Over the past decade, big data and predictive analytics has taken over the landscape of the sports, most prominently baseball, basketball, and football. One thing that all three of these sports have in common is the vast amount of raw data that each game produces. This makes it relatively easy for analytic specialists and mathematicians to create algorithms that produce actionable data. A sport that does not fall under that category is hockey, a sport contingent upon toughness and teamwork. Those two variables are extremely hard to tally as the article states that “The business of sports, however, can’t quantify the toughness of its players”. Nonetheless, hockey teams are attempting to implement big data analytics in their front office operations, just in a different form than most other sports. Teams have started hiring people from all backgrounds to head their analytics departments, while also hiring outside consultants. How teams are collecting data and what data they are seeking was the most intriguing aspects of this article in my opinion.
Unlike most sports, who collect and interpret data in similar ways, hockey teams take varying approaches, depending on how they value certain immeasurable intangibles. Kyle Dubas the assistant general manager of the Toronto Maple Leafs, who assembled one of the first “research and development” staffs in the NHL. His staff consists of people from an array of backgrounds including a chemical engineer. Their team (and many others) values blocked shots, which they incorporate with other stats including hits to compile ‘grit’ stats or shots to derive ‘real shots on net’ stats. Along with in house statistician teams, teams will hire outside consultants, some with no hockey background to assist them strive for analytical success. Teams have hired industry juggernauts such as SAP analytics to assist them with compiling relevant data and analyzing it to produce actionable results. Also, hockey is adopting analytics in a more broader sense than just at the team level.
As the NHL has always been the little brother to the NFL, MLB, and NBA, the league has taken measures to attempt to have competitive ratings with the big 3 sports leagues in America. The league is valuing fans input more than ever as fans are being presented with surveys and other forms of questionnaires to express their opinion on how the league to become more popular. Also, the league compiles data based on viewership to see which teams, match up and time slots are most likely to produce high ratings. This, along with the data from the fans can be analyzed by the league office to produce predictive results that can increase popularity and hopefully make hockey more popular throughout the world. I believe predictive analytics will become more prevalent throughout the hockey world as it attempts to cement itself as one of the most popular (and profitable) sports worldwide.