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🎙️ Speaker: Maximilian Goebel | ⏰ Time: 2 pm UTC / 7 am PT / 10 am ET / 4 pm Berlin

Inspired by the asset-pricing literature, the Soccer-Factor-Model (SFM) is an attempt to determine a soccer player's "alpha", i.e. his/her inherent skill. In this application, "skill" is defined as a player's probability to score a goal after accounting for factors that are actually to be attributed to his team's out- or under-performance vis-à-vis the opponent. In that way, the SFM answers the question, of whether a player's observed goals are an over- or understatement of his "true" skill.

Content:
👉 Discourse Post for more details and discussion: https://discourse.pymc.io/t/12453
🎙️Max’s Interview: https://youtu.be/IkVoZUfCkt4
📝 Notebook: https://github.com/maxi-tb22/SFM/blob/main/PyMCon/SFM_redacted.ipynb

📜 Outline of Talk / Agenda:

  • 5 min: Intro to PyMCon Web Series and Speakers
  • 40 min: Live Talk
  • 15 min: Q&A

💼 About the Speaker:

  • Maximilian Goebel
    Max is a Post-Doc at Università Bocconi, specializing in finance/economics. With research interests in climate econometrics, machine learning, macroeconomic forecasting, and asset-pricing, Max combines expertise in these areas to drive innovation and uncover valuable insights.

🔗 Connect with Max:
👉 Website: https://www.maximiliangoebel.com
👉 LinkedIn: [https://www.linkedin.com/in/maximilian-göbel-188b0413a/](https://www.linkedin.com/in/maximilian-g%C3%B6bel-188b0413a/)

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Data Science
Applied Statistics
Python
Open Source
Statistical Computing

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