The biggest story heading into the 2014-15 National Hockey League (NHL) season appears to not be what is happening with players on the ice. Rather, it is the people working off the ice who evaluate players’ performance on the ice that have a leading role in the NHL’s narrative. The analytics movement has come full force to professional hockey. Teams all across the NHL have hired people with expertise in analytics that can develop proprietary statistical analysis to give their teams a competitive edge. The Toronto Maple Leafs alone hired three analysts this past offseason.
The NHL is the latest league to make a significant investment in analytics. Major League Baseball (MLB) is well-known for its use of sabermetrics, as most famously deployed by general manager Billy Beane and the Oakland Athletics. The National Basketball Association (NBA) has spent the last decade hiring people for senior level positions with strong analytics backgrounds, as exemplified by the Houston Rockets selecting Daryl Morey for their General Manager role.
The rise of analytics to evaluate player performance raises a natural question. If teams and leagues increasingly believe analytics can provide a competitive advantage during competitions, then why not make more use of use analytics to help their businesses as well? In fact, sports teams and leagues should take advantage of the opportunities to hire quantitatively-savvy managers and analysts focused primarily on growing an organization’s revenue.
What value does this provide to an organization? In a recent article in Forbes, I showed how combining analysis of a quarterback’s on-field and off-field performance can provide a more holistic view of his value to an organization. However, focusing on individual athletes’ economic impacts is only the start of how quantitative analysis can impact sports organizations’ businesses. The most common example is with pricing tickets. Dynamic pricing has changed the way that teams, fans, media, and sponsors think about how they purchase tickets. Secondary market ticket sites, such as StubHub, and new dynamic ticket pricing models, such as Purple Pricing, have provided sports organizations with the opportunity to make more money while giving fans better options for buying tickets to games.
Ticket pricing is not the only revenue stream where analytics can be applied. For example, sponsorship revenue can use a more analytical approach to demonstrate how sports organizations often generate a significant return on investment for their partners. Sports organizations have traditionally used qualitative approaches to demonstrate a return on investment for their corporate partners in sponsorship deals. This includes developing recaps that have pictures of sponsorship activation elements during the course of the season such as a picture of a brand’s logo on signage at a sports venue.
However, corporate partners should be presented with a dollar amount for the return on investment that they are receiving by sponsoring an organization. Teams can use analytical models to show how the impressions they generate with lucrative sports audiences creates new customers, helps retain current customers, increases brand awareness, or enhances brand perception. Employing analytics in sports sponsorship provides sponsors with clear reasons why they are getting value by working with a sports organization.
Employing business analytics also helps to specifically address issues when a team or athlete is not successful in competition. Relying on winning is a losing strategy. Teams that rely on winning do not always achieve financial success. In addition, winning is still difficult to predict or control – even as teams hire more people to analyze their competitive performance. Deploying business analytics helps to address these issues. It can show what strategies, marketing campaigns, and promotions work best to generate revenue regardless of a team’s performance. With the influx of new technology into the sports industry impacting ticket purchases, in-game concession sales, digital and mobile streaming, social media engagement, and many others, there is a wealth of new data available to sports organizations. The next Moneyball will be the teams that can find insights from this data to generate money for their organizations.
Headline image credit: Ice hockey stadium. CC0 via Pixaby.