To analyze the performance of various teams historically in the Indian Premiere League, popularly known as IPL, including the number of matches played, winning percentage, venues where most matches have been played, runs per over rates, yearly run distributions, etc. The dataset includes the data of all matches from 2008 to 2020, a decent yet complete data range.
Team performance is visualized graphically using the Plotly library in Python to render interpretation efficiently. Performance data using visual analysis help select players for future matches and provide additional information about the player and team profiles.
The aim is to provide detailed insights numerically and graphically to understand the tournament's history and make data-driven decisions like predicting the winning side of a particular match in the future with an acceptable accuracy solely based on the parameters mentioned above. We realize that the winners are decided by the squad playing at that time, but this is a very volatile parameter and can be ignored for now.
This analysis of a particular match winner can also help predict the possible winner of a particular season.