Behind Hockey's Stars: a Statistical Analysis of Critical Hockey Team Metrics

Author's Notes

This summer, I had the honor of being a part of Bucknell University's first group of Digital Scholarship Summer Research Fellows. A new program run by the library and IT staff, this program, DSSRF17 for short, has allowed me a great opportunity to conduct individual research with the help of facilitators and peers. 

Brought to my attention by Professor Nathan Ryan, the DSSRF program is a fantastic opportunity for undergraduate students to get a taste of research, while answering questions that may traditionally be neglected by those in academia. Before the program, I had no idea what "Digital Scholarship" or "Digital Humanities" referred to. Now I have a strong understanding of these fields, and I value many of the aspects of DH and DS. I especially appreciate the fluidity of these fields, as technology persistently drives the world further, Digital Scholarship continues to develop and adapt, helping to keep research relevant.  

This project has been a eye-opening, rewarding, and challenging. In particular, creating a predictive model for hockey teams was very difficult. Though I am a mathematics major, I have taken very few courses in statistics. Therefore, I needed to rely on the help of my fellow applied mathematic majors as well as Bucknell faculty for advice. Another hurdle was relearning R, which I hadn't worked with in about 18 months when the summer began. Thus, I felt like my progress was limited for the first two weeks, as I familiarized myself with the statistical software. 

For a variety of reasons, my favorite part of the DSSRF program has been the collaboration involved. I've learned about topics I would have never studied previously, courtesy of my research peers. We are each answering our own research questions, ranging from topics on the Chinese economy to mining monuments in Central Pennsylvania. I've also been reminded how important the support of others is in any research. From the program facilitators to our faculty advisors to the Library and IT staff, this project would have gone nowhere without their help. Even though all four fellows conducted very different research, we were all able to help one another, while progressing our own research. This teamwork has made the summer enjoyable.

I owe great thanks to the program facilitators, Courtney Paddick and Carrie Pirmann, for providing creative support throughout the research process. I am grateful for statistician Owais Gilani, who has helped to ensure mathematical rigor in my model. Further, I want to thank Ben Hoover for helping to identify my research question, Ken Flerlage for teaching us Tableau, and the rest of the Library and IT staff for teaching me tools that I can apply far beyond my summer research. This project would be nothing without these dedicated individuals. 

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