Now data analysis is very necessary to win every game.
The use of data analytics has increased over the last half decade.
The importance of data analysis has increased in every sport due to technology. All important decisions are made after a comparative study of gut feeling as well as present data. For example, A.B. If a batsman like De Villiers is capable of playing shots at all corners of the field in T20 cricket, what kind of field will the captain of the bowling team set? How many steps does Neeraj Chopra have to take to throw the javelin the farthest? What should be the angle of the shoulder when throwing a spear? How often does a goal-scoring opportunity arise during a game of football? Speaking of cricket, the use of data analytics has increased over the last two and a half decades.
After studying the strength and weakness of the opposing team before the tournament, all those aspects are studied while formulating the strategy. After a thorough study of hundreds of hours of televised footage, the team is given all the information on which bowler to attack and which batsman to bowl at the beginning of the innings through the important data generated from it.
Each team in the IPL has its own data analysis team, which helps the team management to make important decisions by constantly studying the conditions, performance and scoring patterns during the match. Take the example of Chris Morris. The Rajasthan Royals have bought Morris for a whopping Rs 16.25 crore as the batsman has played the most number of false shots in Chris Morris' overs during the powerplay of the last three seasons of the IPL, with an economy of 7.65 during the same period.
The analysis reveals that if Chris Morris and Joffra Archer are bowled during the powerplay, the chances of taking a wicket are greatly increased. Data analysis is used extensively not only before tournaments, but also to buy or drop players into auctions. As such, each franchise has 25 players. Thus, ball-by-ball tracking of 200 players is present in the IPL alone. Apart from that, the player's annual data at the time of purchase is also now available.
A sample of how deep the information is: Manish Pandey can easily play a bouncer thrown at a speed of 135 kmph, but his scoring shots decrease if the speed is 140+. So if the wicket falls and bowling is done at 140, the team management will send a batsman to the crease instead of Manish Pandey who can play such bowling easily. Apart from bowling and batting, other data points are also used.
Gathering different information such as ground details, boundary length, type of pitch, type of soil used in the construction of the pitch, wind speed and direction if there is a river or beach ground, bowler height, release point, over the wicket or angle of round the wicket. Strategies are created by elaborating at different levels.
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