Data analyticsToday, many F1 car racers are partnering with data analytics companies to make profitable decisions.

Data analytics in racing cars have a long history. Although this technology came to effect only recently, famous car races like Formula 1 have been using big data for many reasons since the 1980s. Even at that time, technical representatives were working closely with drivers to provide a seamless driving experience. Then when the whole concept of big data collection started, computing power got more value. Therefore, it gave birth to data analytics in racing cars. With more technology added, F1 races became extremely interesting. Today, many F1 car racers are partnering with technology companies to leverage disruptive trends in machine learning, data analytics, edge computing, data science, etc. Even famous brands like Mercedes, Honda, McLaren, and Ferrari are relying on data analytics to power their racing cars. In this article, IndustryWired takes you through seven ways data analytics is benefiting F1 and other races.

7 Ways Data Analytics is benefiting Racing

 

Sentiment Analysis in Viewership Engagement

Viewership engagement plays a big role in shaping car races. One of the biggest examples of this is the birth of the NASCAR Fan and Media Engagement Centre. At the centre, data is aggregated based on fans' sentiments and helps sponsorers track what makes them bet on the race. During its first year of operation, over 18 million interactions were analyzed.

Real-Time Damage Control

Car racers often rely on gut feelings to take decisions in real-time. But it is completely different for the team behind them. They can use data to analyze and find the best way to opt out of trouble. For example, if a car gets into a minor accident in the middle of the race, the team can look for a quick solution using data analytics and utilize that.

Understanding the Condition of the Car

Managing the temperature and pressure of the car is as important as a driver’s health. The car designers need to make cars that better suit the temperature to keep the driver and the car safe. Therefore, car manufacturers are collecting geographical data to prepare for the race.

Maintaining Vehicle Performance

While understanding the condition of the car is one side of the coin, maintaining its performance is on the other side. Even a small amount of data can unravel a whole mechanism for tracing cars. That being said, usually, racing cars use this data to analyze where engines go wrong and find appropriate solutions to those problems.

Validating Drivers’ Performance

Similar to vehicle’s performance, drivers’ performance also plays an important role in many deciding factors. Small factors like RPM, speed factors, steering angle, and throttle position will help determine what the driver is up to.

Keeping Track of Maintenance

Thousands of cars take part in the racing every year. Managing and maintaining them particularly might be a difficult thing. Therefore, they keep a backlog of data to ensure how long the car has run and what happened during the time.

Predicting Machine Failure

Machine learning and data analytics is amazing combination of technologies that could predict machine failures easily. When a racing car is speeding at 200 mph, it is difficult to handle in case the machine fails to run properly. Therefore, predictive analytics are used to identify possible failures beforehand.