There is no denying that cricket is a popular international sport that has millions of fans and sites dedicated to it as stumped.app and etc. all over the world. The teams use all techniques and methods available to increase their chances of winning. Players train for years to become professional. Nevertheless, there are techniques besides training that can improve the team’s chances against the competitor. In this article, we will focus on data mining performance analysis in cricket as a tool for a successful match.
First of all, it is important to define data mining. It is a scientific method that analyses a big amount of data to find some patterns. In sports, including cricket, it is mainly used to select players and put them in the best position to achieve the best results. Data mining and analytics can also be used to predict game scores.
How Does It Work
Well, it is a complex question that cannot be answered in one sentence. For example, a coach wants to decide which player plays best in which position. To exclude any biases, data mining analysis can be used. To do that, certain algorithms are used. One needs to consider all data available: the scores of the player, the position, the state of health, the team play, the place of the game and others. As you can see, analyzing a big amount of data and considering each aspect possible can give great results. This can also be used to develop a strategy for matches with the opponent teams.
Data mining and analytics can also be used to predict the results of the game by other parties besides the teams itself. Considering the fact that cricket is a multi-billion-dollar industry, there will be thousands of people trying to bat on a certain team’s win or lose. In this perspective, professionals often use data mining to predict the results of the game. There have been numerous researches that aimed at determining the possible scores and results through data mining algorithms and have successfully done it. For example, a group of analytics used batting and bowling potentials of the players using their scores and statistics during the career. After analyzing that information, they had a pretty solid understanding of the strength and potential one team had over the other. It is also important to realize that not only players’ performance should be used in analytics and data mining. Professional analysts say that run rate, venue of the game, and toss should be always taken into account.
By taking this into account, it becomes clear that data mining and analytics are great tools. As we have already stated, it is used the most by batting institutions and people who make bats to predict the results of the games. For this very reason, before any important game, hundreds of websites try to predict the scores and the results of the match using the data mining method. For example, the Ashes tournament is happening right now between the teams of England and Australia. After Steve Smith being ruled out due to the concussion, many data analysts argued that despite 2 wins in the first two tests, there is a chance that Australia might lose playing on the foreign field under a lot of pressure. That is exactly what has happened: England managed to turn things around and beat Australian cricketers.
To sum everything up, data mining and analytics are powerful tools that can be used efficiently in sports to predict the results of the game and analyze the player’s performance to put them in the best possible position.
