What do AI and sports have in common? In the eyes of futurists, a lot. Some see sports as a way to test new methods for AI to interact with humans.
It can be implemented on the ground, and you can also see the use of AI and algorithms if you watch esports. However, some sports channels are geo-restricted. To learn how to unblock such sports channels in your country, read out beIN Sports TV guide in NZ.
From improving training techniques to providing insights that can help athletes improve their performance to even guiding referees regarding game decisions. AI is significantly impacting the world of sports.
Here are 7 groundbreaking examples of how AI is changing sports as we know it.
Training and Coaching
With AI entering the picture, trainers and coaches no longer have to rely only on their subject-matter expertise and experience.
Instead, they can coordinate their plans and strategies with various data to increase player efficacy and boost match-day preparations.
Using AI that analyzes forward passes, penalty kicks, and other activities in various sports, using high-speed film cameras, real-time film, and wearable sensors, coaches make strategic decisions before, during, and after games.
They can change their tactics and methods to benefit from their opponents’ playing styles and weaknesses by utilising algorithms to learn about the highs and lows of their teams using statistics and graphics.
Using this study of players, coaches can develop training strategies for their teams that are more productive.
However, players’ techniques, performances, and forecast modelling significantly impact when creating plans for athletes.
Additionally, using AI algorithms facilitates player scouting and match preparation.
Player performance has never been better, thanks to artificial intelligence. For instance, tracking and analysing human movements is done via computer vision.
A study by Research and Market points out that Individual and team sports performance would increase by an average of 17% and 28%, respectively.
All sports, including football, tennis, cricket, and golf, are subject to this. For example, basketball players’ skills are assessed using Computer Vision and Machine Learning through apps like HomeCourt, giving them a good foundation for advancing.
The cameras’ data collection results will be the players’ collective spatial-temporal trajectories. A sports expert can learn much about a player’s skills and performance from their player trajectories.
The reliable tracking of performance indicators helps the athletes identify their areas of greatest potential for success and those where they still have room for improvement.
Streaming, Broadcasting, Journalism, and Other Forms of Media
The sports narrative appears to be about to transform thanks to AI. AI has significantly impacted how viewers see sports and have altered the world of athletes and people involved. Also, you can check out the Esports and sports in New Zealand.
Learning algorithms automate various video production tasks. AI is now being used to provide accurate reports explaining significant occurrences, present statistics and facts, keeping the reader interested by keeping the essential emotion for the recent hundreds of sporting events.
Videos of events are currently being created using AI for sports marketing purposes. For example, using an AI-based algorithm to identify the top highlights from a game, the media may reduce their efforts. However, this process could be laborious and take a while to complete manually.
Fitness, Health, and Safety
It is well known that AI has transformed the healthcare sector in several ways and that the sports sector is now benefiting as well.
When it comes to sports, where physical health and fitness are crucial, AI’s extraordinary prognostic and diagnostic abilities may also be utilised.
Teams are progressively implementing technological advances in player healthcare to guarantee their players’ health and fitness.
Wearable technology is used to track athletes’ physical parameters and motions during practice to keep tabs on their overall health.
Players regularly undergo physical examinations that employ artificial intelligence to monitor a range of health factors and player activities to assess their fitness and even spot early indications of musculoskeletal or cardiovascular difficulties or stress-related ailments.
To detect signals that players are forming, AI technologies are employed to analyze the stream of data that wearable devices receive in real-time.
This enables athletic teams to maintain the condition of their most valuable assets throughout lengthy competition seasons.
Player Hiring and Scouting
Artificial intelligence can be utilised in the sports sector to assess the performance of prospective recruits.
Sports teams are using individual performance data more frequently to determine the potential and fitness of athletes.
Before deciding to invest in a player, numerous artificial intelligence, big data, and machine learning technologies can assist in tracking their performance and previous statistics (passes completed, runs made, goals scored, and so on) to evaluate their future potential.
ML algorithms evaluate players’ talents and their total potential to score them in various areas. In addition to tracking player movements and body alignment, teams can use it to discover specific features that can predict future success.
It can also be utilised to evaluate player market valuations to make the greatest offers when hiring new personnel.
This can also be advantageous for athletes, as the use of artificial intelligence-based technology reduces discrimination during the hiring and facilitates the identification of hidden talent, particularly in regions where a given sport is not highly popular.
Those who bet on sports have been attempting to process a ton of information in an effort to forecast the results of upcoming games and earn a big sum of money for years.
Researchers have looked at the winners, serves in tennis, and other minute details to predict the outcomes.
In the end, a person cannot accurately anticipate enough games to make a million dollars, nor can they handle the amount of data an algorithm can. The constraints of being human always constrain them; hence most will never become rich.
AI is also unable to estimate every single match’s result correctly. But a forecasting algorithm can come far closer.
Tops sports teams were still having admission delays in 2021. So following the start of the game, thousands of Southampton FC supporters were left waiting outside and had to be reimbursed.
At major sporting events, it is not unusual for fans to experience difficulty entering stadiums in time. Indeed, that has been going on for years. But, unfortunately, nothing could fix the problem till today.
For instance, Columbus Crew uses facial recognition technology to let spectators enter the stadium. Fans can post a picture of their faces with the barcode for their game tickets using Wicket’s facial ticketing platform.
The stadium’s crowd density is being monitored by computer vision, and staff members are receiving alerts when certain areas become overloaded.
This dramatically improves efficiency and avoids traffic jams at stadium entry. Additionally, it will be beneficial in luring COVID-averse fans back into stadiums who don’t want to wait in long lines.
Additionally, an analysis can predict how many people will attend and when they will likely appear. Organising goods and food in this way makes it easier to meet demand.
Whether you’re a lifelong sports fan or just getting into the game, plenty of AI applications can help make your experience more enjoyable.
From predicting the outcomes of games to helping you improve your skills, these seven examples should serve as a helpful introduction to the realm of sports-themed artificial intelligence.