(5 minutes read)
There are very few things in the world that we cannot quantify. Everything else can be predicted by data mining and artificial intelligence.
In sports, we track a lot of quantitative elements, making it ideal for the use of artificial intelligence.
Applied artificial intelligence in sports sis into 4 categories:
- Athlete research and acquisition
- Coaching and performance analysis
- Maintaining the health and fitness of athletes
- Broadcasting and advertising
Each of these topics deserves an article for itself, but in this article, we will stick to the basics of each of these. For a deeper dive, feel free to send a message about the topic you would like to know more about.
Athlete research and acquisition
As it is still impossible to quantify the desire to win, courage or determination. That means there is no way to quantify the spirit of the person. But we can quantify their effect and impact.
Sports teams are using individual results as a measurement of potential. But, recruiters can’t rely only on measurable metrics such as lane running, goals or number of wins. They also need complex metrics that take into account many factors. In the past, this relied on their experience and knowledge. Humans are perceptually limited and that can prevent them from tracking complex metrics.
With big data and artificial intelligence, sports decision making is becoming easier and reliable.
Artificial intelligence can analyze and interpret several thousand metrics, which is better than humans. That gives a more reliable estimate of future performance and development.
Artificial intelligence can track historical data and predict the development of athletes. Such analysis is crucial before investing in or acquiring them. It is also possible to assess the market values of players, now and in the future.
Coaching and performance analysis
As mentioned with recruiting, general metrics such as goals and wins are not the best way to analyze performances, individually or collectively. To evaluate the performance of athletes, coaches and analysts need to consider many metrics that evaluate individual players and teams, and how they affect each other. Such analysis enables them to identify, at the individual or collective level, the segments of the game in which they need to improve.
As each athlete is scored differently depending on his / her position and role, artificial intelligence may highlight correlations that are not apparent from the general data. Cohesion and cooperation are more important in team sports than individual performances. Cohesion factors are most difficult for human observers to spot. With artificial intelligence, we can correlate between qualitative traits and quantitative variables. And then predict qualitative values by predicting quantitative variables.
Looking outwards, with artificial intelligence, we can analyze the opposing team. We can use their historical data to use to prepare for the challenge ahead. In the past, teams used to review the footage of the opposing team as part of the preparation. Now we can use AI to summarize the strengths and weaknesses of the opponent’s team as readable data. Such analysis can offer an overview of games that replace video content. This can find in-game specifics that are not visible at first glance.
Maintaining the health and fitness of athletes
The introduction of AI is changing the healthcare industry. Opportunities for predicting and analyzing health conditions can also be applied in sports. As the physical and mental condition is crucial to sports, teams invest a lot in the development of their athletes. Diagnostic tests use artificial intelligence to find problems through the correlation of health factors. The appearance of any problems, from the first signs of fatigue or stress to serious problems, can be identified early.
Teams of doctors can respond in time and adjust the training or diet regimen if needed. Such a proactive approach to preventing health problems allows players to reach their peak. And to keep at peak performance for as long as possible without the risk of serious injury or illness.
Any analysis of fitness and performance in training uses wearable technology. These track the condition of athletes. As today almost every device connects to the internet, continuous analysis of such data as:
- Distance passed using GPS position
- Calories spend
- Active minutes
- Time and quality of sleep
- Blood pressure
This can help in the early identification of musculoskeletal or cardiovascular problems.
By using AI teams can ensure that their players are always at their best through competitive seasons.
Broadcasting and Advertising
It’s no secret that sport generates high incomes and that it can be better and advance quickly because of it.
Besides revolutionizing the sport for players, coaches and recruits, artificial intelligence can also provide the viewer with a new experience. Monetization of sports events, apart from tickets and branding, is based on pay-per-view and streams. In broadcasting, artificial intelligence can choose the right camera angle to observe the action. And make that decision in a fraction of a second. Artificial intelligence can even break the language barrier by generating subtitles depending on the language settings of the viewer.
With the advancement of technology, it is also possible to measure the level of excitement of spectators in gyms to allow advertisers to broadcast their ads at the right time, thereby increasing revenue.
There is no doubt that artificial intelligence is increasingly present in sports, and that its share will grow more and more from year to year. Even the outcomes will be more reliably predicted, further highlighting surprise and unpredictability. That human element is what made sports so popular in the first place.
As long as sports events remain the most important nonimportant thing in the world, owners and advertisers will find it a worthwhile investment. As long as it is profitable, the sport will continue to invest in new technologies. We are looking forward to such development, which almost always gets applied in other business segments.