Graph Data Science

Analyze the Graph Structure of Soccer you own this product

This free project is part of the liveProject series Hands-on Graph Data Science with LynxKite

prerequisites: basic SQL • familiarity with tables as CSV files • basic data science and machine learning
skills learned: defining graphs based on event sequences • defining a pass graph among players • defining a graph on areas of the pitch

Andras Nemeth

1 week · 6-8 hours per week · INTERMEDIATE

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Data Science

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liveProject

$19.99

liveProject This free project is part of the liveProject series Hands-on Graph Data Science with LynxKite liveProjects give you the opportunity to learn new skills by completing real-world challenges in your local development environment. Solve practical problems, write working code, and analyze real data—with liveProject, you learn by doing.

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This free project is part of the liveProject series Hands-on Graph Data Science with LynxKite explore series

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In this liveProject, you’ll construct event sequence graphs to reveal interesting information about soccer games. You’ll work to find longest pass sequences, most important players, and to understand the spatial structure of the game. You’ll define and visualize these graphs, and use connected components to find interesting event subsequences. You’ll quickly be able to uncover insights such as the most important players and the spatial structuring of the playing pitch.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Andras Nemeth

András Németh is the CTO of Lynx Analytics, with significant experience (as the top technology executive on client projects) in using graphs in real world consultancy projects. He also led the development of LynxKite, a Graph Data Science Platform in the past six years. He has an MsC in Software Engineering and an MsC in Mathematics. Before Lynx Analytics, he worked for Google where he was the tech lead on a project aiming to annotate web pages with entities from Google's Knowledge Graph.

prerequisites

This liveProject is for data scientists interested in the basic techniques of graph data science. This project is suitable for a large range of expertise levels from beginners to experienced practitioners. To begin this liveProject, you will need to be familiar with:

Basic SQL
Tables, their representation as CSV files
Basic data science and machine learning

you will learn

In this liveProject, you’ll learn the basics of graph data structures and how to define relationships between data.

Defining graphs based on event sequences
Defining a pass graph among players
Defining a graph on areas of the pitch
Various ways of visualizing these graphs
Using connected components to find interesting event subsequences
Applying pagerank and reverse pagerank to gain different importance metrics for players
Working with LynxKite for efficient graph data science

features

Self-paced: You choose the schedule and decide how much time to invest as you build your project.
Project roadmap: Each project is divided into several achievable steps.
Get Help: While within the liveProject platform, get help from other participants.
Compare with others: For each step, compare your deliverable to the solutions by the author and other participants.