To analyze IPL match data to identify trends, top performers, and key insights.
Data cleaning, pivot tables, data visualization, descriptive statistics, conditional formatting.
Imported and cleaned IPL data in Excel. Used pivot tables to summarize team and player performances, and created various charts (bar charts, line graphs, pie charts) to visualize trends. Applied conditional formatting to highlight top performers. Developed an interactive dashboard to present key insights.
Identified winnings with respect to toss decisions, best venues and player of the match stats. Also analyzed team performance over seasons, and discovered key trends in match outcomes by venue.
1.Data Collection:
Data source: kaggle dataset data format: XLSX File
2.Data Cleaning:
Remove duplicates, Missing values, Drop redundancies & Standardize date-format.
3.Data Analysis:
Pivot Tables: Create pivot tables to summarize and analyze the data.
Pivot table showing the number of matches played by each team. Win/loss records for each team on the basis of post-toss decisions.
Matches played at each venue. Win/loss records at different venues.
4.Data Visualization:
Using charts and graphs to visualize the data. Stacked column chart: winnings based on toss decisions. Donut chart: percentage of winnings. Bar stacked chart: Top venues with most winnings and matches. Tree map: Winners and their respective count of winninig titles.
Pivot table summarizing each team's performance by season. Chart showing the number of matches won by each team over different seasons.
Pivot table and chart showing the top 10 Player of match in the tournament.
Match Outcome Analysis:
Pivot table summarizing match outcomes by venue. Chart showing win/loss records for different teams at various venues.
5.Presenting Findings
Created a summary dashboard with key insights, including charts, pivot tables, and key statistics. Using slicers we enable interactive filtering of data (e.g., by season, team, player).
