With Wimbledon, the oldest tennis tournament in the world starting this week, we’ve been reading up on IBM’s new predictive analytics tool used for the tournament, Slamtracker. And we can tell you that IBM has been acing predictive analytics by analyzing possible outcomes for world tennis tournaments.
Slamtracker is based on the same analytics software that many organizations use to improve their predictive business capabilities. However, in this case IBM is using Slamtracker for a slightly different purpose—to predict what it takes for each tennis player to beat his/her opponent. The tool compares this data with each player’s stats to track his/her strengths and weaknesses—calling out what specific moves will give the play or opponent an edge in the match.
Slamtracker starts by analyzing the last 7 years of Grand Slam Tennis data—a whopping thirty-nine million data points, then analyzes what patterns and styles past players have exhibited to win the tournaments. These statistics are updated in real-time during the match, adding another dimension of analytics. Slamtracker evaluates the matches to determine what the second by second “keys to winning” are.
Slamtracker is just one of many IBM tools used to harness the power of data to gain insights on and off the court providing information in a way to make smarter business decisions.
For example, an IBM retailclient, fashion brand Elie Tahari, mapped future orders, current production and inventory against the plan, adjusting for any unforeseen factors such as stores opening or closing. Using historical sales data from the stores where the line was sold, Elie Tahari was able to target inventory figures to meet anticipated customer demand levels for up to four months in the future.
Other clients use predictive analytics software to analyze changing weather patterns and the effects on delivering goods or to decide what social media tools and strategies had the biggest impact on meeting company communication goals. No matter the purpose, the point is, data analytics is everywhere.
But mostly predictive analytics has a place outside the sports arena and inside almost any business.