In recent years, due to the influence of the Tokyo Olympics, there has been a growing movement to promote the use of AI in the sports industry. For example, it can be used in a variety of ways, such as during a match, spectating, management, and personal training.
In particular, image recognition and data analysis are highly compatible with various sports, and are expected to spread further in the future.
However, there may be many people who do not know in detail about the specific use cases of sports x AI.
Therefore, in this article, we will thoroughly explain 13 AI utilization cases by scene (during the game, watching the game, management, personal training).
Also, in the second half of the article, I will look into the future of AI and sports for those who are thinking about doing business related to AI, so please take a look.
Table of Contents
- 12 Use Cases of AI x Sports
- [During the game] Examples of AI x sports utilization
- [Watching] Examples of using AI and sports
- [Management] Examples of using AI x Sports
- [Personal training] Examples of AI x sports utilization
- The future of AI x sports
12 Use Cases of AI x Sports
From here, we will introduce examples of the use of AI x sports in the following four fields.
- Examples of using AI x sports “during a match”
- Examples of using AI and sports in “watching”
- Example of using AI x sports in “athlete management”
- Example of AI x Sports Utilization in “Personal Training”
[During the game] Examples of AI x sports utilization
The following three are introduced as “examples of AI x sports utilization during games”.
- [Tennis] Automatic line judgment system
- [Gymnastics] Scoring support system
- [Baseball] Robot Referee
I will explain each.
①【Tennis】Automatic Line Judgment System
In recent years, line judgment systems using cameras have become popular in tennis matches. Today, it is notably used in professional competitions such as tennis clubs and Grand Slams.
The accuracy of judgment is higher than that of human eyes, and many athletes have shown positive reactions, so it is highly likely that this system will continue to be established.
On the other hand, it is also true that there are voices of skepticism and dissatisfaction.
“Hawk Eye” developed by Sony is said to cost at least 60,000 dollars (about 6.5 million yen) to introduce one court, and the cost will be enormous if it comes to all courts of the Grand Slam. Become.
In this way, due to the high price, it has not been introduced in tennis competitions as general entertainment, and even at present, there are no products in the low price range on the market.
In addition to tennis, this system has also been introduced in soccer and cricket, and it is expected that it will spread to various sports in the future.
② [Gymnastics] Scoring support system
In recent years, in gymnastics, the increasing difficulty of techniques has increased the burden on referees, which has become a serious problem.
Therefore, the “AI scoring support system” was introduced to accurately score the performances of athletes who continue to challenge difficult techniques.
Using a 3D sensor, the system uses a 3D sensor to irradiate a laser beam more than 2 million times per second on a player performing a technique with a high degree of difficulty. To do.
In 2018, the International Gymnastics Federation decided to officially adopt it, and it was also introduced at the World Artistic Gymnastics Championships held in Germany in 2019.
This system is also being considered for use in figure skating, where techniques are becoming more sophisticated in the same way as gymnastics.
③ [Baseball] Robot Referee
2019. “Major League Baseball (MLB) and the umpires’ union have agreed to introduce computerized strike ball judgment in the future in a labor union agreement through 2024.
Currently, in the major leagues, many teams are creating their own heatmaps of the umpires. Apart from the strike zone in the rules, this is to visualize the trends of where on the plate was actually judged as a strike and use it to create a game plan.
As is well known, the strike zone is determined by the rules, but the actual situation is that it is the umpire who calls the ball and it is left to individual discretion. As a result, discrepancies arise due to differences in rules, and individual differences are also created.
Baseball referees make different judgments depending on the physique of the players, so it is undeniable that there are some technical issues that are incomplete. However, there is no doubt that it will bring a big change to the baseball world as it takes baseball to the next level.
[Watching] Examples of using AI and sports
The following four are introduced as “examples of AI x sports utilization in spectator”.
- Real-time win/loss prediction
- Camera relay by drone
- A new watching experience with AI match analysis
- Congestion prediction around the venue
I will explain each.
④ Real-time win/loss prediction
In 2019, three companies such as Dentsu announced that they had developed a system called “AI11” that predicts the outcome of a soccer match from real-time video, and launched the service.
AI11 is a mechanism that calculates the probability of winning and the probability of a draw for each opposing team based on the movement of the ball and players, and displays it as a percentage.
A logic for predicting wins and losses was constructed by using deep learning to learn data from approximately 480 matches of the EAFF E-1 Championship, an international match sponsored by the East Asian Football Federation.
Going forward, we plan to introduce this system to various competitions through content distribution companies and other organizations, with the aim of improving the value of the viewing experience.
⑤Camera relay by drone
Camera broadcasts with drones are used in sports such as soccer, rugby, and snowboarding/snowmobiling, where it is necessary to see the detailed movements of players as a whole.
By grasping the situation and positional relationships of the entire course and competitions where players often concentrate in one place, it is now possible to simulate tactical movements and the thrills that players feel.
In addition, drones are used not only for relaying game footage, but also for practice and consideration of tactics, and more and more drones are expected to play an active role in the future.
⑥ New watching experience by AI game analysis
Leiblits Co., Ltd. has started providing the video production tool “Fastmotion V3” from June 20, 2021. This tool is a service that analyzes baseball play footage with AI, animates the movements of the ball and players, and creates video content along with the data.
Spectators can present a new spectator experience to fans by being able to express the athlete’s athletic ability and the power of play, which they had previously perceived intuitively, with objective data and visually easy-to-understand images.
⑦ Prediction of congestion around the venue
At the Tokyo Olympics and Paralympics held in 2021, a congestion mitigation system using artificial intelligence was introduced to deal with the congestion that occurs around the venue.
In the past, the main focus was on easing congestion through vehicle traffic regulations, etc., but congestion countermeasures were also taken to target pedestrians as well.
AI judges the situation around the venue and uses electronic signage and smartphones to inform you of the congestion situation 30 minutes later. Spectators will choose routes and stations that are open, so congestion can be alleviated efficiently.
The spread of this system has had a positive impact in various situations, such as being able to use it to place security guards in places that are likely to be particularly crowded.
[Management] Examples of using AI x Sports
The following three are introduced as “examples of AI x sports utilization in management”.
- Tactical planning by AI
- Player condition management
- Motivate players
I will explain each.
(8) Tactical planning by AI
In recent years, the basketball industry has pursued optimal strategies by visualizing data. Eight cameras were installed on the ceiling of the gymnasium where Fujitsu’s women’s basketball team (Red Wave) practices.
By installing a camera, it will be possible to record the movements of all players and visualize the success or failure of shots in a distribution map, enabling more detailed analysis than before.
If such a service develops, it will be possible to develop tactics by analyzing not only your own team, but also each opponent.
⑨ Player condition management
In 2019, Euphoria Co., Ltd. and NEC Corporation (NEC) conducted a demonstration experiment in the field of condition management services for athletes and started working toward collaboration.
As a specific initiative, through clinical trials cultivated in “ONE TAP SPORTS” such as biological information data acquired by wearable devices and daily condition data input by athletes themselves, and data analysis using NEC’s AI technology, We are building a system that supports performance improvement and injury prevention.
Based on this analysis data, the athlete’s fatigue, heat stress, sleep quality, etc. are indexed and provided as objective and quantitative values, aiming to improve athletes’ self-care awareness, performance improvement, and injury prevention. to support
In June 2019, prior to the collaboration, the two companies conducted demonstration experiments for the NEC Red Rockets of the V League and the NEC Green Rockets of the Japan Rugby Top League, and realized commercialization in 2020.
(10) Motivation of athletes
One of the systems designed to motivate athletes is Life Beams’ earphone-type personal trainer “Vi.”
Vi measures the following six types of values from biosensors, GPS, etc.
- Heart rate
- slope of the road
- change of pace
- Moving Speed
- Travel time
- Moving distance
The secret of these functions is that the results accumulated and analyzed from measurements are conveyed to the user as voice. If you tweet the information you want to hear while driving, it will answer like “Siri” or “Google assistant”.
Vi also has a function that creates an original playlist according to the type of exercise.
With a wealth of other support, you can expect to get better performance than exercising alone.
[Personal training] Examples of AI x sports utilization
The following two are introduced as “examples of AI x sports utilization in personal training”.
- Fitness gym “FURDI” that provides training suitable for individuals
- Food training app “food coach”
I will explain each.
⑪Fitness gym “FURDI” that provides training suitable for individuals
FURDI is a non-contact, women-only AI fitness gym where a personal trainer creates an original program for each user, and a menu according to that program can be exercised with the guidance of an AI trainer displayed on a large screen. is.
Fadi has three points.
- Home training possible
- View exercise score
In this way, the results of training are displayed as points, so even beginners can enjoy it as if it were a game.
In addition, it is not uncommon for gyms with exclusive trainers to charge more than 100,000 yen per month, but at Fadi, we have realized a monthly fee of 6,980 yen (excluding tax) by incorporating both AI trainers and human trainers.
⑫ Diet training app “food coach”
food coach is Japan’s first AI-equipped meal training app developed by Shigakukan University, which has nurtured the strongest wrestling team.
Since it has 100,000 meal data such as home cooking, convenience stores, family restaurants, etc., you can easily calculate the nutritional value by selecting the food you ate from the list.
In this app, AI analyzes detailed data such as “weight”, “body fat”, “muscle mass”, “sports”, “position”, etc., and visualizes the excess or deficiency of nutrients by graphing and scoring.
In addition, we will consider conventional snacks as ‘complementary food’ and propose snacks to compensate for the lack of nutrients, and propose meals suitable for pre-match and post-match recovery from fatigue. The health app is packed with features that were not there.
The future of AI x sports
In the future, it is expected that the introduction of AI will expand in sports. By predicting play and match results by AI, there is the possibility that the game itself will change, such as eliminating unnecessary moves and tactics.
In addition, spectators will be able to enjoy sports with increased entertainment while viewing the data they want, so it may be possible to enjoy watching sports from a variety of perspectives.
Due to the influence of the Tokyo Olympics and Paralympics, AI technology in the sports industry will show major changes in the next few years. In any case, AI is already closely related to sports.
This time, we have explained AI utilization cases in the sports industry by dividing them into different situations. How was it?
By getting along well with AI, more efficient training becomes possible. Let’s understand the merits and demerits of AI introduction and use it appropriately.
I would be very happy if the knowledge that you could not grasp about AI could be clarified, even if just a little.