Dahel Consultant Techies Internship: This is a project that entails the analysis of a chess game. (The picture below is gotten from chessbazaar.in Website).
Disclaimer: This is not a real company as we know this is a dataset compiled by Dahel Consultant Techies for Internship purposes.
This is chess game performance analysis. It is done by analyzing data from the chess game table which comprises of ranking_date, rank, name, title, country, rating, games, and birth_year fields. I used Excel to get an overview of the dataset before importing it into Power BI where the actual analysis was carried out.
The goal of this analysis is to know:
- How many games were played?
- How many players played?
- How many countries participated in the game?
- What is the average age of the players?
- Top 5 highest ranking players?
- Countries with the most players?
- Player that played the most game.
- What is the correlation between players age and their rating?
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Power BI concepts like:
- Creating key performance indicators (KPIs) and other business calculations
- Developing general DAX calculations that deal with text and numbers,
- Performed advanced DAX calculations for solving statistical measures and other mathematical formulas,
- Data Modelling,
- Measures,
- Filters,
- Tooltips,
- Page buttons,
- Data visualization
The dataset for the work is gotten from Dahel Consultant Techies. It consists of 11,512 records and 8 fields of data. I studied the dataset well to gain proper insight into the dataset. You can find a link to download the dataset here:
Step 1:
- After downloading the dataset, I imported it POWERBI.
Step 2:
- It loaded the dataset authomatically in Power Query Editor but there was no cleaning needed because it was already a cleaned data.
Step 3:
- The data type year was changed to whole number
Step 4:
- A new column was created for Age of the player as at 2024
Step 5:
- After checking the columns, it was loaded into POWERBI for visualization
Several expressions and functions were made to arrive at the desired KPI or Metrics. I arrived at a report with a single dashboard consisting of different visuals such as bar chart, doughnut chart, line chart, slicer, and KPIs, giving the summary of the insights gained into the game performance.
The dashboard conveys information about the following key areas:
- Number of games played
- Number of players played
- Number of countries participated in the game
- The average age of the players
- Top 5 highest ranking players
- Countries with the most players
- Player that played the most game
- The correlation between players age and their rating
Summary of the insights gained into the chess Game performance:
- The total games played was 121,868 and 346 players from 64 countries participated in the game.
- There is no correlation between player’s age and their rating
- There was four different titles (f, m, g and wg)
- The average age of the player as of 2024 is 44 years old.
- Russia had the highest number of players in the game followed by Ukraine and then China.
- Tiviakov Sergei from Netherland played the most gamed followed Van Wely Loek also from Netherland.
- Russian played the most game followed by Ukraine.
- Top ranked players are Anand Viswanathan, Carlsen Magnus, Kasparov Garry, Kramnik Vladimir, Topalov Veselin.
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Choosing Anand Viswanathan, Carlsen Magnus, Kasparov Garry, Kramnik Vladimir, Topalov Veselin, as they are the top ranked players, will yield more wins.
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Tiviakov Sergei from Netherland who played the most gamed followed Van Wely Loek also from Netherland should be given more preference by the chess selecting teams inorder to triumph more.
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As for there is no correlation between player’s age and their rating from the analysis above, player's age should not be a limiting factor to express their dexterity.
I am open for entry-level to mid-level data analyst role.