Fan Engagement Tools Help F1 Coverage On Social Media Thrive
![A variety of data metrics is helping fans better understand what’s happening on the racetrack as well as inside each car.](/cache/uploads/content_images/F1_Car_Performance_Scores_imge_789_527_70_s.jpg)
A variety of data metrics is helping fans better understand what’s happening on the racetrack as well as inside each car.
Formula One has enjoyed decades of being one of the world’s most popular sports, with millions of fans making up a diverse and passionate community of TV viewers. Now it’s being considered the fastest growing sport brand on social media platforms too.
Total video views across Formula One’s own digital platforms and social media were up 46 per cent against in 2021 to 4.9 billion, with its unique users on F1.com and the F1 app up 26 per cent to 70.5 million, and page views up 13 per cent to 1.3 billion. The sport’s audience between the ages of 16-35 is expected to rise to one billion this year, according to global sports analysts Nielsen Sports.
When it comes to fan engagement on social media, F1-owned accounts generate 60% of the interactions and video views, with teams generating 29% and drivers 11%.
All of these eye-opening numbers are a direct result of television broadcasters’ continued efforts to engage fans away from the big screen with live streaming of races along with new interactive features and thrilling driver POV footage (and race car metrics) that keeps them glued to their portable screens. The 2022 F1 season started on March 27th (in Saudi Arabia) and runs until November 20th (in Abu Dhabi).
Indeed, social media has turned out to be a highly efficient way for racing fans to talk about the sport, read the latest news, and engage with drivers (and themselves) and for broadcasters to increase their viewership, with the sport enjoying new fans in countries it has previously not been able to break into, like India and the U.S. By leveraging their various digital platforms (Facebook, Twitter, Instagram, etc.) broadcasters of the sport—like Sky Sports and BBC Sports—are developing a closer relationship with fans, which in return helps TV viewership as well.
![Broadcasters see social media as a highly efficient way for racing fans to talk about the sport, read the latest news, and engage with drivers (and themselves).](https://www.thebroadcastbridge.com/uploads/content_images/_Medium/Sky_Sports_Fi_Coverage_online.png)
Broadcasters see social media as a highly efficient way for racing fans to talk about the sport, read the latest news, and engage with drivers (and themselves).
For the 2022 season, a variety of new technical regulations mean a brand new generation of F1 car which in turn will bring a new set of data for broadcasters to serve up to the fans—both nonlinear TV and online. With 20 cars and 10 constructor teams all generating live monitoring data every second, there is a plethora of information that can be turned into visually stunning features for fans to follow and interact with. The latter is the goal of broadcasters looking to keep fans engaged.
With 300 sensors on each race car generating more than 1.1 million data points per second transmitted from the cars to the pits, and drivers wearing special devices that monitor heart rate and temperature, Formula 1 is a truly data-driven sport where much of the thrill comes from extracting on performance statistics. To enable fans to see it all in real time, F1 has formed a relationship with Amazon Web Services. In 2020 the sport was able to add six new, real-time racing statistics graphics.
F1 relies on the wide variety of AWS cloud-based services to stream, process, and analyze the data in real-time, and then present it in a meaningful way for F1’s global TV viewers.
One example is “Car Performance Scores”, which isolate an individual car's performance and allows race fans to compare its performance to that of different vehicles head-to-head. The new set of statistics is processed using machine learning to give fans the ability to compare their favorite drivers and cars and better predict race outcome.
These new metrics will also be used to display as an on-screen graphic that provides fans with a complete breakdown of a car's total performance using four core metrics: Low-Speed Cornering, High-Speed Cornering, Straight Line, and Car Handling. The graphic clearly illustrates how those metrics compare from one car to another, enabling race fans to gauge a given car's relative performance in those different areas and see where each team and driver is leading the pack or losing crucial time to their rivals.
Other “F1 Insights” that are keeping fans engaged include: Exit Speed, Predicted Pit Stop Strategy, Pit Window, Battle Forecast, Pit Strategy Battle, and Tire Performance. In total, they offer fans more visibility into the split-second decision-making and action on the track, as well as behind the pit wall where the team strategists operate.
![The BBC Sport app will bring together live streams, on-demand video, social commentary and additional content.](https://www.thebroadcastbridge.com/uploads/content_images/_Medium/BBC_Sports_App.png)
The BBC Sport app will bring together live streams, on-demand video, social commentary and additional content.
Another online feature, High-Speed/Low-Speed Corner Performance, allows fans to see how well drivers tackle the fastest bends on the track traveling at more than 175 kph/109 mph and slow cornering (below 125 kph/78 mph) compared to other vehicles, which is critical to lap time.
To create these new insights, Formula 1 uses 70 years of historical race data stored in Amazon Simple Storage Service (Amazon S3), combined with live data that is streamed from sensors on F1 race cars and the trackside to the cloud through Amazon Kinesis, a service for real-time data collection, processing, and analysis. During each race weekend 160 terabytes of data is sent between the remote race circuit and the F1 Media and Technology Center in Biggin Hill, England. It is then uploaded to the AWS cloud for near real-time processing.
F1 engineers and scientists use this data to leverage machine learning (ML) models with Amazon SageMaker, AWS's service for building, training, and deploying ML models. F1 analyzes race performance metrics in real-time by deploying those ML models on AWS Lambda, which runs code without the need to provision or manage servers. All of the insights are then integrated into the international broadcast feed of F1 races around the globe, including its digital platform F1.TV, giving fans a better understanding of what’s happening on the racetrack.
AWS's services help F1 perform intense and dynamic data analysis, said Rob Smedley, chief engineer at F1. “The F1 Insights we're delivering together are bringing fans closer to the track than ever before, and unlocking previously untold stories and insights from behind the pit wall. We're excited to bring these insights to life, allowing fans to go deeper into the many ways that drivers and racing teams work together to affect success.”
There’s no denying that online fans are hooked and each year F1 adds new features and services that increasingly resonate with them. For broadcasters, collecting data, aggregating, and analyzing it from those 300 car sensors, is leading to a growing online fan base and, ultimately, financial success.
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