Dr. William Marshall

Assistant Professor, Mathematics and Statistics
Faculty of Mathematics and Science

The second of our series is an interview with Dr. William Marshall, Assistant Professor of Mathematics and Statistics in the Faculty of Mathematics and Science.

What is your connection to the Canada Summer Games?

I received a VPR Canada Games Grant for my research project, “Using Data Science to Predict Golfer Performance.”

How did you draw upon your research to present your VPR Canada Games Grant application?

The VPR Canada Games Grant project is an extension of an undergraduate Honours Project I supervised. The student, Brad Klassen, developed a statistical model for predicting golfer performance on the PGA Tour.

The grant provides an excellent opportunity to further develop the model to use more sophisticated data science methods and use an expanded data set (Canadian Tour and Canada Games golf statistics) to improve predictions.

How is Mathematics and Statistics research related to major sport events such as the Canada Summer Games?

Major sporting events such as the Canada Games generate large amounts of data. This data comes in many forms, for example, measures of athlete performance, economic impact, or fan participation. Data science provides the tools to analyze these large datasets and uncover patterns and relationships. The results of these analyses can impact all aspect of major sporting events, from athlete training, to marking decisions.

Can you provide specific examples of how Mathematics and Statistics research has increased understanding of major sport events?

The mixing of statistics and sport – sports analytics – is a fast-growing field. Recent history has seen sports analytics play a major role in professional sport, impacting how athletes are trained and evaluated. Advanced statistics developed in sports analytics changed how we understand the sports, and what we think makes an athlete great.

In professional hockey, for example, coaches and managers no longer evaluate players based on simple statistics like goals and assists, or qualitative intangibles like “grit.” Now players are evaluated using advanced statistics, for example, “relative Corsi,” or “Fenwick statistic.” 

Do you have any research ideas for your colleagues in Mathematics and Statistics and, more broadly, the Sciences?

Data Science is an interdisciplinary endeavor. My project, “Using Data Science to Predict Golfer Performance,” combines mathematics and statistics with domain specific knowledge from sports management, specifically relating to golf. In tailoring these methods to a specific problem, I find that it can help stimulate new mathematical or statistical ideas.

I would recommend that my colleagues in Mathematics and Statistics seek out collaborations with other disciplines. For the Canada Games specifically, I think there are many opportunities with sports management, health sciences, or business and economics.