Sports Analytics at SFU

A brief history of the SFU Sports Analytics Group

The SFU Sports Analytics Group (SAG) was formed in 2014 to bring together SFU faculty, students, coaches, and sport staff who share a passion for sports and the analytics behind them. We met regularly, engaged in research collaborations, our students formed a club, and we hosted two conferences in 2016 - the Vancouver Hockey Analytics Conference (VanHAC) in the spring and the Cascadia Symposium for Statistics in Sport (CASSIS) in the fall.

Our activities were interrupted by the COVID pandemic, but we pivoted quickly to moving our seminar series online. The SAG virtual seminar series attracts attendees and speakers from across Canada and around the world. In 2020, we attracted a major team grant from the Canadian Statistical Sciences Institute (CANSSI). Throughout our existence, alumni of the SAG have been routinely hired by professional sports organizations.

Sports analytics is appealing because it provides for fascinating research problems owing in part to the public availability of data, and sport data provides teaching material that many students find relatable. Sport can serve as a model for many aspects of life, it can provide fundamental insights into human biology and behaviour, and sport data can serve as the test bed for new statistical and computational methods.  

What is sports analytics?

Sports analytics is the "management of structured historical data, the application of predictive analytic models that utilize that data, and the use of information systems to inform decision makers and enable them to help their organizations in gaining a competitive advantage on the field of play." [Alamar & Mehrotra (2011) Analytics Magazine]

Sports analytics arose from the increasing availability of data and the motivation to inform decisions with objective evidence. Analytics supplements the "coach's eye." Sports organizations at all levels are increasingly using statistics to help evaluate the performance of players and teams. General managers look to statistics to valuate present and future players, while agents use statistics to make a case for a better contract for their client. Players use statistics to identify areas for improvement and to understand the strengths and weaknesses of their opponents. Business people use data to increase ticket and merchandise sales. Media companies include data visualizations in their broadcasts.

Sports organizations are increasingly employing people whose jobs are to analyze data. Such people are commonly trained in quantitative sciences such as statistics, computer science, engineering, physics, and mathematics. However, those trained in the sciences underlying sport and business, such as kinesiology, sports medicine, management, and psychology, have essential domain-specific knowledge that inform data analytics.

How does one get involved in sports analytics?

If you are curious about sports and data, then consider participating in the SAG. The SAG is inclusive: we welcome individuals from diverse academic backgrounds; indeed, our members come from disciplines across campus, including statistics, kinesiology, computer science, business, engineering, and mathematics. SAG members are interested in many sports: basketball, ice hockey, soccer, cricket, golf, curling, cycling, swimming, etc. Every sport has interesting features, nuances, and data sets!

Ways to get involved:

  • Members of the SFU community may wish to join the SAG email list, which is used to disseminate information about SAG activities and items of interest.
  • For those external to the SFU community, we have a separate SAG virtual seminar email list. Both email lists are managed by Dr. Dave Clarke.
  • Students at SFU may consider joining the student-run SFU Sports Analytics Club, which is an official Simon Fraser Student Society club. The club is active and has hosted the very successful Vancouver Sports Analytics Symposium and Hackathon (VanSASH) in the past.
  • Students and trainees interested in pursuing research training in sports analytics should contact a faculty supervisor of interest.