On Day 2, the dataset was the English Women’s Football (EWF) Database.
The database contains three tables:
- ewf_matches contains all matches that have been played and has one observation per match per season.
- ewf_appearances contains all appearances by a team and has one observation per team per match per season.
- ewf_standings contains all end-of-the-season division tables and has one observation per team per season.
In Power BI, the following data model was used.
The Members and References tables were related to Expeditions using the Expedition ID. The Peaks table was related to Expeditions via the Peak ID field. A helper table, Sherpa_Tibetan, was created with two fields:
The ewf_matches table was related to ewf_appearances by the match_id field with a one to many cardinality. ewf_standings was related to ewf_appearances on a combination of season_id and team_id, also with a one-to-many cardinality.
The data story focused on Promotion vs. Relegation, a system which ensures that high-performing teams earn a place in the top division, while lower-performing teams drop to the Championship. This analysis was broken into three key sections:
- The Points Gap for Promotion & Relegation – Looking at average points for promoted vs. relegated teams across all seasons, the margin of safety across all seasons, and the distribution of points between promoted and relegated teams overall.
- Goal Difference Comparison – Analysing whether there is a disparity between goals scored vs. conceded, goal difference by season and season outcome, and goal differences for home vs. away games.
- Home & Away Win Performance – Evaluating whether play at home or away effects the win percentage across seasons, and an overall comparison between all teams promoted/relegated for their home/away win percentages.
Key Findings:
- Over the past decade, the Barclays Women’s Super League has seen more teams promoted than relegated, reflecting changes in league structure and competitiveness.
- Promoted teams consistently outperform relegated teams in points, goal difference, and win percentage, with a clear distinction between those moving up and those dropping down.
- However, recent seasons suggest a tightening competition, with promotion margins narrowing.
Author: Troy
Troy holds degrees in Science, IT, and Education. These have equipped him with a multidisciplinary foundation combining analytical thinking, problem-solving, and technical proficiency. During his graduate studies at CSIRO, where he analysed genetic sequence data and gene expression profiles as part of a broader research project, he developed a deep interest in uncovering insights through data. After several years as a STEM educator, Troy has transitioned back to being data-focused, bringing a unique perspective shaped by his teaching experience and ability to convey complex ideas effectively. His skills cover the entire data lifecycle, from data cleaning and analysis to creating effective visualisations that support decision-making. In his free time, Troy enjoys trail running and staying active, relishing the chance to clear his mind and explore the outdoors.