How data analytics is changing the game of modern sports: Understanding sports analytics
November 10, 2017
In today’s scenario, when every industry is facing a constant roller-coaster ride with profits and losses, there is one industry that is going straight up regardless of the market scenarios. The sports industry has been blooming over the decades. However, one of the changes that revolutionised the sports industry and proved as a game changer was the merger of data analysis with sports. No one had ever thought that these two things combined would create such a massive success.
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.’
Its applications:·
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.
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.’
Its applications:·
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.
Future Enhancements:
1. Data analytics can be used to determine specific playing styles of players and then determine best strategy to play a shot
2. Constant monitoring of a player could lead to findings related to the effect of a routine on a player's life. Their sleeping patterns and eating habits could be altered to obtain the best results on the field
3. The effect of genes on the performance of a player could be determined by compiling data from their family tree
Conclusion:
Data analytics in sports is a huge revolution that has begun to change the face of modern sport. With the entry of wearable trackers and sensors, the accuracy and precision of judgement in sports has reached heights. Using it further, many more ground breaking developments can be made in the field of sports.
1. Data analytics can be used to determine specific playing styles of players and then determine best strategy to play a shot
2. Constant monitoring of a player could lead to findings related to the effect of a routine on a player's life. Their sleeping patterns and eating habits could be altered to obtain the best results on the field
3. The effect of genes on the performance of a player could be determined by compiling data from their family tree
Conclusion:
Data analytics in sports is a huge revolution that has begun to change the face of modern sport. With the entry of wearable trackers and sensors, the accuracy and precision of judgement in sports has reached heights. Using it further, many more ground breaking developments can be made in the field of sports.