The most popular example of application of analytics in sports is from the Hollywood movie Moneyball, which is based on the true story of a baseball coach who assembles a stellar team despite having a very limited budget. He uses the help of an economics student to use data models to identify players who have the potential to perform outstandingly, but are under-valued in the market. Fast forward today, and this has become a best-practice in team-building across nations, across sports. This has made it necessary for player data to be collected and maintained exhaustively. The availability of all this data has led to many more analyses.
Analytics for winning
The rise of analytical approach in sports can be seen in the areas of training and strategy. Many coaches believe that performance analytics is the most important tool today for players and teams to identify their weaknesses track their improvements, observe particular trends in performance, and to study the performance of opponents in order to devise an effective strategy to defeat them. In every sport, there are now numerous tools available for making more sense out of game-play data. The data gathering activity is a challenge since a large part of it still relies on humans observing the game and interpreting what data to feed into the system. There is also a lot of subjectivity in the data, which is a black-box for analytics tools. But with advancements in image processing and artificial intelligence, this gap is being addressed faster than most people are aware of.
Using data to engage the audiences
In the last decade, many sports fans witnessed a fad for collecting trading cards which carried the performance data of their favorite players. As audiences get more tech-savvy, their appetite for numbers is growing too. This has given rise to a whole new industry of fantasy sports, which use real-world player data to simulate virtual tournaments where users can build their own teams and manage them, and also bet on their favorite players. Even live sports broadcast programs now include more than just commentary to engage the audience: they use real-time analytics and animation to play out what-if scenarios, to predict the performance of key players, and also use social media analytics to gauge the sentiment of the audiences in order to create the right content for the right opportunity.
The dark side: Betting Scandals
Every powerful tool lends itself to misuse in the wrong hands. Illegal betting in sports is perhaps as old as sports itself, and has been at par with (sometimes ahead of) sports when it comes to using the latest technologies. The availability of huge amounts of data and analytics has made it easier for team managers to optimize their budget when recruiting players. Similarly, it has made it easier for amateur bettors to participate in illegal betting, giving them access to the same information and tools used by professional bettors. As a consequence, there is now a huge online illegal betting market, with a high demand for quality data. Even fantasy sports has fallen prey to this trend, as was seen in last year’s unearthed insider-trading scandal in a large fantasy sports management company.
It is with high level of certainty that we are going to witness heavy use analytics in different sports. For further reading on role / application of Analytics you can refer to www.globcontech.com/blog/.
