How Data Analytics Drives the Best Formula One Teams Ahead?

Big Data Analytics has already taken the world by storm. But will using this concept for a sport like Formula 1 Racing be fruitful? If yes, then in what ways? Let's find out in this article!

How Data Analytics Drives the Best Formula One Teams Ahead?
06th Mar, 2019
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Speed is an important quotient whether it is a technology or a race. With information being a driving factor for each process, every industry has started using data to analyze and compare the outputs. The same happens when we watch a cricket match ranging from run rate to average speed, everything is measured using sensors. Later on experts analyze the data and compare the performances of each and every player. That is when Big Data Analytics comes into picture. Formula 1 racing is next in this row. As the entire game is about speed, the teams have moved to big data analytics to up the level of performance.

What concerns can be addressed by Big Data Analytics?

  • Analyzing the relative speed of the car
  • Machine/Engine failure or damage
  • Predicting the outcome of a race
  • Strengths and weaknesses of a car
  • Communicating between the departments

And how can all these be overcome:

Analysis of speedBy deploying sensors on the racing pit
Failure or damage recoveryBy constant monitoring the machine status
Failure or damage recoveryBy building a connectivity between departments

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How are they going to do it?

McLaren Group, the famous Formula 1 race team has moved on to use Data Analytics to determine the speed of the car on various points and curves to analyze the performance. A car’s speed depends on the driver as well as the machinery used. Here the turning point is that the data analytics is going to be used not just to measure the speed of the car but the relative speed of the opponent as well. The analysts can predict the race before it even starts.

It is said that an F1 car racing with the speed of 200mph generates 1 GB of raw data each time using the sensors deployed on them. This gigantic data is transformed into predictive models and used to analyze the performance based on the historical data. These sensors record each aspect of the performance whether it is tyre pressure or fuel burn and hundreds of such sensors produce a huge amount of data to be analyzed and predicted.

Is it just about performance?

Looking at the above description you may wonder about how such experts can rely upon such data for performance. However there is another aspect attached to it, which is not just about increasing the performance but about optimizing the stability as well.

F1 race has strict rules about the number of engineers allowed on the pit, which is why at times the teams are unable to analyze the weak points of a car. The mechanics and aerodynamics of a F1 racing car is quite different and complicated from that of a normal car. Hence there is a need for in-depth analysis before and when it finally goes to perform. Due to the restrictions posed on the number of engineers on the race circuit, the communications becomes a major hurdle when there is a technical failure. However with the help of big data analytics real-time strategic decision-making will be possible during the race and technical complications handling will be possible.

Which tool is being used?

The foremost questions arises that which technology may solve this problem? Apache Spark which is an in-memory high speed big data processing engine? Or a smart business intelligence tool like Tableau which will throw the output the moment data is fetched?

McLaren Group is already using SAP HANA which is a strong result-oriented tool equipped with the ability of data modeling, real-time analytics, and much more. SAP has already been one of the leaders in the business analytics market, but associating with a sport like F1 race is a huge milestone.

Till yet we have seen analytics to be used in cricket, with the sensors deployed in the stumps and pitch, each and every movement with the intensity is captured and reflected in the graph. However, it will be interesting to see how real-time data analytics can keep audience engaged with the sport.

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