Data analytics in sports was thrown into the limelight when Billy Beane and the Oakland Athletics used the power of data to finish first in the American League West although they lacked true star power. The now famous general manager was able to identify undervalued MLB players and use the A’s limited resources to put together a strong team while flying under the radar. If you want to hear more about this amazing story I highly recommend reading or watching Moneyball to see how the use of data analytics was pioneered before becoming widely adopted in the MLB and other professional leagues. The fact of the matter is, essentially all teams now use data analytics to analyze patterns over long periods of time and maximize potential value based on these analyses. But a new trend developing across the entire sports analytics market is the use of data in real time to analyze how to best beat an opponent during the game, and the use of data to improve fan experience and loyalty. The entire sports analytics market is growing at an extremely fast pace and is expected to continue at a CAGR of ~40% through 2022 to a size of almost $4 billion – this growth highlights just how interesting this industry is becoming and the importance it will have on nearly any professional sports enterprise on earth.
My interest in this topic was sparked when I was watching the Stanley Cup playoffs this past week and saw coaches as well as players constantly looking at iPads while on the bench to analyze past shifts and the metrics of the game. It turns out the NHL has struck a deal with Apple to provide three iPads on the bench in every arena in the league to allow teams to analyze in game data. Providing this technology in every arena has evened the playing field between teams which were previously more innovative in this aspect and those who were not. Teams even have specific “video coaches” sitting in an office and splicing together game clips and metrics so the team has access immediately. As we heard in a previous presentation, there are companies developing software with the help of artificial intelligence to make this process even more accurate and instantaneous, which are slowly being rolled out throughout the league. Using these analytics allows coaches to make adjustments in game to take advantage of weaknesses they are seeing that day, or better defend against players playing especially well – for instance if a goalie is weak on the glove hand a coach can have their players block shooting lanes from that side to help prevent goals. Beyond these in game adjustments, the ability to immediately re-watch plays allows coaches to more effectively challenge goals if they believe a play was offside, there was a high stick that redirected the puck, or goaltender interference inhibited their goalie from making a save. This ability is invaluable in the playoffs where goals are hard to come by and any of these plays could decide who progresses to the next round.
Beyond hockey, analytics are being used in similar ways in tennis, basketball, football, and nearly any other sport being played at a professional level. The NBA is likely at the forefront of this movement and nearly every team in the league has hired a staff of data scientists to help with the endeavour. The Golden State Warriors are said to be one of the teams using data most effectively which has helped them launch a dynasty and become one of the most successful franchises in league history. In addition, many analysts attribute the rise in three-point shooting to data analysis, as it has risen in each of the past eight seasons. Athletes are embracing this trend and even using wearables to track attributes such as sleep and fatigue levels – data analysis is becoming part of the day to day life of professional athletes and not just something used on the playing field.
Professional franchises have even more incentive to pursue data analytics than simply maximizing their talent, it also has the ability to build fan engagement and loyalty. However, the data collected for this purpose is often that of the fans themselves and not the players. Jonathon Kraft, president of The Kraft Group and the New England Patriots has launched the Kraft Analytics Group (commonly referred to as KAGR) initially focused on mining data for the benefit of the Patriots. KAGR focuses on all sorts of fan behaviour, tracking everything from pro shop purchases, to which ticket holders show up to the game, to who opens emails from the franchise. This data then allows them to draw conclusions about what truly matters to the fans and how to cultivate an experience that will build better fan loyalty and cause people to spend more on the franchise. Kraft believes it is easy to keep fans engaged while the team is hot and making deep playoff runs year after year, but he recognizes that these good times will end and it is important to have a loyal fan base to keep the Patriots going through difficult years. Although KAGR was created to serve the Patriots franchise, they have begun to grow and are offering their services to other professional sports franchises and colleges who have seen the value they offer in creating a better fan experience and more loyal base.
As we have seen throughout the years, data analytics in sports is becoming ever more important in remaining competitive and building a premier fan experience. These trends span almost all professional leagues and promise to elevate the quality of play and the fan experience in the years to come. I’m interested to hear if any of you have ideas of how data analytics will disrupt the athletic landscape next!