Identifying the next big star athlete has always been a combination of art and science, but artificial intelligence, which is altering everything from business to healthcare, is making inroads in professional sports as well.
Computer vision, machine learning, and other AI techniques employ algorithms to examine player performance statistics, game recordings, and data from different sensors to find potential that coaches and scouts would otherwise overlook. And, because the computers scan through data far quicker than people can, they provide teams with significantly more detailed information about players than was previously available.
Artificial intelligence is a broad concept. At its most basic level, it entails creating “intelligent” computers that, like people, can acquire and use knowledge, information, and professional abilities to solve problems. Data analytics, predictive analysis, machine learning, pattern recognition, and, at the absolute least, a simulation of sentience is all part of it. Supercomputers combine all sorts of data to predict league winners, and while they do not always make correct projections, they account for some rather sensible arguments.
However, machine learning, artificial intelligence, and data science have advanced dramatically. We can now track an athlete’s activity, and health data like never before, thanks to the advent of wearable technology and RFID tags. Similarly, developments in computer vision have enabled computers to extract an increasing amount of data from each second of a video broadcast. As AI technology has progressed and has its application in professional sports and leagues like the Premier League, you can click here for early next year predictions.
More data, more power
Football, hockey, basketball, and baseball are among the sports that are currently adopting artificial intelligence to enhance traditional coaching and scouting.
Scouts in football, in particular, have historically relied on statistics to assess players. Teams are increasingly using AI to evaluate a growing variety of player data.
Premier League big guns take zero chances when it comes to recruiting — there is too much money on the line to make a mistake. Data provided by companies like Opta has remained valuable over the years, but the introduction of AI in sports gives more. While on-field or on-screen scouting cannot be replaced, data evaluation through AI-powered structures is a breakthrough for Premier League managers.
Modern scouting operations are exceedingly complex, involving worldwide talent scouting networks, teams of analysts, and massive volumes of data and video.
Scouting has gotten more complex as the sport has become more professional, the globe has become more international, and technology has evolved. A typical organization consists of global talent scouts and in-house analysts sifting through massive data and video material.
Artificial intelligence scouts
Similarly, youth setups are becoming more data-driven, with clubs tracking young players at each age group to determine who makes the cut. Nonetheless, there are fears that some players are slipping through the net, particularly during a pandemic that has disrupted soccer at the grassroots level.
Lower-league teams lack the scouting resources of their more wealthy rivals, and certain regions of the world are just too far away to be covered. Some prospects who were turned down by one young academy may be deserving of a second shot, while others may have been scouted but were subjected to unconscious bias.
A new tool claims to revolutionize player scouting, much how technology, notably Artificial Intelligence (AI), has helped democratize other aspects of soccer, such as coaching and match analysis.
AiSCOUT allows anybody in the globe to record oneself undertaking trials and training exercises and then use video recognition technology to evaluate their performance. The player’s technical, physical, cognitive, and psychometric abilities are then revealed to professional scouts. AiSCOUT, meanwhile, connects with a variety of other analytics systems now in use at professional teams.
Algorithmic injury predictions
The most difficult issue for any coach is finding that 1% in marginal performance increases. This is where artificial intelligence comes in. Artificial intelligence (AI) can be applied to keep a player in peak form or forecast when he is going to get injured. In reality, this technology is quickly becoming an important part of the game. For example, the new Zone7 artificial intelligence software uses data from medical profiles, fitness evaluations, and wearables to predict athletes’ danger of injury. The Zone7 AI program is already in use by more than 50 clubs across the world. The users are European football clubs, NCAA teams, MLS clubs, MLB franchises, and national Olympic teams. Many clubs, however, choose to remain secret to maintain any competitive edge that the program may bring.
The system displays green, yellow, and red signs for a player’s daily risk levels, allowing a coach to determine whether or not to reduce the intensity of a player’s training sessions to reduce the chance of injury. The system has already documented and analyzed over one million training sessions and injuries, and when more athletes are added to the database, Zone7’s software will become even more advanced. The technology has already attained 95% accuracy, according to the Zone7 website, and has resulted in a 75% reduction in injuries.
