What is data analytics?Data analytics is the process of examining multiple sets of data in order to draw conclusion about a future event.
Why is it a game changer in sports?
With the availability of huge amounts of data, if data
analytics is applied to sports, astonishing and accurate conclusions can be
drawn out of them. Taking the game of baseball as example, the speed of a
pitch, speed of the bat, ground conditions, humidity, temperature etc. are the
data recorded for every match. This data might seem useless to a viewer, but
using data analytics, we can process it and draw comparisons and conclusions
about a game. Comparisons like ‘performance of a player under particular
temperature/humidity’ or ‘performance of a batsman against a particular pitch.’
· Better precision in
decisions – With the currently available
technology, the speed and other parameters of a game can be evaluated better by
using data analytics. Many times during a game, certain movements are not
accurately visible to the naked eye. They can cause an error in judgement from
the referee’s end. Using technology to determine the accuracy on a real time
basis can help in achieving precision in result.
· Making the game
interesting – Using the tons of data available
from multiple matches, interesting bits and pieces can be carved out for the
viewers. Considering the duration of one season of baseball, things like
‘strong zone of a pitcher’, ‘weak zone of a pitcher’, ‘change in throw of a
pitcher over the season’ and many other interesting details can be compiled by
using data analytics.
· Live on field data
collection – Adrenaline filled sports such as
football and basketball are played at such speed that many of the interesting
moments are just lost in time without being recorded. Using the concept of data
analysis in today’s scenario, the stadiums are now equipped with special
cameras dedicated to every player on the ground. These high speed cameras
record every minute detail from the ‘speed of the ball’ to ‘the body
temperature of the player’ and send it to the server in real time. This data is
further used to make accurate decision in case of confusion and then later on
analysed to determine the performance of players over the series or season.
· Prediction of fan
preferences – A game is made popular by the
number of people watching it. Today, publicity and fan following are the
parameters to measure the success and income of a player. Keeping this in mind,
the preferences of fans play a very important role in sports. Using data
analytics the fans of a particular game can be attracted towards it. Things
like ‘Are the tickets economical for viewers’, ‘Is the timing of a game
accessible to most of the viewers’, and ‘Who is the favourite player in a match?’
can be accurately answered using data analytics.
· Better coaching – With the wearable technology now in market, the coaches can have real time access to the data from a player. Details like heartbeat, perspiration level, fatigue and stress can be monitored by the coach for every player on the field. This will not only help then coach the player better, but also avoid injury. Research shows that the maximum loss faced by a sponsor is when an expensive player sits out of a game or a series because of some injury. This can be avoided with the wearable technology now available.