In the popular world of sports, with the growth in Big Data, there has been an emergence of sports data companies. The role of such organizations is to collect data, historical and even current, analyze it and provide their clients with predictive insights. Their clients are usually sports teams, associations and federations. Sports television channels also use these insights to make their broadcasts more meaningful and engaging for the viewers. Those who work in Big Data, therefore, apply to the best data analytics programs which gear them up for roles like this.

 

Accuracy in tracking team performance – Historical performance by different countries was tracked using a range of parameters that could impact current performance. For example, the data scientists looked at aspects like what difference does it make if the team was playing as the host nation, on home ground or continent and other such aspects.

 

Impact of individual players – Some Big Data models used the process of trying to understand the impact of the presence or absence of an individual player in it. Such models can work out how the team will perform, and is also quantify the impact by creating situations created due to swapping players in and out of the team.

 

Simulation of tournaments – Many data analytics companies came up with probabilistic forecasts based on a simulation of tournaments that they were able to create and evaluate. Using technology to analyze all past matches and then using it to create a match that replicates what the upcoming one is expected to be, helped teams to become better prepared for the strategies they need to use.

 

Key parameters – Indicators like the number of touches, the movement speeds of players and average possession time were crucial elements that some teams which used Big Data for their performance assessment, tracked.  This kind of in-depth analysis allowed them to rectify issues that had the potential to slow down their game or make them weaker opponents. They worked to improve the parameters that had gaps.

 

German Football Association in collaboration with SAP had actually developed a tool based on Big Data for competitive advantage during the FIFA World Cup. Big Data itself will not be able to forecast results correctly. The data analysts and scientists have to be able to apply their skills and knowledge to turn the raw data into insights that have the potential to make a difference to actual performance on the field.

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