Artificial Intelligence and its impact on sports industry

Written by – Ayush Pandey 

Artificial Intelligence (AI) refers to the computer science capability that allows technology to imitate intelligent human behavior such as speech recognition, translating languages, interacting with the physical world through visual analysis and decision making.

Artificial Intelligence is defined as software that is capable of making its own conclusions on the way of reaching a goal. In that process, AI software has to have the ability to learn, self-optimize and, ideally, return data output.

On another hand, everybody, even slightly familiar with how the IT operates and advances, is well aware that every human task that can be replaced with technology will eventually be replaced with technology. In the world of sports, 2016 was the year of data analysis and 2017 was the year of AI.

Amazon’s Alexa, Echo and Echo Dot also already use AI (mostly successfully).

From the goal-line technology used in football to the Hawk-Eye and the Direct Review System (DRS) in India’s favourite game – cricket, technology is being used every moment to make decisions on-ground, and to enhance viewer experiences off-ground. Right from marketing, ticketing, merchandise sales, sponsorship activations, athlete training, visual analysis and more, capturing and analysing data has become the life and blood of sporting events worldwide.

In the sports industry, artificial intelligence seeks to evolve technology in hopes to bring automation and increased data analysis to business decisions, sponsorship activations, ticket sales, athlete training and more. Grabyo has teamed up with Opta Sports to publish automated real-time video clips to fans at specific events using AI. GiveMeSport utilizes a similar concept, however they publish their sports moments to Facebook to appeal to their mass following. NASCAR is changing the game by adopting a new way to streamline the officiating process, which uses technology and cameras to identify racing infractions. Lumo Bodytech and Puma have formed a connection to create a cutting-edge AI product that uses real-time data to analyze human biomechanics. NBA summer league has debuted the Aspire Ventures product, Connexion kiosk, to be the “Iphone of health care.” The Connexion kiosk will use its artificial intelligence software to analyze player’s health data to allow teams to stay informed of any injuries or setbacks. Arccos Caddie is golf’s first AI powered-platform that allows players to walk the course with their own virtual caddie who will assist players on what club to use, what direction to hit into, and more based on weather, course location, and player ability. Fitness fans will see AI incorporated with their workouts and nutrition with an automated workout “buddy,” which will support users during their workouts with expertise and encouragement through the app Talk Human to Me.

 

Role of AI in the FIFA mania

With technology itself undergoing several transformations, new and disruptive ones are emerging more frequently than ever, and Artificial Intelligence (AI) is gaining popularity as it covers several areas within the sports domain. Examples on the rise of this trend are rife, such as Goldman Sachs’ analysis on the likely winner of the FIFA World Cup, 2018. They did this after running over 2,00,000 scenarios, based on team data and individual player attributes to project-specific match scores and simulate over 1 million variations of the tournament draw to calculate the probable winner. Using Machine Learning (ML) to predict the outcome of the NBA, and leveraging AI to predict the winners in soccer, is other good examples of the trend.

Then, there’s what we see right now. From mid-June to mid-July this year, enthusiasts were glued to the greatest in football clash – the FIFA World Cup 2018. Fox Sports took advantage of AI and ML to deliver the innovative FIFA World Cup Highlight Machine, making video analysis possible from the FIFA World Cup archive, as well as the 2018 footage; it also extracted data, allowing users to search for goals, red cards, and players by name.

 

Enhancing experiences                                                      

The enthusiasm for AI spans beyond football and will be extended to the Olympic Games Tokyo 2020, for which the Japanese government is developing an AI-based spectator guide system. Developers have also been invited to share ideas that will enhance the athlete and viewer experience, and even span business applications – from operations and logistics, that could improve the Olympics event as a whole.

On the motorsport tracks as well, it has literally become a race to adopt technology and we are not talking mere analytics; using AI, 100s of sensors talk to each other about the wind movement to help the driver decide on how to handle the curve ahead, when to step on to the accelerator to capitalise on those last crucial 90 seconds of the race and much more. The Renault Sports Formula One team is now working on a digital transformation plan for the next major F1 event. Designers are working with Microsoft HoloLens that will also give fans the option of understanding the mood of the driver as he races towards the checkered line.

The use of these technologies, though, is not just that of a crystal ball. It is extremely useful in player performance analysis, as well as training and development. Right from their daily schedules, training session details and more, AI helps sports professionals understand their strengths and overcome weaknesses. It also makes the whole sporting experience more personal for the spectators allowing them to feel that they are a part of their favourite team or close to their favourite player.

 

Current applications of AI appear to fall into four major categories:

  • Chatbots– Sports teams are using virtual assistants to respond to fan inquiries across a wide range of topics including live game information, team stats and arena logistics.
  • Computer Vision (as it pertains to professional auto racing)– Researchers are training deep learning neural networks to achieve accuracy beyond humans in the ability to identify specific cars at high speeds which typically produce photographic images with reduced clarity.
  • Automated journalism – Media outlets are leveraging AI-driven automation to expand their sports coverage capabilities and increase revenue.
  • Wearable tech – Companies are using AI in conjunction with IoT devices to gather data to attempt to optimize training and performance.

 

AI Applications in Across Major Sports

1 – Chatbots for Sports / Sports Teams

NBA

  • In June 2016, in partnership with Sapien, a custom bot developer (formerly known as JiffyBots), the Sacramento Kings introduced a chatbot called KAI– an acronym for Kings Artificial Intelligence.
  • The chatbot operates through the Facebook Messenger platform for the purpose of answering fan inquiries including info about franchise history, current team stats, the team roster, franchise history and details about the Golden 1 Center, the home arena of the Sacramento Kings.
  • While the franchise is keeping details on the number of users and their strategic goals for the chatbot under wraps for now, Kings CTO Ryan Montoya has statedhis “commitment to utilizing technology to enhance the fan experience.” In fact, the franchise claims that the Golden 1 Center is the “world’s most technologically advanced and sustainable arena.”
  • According to a 2016 reportpublished by communications firm Avaya,“a digitally connected fan is becoming a [sports] venue’s biggest online influencer.”
  • “Stadium owners and teams that provide more personalized digital experiences through stadium apps, digital offers direct to mobile phones, and game information on digital boards can increase fan engagement and generate new revenue opportunities.”–  Connected Sports Fans 2016 report by Avaya
  • Hailing from Silicon Valley, team owner Vivek Ranadive is shaping the vision for the Kings and it appears that technology is a priority:
  • “The mission is to build a winning franchise…And so we have to win, and we have to win a championship. And that’s the goal; that’s a given. But the fans here are pretty amazing; they’re actually heavy consumers of technology. It’s a young fan base; we have 160,000 young people in this area. And they have a voracious appetite for technology and for new things. And so I think the fans are ahead of us. I don’t think we are ahead of the fans.” -Vivek Ranadive, 2015 interview with the Sacramento Bee.

 

2 – Computer Vision Applications in Sport

 

NASCAR

  • Safety continues to be a primary focus for NASCAR, the sport has averaged more than one death annually since 1950 and shows a continued trend in the past five years. Fatal crashes are both tragic and costly. A single race car is estimated at $300,000(not including repair, maintenance or labor costs) and tires are changed every race with a reported price tag of $500 per tire.
  • Argo AI/Ford Motor Company has used deep learning to develop self-driving cars and is now expanding its application of deep learning to help improve safety measures in the world of auto racing.
  • Specifically, the design team recognized that its deep learning neural network was capable of identifying specific cars using images. The design team originally used a dataset containing thousands of images to train the neural network. It is unclear as to how much better the network performed but the team claims it was particularly evident in the case of blurry images. The reduced visibility is due to high speeds at which the cars are moving.
  • As the network gained proficiency, it reportedly provided more accurate results than humans in its ability to identify specific race cars. The ability to quickly identify and access a car that is experiencing a malfunction during a race is significant; small malfunctions can quickly lead to more serious problems such as fires, putting the driver in danger.

 

3 – Automated Sports Journalism

Sports works well for automated journalism since sports stats are numbers-based. These data can be structured in a way which makes automated articles easy to write.

4 – Wearable AI Tech

Boxing

PIQ, a French sports robotics startup and Everlast joined forces to develop what is described as the “first AI-powered wearable for combat sports.” Crafted using GAIA Intelligence, (machine learning platform for sports analytics) the startup claims that the platform is capable of tracking and analyzing “microscopic variations in boxing movements” to help maximize the efficiency of workouts and training.

The data that are recorded can also be accessed through a phone app which allows users to track their activity and see how they compare to other users based on a leaderboard.

To date, PIQ has reportedly raised $5.5 million in Series A funding from 3 investors. Time will tell if this promising collaboration will make a sustainable impact on the sport of boxing.

Connected Sneakers

India-based Boltt Sports Technologies is looking to disrupt the international market with its brand of AI-powered wearable products. The company is attempting an interconnected approach to its offerings which include “connected sneakers,” fitness trackers and a “stride sensor.”

The connected sneakers are designed with a stride sensor which can be synced via Bluetooth with the company’s app. Using machine learning; the app tracks performance data and then provides recommendations based on user goals. Other app features include a nutrition guide, workout library and custom training programs.

We’re trying to displace the need for a nutritionist, a doctor, and an activity center.” “We think that this is the next thing for the future of wearables, where you need to go beyond just tracking.” – Aayushi Kishore, co-founder, Boltt Sports Technologies (Sports Illustrated, January 2017)

Prior to launching Boltt, in 2011 co-founder and CMO, Aayushi Kishore established a shoe brand in India called Globalite. Estimated annual revenues for Globalite which became a competitor of international shoe brands (such as Nike and Adidas) totaled $7.5 million USD (500 million rupees). To date, Boltt has reportedly raised $600,000 in total equity funding in its quest to become an internationally competitive brand.

Way ahead

Despite the amazing potential, prevalence and use of AI is still limited in India, presenting a huge opportunity for entrepreneurial minds to bring benefits of AI to the table for the players (AI connected sneakers by Boltt Sports Technologies, an India-based startup) and for viewer experiences (RCB Chatbot introduced in 2017 to interact with fans).

As machines become ever faster and ever more adept, there is no doubt that in the not too distant future, technology will create better venue experiences that not only draw fans out of their living rooms and onto the stands to cheer their players on, but also to experience the live passion of the sport within the comfort of their own homes – changing a sporting experience forever.

 

Potential Future Applications

Next, we will explore some potential future applications of AI in professional sports. It is important to note that is not an exhaustive list. We aimed to provide a high-level view of major applications that emerging from the sports industry, giving readers a sense of technologies that either (a) may become mainstream, or (b) are indicative of an important future trend.

 

1 – AI Assistant Coaches

NFL

Using AI to help NFL teams develop and/or improve game strategies may not be too far in the distant future. Oregon State University researcher Alan Fern is using videos of games and deep learning to train computers how to understand the game of football and coach plays.

Effective coaching is a skill that requires experience and is developed overtime; it is also an imperfect science. Computers could possibly provide coaches and teams with improved accuracy in analyzing common mistakes and improving plays at a faster rate than humans.

“For example, knowing how players move during a game could help coaches plan an athlete’s training so he reaches peak performance. It could also shed light on the best matchups between receivers and cornerbacks and measure the contribution of each player to every play.” – Alan Fern, a computer science professor at Oregon State University

While the ROI on developing virtual assistant coaches may not be readily apparent, the focus is on using deep learning to uncover strategic insights that may not have been previously achievable.

2 – Smart Ticketing

NLS

The San Francisco Deltas, a new soccer team that debuted in 2017, aspires to use AI to build and increase fan engagement. Among the team’s interest is smart ticketing, a technology that allows ticket buyers to change seats, from game to game, based on their backgrounds and interests.

For example, a fan could sit with their family during one match and move to a section with a “louder, more energetic supporters’ section.” This option follows a industry-wide trend of enhancing sports fan’s experience with their favorite teams.

3 – Automated Video Highlights

Tennis

IBM announced plans to enhance the Wimbledon experience using cognitive computing capabilities through the Watson platform beginning in 2017. Examples, include AI-automated video highlights. CNBC put together a video explaining how IBM’s system picked up “key moments” in the match by drawing data from players, fans, and more:

IBM claims its technology will support a team of research scientists and consultants, to automatically curate game highlights based on game-specific data such as “analysis of crowd noise, player’s’ movements and match data.”

The process of organizing and processing video highlights can normally take hours and IBM aims to significantly accelerate the process. It is not clear from the company’s announcement, how much faster they expect their platform to perform this procedure.

4 – Computer Vision Referee

Tennis

Bay Area-based French inventor Grégoire Gentil has designed a $199 pocket-size device that called “Tennis In/Out”, which uses computer vision to detect the speed and placement of a tennis shot – including whether the ball was out of bounds:

While the device is currently a novelty application, it demonstrates the increasing accessibility of AI software and camera hardware. Hobbyist AI applications are today still rather novel, but it’s unlikely to remain rare as open source AI tools and online education courses flourish. Combinations of IoT and AI are becoming more popular, and we presume that sports (and broadly: Health) will be an industry ripe for innovation of this kind.

Concluding Thoughts on AI in the Sports Industry

AI is impacting nearly every major professional sport. This is a timely disruption of the industry as media involvement becomes increasingly important as the leading source of revenue in professional sports.

It is clear from the direction of this trend that fans are demanding more access to their favorite sports team and technology is a necessary conduit to meeting this demand. AI is providing customized frameworks for fans to feel closer than ever to the players and the game.

More personalized experiences and more helpful automated interactions may well mean more fan loyalty and engagement over time. In this respect, artificial intelligence in sport won’t be much different than its applications in media and software generally.

Wearable tech is another application of AI in sports that holds great promise for future growth. Companies are realizing the need to go beyond just tracking data to converting it to meaningful insights that actually help athletes meet their performance goals. These products can also appeal to fitness enthusiasts as well as professional athletes, offering wide market reach.

The NCAA estimates that nearly 8 million individuals currently participate in high school athletics. On the professional front, the U.S. Olympic Committee’s director of technology and innovation, Mounir Zok, has stated that wearable tech contributed to Team USA earning 121 medals at the 2016 summer Olympic Games.

Wearable tech could easily move from a competitive advantage to a standard component of athletic training in the coming years. As in the world of heavy industry and manufacturing (where we covered recently), smart companies may be able to gain a continual edge over the competition by gaining more and more granular data on their equipment – in this case – the athletes themselves.

It’s important to note that most of the applications of AI in sport are still in a “test” or “pilot” phase, and it may be another three or four years before stadium chatbots and IoT wearables become commonplace and clearly advantageous. They may cost more than they return for the time being, but companies making the investment are hoping to stay ahead of the pack as the innovations deliver returns.

Impact of AI on employment

Right now I look at it and say – well if we are all out of jobs, who is going to buy their damn tickets and merchandise! But that is a superficial approach. Businesses don’t want to bite the hands that feed them; they want to enhance the experience. That is their stated goal, but let’s hope the unintended consequences aren’t too harsh.

In reality – look to the relational roles as see their stability. Sales happen because people like the person they are dealing with and they appreciate the product. If the product improves, it’s an easier sell for the relational person.

Marketing happens because you have minds connected to the emotional purpose of their audience.

Coaching happens because they are able to relate, motivate and inspire individuals to reach beyond what they think is their best.

Community relations happen because people care and want to enhance the connectivity between the local community and the organization.

Sure, AI will provide data and information and let’s be honest it will replace some jobs. But figure out your value, what makes you unique and special and lean into that. Lean into your ability to relate, motivate, lead and work as a team. These are hard to find qualities in a software system.

 

How will Artificial Intelligence Change the World of Sports?

Creative AI operates better when it has access to more data. Therefore the challenge is to steer AI to collect significant amount of correct data, and use that same data to create. In 2017 this technology will only grow and it will be directed to personalization. What we want to do is predict, this is what we’re looking for, everything else we can do, “The answer to AI in sport is prediction.” To keep costs down whilst ensuring a team is as competitive as can be, AI could even be used for scouting talent. Players which could have the biggest impact can be identified earlier on in their careers when their salaries are less demanding than seasoned professionals.

Can we perform tests on young players? Try and understand their trajectory as they grow older and whether they’ll become premier league players. That would save a lot of money if we can produce our own players rather than buying them in. Even more exciting for a club is to implement this knowledge into whether particular strategies are likely to result in a win.

 

“There’s a great likelihood that by 2022 artificial intelligence will be able to create brand identities and experiences.

 

Sport Performance Corner

As I mentioned earlier, Under Armour is using AI to improve their relationship

With the customer. Furthermore, Under Armour is a fast growing sports gear manufacturer, and as such they started to rely on AI to improve their products. Their new Health Box is an AI powered personalized fitness system. And this is just a start since Under Armour plans to turn their sports gear into gadgets using AI.

Researchers from Disney Research, California Institute of Technology and STATS have introduced an AI approach to sport preparation that can help teams and athletes better prepare for specific opponents by using both advanced analytics to study the opponents and AI to calculate the predictions of opponents’ most likely reactions to certain on-field actions.

To make it reality, this approach takes individual behavioral data and from it builds individual models using AI’s learning and AI’s prediction abilities. Athlete’s predicted moves are then visually presented as a ghost. Ghost is a transparent image that shows predicted movement of a certain athlete. Everybody who used to play car games and tried to improve lap records knows what this is all about.

You simply know this will make its way to game preparation routines, if not even games themselves. Especially with improvement of VR. There will no longer be a need to film the opponents plays in VR. AI will gather data on certain teams and players, use it to predict their reactions and, with the help of VR, visually present it to the players.

It goes without saying that artificial intelligence will impact almost every industry imaginable in the future. According to Constellation Research, the artificial intelligence market will pass $100 billion by 2025.

 

Bibliography

  • https://www.techemergence.com/artificial-intelligence-in-sports/
  • https://www.workinsports.com/blog/how-artificial-intelligence-will-affect-the-sports-industry-of-the-future-work-in-sports-e/
  • http://promoovertime.com/will-artificial-intelligence-change-world-sports/
  • https: //www.firstpost.com/tech/news-analysis/how-artificial-intelligence-is-going-to-disrupt-the-sports-viewing-experience-4768261.html
  • https://www.leadcrunch.com/articles/impact-artificial-intelligence-sports-industry/
  • https://www.sporttechie.com/artificial-intelligence-sports/

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