As the countdown begins for the Olympic Games in London starting July 27, 2012, the global sporting fraternity is expectedly making predictions on superstar performances. Will the 100-meters favorite Usain Bolt beat the world record at the Games? Predicting if Bolt can become the fastest athlete at the Games will indeed depend on his current form, the quality of competition, the external environment, among a host of other factors. However, Predictive analytics can tell you if Bolt is indeed best placed to walk away with the top honours.
Predictive analytics has entered the sporting arena in a big way, because sports has become a big business with diverse stakeholders that include business groups which double up as major sponsors, consumer products that leverage celebrity endorsements, sporting bodies and club owners, and of course the sports persons themselves. Data analytics is being applied in different sporting disciplines to predict players performance, team building, market segmentation, and attendance forecasting – which is key to revenue forecasting for most stakeholders. Analytical tools are also being used for planning and organizing major events like the Olympics itself.
In fact, even a sporting team's logo, colors, advertising campaigns and promotions, are being decided based on audience data. The analytics weighs the importance that fans attach to these symbols, and the resultant audience response and turnout at the events.
Baseball was arguably the first discipline to use data analytics to enhance team performance. During the late 1990s, a little known US club Oakland Athletics hired a stats grad to analyze baseball statistics in order to hire promising players undervalued by the market. When signing up the players, the club analyzed data on every player and every game to predict their performances. This allowed the club to sign top players who may have been less known but were equally good on the field. In just a year, Oakland Athletics climbed to number 2 ranking in the league. This also set off the adoption of data analytics by baseball teams, and then by a wide variety of sports.
Take the case of Leicester Tigers, nine-time champion of English rugby union's Premiership and two-time European champion, which is now using predictive analytics to build its talent base, measure performance, optimize tactics and detect risk. The club uses analytics software to assess the likelihood of injury to players. Losing key players can hit the team's performance and affect spectator attendance.
Analytics was reportedly being tried at this year's Wimbledon too, wherein the software tracked aces, serve speed and many other real-time statistics during matches. Viewers could get a sense of how the match would progress. Such analysis would even help coaches to better prepare their players for the big matches.
Analytics has created grounds for more enterprises to enter the sporting arena, with precise judgment calls on how far their investment can take them.