Hockey analytics is continuing to gain prominence, both as a tool for professional teams to make on-ice decisions and for fans who want to better understand the game. The online fan community has really been the driver of hockey analytics as they seek to answer questions and contribute to the information and knowledge that surrounds the game.
But with all the great advances there have been in hockey analytics, some challenges are surfacing that could potentially slow down the online community that drives it. I’ve tried to outline the few that I’ve noticed and that other knowledge-based communities have faced. I also reached out to a few members of the online hockey analytics community and embedded their responses.
A very big thank you to Gabe Desjardins of Behind the Net, James Mirtle of The Globe and Mail and Scott Reynolds of The Copper and Blue for their insights. All three individuals have made significant contributions to the hockey analytics field and continue to play a role in information and knowledge development.
Hockey analytics relies on various information communication technologies (ICTs) to derive data, share information and develop ideas regarding the game. And as more ideas are developed and discussed online, further questions arise resulting in more data being pulled and analyzed. Analytics is a continuous process, which means the technology has to be able to keep up with the needs of the hockey analytics community.
According to Desjardins, the lack of real-time data is holding back the hockey analytics community. Improving the technology that collects the data can help answer many questions about the game. Electronic tagging, for example, could be implemented by the league to monitor plays more accurately.
Mirtle provided a similar recommendation, pointing out that currently, hockey analytics has to use statistics such as shot attempts as a proxy to determine a team’s possession statistics. Instead, James recommends the NHL improve their data collection methods similar to what Desjardins recommended.
If the league refrains from expanding their technology to collect better data for fans, it may be up to the hockey analytics community to somehow do the work themselves. This may require the input from those outside of the hockey community who specialize in ICTs to provide data collection and data processing solutions.
Connection to Academic Community
Hockey analytics can only grow if an open environment exists for its development. Hockey analytics is currently being done openly by the online fan community, but also in a silo by the academic community.
Academic research explores similar topics that the online fan community is interested in, but tend to view their own work as superior to that done by fans. For instance, academic researchers tend to view their practices as much more robust. For example, according to Berri and Bradbury (2010), the work done by online sports-fan communities, “should be interpreted with caution because it is not subject to an academic peer review”.
The problem with having this mentality is that academics miss out on ideas that have been developed by non-academics, writing it off too early and end up re-doing a lot of work. Academic researchers may unnecessarily use the tools available to them to reinvent things that the online community has already uncovered (Dellow, 2013). An informal process review is in place for online content as ideas can get discussed openly by a wide array of people (Tango, 2010). There defintely are some pitfalls to online peer review (Eric T., 2013), but the right environment is there to facilitate it.
In order for hockey analytics to grow, a connection must be made and an understanding must be reached between the online fan community and academics. Hockey analytics can really benefit from the cooperation which can bring together the ideas of the community and the resources available to the academic community.
With the amount of work being done and the valuable information that is being derived from it, hockey analytics has become an important asset to many people. Professional hockey teams, the NHL, hockey broadcasters, mainstream media outlets (such as newspapers), and fans recognize the importance of hockey analytics. And as demand for hockey analytics grows in the sports entertainment industry, individual analysts may begin seeking compensation for the work they have contributed to the field.
Reynolds of The Copper and Blue feels that the work of those who want compensation may not get reviewed by others, who could provide insight and perhaps enhance the analysis. Allowing for compensation could encourage more people to focus on hockey analytics full-time, but it could negatively impact the relationship between online community members.
Others who are not necessarily looking for compensation may be reluctant to share their analysis, methodologies and results with the online community fearing that someone will profit from their work. Knowing that others are monetizing their work is enough to discourage others from contributing.
- Maintain a “Produsage” (Bruns, 2008) environment. Among other things, keep the content open, allow for continuous development with the right tools and allow those that contribute to share in the ownership of the information developed.
- Establish positive relationships with those outside of the fan community such as tecnical experts and the academic community. There is an abundant amount of resources available. However, every group, whether it be online fans, the academic community or technical experts, has its own set of values, norms and rules, making it challenging to accomodate one another.
- Continue using blogs as the main communication and information development tool. Keeping the analysis open and available to comment on will benefit the hockey analytics field.
Feel free to leave comments regarding what other challenges the hockey analytics community encounters.
Berri, D. and Bradbury J. (2010). Working in the land of metricians. Journal of Sports Economics 11(1). Pg. 29-47. Retrieved from http://www.suu.edu/faculty/berri/BerriBradbury2010.pdf
Bruns, A. (2009). Blogs, Wikipedia, Second Life and Beyond. New York: Peter Lang Publishing.
Dellow, T. (2013, April 23). The problem with experts. MC79Hockey. Retrieved from http://www.mc79hockey.com/?p=5801
Eric T. (2013, June 16). Factoring regression into analysis. Broadstreet Hockey. Retrieved from http://www.broadstreethockey.com/2013/6/16/4430864/shooting-percentage-regression-goals
Tango, T. (2010, January 20). A saberist reviewing a paper of economists reviewing saberists. Inside the Book. Retrieved from http://www.insidethebook.com/ee/index.php/site/article/a_saberist_reviewing_a_paper_of_economists_reviewing_saberists/
Wilson, K. (2013, March 8). Hockey’s structure and incentive problem. NHL Numbers. Retrieved from http://nhlnumbers.com/2013/3/8/hockeys-incentive-problem