This Python script analyzes Indian Premier League (IPL) data, focusing on various aspects such as player performances, match outcomes, and match locations. It includes tasks like determining the frequency and top players of Man of the Match awards, examining match results and toss wins, and visualizing data through histograms, bar plots, and pie charts.
Tasks Completed Obtained frequency of Man of the Match awards and identified top players. Generated a bar plot for the top 5 players with the most Man of the Match awards. Analyzed frequency of match results and toss wins for each team. Extracted records where a team won batting first and created a histogram for runs distribution. Investigated number of wins after batting second and visualized it through bar plots and pie charts. Explored number of matches played each season and in each city.
Note This project provides insights into IPL match outcomes, player performances, and venue statistics, aiding in understanding trends and patterns in the league over different seasons and locations. Further analysis or machine learning modeling can be conducted based on the insights gained from this exploratory analysis.