Fine-Grained Player Prediction in Sports with Jennifer Hobbs - TWiML Talk #157
Published:Jun 27, 2018 16:08
•1 min read
•Practical AI
Analysis
This article summarizes a podcast episode from Practical AI featuring Jennifer Hobbs, a Senior Data Scientist at STATS. The discussion centers on STATS' data pipeline for collecting and storing sports data, emphasizing its accessibility for various applications. A key highlight is Hobbs' co-authored paper, "Mythbusting Set-Pieces in Soccer," presented at the MIT Sloan Conference. The episode likely delves into the technical aspects of data collection, storage, and analysis within the sports analytics domain, offering insights into how AI is used to understand and predict player performance.
Key Takeaways
- •The episode focuses on the application of AI in sports analytics.
- •It highlights the data collection and storage methods used by STATS.
- •The discussion includes a research paper on soccer set-pieces.
Reference
“The article doesn't contain a direct quote, but it discusses the STATS data pipeline and a research paper.”