Use Case: Oracle Machine Learning in football - Expected Goals

Thanks to the partnership between the Premier League (the top tier of England's football) and Oracle we have the opportunity to experience what it is to be a football analyst and apply advanced analytics and machine learning to real match data. In this session, you will learn about the concept of "Expected Goals" (xG) in football. Expected goals (xG) is a predictive model used to assess every goal-scoring chance and the likelihood of scoring. The xG model computes for each chance, the probability to score based on factors such as distance, the position of defenders, type and speed of pass, type of shot, shot angles, and various other aspects. In this demonstration, you'll see how we can use Oracle Machine Learning, Autonomous Datawarehouse, and Analytics Cloud to: - Visualize data on a football pitch - Prepare data for machine learning - Train the xG model - Apply the model to recent matches to understand team and player performance.

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Premier League Challenge - Hands-on Lab

If you are passionate about football and data, this live hands-on-lab is for you! Thanks to our partnership with Premier League you have the unique opportunity to experience first-hand what it is to be a football analyst and apply advanced analytics and machine learning to real match data! In this first hands-on-lab you will learn about the (xG) Model.

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Session Has Completed - 21 June 2022

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21 June 2022

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Use Case: Oracle Machine Learning in football - Expected Goals

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Oracle LiveLabs

Premier League Challenge - Hands-on Lab

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