Learning Bayesian Statistics

#116 Mastering Soccer Analytics, with Ravi Ramineni


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Takeaways:

  • Building an athlete management system and a scouting and recruitment platform are key goals in football analytics.
  • The focus is on informing training decisions, preventing injuries, and making smart player signings.
  • Avoiding false positives in player evaluations is crucial, and data analysis plays a significant role in making informed decisions.
  • There are similarities between different football teams, and the sport has social and emotional aspects. Transitioning from on-premises SQL servers to cloud-based systems is a significant endeavor in football analytics.
  • Analytics is a tool that aids the decision-making process and helps mitigate biases. The impact of analytics in soccer can be seen in the decline of long-range shots.
  • Collaboration and trust between analysts and decision-makers are crucial for successful implementation of analytics.
  • The limitations of available data in football analytics hinder the ability to directly measure decision-making on the field. 
  • Analyzing the impact of coaches in sports analytics is challenging due to the difficulty of separating their effect from other factors. Current data limitations make it hard to evaluate coaching performance accurately.
  • Predictive metrics and modeling play a crucial role in soccer analytics, especially in predicting the career progression of young players.
  • Improving tracking data and expanding its availability will be a significant focus in the future of soccer analytics.

Chapters:

00:00 Introduction to Ravi and His Role at Seattle Sounders 

06:30 Building an Analytics Department

15:00 The Impact of Analytics on Player Recruitment and Performance 

28:00 Challenges and Innovations in Soccer Analytics 

42:00 Player Health, Injury Prevention, and Training 

55:00 The Evolution of Data-Driven Strategies

01:10:00 Future of Analytics in Sports

Thank you to my Patrons for making this episode possible!

Yusuke Saito, Avi Bryant, Ero Carrera, Giuliano Cruz, Tim Gasser, James Wade, Tradd Salvo, William Benton, James Ahloy, Robin Taylor,, Chad Scherrer, Zwelithini Tunyiswa, Bertrand Wilden, James Thompson,

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Learning Bayesian StatisticsBy Alexandre Andorra

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