Part – 4
Moneyballisation
The concept of Moneyballisation. Let us try to understand it by some examples to elaborate.
Moneyballisation is the term used to describe the application of data analytics and statistical methods to optimize the performance and efficiency of a team or an organization, especially in sports. The term is derived from the book and the film Moneyball, which tell the story of how the Oakland Athletics baseball team used sabermetrics to assemble a competitive team on a low budget.
Some examples of moneyballisation in other sports are:
– In football (soccer), teams like Liverpool and Leicester City have used data analysis to identify undervalued players, improve their tactics, and increase their chances of winning.
– In basketball, teams like the Houston Rockets and the Golden State Warriors have used analytics to emphasize the importance of three-point shooting, spacing, and ball movement, and to reduce the reliance on mid-range shots and isolation plays.
– In cricket, teams like England and India have used data analysis to improve their selection, strategy, and performance in various formats of the game, such as Test, ODI, and T20.
Some of you may be wondering that how the idea of Sabermetrics or moneyballisation is relevant and can be used in Indian context. Let us present two examples of its application one from the entertainment industry and other from politics.
For an ongoing franchise like movie Don, the producers have to decide whether to opt for a star with a larger fan base who is demanding higher fees compared to less known star but at a lower fees.
In politics while distributing tickets there is a definite possibilities of a candidate quitting the party if he is not allotted the ticket. Should the bosses take the risk of denying him the ticket or not? Questions like this at present are decided by experienced players on the basis of their gut feelings. However, data analytics of the various aspects such a voter or fan database is available, such questions may be answer more objectively using AI algorithms like Sabermetrics.
Concluded.