The future of AI in sports for players, broadcasters and fans

AI already plays a significant role in the technology that we all use. This goes for sports, telecoms, mobile technology and so on. During a period when there’s less live sport for us to consider, it seems apposite to ponder what new advancements will be incorporated into the industry in the years ahead.

What developments can we expect from AI in the next few years? How, if at all, will innovation in this sector change the way athletes analyze performance? How can broadcasters provide more value to their viewers using this technology? And what should we in the innovation community remember when finding the AI solutions of tomorrow? 

As an industry, we’ve already made great advancements in this area. In sport, semi or fully automatically generated clips and highlights are common. Increasingly, the audience watching at home can access AI-powered data insights, enhancing the way they experience the sports they love.  

For players, coaches and teams 

Sportspeople and sports teams are forever striving to find that extra 1%, the element that will separate them from the competition. Over the years, this has meant embracing sports science, nutrition, and conditioning. Big data analysis is the latest must-have for those in the industry. 

Let’s take a real-life example of how AI fits into this. We know AI can detect and analyse an opponent’s most frequent attacking patterns – and consequently, how best to defend against it. It can identify players’ most recurrent positioning and movements, i.e. which way does the player feint before dribbling?  What is an opponent’s most successful corner routine? Automated formation recognition is particularly crucial in this, as it can add real-time insights which managers and coaching staff can react to during a game.  

AI allows us to analyze a much wider data set and deliver more relevant takeaways, and at a faster rate. Another instance is identifying a player’s biometrical parameters to detect if or when they are most likely to suffer an injury during a game. Or if they’re entering what is known as the ‘red zone’ – in which a player is most liable to pick up an injury. Clever use of this technology keeps a team’s best players fitter for longer, meaning they’re available to the coach for a greater percentage of the season.  

What’s more, while leading sports organisations now use data in their recruitment strategies, AI will add an extra element to this. While there will be the need for that ‘human’ element when evaluating a potential player, AI complements this with greater depth and granularity. 

For broadcasters and journalists 

AI gives broadcasters the opportunity to satisfy their viewers’ demands like never before. They can provide much more insight, content, and data to those watching – the depth of information they can now communicate was not imaginable only a few short years ago. Simply, broadcasters and journalists can cover the sport in more detail, broadening their appeal by offering more accuracy, more angles and ultimately, more talking points. Now, the real reason your team lost can be pored over extensively – not just blamed on the referee. 

But what does this mean in practice? Well, it gives greater opportunity for fans to become involved in the broadcast and shape their experience. Think about face-recognition-based interactive graphics. Depending on which player the camera focuses on, the viewer can click on their face and learn that person’s stats for the game or season.  

In-game opportunities also exist, particularly linked to the biometric profile of a player. Communicating with a viewer how fatigued a player is, and in turn the potential impact this has on this ability to score his next opportunity gives a detail that hitherto, has not been part of regular broadcasting.  

Fans crave control. Even to be their own data analyst – when the game or race is happening. Think of Formula 1 and the complex strategies that feed into a race. How can AI better inform the viewer at home about tyre degradation and the best time to pit, for example? We know that operators are constantly looking for ways to further engage their viewers on top of the action. AI feeds perfectly into this.  

We can foresee a time when AI is analysing 10 games at once, and then feeding back to the viewer, prompting them to an individual’s preferences – helping them decide if a particular player is heavily involved, or if the pattern of play has turned sufficiently in a game which looked to be over.  

In stadium/out of the stadium  

There are many opportunities that AI technology can exploit both in and out of stadium. For those watching a sporting event live at the arena or stadium, naturally, the focus is on the action that is taking place in front of them. AI has a role to play in helping generate excitement and an atmosphere prior to the players taking to the field, or during half-time.  

Also, think of time-outs in American Football or Baseball – in this case, any AI technology could relate to the event the fans are experiencing, i.e. automated triggered insights and stats, AR overlays on the pitch. We should note that 5G will be transformative for the in-stadium experience, allowing much more of this to be realized.  

For the at-home fan, there needs to be a focus on providing continuous, multiple interactive experiences. This means an emphasis on the second screen, features that exist on the specific streaming platform or, perhaps, a voice assistant. All of which should supplement what the fan is watching live, helping to keep them more informed and more engaged.   

What’s next? 

While it can be something of a fool’s errand predicting exactly how the sport AI industry will evolve in the next few years, we can still speculate.  

What we can be sure of is that AI fits perfectly with other technologies and does not pose specific limitations to integrations. A great example is 5G: it will enable high-speed data transfer from clients to the central processing entity, allowing for consumption of AI-based services or features from devices that do not have the processing power locally in a real-time or near-real-time.   

We can expect greater efficiency – specifically thinking of recent innovations such as VAR (which has courted controversy in several European leagues – due to the way it has been implemented). For some, any AI technology that is introduced will always be unpopular simply for ideological reasons. The key is to ensure that we don’t eliminate the ‘human’ element of sports, and the element of unpredictability, but instead, use AI to complement what we already know and love.  

That’s the challenge for those of us working in the sports and broadcast innovation community. At Deltatre, we’re particularly interested in how we can help our clients, and the industry in general, make improvements in this area. While the current situation without live sport is challenging, we’re using this time to reflect on our successes thus far and refining our ideas so that we can offer our partners even more exciting solutions, and in turn, entertain viewers like never before.  

This article originally appeared in The Future Shapers

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