The use of artificial intelligence in sports isn’t a major surprise, given the advancement in technology. Rise in computing power, availability of massive amount of data and an increased willingness of stakeholders to leverage such tools are the three principal reasons why the role of artificial intelligence in sports has gained a lot more importance recently.
Someone who thinks the application of artificial intelligence in sports is limited to improving the performance of players is in for a pleasant shock. That’s because there are many more avenues where AI is used.
Here we list 9 applications that AI has found in the world of sports.
1. Scouting for Talent and Player Recruitment
A lot data were earlier were either not noticeable, recordable, or not easy to make sense of. Using data science in sports allows teams, coaches and selectors carry out a deeper analysis of complex metrics of potential teammates or players.
Besides, there were areas within players’ performance that were not possible to study, owing to the natural limitations of humans perceptual abilities. Wearables are making such data and recording possible.
With machine learning platform for sports analytics, it’s easier to identify how each player is unique and what unique set of skills they bring. Further, with the help of big data, we are coming closer to building reliable, sophisticated models that intelligently calculate the probability of talent a player can bring.
2. Analyzing Workout and Training Effectiveness
Artificial intelligence is fast building up expertise in building a correlation between quantitative, measurable variables (e.g. runs, goals, timing) and qualitative factors (e.g. concentration, ability to strategize, teamwork).
AI can help put together teams where players best complement each other. To do that, it must first see how and whether the workouts and training programs have been effective in preparing the players.
For deeper analysis, PIQ and Everlast developed what is perhaps the first AI-powered wearable for combat sports like boxing or martial arts. Using machine learning platform, the device captures and analyses small variations in the actions of the boxer. This helps the system understand how successful the training and workouts have been in bringing about a positive change in the boxer.
This information is channeled through a mobile phone app into a leaderboard. This leaderboard displays the performances of all other boxers and points how where individual boxers stand vis-à-vis others.
Such apps can also offer tips on nutrition, fitness guides and personalized training programs that help sportspersons better achieve their goals.
3. Designing Coaching and Performance Improvement Programs
Artificial intelligence is already being deployed in education in China in a big way. So it shouldn’t be surprising to see AI helping sports coaches.
One good way to understand how AI is transforming sports is by studying the role of AI in helping coaching, especially in competitive sports.
Artificial intelligence removes or drastically reduces some of the weak spots in traditional coaching. For instance, professional coaches need to spend years sharpening their skills, and yet there is always some probability of committing an error or overlooking something.
Computing technology can resolve this problem by providing accurate analysis and speed up the process of consistently providing correct analysis. For instance, artificial intelligence could carefully study and analyze the bowling action of a bowler and suggest a training plan that could help the bowler achieve better results.
Constant monitoring of health and fitness parameters, using devices, could prevent injuries. It could spot things like repetitive stress injury before it temporarily or permanently stops a player from playing. Thus, it can end up being an invaluable assistant or perhaps a substitute to the team’s medical professional.
4. Creating Better Fan Experience
If there’s one thing organizers and broadcasters are keen to do in sports today, it’s pleasing fans and creating a superior experience for fans. It appears that artificial intelligence in sports management can do this pretty well.
It can begin with the way fans buy tickets, or rather ‘smart ticketing’. That means fans get a variety of options of buying tickets with variable seating options across the different games they attend.
Fans could choose to sit with different people during different times – for instance they could sit with their family during some games and with friends or business associates during other games.
The San Francisco Deltas, a new soccer team, is believed to be trying to leverage AI to improve fan engagement.
Next, artificial intelligence could place more choices in the hands of viewers. It could build algorithms that allow build match highlights in forms and lengths that viewers want.
Besides that, the logistics at the game venue could significantly change fans’ experience. Better parking and availability of quality food and merchandise could help fans get a thrilling experience at the game venue. At events like a marathon where there’s a large number of participants, logistics powered by AI can impress both participants and the fans.
AI is creating sports merchandize that’s not just dependent upon the trend but also based on the fans’ preferences emotions and reactions.
Finally, chatbots that could respond to fan queries with basic statistics could also make a sizeable difference.
5. Optimizing Advertising Opportunities
Brands could soon be getting better advertising opportunities, based on the top moments of the game as identified by artificial intelligence.
The automated learning algorithm monitors players’ actions, spectators; emotions and expressions, and commentators’ language to understand which moments of the game are the most exciting or thrilling. IBM has tested Watson to do this in Wimbledon 2017.
Based on this, advertisers would be recommended time slots where their ads, if displayed, could earn optimum engagement.
Apart from offering better value to advertisers, machine learning will help sales people point out parts of the game they can sell better to prospective advertisers.
6. Maximizing Broadcasting and Streaming
One of the key ways sports broadcasting companies try to remain favorites of viewers is by providing quality coverage. That includes great photography, high-quality relay, excellent commentary, interesting graphics based on statistics and language that viewers prefer most.
From the looks of it, artificial intelligence is about to make a huge impact on all of this. To begin with, AI can help choose the most appropriate camera angles both during the match and also while choose replays or re-runs. Any sports fan will tell you how important angle is in photography of almost any sport.
Next, AI can provide accurate and timely statistics to commentators so that they may provide a better real-time commentary. Also, the system can be tuned to allow subtitles in different languages in case of live events, based on the viewers’ choice and location. Beyond this, broadcasters can use to identify correct opportunities to display ads. A combination of all this will provide a better viewing experience.
7. Leveraging Automated Journalism
Automated journalism powered by AI is likely the next big thing in sports broadcasting. The core idea is simple but the applications are powerful: let machine learning evolve into a technology that can prepare readable reports on sports events.
AI is being used to build videos that better capture the highlights of the day’s match. It curates the most exciting moments of the event and compiles it into a video. When done manually, this task took considerable number of man hour, but with the use of AI the time required for the same task can be reduced considerably. This will help media houses cut their time to market for every video.
Wordsmith, a solution built by Automated Insights (Ai), is capable of processing data of the sporting events to quickly produce summaries and stories of the major event of the day. It is capable of understanding style, language norms and grammar rules while crafting the story.
What’s more, there has been research into getting AI deliver cricket commentaries that are 90% accurate.
8. Managing Safety in Games
One answer to how AI is improving sports is the way it helps better manage parking, reduces congestion and improves the overall experience safer by cutting the chances of mishaps due to poor or bungled parking arrangements.
There’s more too: in sporting events like car racing, safety is a much bigger issue than in sports like, say, swimming or volleyball. Here, AI can use deep learning to develop and improve self-driving cars. These cars will be tested for safety before human drivers use them.
9. Making Refereeing More Accurate
One of the earliest uses of technology in sports is in aiding referee decisions.
For example, in lawn tennis, high-speed cameras have been used to make “in or out” decisions. In cricket, the Hawk-Eye technology has been used in assisting umpires whether the batter is lbw.
Using technology makes the sports event fair and more rule-abiding. It brings in more objectivity in decisions of the referees or umpires. In games like cricket where the batter often gets the benefit of doubt in cases where it’s not possible to judge accurately, the use of technology and AI will make it a more level-playing field.
The system will be able to learn quickly over time, using data to classify position, shots and player stance or positions. As machine learning gets better, rule-infringement will become a great deal accurate and consistent.
It is not easy to trace the introduction of artificial intelligence in sports, but what is sure it is here to stay. It might have started as something of novelty value but quickly became something that gave a competitive advantage to players and teams.
Going forward, it will become a standard fixture, sooner than we think.
Additional reference: CIO