This project appeared as a poster entry in the 2019 Rocky Mountain Symposium on Analytics in Sports hosted by the University of Denver.
The goal of the project was to predict the 19 NCAA Men’s Hockey Tournament participants using six seasons of only regular season statistics as inputs. The projected utilized machine learning techniques and was coded exclusively in R. The chosen model, a logistic regression obtained 84.51% accuracy. 15 of the top 16 bids ranked by probability are positively identified.
Please visit this project on shinyapps.io for an improved user experience of the project app displayed below.
