This project is intended to show the activities of the NPFL (Nigeria Professional Football League), Nigeria's top-flight football league.By conducting an EDA (Exploratory Data Analysis) into the League, this project exposes the performance of NPFL teams in the 2018/2019, 2019/2020, 2020/2021, 2021/2022 seasons.
Some of the KPI's to watch out for include:
- Final League Position
- Total number of Goals Scored
- Average Goals Scored per Match
This project for the public most especially Sports analysts, Club owners, Club managers, League officials, Sports Journalists, Data Scientists, and Sports Enthusiasts with much recommendations for people aiming to get into the field of sports analytics, and also club managers that want to see how an interactive dashboard can give insights into the performance of their clubs.
The data was sourced by performing web scraping operations across several news sites, sports betting sites, blog sites, and wikipedia. The data was compiled together and published on kaggle, an open source platform for getting open source public datasets, for anyone intending to conduct further analysis on the dataset. The links to the dataset are: 2018/2019 Season, 2019/2020 Season, 2020/2021 Season, 2021/2022 Season.
The datasets were compiled into one CSV (.csv) file as worksheets and imported into PowerBI.
Before the dataset was loaded into PowerBI, it was first transformed.
- New Features were engineered from the existing features, and added to each of the data set [W, L, D, GF, GA, Ordinal Position].
- A new table called Teams was cretaed for analysis on the most consistent teams across all four seasons.
- The transformed data was then apllied to the visualization panel.
New relationships were created between the tables, and Teams was used as the relationship between all the tables.
- A measure table was created and Total Matches Played, Total Goals Scored, Avearge Goals Scored per Match were all calculated using DAX.
- Charts, Tables, and Cards were used to check for:
- Top Teams with most Goals in the Season
- League Standings
Check out my Medium Aritcle on the Insights gotten from my analysis: NPFL Analytics Insights
The data was published from the PowerBI environment and a link was generated for others to view and interact with the dashboard. Link to my dashboard: NPFL Dashboard
If you have any feedback, please reach out to me at: [email protected]
I'm a Data Scientist with experience in building end -to- end data analytics projects and machine learning models.
Introduction to Data Science : cognitveclass.ai
Data Science Tools : cognitveclass.ai
Top 50% AI and ML with Python Regression Hackathon : datasciencenigeria.org (ID for Authorization: DSNAI0009981)
Python (OOP), Data Analytics, Machine Learning, Features engineering.
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