Football Data Analytics Portfolio
February 2024
Slides: docs.google.com/presentation/d/1sWb5UDDp_3klAdLF0E30HTOo0ZKNcK2KPPHAfmsclF8
Web: eddwebster.com
EDD WEBSTER
PORTFOLIO OVERVIEW
This portfolio aims to demonstrate the professional data science experience that I have gained over the last five years, developed from working in an elite, first team football environment, as well as several best-in-class organisations.
A strategic approach to dissecting and addressing examples of difficult industry issues are discussed in detail. For each challenge, an approach and a summarised solution is provided with some real-life examples.
Finally, this portfolio aims to showcase the measurable impacts of the challenges tackled, as well as provide opportunity to demonstrate further work and skills.
The decks demonstrates a broad range of data insights skills, ranging from data processing, modelling, visualisation and results communication.
CONTENTS
Contents
3
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
All publicly available code: github.com/eddwebster/football_analytics and Tableau visualisations: public.tableau.com/profile/edd.webster.
Summary
4
INTRODUCTION
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
The reason for producing this
football data analytics portfolio?
To demonstrate my broad range of data science and data engineering skills, as well as my experience and knowledge of football analytics concepts and analytical techniques.
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
5
Summary
INTRODUCTION
Timeline of My Background and Education Over the Last Ten Years
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For more information, see: linkedin.com/in/eddwebster and my CV: eddwebster.com/downloads/EddWebsterCV.pdf
Data
Scientist
Apr 2022 – Apr 2023
London, UK
Business
Analyst
Aug 2018 – May 2018
London, UK
Lead
Data Analyst
Jul 2018 - Apr 2020
Lima, Peru
MSci Degree
Chemistry
2012 – 2016
London, UK
Team
Leader
Jan 2017 – Jul 2017
Tamale, Ghana
2016
2017
2018
2019
2020
2021
2022
2024
Senior Data & CRM
Manager
Oct 2021 – Apr 2022
London, UK
Data Science
Consultant
May 2022 – Apr 2023
Remote
Lead
Data Scientist
Apr 2023 – June 2024
Leicester, UK
Data & Insights
Analyst
Apr 2020 – Oct 2021
Manchester, UK
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
2023
Senior Data
Scientist
Jun 2024 – Present
Remote, UK
Objectives of the Data Insights Department of a Football Club
INTRODUCTION
7
To provide access to data for the club, to enable every decision made by for football operations to be objective and informed by data.
Educate decision makers and empower them to want to use data.
To maximise performance and subsequently, win more games.
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2
3
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Areas of a Football Club that Data Insights Can Have an Impact
INTRODUCTION
8
Recruitment and scouting – using models to bring a positive impact on player trading outcomes in the transfer market;
Performance evaluation and player development – measure the performance of players through models;
Sport science and athlete monitoring – provide reviews, audits, and recommendations for interventions; and
Club strategy – discovery of new insights through physics-based modelling that can be implemented by coaches in team strategy and affect performances on the pitch.
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4
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Data-Driven Decision Taking Place Across a Football Club Club
INTRODUCTION
9
Manager
Director of Football
Academy
Agents
Performance
Analysts
Data Scientists
Players
Data
Recruitment
and Scouts
Areas of Expertise Required in a Functioning Data Analytics Team
INTRODUCTION
10
Data
Engineer
Data
Scientist
Data Insights Analyst
Performance Analyst
Technical
Expert
Infrastructure
Organise
Support
Connect
Enrich
Explore
Discover
Predict
Investigate
Infom
Visualise
Advise
Bridge
Connect
Align
Insights
Observe
Interpret
Context
Implement
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Slide recreated from a slide by Tom Garner in his presentation: “Delivering Football Performance Insights” at the StatsBomb Conference 2023: https://www.youtube.com/watch?v=ApWqVlz-ztQ&ab_channel=StatsBomb. Slide can be found at around 4m30s
11
AREAS OF IMPACT
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Application of Data Across Different Workstreams
AREAS OF IMPACT
Football Intelligence Reporting
Data and Infrastructure Engineering
Insight Delivery to Football Stakeholders
Internal Scouting Player Rating System
Open Source Contributions
The application of data to make evidence-based decisions, that are delivered efficiently and effectively to seniors stakeholders and football practitioners.
Adding context to the scouting and recruitment process with data via a bespoke, player rating system, based on a system of defined and weighted metrics, custom-made to the needs of the First Team and the game model.
Creation of a back-end infrastructure, to enable automated reporting, player mapping, and predictive modelling, including the creation of the ‘Player 360’ reference tables.
Open source projects using publicly available event and tracking data. Projects include working with tracking data including Pitch Control modelling, Chance Quality modelling of shots from Event data, and determining ball-playing centre backs through clustering, to determine the ”the next Gerard Piqué
Automated reporting for opposition and post-match analysis, implementing bespoke KPIs and modelled metrics, curated to the football club’s game model. Custom reports for the purposes of recruitment, performance analysis and sports science.
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
13
FOOTBALL INTELLIGENCE REPORTING
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Turning Big Data into Meaningful Insights Using Tableau
FOOTBALL INTELLIGENCE REPORTING
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Simplicity - deliver clear and concise messages that can be comprehended quickly and concisely.
Enable Control - dashboard and visualisations need to include filters, tool tips, and actions, that can allow the user (often coaches) to find the insights themselves without the need for programming or dashboard building skills.
Flexibility - filters, tooltips and actions can allow the user to find the insights themselves.
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3
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
A Selection of Football Insight Analysis Tools 1/2
FOOTBALL INTELLIGENCE REPORTING
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Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Tableau visualisations created with publicly available data can be found at my Tableau Public profile: public.tableau.com/profile/edd.webster.
Summary
A Selection of Football Insight Analysis Tools 2/2
FOOTBALL INTELLIGENCE REPORTING
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Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Tableau visualisations created with publicly available data can be found at my Tableau Public profile: public.tableau.com/profile/edd.webster.
Summary
17
INSIGHT DELIVERY TO FOOTBALL STAKEHOLDERS
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Providing Post-Match and Opposition Analysis to Key Stakeholders
INSIGHT DELIVERY TO FOOTBALL STAKEHOLDERS
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Delivering Insights Directly to the Club’s Senior Stakeholders
INSIGHT DELIVERY TO FOOTBALL STAKEHOLDERS
"Our Toughest Match" 🎙️ | Enzo Maresca Previews Rotherham United. Stats quoted 3 minutes and 58 seconds into the video: youtu.be/kWlyTNaqXCA?si=1HotJWAVe9TkehW1&t=238
"A Complicated Team" | Enzo Maresca Assesses Plymouth. Stats quoted 4 minutes and 6 seconds into the video: youtu.be/eRyX4LNp6LE?si=ZyGG9IWGM8suTugK&t=246
Delivering Insights as Part of Analytics FC Coach ID Service
INSIGHT DELIVERY TO FOOTBALL STAKEHOLDERS
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Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Tailor-made Analysis for Online Publication
INSIGHT DELIVERY TO FOOTBALL STAKEHOLDERS
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PLAYER RATINGS FRAMEWORK
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
The Purpose of Data Analytics for Recruitment and Scouting
PLAYER RATINGS FRAMEWORK
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To narrow a whole cohort of players to a manageable number of targets for further investigation by domain experts, to optimise the resources available to the department.
Provide an objective assessment of player’s in-game performance for both their output and playing style.
Empower decision makers that want to use the data to further inform their decision making and increase the likelihood of success for the purposes of player recruitment.
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3
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
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How do you measure…
Shooting?
Scoring?
End Product?
Finishing?
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
PROSPECTS Rating System
PLAYER RATINGS FRAMEWORK
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Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
PROSPECTS Rating Proposed Categories and Respective Qualities
PLAYER RATINGS FRAMEWORK
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Scoring
Creating
Passing
Goals
Shots
Conversion
Position
Crossing
Assists
Dribbles
Carries
Involvement
Accuracy
Direction
Intent
Composure
On-Ball Decisions
Progressive Passing
Interceptions
Possession
Defending
Goalkeeping
Aerial Ability
On Ball
Off Ball
Fouls
Shot Stopping
One-on-Ones
Distribution
Decision Making
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Rating Players Based on a Specific Game Model
INSIGHT DELIVERY TO FOOTBALL STAKEHOLDERS
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3
2
5
4
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1
HIGH PRESSING
LINK UP PLAY
ATTACKING FIRST POST FOR CROSSES
RUNS IN BEHIND
STRETCH LINE OR FALSE 9
Striker
OFFENSIVE
GOOD FOOTBALL
FROM THE BACK
ORGANISED, DYNAMIC
3-2-2-3
In Possession
NUMBERS REPRESENT PLAYER PROFILES
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DATA ENGINEERING AND INFRASTRUCTURE
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Licensed and Public Data Providers Accessible to the Club
CURRENT STATE AND RECENT PROGRESS
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Event
Data
Scouting and Financial Data
Tracking
Data
Sports Science and Physical Data
Additional Data
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
AWS Cloud-Based Data Infrastructure and Tooling
DATA ENGINEERING AND INFRASTRUCTURE
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Building the Player 360 Database
INSIGHT DELIVERY TO FOOTBALL STAKEHOLDERS
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Event data
(40+ competitions)
Optical Tracking data
(Premier League)
Physical data
(Leicester City only)
Additional Data
(TransferMarkt, WhoScored Ratings, SmarterScout metrics, etc.)
Player 360 Reference Table
table of common identifiers containing each player's key details and unique ID across the systems, allowing data to be matched
Well-being and sports science data
(Leicester City only)
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Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
OPEN SOURCE CONTRIBUTIONS
Summary
Overview of Open Source Projects
OPEN SOURCE. CONTRIBUTIONS
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Recruitment analysis of ‘ball-playing’ centre backs
Scenario for a data-driven recruitment analysis, to determine ”the next Gerard Piqué”, for a hypothetical, newly-promoted club in the ‘Big 5’ European leagues. This analytical piece features the use of Machine Learning techniques as part of the player selection process, including K-Means clustering and Principal Component Analysis.
Opposition analysis of a Premier League team through the application of Event and Tracking data
Application of Opta Event data and Second Spectrum Tracking data for two of Crystal Palace’s matches in the 21/22 season against Brighton & Hove Albion and Leicester City, as part of an opposition analysis report for a Premier League club.
Physical data analysis of player GPS training data
Working applications of player training data for the purposes of performance analysis in a club setting, with an output of player reports to measure speed, time, distance covered, acceleration, and number of sprints that players conducted in each of the training sessions they participated in.
Post-tournament analysis of the England men’s team at EURO 2020 through the application of StatsBomb Event and OBV Data
Short analytical piece that applies a data-driven approach in an attempt to answer the question ‘England at EURO 2020: How Good Were They Actually?’.
Tableau Football Intelligence reporting tools
Creation of analysis tools for analysing player performance, pre- and post-match tactics, and recruitment, enabling the democratisation of data to all levels of a footballing organisation or club. Data used features StatsBomb Event data for the FA WSL for the 19/20 and 20/21 seasons.
Applications of Tracking data
Engineering and analysis of Signality, Metrica Sports, and Stats Perform Tracking data. Analysis includes analysing passages of play, determining physical performance, the implementation a basic Pitch Control models, and applying Expected Possession Value (EPV) frameworks.
Expected Goals (xG) modeling
Training an Expected Goals (xG) model using Event data, subsequently applied to a separate match dataset of Event and Tracking data, to analyse the performance of the teams in question. Models created using Logistic Regression, Random Forests, and Gradient Boost Decision Trees (GBDT) algorithms including XGBoost and CatBoost.
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These projects are all discussed in further detail in my Data Science Portfolio: docs.google.com/presentation/d/1EQ4meB5Y2TGuIn3K31OdkvoI-8QlPW2MhZE8UEhZ38c.
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
34
SUMMARY
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
Insights this Football Data Portfolio Aims to Provide
SUMMARY
35
Data insights experience – this portfolio aims to have provided cross-section of my five years of data insights experience, developed from elite football environments and the commercial departments of top-flight football club, as well as best-in-class industries.
Diverse skill-set and problem-solving approach – breakdowns are provided for tackling common industry challenges with working examples, covering the concepts of data processing, modelling, management, visualisation, and strategic planning.
Measurable impact – demonstrating the quantifiable outcomes for football analytics data and insights.
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3
Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary
For More Information…
SUMMARY
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Introduction
Areas of Impact
Football Intelligence
Insight Delivery to Stakeholders
Player Ratings Framework
Data Engineering and Infrastructure
Open Source Contributions
Summary