Sports analytics is set to become a driving force in the sports industry. Internet of things generates the big data which drives the analytics that is helping industry experts to take better decisions on a variety of issues ranging from selection of players during team formation to tactical plays during a game to increasing fan engagement. For example, in earlier article on Predictive analytics in cricket, it was explained how the possible outcome of a game could be predicted based on earlier data for similar events. The way fans consume sports data and how the game is played is changing the face of sports. The objective of analytics applied to sports data is to turn it into the value for both consumers as well as sports professionals.
Due to advances in technology and the need for real time analysis and prediction, the way in which we collect data is also evolving rapidly. Connected devices and the internet of things is going to play a huge role in this transformation. In order to track the performance of a person during a sporting event, many varieties of wearable gadgets are coming into the market. (Recently Google pushed this “wearable” concept into the mainstream and wearable market is growing at rapid rate). Wearable gadgets that are designed to track daily workout routines and calorie burn are getting more stylish and easier to include in our daily lives versus the old school heart rate monitors that relied on a body strap and a clunky watch. Tracking, saving, sharing and comparing your workout statistics like route, speed, distance, calories burned and even your ‘Suffer Score’ takes seconds but these are nothing compared to what’s being implemented at professional level to track the efficiency of sports person.
Example – Athletes tuck lightweight tags into their jerseys and GPS nodes that are spaced throughout the stadium pick up player movements down to 20 centimeters. The system tracks all of the basic information like heart rate, speed and distance but goes way beyond. After scientific micro-measurement like Inertial Movement Analysis can measures acceleration, deceleration, changes in direction, jumps and force using accelerometers and gyroscopes tracking every athlete’s movement in a real-world coordinate system. Data is synced in the cloud and immediately available for visualization and analysis to take further decisions if required.
What if upon entering a sporting event, fans are given wristbands to wear that track their movements or their own wearables are synced to the team app and GPS nodes in the stadium? Once the fans wearable starts delivering data during the sports event different types of analytics could be generated which could predict the reaction of a particular person/team or even the outcome of game as well. For example
Fan Analytics – heart rate, calories burned, arms waived, hands clapped, jumps up and down combined with decibel levels in the stadium.
Athlete Analytics – heart rate, burst speed, mph, total miles, g-force of a tackle and vertical jump on a dunk or catch.
A modification of this type of application is already being implemented in manufacturing. One of our customers has installed such GPS-enabled devices for tracking their manufacturing operations. Instead of the devices worn around by fans, their employees wear a lanyard and this allows the company to get a good picture of their labor costs. For example, they can generate up to the hour (or even minute) data on how much time employee #5 spent on workstation A and how much time s/he spent on workstation B in the last two days. This enables management to accurately account for their labor costs in their manufacturing operations, thus helping them to track manufacturing overhead, for example.
The underlying similarity between all these applications must be clear: Internet of things enabled connected devices generating tons of big data to enable experts to better understand their systems – whether the system is a sports team or a small manufacturing plant ultimately does not really matter.
Originally posted on Wed, Apr 09, 2014 @ 08:52 AM