Uploaded December 2022 | Updated September 2026, 1 day ago

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At NeurIPS 2022, Amazon scientists present a robust method, the spliced binned-Pareto (SBP), for modeling heavy-tailed problems. In this demo, they discuss how the SBP’s ability to provide multi-model, heavy-tailed distribution forecasts of an American football play’s yards gained outcome given the players’ temporal dynamics, allowed for the NFL’s QB Passing Score announced at the 2022 Super Bowl. They further demo the robustness and accuracy of their method against other state-of-the-art methods on a public benchmark data set.

Amazon scientists include:
• François-Xavier Aubet, applied machine learning scientist
• Elena Ehrlich, principal data science manager
• Paul Budnarain, applied scientist
• Brad Gross, senior data scientist

Read more about the method on Amazon Science: https://www.amazon.science/blog/the-science-behind-nfl-next-gen-stats-new-passing-metric

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