Data Analysis in Soccer - Article Politeknik AI BMD
Machine Learning

Data Analysis in Soccer

Oleh Arwan Ahmad Khoiruddin, S.Kom., M.Cs (Wakil Direktur PLAI BMD)

30 Mei 2025 Machine Learning
data-analysis-in-soccer

⚽ What Is Data Analysis in Soccer?

Data analysis in soccer means looking at numbers and information to understand how players and teams perform. This helps coaches and teams make better decisions.


📊 How Is It Used?

1. Understanding Player Performance

Teams collect data on things like:


  • How many passes a player makes
  • How far they run
  • How many goals they score


This helps coaches see what players are doing well and where they can improve.

2. Planning for Games

By studying data from past games, teams can learn about their opponents' strengths and weaknesses. This helps in creating strategies to win matches.

3. Preventing Injuries

Using special devices, teams track players' movements and physical activity. If a player is getting too tired, they can rest them to avoid injuries

4. Finding New Players

Data helps teams find players who might be a good fit. For example, Leicester City used data to find N'Golo Kanté, who helped them win the Premier League.


📈 Simple Tools Used

  • Heat Maps: Show where a player spends most of their time on the field.
  • Radar Charts: Display a player's strengths and weaknesses in different skills.
  • Expected Goals (xG): Estimate how likely a shot is to result in a goal.


Here's a video if you want to learn about data science in soccer

https://www.youtube.com/watch?v=JoFdTkjBKW8&ab_channel=SPORTSDATACAMPUS

Here's an overview of how football clubs utilizes data analysis to enhance their performance:

⚪ Tottenham Hotspur

Tottenham has significantly invested in data analytics to support their coaching and recruitment strategies. They have appointed key personnel, including Sasha Satikova as Lead Data Scientist and Pawel Kapuscinski as Lead Data Engineer, to strengthen their data-driven approach. These experts assist in creating interactive dashboards and real-time performance analyses to inform tactical decisions and player evaluations


🔴 Manchester United

Manchester United has been working to modernize its data analytics infrastructure. Chris Shumba, the club's Head of Data Operations, has emphasized the importance of understanding day-to-day operations to integrate data effectively. Additionally, the club is reportedly seeking to enhance its data analysis capabilities by recruiting experts from other industries, such as Formula One, to improve their transfer strategies and overall performance


🟡 Al-Nassr

Al-Nassr employs data analysis to monitor player performances and team tactics. Platforms like FBref provide detailed statistics on the team's performance across various competitions, offering insights into player contributions and areas for improvement


🟢 Al-Khaleej

While specific details on Al-Khaleej's data analysis practices are limited, as a professional club, it's likely they utilize basic performance metrics to assess player fitness and match readiness.


🇹🇭 Buriram United

Under the guidance of coach Arthur Papas, Buriram United has implemented a data-driven approach to analyze team tactics and player performances. This strategy has been instrumental in their domestic and regional successes, allowing for informed decisions on formations and player roles


🇻🇳 Công An Hà Nội FC

Công An Hà Nội FC utilizes statistical data to track team performance in domestic leagues and regional competitions. Platforms like Soccerway provide comprehensive statistics, aiding the club in evaluating player performances and strategizing for upcoming matches


🟣 Al Wahda

Al Wahda has embraced data analytics by implementing interactive dashboards to monitor training sessions and player performances. These tools help coaches and players assess progress and plan future training effectively


🔵 Al-Hilal

Al-Hilal has partnered with Kitman Labs to deploy an advanced 'Intelligence Platform' across their men's and women's first teams. This platform integrates various data sources to provide comprehensive insights into player health, performance, and training, facilitating informed decision-making by the coaching staff.


Some Datasets To Learn Data Science in Soccer

  1. Statsbomb (https://github.com/statsbomb/open-data)
  2. European Soccer Data (https://www.kaggle.com/datasets/hugomathien/soccer)
  3. Soccermatch Event Dataset (https://figshare.com/collections/Soccer_match_event_dataset/4415000/5)
  4. SoccerNet (https://arxiv.org/abs/1804.04527)