- by Shray Gandhi (PAP Cohort-2)
Introduction
Artificial Intelligence
is changing the sports industry by improving performance, improving fan
engagement, and management. From player analysis to injury prevention, AI has
been playing a huge role in modern sports.
An Image taken from Rocketmakers
1. Player Performance Analysis
AI collects data of the players past performances and it uses this data for machine learning or ML. AI also tracks the players heartbeat and other vitals , together with all of this data AI can find out the players' strengths and weaknesses. Video analysis using AI helps players improve their techniques and gives them precise feedback to improve skills.
2. Injury Prevention and Recovery
AI is used to predict potential
injuries by analysing an athlete's movement and workload. ML models recommend
specific training adjustments to prevent injuries. AI also helps in the
player's recovery after an injury. AI helps to track the rehabilitation state
and monitor the players in real time.
3.
Game
Strategy Optimization
Teams use AI to analyse opponents'
tactics and predict their moves. AI processes historical data to identify
patterns and suggest the best strategies, helping coaches make beneficial
decisions during games. This is very highly applicable in racing sports such as
Formula 1, Nascar, etc. It helps the teams to decide on which type of tyres to
use and when to take a pit-stop. AI also helps them to make more effective
strategies against their opponents by analysing them.
4.
Referee
Assistance and Decision-Making
AI helps to reduce mistakes in
judging through various technologies. These systems use computer vision to
analyse the match and help the referees to make precise decisions. Apart from
this AI has many applications in tracking player movements, identifying fouls,
and reducing errors.
Cricket : Hawk-eye and ultra-edge,
Football : VAR and offside, Tennis: Hawk-eye
5.
Smart
Training Programs
AI-powered training systems are used
to create personalized workout routines for athletes. These programs adjust
exercises dynamically to maximize performance and reduce the risk of
overtraining.Training tools made by AI also use motion tracking to suggest form
corrections and help athletes train more efficiently. AI analyses the players
strengths and weaknesses helping them to develop specific skills that help to
improve their performance.
6.
Scouting
and Recruitment
Creating teams that are balanced and good is a very hard task. Many
selectors had to work hard to make the team balanced, however now AI can do all
of this faster and better and hence improving the teams overall performance.
Machine learning models compare emerging talents with established players,
helping teams make data-driven recruitment decisions. AI-based scouting
platforms can analyse thousands of players worldwide, ensuring the best talent
is identified.
7.
AI
in Sports Equipment Design
AI assists in designing sports gear,
such as running shoes, helmets, and tennis rackets. By analysing biomechanics
and material properties, AI helps create safer, more efficient equipment.
Simulations test new materials and designs before physical prototypes are made
helping to reduce the cost and waste of materials.
8.
Virtual
and Augmented Reality in Training
VR and AR simulations help to make realistic environments that the athletes can practice in. These tools improve decision-making and reaction times by letting players experience different game scenarios. AI also creates personalised VR training to simulate specific situations.
Specific Uses of AI per Sport
Formula 1
AI is a huge component of Formula 1 or F1. It is used for the race strategy to the tire and the pit stop strategy. In sports like F1 the aerodynamics of the car is very important and AI helps to run various tests that make sure that the car is optimal for the race.It also analyses the cars data in real time to help in fuel efficiency
Football
AI has several applications in football. They include strategic decision making, preventing injuries to the players and in officiating. It is mainly used for officiating as it uses techniques like offside detection and VAR.
Cricket
AI is mainly used in officiating in cricket. It is used to check for lbw or leg before wicket and ultra-edge. One example is the str8bat that helps the players in training by analysing their strokes.
Cycling
It helps in rider positioning, aerodynamics and maintaining hydration levels.
Future Applications of AI
VR and AR experience
Fans can watch the game from different views and perspectives. For example, the spectators can see the game from the players perspective or see the stats of each player while the match is going on.
Referees
In the near future AI powered referees will be widely used so as to reduce bias and errors while making decisions in the game.
Stadiums
As AI grows and develops soon the ticketing process , the stadiums, the crowd management and the security will all be handled using Artificial Intelligence.
AI in Paralympics
AI can be used to create personalized training equipment and sports gear for the disabled.
Recent Developments of AI in sports
Paris Olympics
The 2024 Paris Olympics had a huge amount of AI used in it. The entire event was integrated with a large amount of applications of AI.
Badminton Shot Prediction
Some researchers recently developed a network to predict the shot that will be used by the opponent and the type of shot. This network is called the Multi-Layer Multi-Input Transformer Network (MuLMINet). This is vital for coaching, strategic planning and for better training programs.
Tennis
AI has been extensively used in tennis . AI powered sports narration has been used in major tournaments such as US open and Wimbledon. This helps to give the fans good content and reduces the time.
Conclusion
AI is changing sports by improving performance of the players, their safety, and engagement of the fans. It helps athletes train smarter to improve fan experiences, and AI is truly changing the way sports are played and enjoyed. As AI advances, its impact on sports will grow and benefit the sports industry.
Sources
The sources used to make this article were
● Rocketmakers
● Intuz
● LinkedIn (Infosense AI)
● Appinventiv
● Markovate
Links
httDs://www.rocketmakers.com/blog/ai-in-sDorts httDs://aDDinventiv.com/bloq/ai-in-sDorts/
https://www.intuz.com/blog/ai-in-sDorts
https://markovate.com/blog/ai-in-sports/
httDs://www.linkedin.com/Dulse/aDDlications-artificial-intelligence-sDorts-industry-infosense-a
