Cricket world cup analysis

​Overview​

This project analyzes historical One-Day International (ODI) cricket data to derive insights about player performances, team achievements, and match outcomes. Using datasets of batsmen, bowlers, and match results, I built interactive dashboards in Power BI to visualize key statistics and trends in cricket. The project demonstrates my proficiency in data wrangling, visualization, and storytelling with data.

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Datasets Used

1. Batsman_Data.csv: Contains performance metrics of batsmen, such as total runs, number of boundaries, and centuries.

2. Bowler_Data.csv: Includes bowling statistics like wickets, overs bowled, and economy rates.

3. ODI_Match_Results.csv: Details match outcomes, including scores, margins of victory, and participating teams.

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What I Did?

• Data Cleaning and Preparation:

  • Removed inconsistencies and duplicates in player and match data.

  • Normalized datasets for easier integration and analysis.

• Data Analysis:

  • Identified the top-performing batsmen and bowlers using aggregated metrics like total runs, highest scores, and wickets taken.

  • Calculated team statistics to measure win/loss records and dominance over other countries.

• Data Visualization in Power BI:

  • Built interactive dashboards showing key insights:

    • Top Players: Highlights of highest scorers (e.g., Virat Kohli with 10,843 runs) and wicket-takers (e.g., Lasith Malinga with 322 wickets).

    • Team Statistics: Win/loss records and largest winning margins by country.

    • Performance Trends: Graphs of runs scored and wickets taken by top players.

    • Match Outcomes: Distribution of match results with visualization of winning margins.

• Power BI Features Used:

  • Slicers for interactive filtering (e.g., by batsmen, bowlers, or teams).

  • Line and bar charts for trend analysis.

  • Pie charts to visualize the distribution of results.

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What I Learned

1. Power BI Skills:

   • Created dynamic dashboards with slicers and drill-through capabilities.

   • Learned to optimize visualizations for storytelling.

   • Gained experience in publishing and sharing Power BI reports.

2. Data Insights:

   • Learned how to analyze cricket performance data effectively.

   • Discovered trends in team performances and individual player achievements.

3. Problem-Solving:

   • Tackled challenges like handling missing data and integrating datasets.

   • Improved data modeling skills by creating relationships between datasets.

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Key Highlights

1. Top Performers:

   • Batsman: Virat Kohli with 10,843 runs.

   • Bowler: Lasith Malinga with 322 wickets.

2. Team Achievements:

   • India with the highest number of matches played and wins (e.g., 663 total matches).

   • Australia’s dominance in terms of matches won with a high win ratio.

3. Interactive Insights:

   • Largest victory margin of 95 runs highlighted.

   • Detailed country-wise analysis of performance metrics.

4. Visual Appeal:

   • Clear and concise visualization of trends and comparisons across players and teams.