mayadebanjo/premier_league_analysis — explained in plain English
Analysis updated 2026-07-25
Explore an interactive Power BI dashboard to discover Premier League trends across 25 seasons.
Run SQL queries in PostgreSQL to analyze match results, goals, referees, and team statistics.
Examine Arsenal's performance data, including points per season and records against top rivals.
Learn how to build a data analytics project from data cleaning to SQL queries to visual dashboard.
| mayadebanjo/premier_league_analysis | 00kaku/gallery-slider-block | 04amanrajj/netwatch | |
|---|---|---|---|
| Stars | 0 | — | 0 |
| Language | — | JavaScript | Rust |
| Last pushed | — | 2021-05-19 | — |
| Maintenance | — | Dormant | — |
| Setup difficulty | moderate | easy | moderate |
| Complexity | 2/5 | 2/5 | 3/5 |
| Audience | data | general | ops devops |
Figures from each repo's GitHub metadata at analysis time.
Requires installing PostgreSQL and Power BI Desktop, plus downloading the Kaggle dataset to load the database.
This repository contains a data analytics project focused on 25 seasons of English Premier League football, from the 2000/01 season through 2024/25. The project uses match results and statistics from Kaggle, covering roughly 9,500 matches. The data includes details like match dates, teams, goals scored, referees, shots, cards, and corners. The creator built the project using PostgreSQL for storing and querying the data, pgAdmin for running SQL queries, Excel for initial data cleaning, and Power BI Desktop for building the visual dashboard. The dashboard itself is split across three pages. The first page gives a broad league overview, showing summary numbers like total goals, total clubs, and average goals per match, alongside charts for goals by season, match result distribution, and top scoring or conceding clubs. The second page digs into match dynamics, looking at how games unfold. It covers home versus away goal averages, how often half-time leaders go on to win, which half produces more goals, and the most common final scorelines. The third page is dedicated entirely to Arsenal, examining their performance across the same 25-season span. It tracks their points per season, goals scored versus conceded, home and away records, and how they have fared against their top five rivals: Chelsea, Liverpool, Manchester United, Manchester City, and Tottenham. The project also highlights several findings from the analysis. Arsenal are the highest-scoring club in the dataset with 1,809 goals. Home teams win about 46% of matches. Over 55% of goals are scored in the second half. The most common scoreline is 1-1. Teams leading at half-time win 80% of the time. Arsenal's best season was 2003/04 with 90 points, and their strongest rivalry record is against Tottenham, with 23 wins from 50 matches.
A data analytics project exploring 25 seasons of English Premier League football, using SQL queries and an interactive Power BI dashboard to reveal trends across roughly 9,500 matches, including a deep dive into Arsenal's performance.
The explanation does not mention a license for this project, so it is unclear how the code and dashboard can be reused or shared.
Setup difficulty is rated moderate, with roughly 30min to a first successful run.
Mainly data.
This repo across BitVibe Labs
Verify against the repo before relying on details.