Growing up in Carleton Place, Ont., Matt, Artsci’13, MA’14, and Will, Artsci’15, Courchene played golf every chance they got, perfecting their game and going on to golf for the Gaels during their studies at Queen’s. Now they’re turning their love of the game into a successful business with the creation of Data Golf, a website the Wall Street Journal says is a “must-read for anyone who enjoys geeking out about the game” and that the Global Golf Post describes as “a statistical wonderland that soothes the golf nerd’s soul.” (The brothers’ aptitude for statistical analysis may be in their genes – their grandfather is renowned Canadian economist and emeritus professor Dr. Tom Courchene, former director of the School of Policy Studies at Queen’s.) The two started Data Golf in the summer of 2015, when they received academic access to a dataset from the Professional Golfers' Association (PGA) Tour. Given their lack of web development skills, Data Golf initially took the form of a simple blog. But, over the next few years, they learned how to build interactive tables and graphs and created a predictive model of golf performance, moving from a simple WordPress template to a site built with their own custom code. In April 2019, the week of Tiger Woods’ last major championship win, they launched a paid subscription option for the site. Fifty people signed up the first day, with thousands more to follow.
You have very different academic backgrounds – biochemistry and economics. How did these disciplines blend to influence the development of Data Golf?
Will: Matt ended up minoring in economics, and we both pursued graduate studies in econ, so our economics background was much more influential in the development of Data Golf (DG). The primary driver behind DG was our passion for golf and wanting to create the best data-driven website we could given the tools we had at the time. Of course, this meant we had to learn many new things about programming, web development, web servers, etc., to complement the strong statistics/econometrics base we had from our time in university.
Can you discuss some of the initial challenges you faced when transitioning Data Golf from a hobby to a full-time business?
Will: From a business perspective, there fortunately haven’t been too many challenges. Data Golf was a free website for a few years before we added a paid subscription tier. The initial response to that was encouraging, and our subscriber base has slowly grown since then. Looking back, I think our main advantage was how much we enjoyed working on DG before there was any monetary benefit. Most startups have to hire early, potentially borrowing money to do so, which leads to deadlines from investors. Because we did it ourselves, putting thousands of hours of unpaid labour into the site. This gave us more flexibility and time to create the website we wanted prior to worrying about revenue.
Matt: Even before Data Golf became a business, we took it very seriously. We’ve always cared a lot about the quality of our work, as well as our reputation within the golf and analytics communities, and that hasn’t changed since it became our livelihood. One thing we have struggled with as a business is being both owners and employees of DG. Running the day-to-day operations of the site, while also focusing on its long-term direction, can be a tough balancing act.
How do you see the role of Data Golf in the broader context of sports analytics and golf in particular?
Will: DG serves the most engaged fans of professional golf. We’ve found it rewarding to create a website for a smaller group of like-minded people rather than trying to appeal to a broad audience. It seems like this is a theme in other sports as well: bigger websites are more driven by traffic numbers and generating ad revenue, which allows little guys like us to specialize and create a higher-quality product.
Matt: In sports analytics, I think we are a good example of an independent website that has managed to turn itself into a viable business. In the golf community, we are the go-to resource for anyone looking for a data-driven perspective on the game. We also have influence in the sports betting sphere: our model predictions impact how golf odds are set around the world, and lots of our paid users are bettors trying to find an edge.
Can you share some of the future plans for Data Golf? New features or expansions on the horizon?
Matt: Our main goal for the future is just keep incrementally improving the website, which could mean creating new interactive pages, improving the predictive model, or writing more blog posts. But two bigger projects we’ve had on our radar for a while are building a shot-level model (as opposed to the round or hole-level) and building out our site to incorporate data from the women’s game.
Do you still find time to play golf and, if so, how has your approach to the game changed since starting Data Golf?
Will: We still play a bit, but not nearly as much as we used to. Living in Toronto makes playing golf difficult, so we are happy if we get out a few times per month. Surprisingly, the analytical nature of our website has not extended to our own golf games. I suppose we still view the actual playing of golf as more of an art than a science.
How did your academic experiences at Queen’s influence your approach to data and analytics?
Will: Our coursework in economics, specifically econometrics (which we took together while Matt was in fourth year and I was in second year), played a big role in developing our interest in data analysis. But, for me, the most pivotal class I took was an introductory computer science course in my final year as it set the foundation for expanding outside of my academic area of expertise.
Matt: Having a background in economics makes you wary of “black-box” modelling, which is what a lot of modern machine learning consists of. If our model makes a bold prediction for a golfer, I want to be able to understand where that prediction came from. Economics teaches you to think carefully about causation and the interpretation of statistical models – as opposed to only caring about predictive output – which are probably underrated skills in the field of data analysis.
Looking back, what advice would you give to your younger selves after you graduated?
Will: I would encourage myself to start working on non-academic projects earlier, no matter how trivial. As a student, I was overly focused on getting high grades and never really stopped to think about what I was learning. Having a project or two on the side can provide a different lens to view academic coursework through and push further learning on a topic. Also, courses and exams come and go, but a project can slowly build over many semesters and years – one day you might realize you have something great!
How did your experiences in university prepare you for the challenges of building and running your own company?
Matt: I first started to engage deeply with intellectual subjects at Queen’s, and that mindset has carried through to Data Golf. A lot of the additions to our website start with a question we find interesting (e.g. How do golfers perform under pressure? What makes a golf tournament entertaining?). Luckily, this works for us as a business, because what interests us is often what our users find interesting, too. This intellectual curiosity, combined with a desire to share our findings with other people, were the main drivers behind all the early work we did on the website.
Do you feel you are continuing your grandfather’s legacy through your work with Data Golf and, if so, how?
Matt: I wouldn’t say we are continuing his legacy – those shoes are probably too big for us to fill – but we are very passionate about our work, just like our grandfather is about his. He also wasn’t afraid to write things that went against the mainstream throughout his career, which is also true of some of our work and writing in the golf space.
Will: Also, while he is known for his contributions to Canadian public policy, to us our grandfather’s legacy is equally tied to the time we spent with him and our grandmother exploring Kingston, playing golf, and enjoying weekly Sunday dinners during our years at Queen’s.
Who are your favourite golfers?
Matt: We were both huge Tiger Woods fans growing up. It used to be that whenever a new player started doing Tiger-like things, I would get defensive and root against them. But now that Tiger has almost retired from professional golf, I find myself rooting for Scottie Scheffler, who is having a historic 2024 season. I tend to cheer for favourites in all sports, but in golf especially it’s hard to be a fan of non-superstars because their wins are so few and far between.
For our alumni who are golf fans, and based on Data Golf’s numbers, who are some golfers to watch?
Matt: Our model tends to like players (relative to the general public) who have been playing consistently well without having any high finishes or wins. Winning in golf involves a lot of luck but has an outsized influence on how players are perceived (see Xander Schauffele’s recent breakthrough victory at the PGA Championship), which creates a situation where an unbiased model can be helpful. Some players that are flying under the radar right now (in late June) are: Christiaan Bezuidenhout, Alex Norén, Aaron Rai, and Maverick McNealy.
