Punt Returns: Using the Math to Find the Path

Apr 22, 2022
Kaggle Submission Data and Code Big Data Bowl Finals Presentation SFU SAG Presentation RStudio Presentation

Placement: 1st out of 268

In this project with Robyn Ritchie, Ryker Moreau and Elijah Cavan, we create a custom algorithm to find the optimal path to the endzone for punt returners and build an expected return yards model on punt return plays using a Random Forest Conditional Density Estimate Model.

Our team - representing the Simon Fraser University Sports Analytics Group - was named the Grand Champion of the 2022 Big Data Bowl, finishing 1st place out of 268 submissions.

My role in this project involved designing the optimal path algorithm with Robyn as well as creating visualizations of our work.

Additionally, we presented a deep dive on our project at the SFU Sports Analytics Group Seminar Series in February 2022. The link to this video is listed above.

Brendan Kumagai
Brendan Kumagai
Data Scientist

Data scientist with a passion for hockey and science.