Hello, I'm
Moritz Philipp Haaf
Data Analyst focused on Data & Football Analytics
The Beautiful Game, Explained with Data.
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About Me
Experience
5+ years
in Data & Analytics
Education
B.Sc. Business Administration
M.A. Digital Media Management
I am a certified Data Analyst with a passion for transforming complex datasets into actionable insights that drive business growth and operational efficiency. With a strong background in sports, media, and technology, I excel at leveraging data-driven strategies to enhance decision-making and optimize performance. My technical toolkit includes Python, SQL, R, Tableau, Looker Studio, Datorama, and Power BI, which I utilize to analyze data, automate workflows, and deliver results that make a difference.
Explore My
Professional Journey
Publicis Media Austria
Senior Digital Data & Dashboard Manager
Regionalmedien Austria AG
Analytics & Ad Tech Development Manager
Red Bull Media House
Digital Competence & Ad Tech Specialist
Sportradar Media Services GmbH
Manager Digital Advertising
Hawk-Eye Innovations Ltd
Football Systems Operator
E2 Communications GmbH
Oddsserve & Ad Operations Manager
TorAlarm GmbH
Internship
Explore My
Skill Set
Core Competencies
Data Analytics
Experienced
Data Science
Intermediate
Business Intelligence
Experienced
Data Visualization
Experienced
Dashboard Development
Experienced
Ad Tech
Experienced
Project Management
Intermediate
AI & Machine Learning
Basic
Sports Technology
Intermediate
Tools & Technologies
PythonExperiencedSQLExperiencedRBasicDatoramaExperiencedTableauIntermediatePower BIIntermediateLooker StudioIntermediateStreamlitBasicGit, GitHubIntermediate
Check Out My Recent
Projects
Football Analytics Portfolio - Expected Goals (xG) & Passing Networks
Project Overview
Developed a football analytics project applying machine learning and data visualization to analyze expected goals (xG) and passing networks. Built an xG prediction model using XGBoost and analyzed team passing structures with NetworkX. The results are displayed in an interactive Streamlit dashboard. You can find the complete implementation and code in the accompanying GitHub repository.
Technologies Used:
- Programming Language: Python
- Machine Learning: XGBoost, scikit-learn
- Data Processing: pandas, NumPy
- Data Visualization: mplsoccer, Matplotlib, Plotly
- Web App: Streamlit
- Data Source: StatsBomb event data
- Version Control: Git, GitHub
More to come
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