Olympics Data Dive: Unveiling Performance Trends

INTRODUCTION

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• The Olympics are a premier international sports event uniting athletes globally, with a rich history dating back to ancient Greece. 
• Data analytics plays a crucial role in understanding and enhancing athletes' performance, training methods, and overall outcomes.
• This project employs Power BI for analyzing Olympic data, providing interactive visualization and advanced statistical modeling.
• The project aims to analyze athlete and country performance across Olympic events, identifying trends and correlations to inform sports management and training strategies.

OBJECTIVES

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• Explore historical performance trends.
• Study data analytics using tools such as Power BI
• Develop interactive dashboards for intuitive exploration.
• Utilize Python for statistical analysis and modeling.

WORKING

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Step 1: Collection of Required Data

• Utilized our newly constructed dataset ‘Olympics Legacy: 1896-2020’.
• It includes comprehensive data spanning 124 years of Olympics.
• It’s primary file has 12 features and 2,86,238 records.

Dataset Link - Olympics Legacy

all_athete_games.csv

Step 2: Dashboard Creation using Power BI

• Transform Data: Into a final dataframe by

  • Removing columns
  • Defining relationships / Merging
  • Other measures

• Analyzing Olympics data using various charts such as-

  • Table chart: Medal Tally
  • Ribbon chart: Age-wise Performance
  • Pie chart: Gender-wise participation
  • Cards for specific stats

Step 3: Python Analysis

• Performed some strategic analysis in python such as:
  • Merging files on the basis of specific features
  • Extracting summer olympics data
  • Calculating number and names of countries participated
  • Handling missing and duplicate values
  • One Hot Encoding of Medals
  • Grouping encoded data along with original on the basis of specific features
  • Calculating two different medal tallies with respect to accuracy

RESULTS AND VISUALIZATIONS

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Table Chart - Medal Tally for TOP 10 Countries

Ribbon Chart - Performance of Athletes on basis of Age

Complete Power BI Dashboard - Overview

CONCLUSIONS/OUTCOMES

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• Comprehensive Dataset Formation: Through meticulous exploration of 3-4 datasets, curated a comprehensive repository of Olympic data spanning various aspects, including athlete performances and other logistical details.

• Insightful Dashboard Creation with Power BI: Utilizing Power BI, transformed our analytical findings into interactive and visually appealing dashboards, offering stakeholders a user-friendly platform to explore and understand the intricacies of Olympic performance trends.

• Strategic Python Analysis: Conducted strategic Python analysis, including one hot encoding on medal columns and data deduplication, resulting in a 75% improvement in accuracy of country medal tallies.

FUTURE PLAN

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• Analyze data using Python in detail
• Create a user-friendly interface, like a web app.

FUTURE SCOPE

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• Analyze data through Tableau.
• Enabling dynamic and up-to-date analysis.
• Enhance predictive modeling capabilities to forecast athlete performances.

REFERENCES

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1. Pradhan, Rahul, Kartik Agrawal, and Anubhav Nag. "Analyzing Evolution of the Olympics by Exploratory Data Analysis using R." IOP Conference Series: Materials Science and Engineering. Vol. 1099. No. 1. IOP Publishing, 2021.
2. Asha, V., Sreeja, S. P., Saju, B., Nisarga, C. S., & Prasad, A. (2023, March). Performance Analysis of Olympic Games using Data Analytics. In 2023 Second International Conference on Electronics and Renewable Systems (ICEARS) (pp. 1436-1443). IEEE.
3. Abeza G, Braunstein-Minkove J R, S´eguin B, O’Reilly N, Kim A and Abdourazakou Y 2020 Ambushmarketing via social media: The case of the three most recent Olympic Games Int. J. Sport Communication1–25. 

TECH STACKS INVOLVED

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• Python
• Power BI
• Streamlit

TEAM THE BOYS

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Krishna Dubey (Data Collection, Dashboard and Analysis), Pankaj Kumar Giri (Data Collection), Nayandeep (Android)