Advanced Statistics for English Premier League Analysis

Data is the new currency of football, and the English Premier League dataset is your key to unlocking its wealth.

At DataHub, we decided to share an open-source treasure: spanning 32 seasons and packed with over 20 detailed variables per match, we aim to offer unparalleled insights for professionals who want to strengthen their activity with sound figures.

After all, European football is a constantly expanding market, with total revenues being by now constantly over €30 billion per year (El País). In this goldmine, the English Premier League is leading the ranks both for total income and betting returns.

Our dataset characteristics make it the perfect toolkit for a wide range of professionals who want to dive deep into the effective statistics of English football.

1. The English Premier League dataset identikit

In contemporary football, familiarity with the matches’ statistics transforms amateurs into professionals.

Before our English Premier League dataset, investigating the figures from the home of football was laborious and often stressful. DataHub's repository now offers overarching data from ‘93-’94 up to the current season, for a total of 32 files.

We value the football industry professionals’ need for reliable information on a wide range of statistics. That’s why we decided to address more than 20 variables for each game:

• Home and away team;
• Date and referee;
• Results and goals both at half-time and full-time.

For the ones looking for even more detailed information, we included also each team’s counts for:

• Total and on-target shots;
• Fouls committed;
• Yellow and red cards;
• Corners.

Last but not least, data visualization can be complex when dealing with large amounts of data, which is why you can easily consult our previews for the last five seasons of the English Premier League.

2. Highlights - The dataset features

The English Premier League dataset is part of a DataHub project that collected and structured comprehensive data on the five major European football leagues.

As data professionals and football fans, we are proud to have created detailed datasets that fill many of the gaps in existing open-source information. Our prime aim is to provide professionals with detailed, consistent, and highly usable datasets, allowing them to have a backbone for their management decisions.

That’s why, in each of our datasets on the five major European football leagues, we have valued:

• Labeling consistency, allowing for agile cross-season comparison from 1993 up to the present day;
• Progression, with growing available information for each season reflecting football’s evolution in thirty years;
• Synchrony, granting daily updates to our dataset for the current season through automated data pipelines.

These features altogether make the English Premier League dataset a great fit for both researching previous seasons and following current developments. In other words, our users are never left behind.

3. How to exploit the Premier League dataset

Although the high usability of the English Premier League dataset makes it accessible to fans and amateurs, it is no secret that DataHub.io engineers crafted this open-source repository with professionals in mind.

We think indeed that its depth and consistency make it highly suitable for many football-related businesses.

• Investors and stakeholders: as we mentioned in our article about Football Data collection, the English Premier League alone recorded a €7 billion profit in 2023 (source: El País). Not only that: the steeping figures in Europe are telling us that football is a constantly growing market where investments could return high dividends.
  • Data-driven money allocation
  • Spotting the most consistent clubs
  • Individuate possibly profitable underdogs

• Team management: from Jürgen Klopp’s Liverpool to Pep Guardiola’s Manchester City, football's game-changers of the last years have all integrated data analytics into their coaching. But why did they choose statistics to improve their teams’ performances?

  • Matchday preparation
  • Targeted training sessions
  • Team’s attitude assessment
  • Individuation of critical spots

• Journalists and content creators: the English Premier League has always been one of the most dynamic competitions worldwide, and still surprises us at every match day. Especially within a quick and spectacular football culture, sound-prepared information becomes crucial to building engaging narratives.

  • Building hype before a game
  • Postgame analysis
  • Recalling iconic matches of the past
  • Agile creation of half-time flashcards

• Advertisement: the labeling consistency of the dataset makes comparisons between teams kids play, immediately spotting both winning and goal trends. This feature can even back cross-country comparisons, as the English Premier League dataset is part of a broader collection including data for the European fabulous-five.

  • Spot possible partnerships
  • Identify the most consistent and/or spectacular teams
  • Evaluate the team’s possible public appeal

• Betting industry: England is not only the home of the game but also the home of football gambling. As reported by SafeBettingSites, bets on the Premier League generated over €68 billion worldwide, surpassing the sum of the Italian Serie A and German Bundesliga.
  • Bookmaking support
  • Individuation of profitable commercial partners
  • Back decisions on odds wagers

Put simply, the dataset on the English Premier League might be the best example of profitable football data.

4. RECAP TABLE

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