrait aspect ratio
I don’t know how many years we have to live with the Internet to quit the argument “the Internet is where it’s at”.
Let’s just take it as a universal truth. All of us use it. All of us interact with both people and brands there, making it a great place for media companies covering sports to meet their existing audience and lure in new ones.
To do that, the team has to adapt the content for the most comfortable viewing experience on a certain platform. I think that we can all agree that regular 16:9 videos are that enjoyable on your TikTok “For you” page.
And that is what Artificial Intelligence can do for us.
Instead of spending hours cropping the clips from landscape to portrait aspect ratio, the video editor can have an AI system that analyzes the footage, identifies the most important parts of the scene, and crops the clip accordingly.
Recognizing faces of athletes
Athletes contribute quite a lot to the sports promotion. They become role models for aspiring athletes, make the waves in news when switching teams, and generally capture a lot of attention.
Which is what media companies are after. To get their share of online activity, media companies and broadcasters can share the content featuring renowned athletes.
Which is why they need celebrity face recognition, if they want to automate that process.
The manual way, as it goes, is tedious and inefficient. Instead, the editors can have an automated system looking through every piece of content, and identifying celebrity faces: famous quarterbacks, coaches, or even movie stars attending the event.
The information that can be used by other automation systems: creating a best moment compilation with a certain athlete, adapting it to social media, and push to said platforms.