In recent times, the use of Artifical Intelligence (AI) has been increasing tremendously. The market value of AI is expected to reach $267 Billion Dollars by 2027 globally. AI is estimated to provide $15.7 Trillion Dollars to the global economy by 2030. As of today, about 37% of businesses and organizations have started to employ AI. (Source: dataprot.net)
We find the use of AI in our everyday life, for example, they are used in cars like Tesla; smart assistants like Siri or Alexa; navigation help like Google Maps; OTT recommendations like Netflix, according to the watch history of a user, etc.
But the most recent development where AI has found its use is in sports. AI is no alien to the field of sports and has largely impacted each of its areas.
One such area is cricket.
The impact of AI on cricket cannot be ignored in the recent past. From snickometers to DRS reviews, cricket has adopted the advancement of technologies in several ways and uses AI and Data Analytics on a regular basis to improve the game.
In this article, we tell you how AI is used in cricket. But before we dive into the how part, let us find out what AI is.
What is AI?
Artificial Intelligence, or commonly known as AI is a wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence.
AI mimics human intelligence to perform tasks faster and more effectively.
Artificial Intelligence is a method of making a computer, a computer-controlled robot, or a software think intelligently like the human mind.
AI is accomplished by studying the patterns of the human brain and by analyzing the cognitive process. The outcome of these studies develops intelligent software and systems.
Now that you know what AI is, let us find out how AI is used in cricket.
Use of AI in Cricket
Cricket is one of the most popular sports in the world and it keeps adding new dynamics to the game. All these dynamics have been either brought about by increase in competition or use of new tools. AI is one such tool that has completely transformed the game.
Here are some of the ways in which AI is being used in cricket:
Most bats that are used in international cricket are powered with a sensor chip and are known as ‘Batsense’. The sensor would generate data for every stroke a batsman plays. It has storage onboard to retain session information, and Bluetooth connectivity to enable real-time data transfer.
The sensor measures a variety of things like:
- Bat-speed when playing a shot,
- Power & twist of the ball hit from the bat,
- Quality of the shot.
2. Bowling Chips
Each ball in modern-day cricket is fitted with sensor chips which are called ‘smart balls’ and provide:
- Speed of the ball when it leaves the bowlers’ hand, and after it pitches,
- Length of the ball,
- Degree of turn and swing/spin,
The role of a third-umpire is extremely crucial to a match and they are given many tools to bring out the correct decision when the on-field umpire needs their help. Their Decision Review System or DRS is powered by AI and some examples of it are:
- Snickometer: Used by the bowling team to get a batsman out, the third umpire graphically analyzes sound and video to ascertain whether the batsman has edged the ball or not. This is a very common tool used by the third umpire and is broadcasted during the game on television as well. Nowadays, this is know as ‘ultra edge’.
- Hot Spot: Another technology which is for the bowlers’ assistance to determine whether the batsman nicked the ball. It is an alternative to Snicko. It uses an infra-red imaging system to analyze if the ball struck the bat before reaching the fielder.
- Hawk-Eye: A very popular technology named after its developer Paul Hawkins, Hawk-Eye is not only used in cricket but in several other sports like football, tennis, badminton, etc.
This unique technology is used by umpires in LBW (Leg Before Wicket) appeals. It uses ball tracking and displays a path of the ball to the wicket, the location of impact with the batsman’s leg, and whether the ball would hit the stumps or miss them. It can also the bowling length deliveries of a pacer and spin turn of a spinner.
4. Duckworth-Lewis Method
This is a relatively older method but still finds relevance in today’s game. The DL method is a mathematical rule used to find out results in games that are interrupted by rain or other unavoidable factors in the limited-overs format. This method takes two key factors into account:
- Number of overs remaining in the match, and
- Number of wickets lost by the chasing team
Complying with this method, if the game can be resumed – the target and overs are reduced, and if the game cannot be resumed – a winner is decided.
5. Match Analysis
AI is also used to predict and analyze certain outcomes, both before and during a match. This machine-learning model helps in analyzing:
- Venue/Pitch conditions,
- Predicted score of a team according to run rate,
- A batsman’s record against spin vs pace,
- Ideal bowling length of a bowler,
- Probable match-winner according to the status of the game, etc.
These are some of the ways where we can find the application of AI in cricket.
Impact of AI in cricket
AI has completely changed the game of cricket and has made it much more competitive. Apart from the ways listed above, the coaching staff takes the help of AI to measure the team’s performances by analyzing player data and statistics.
AI helps in the performance enhancement of players as it helps them understand their strengths and weaknesses. It gives them insights on how to work on their game and improve their performances.
Every team relies on AI & Machine Learning (ML) for key data and insights which they use to their best advantage. One can achieve so much through AI and with the advancement of technology, the involvement of AI in cricket will only be increasing.
In this blog, we have aimed to give you a brief on what AI is, how it has been used in cricket and how it is transforming the popular sport.
With the help of AI, one can get automated match predictions, match summaries, etc, and it has become a common tool in Sports Journalism as well.
Not only has AI transformed the way cricket is played, but it has also improved the way people watch it. The viewer experience has gone to a whole new level.
The different camera angles, broadcasting techniques used by third-umpires on television, display of interesting data and insights during the match, it has all made cricket a much more dynamic experience for the viewer. And we only expect this to get better!