When Marcus Ericsson, driving for Chip Ganassi Racing, won the Indianapolis 500 in May, it was in a car outfitted with more than 140 sensors that provided data and predictive analytical insights not just for the race team, but for fans as well streamed world on and around the Brickyard.
NTT, Penske Entertainment’s partner for the NTT Indycar series, including the Indy 500 race, collected an estimated 8 billion data points through the sensors on Ericsson’s car and those of its 32 competitors. Along with data collected from previous seasons and the first five events of the NTT Indycar Series, NTT uses a combination of data analytics, digital twins and artificial intelligence (AI) capabilities to give fans access to in-depth, real-time insights Head-to-head overtakes, pit predictions and other elements of the race.
“From a business and sporting perspective, our sport has always been based on the development of technology,” said SJ Luedtke, Indycar’s vice president of marketing. “If you look back to the early days of the Indianapolis Motor Speedway, it was built in a sense as a proving ground for the burgeoning auto business and as a location for many automakers based here in Indianapolis and the Midwest to bring their latest inventions and test drive them you.”
Today, Luedtke says, NTT and Indycar are continuing that tradition by considering how to use data beyond the track to build engagement.
“We want to leverage all of this technology and the data it generates and find ways to build engagement elements for our fans, our sponsors and other stakeholders involved in the sport outside of the circuit to make it more attractive, more enjoyable, and speaking ideally targeting new fans who may not be automobile-related but are super tech-savvy and love data and/or storytelling,” he says.
Improving the fan experience
For this purpose, NTT creates a digital twin for each car in the series. Historical data forms the basis, and each car is equipped with more than 140 sensors that collect millions of data points during the race to feed the digital twin. This data includes everything from speed and oil pressure to tire wear and g-forces. NTT uses AI and predictive analytics on the digital twin’s data to provide fans with insights that previously would only have been available to race team engineers, including race strategies and predictions, intercepts and battles for position, the impact of pit stops and the impact of fuel levels and tire wear .
Indycar provides fans with insights through the interactive Indycar app and social media channels. It also provides insight into NBC’s production team.
“Our most ardent fans have the opportunity to get closer to a sport they love or a driver or team they love,” says Luedtke. “This is where the data and analytics come in. We’re working with the team to capture these millions of data points over the course of a 90-minute race to help fans understand what’s going on.”
For example, says Luedtke, it’s common to look at the front of the race, but sometimes what’s happening in the middle of the field gets lost in the mix. “People compete for positions in order to move up in the points system overall,” says Luedtke. “We can look at this data in real time and then start making predictions using AI and the Smart Platform.”
You’re not allowed to change channels if the NBC analyst mentions that your favorite driver is in seventh but can overtake sixth in five laps because they’re fighting for the championship, Luedtke says.
“There are also opportunities for us if we involve casual viewers to help them understand what’s going on in the race,” he adds. “Being able to tell a story about why someone progressed based on different key components or data based on two drivers’ pit stops allows us to explain the sport to new fans.”
In just over three years, Indycar has doubled engagement and dwell time on its app at race weekends, says Luedtke. “It’s possible to see your favorite driver’s telemetry data in real-time during the race, in sync with the onboard camera, so you feel like you’re in the cockpit with them,” he says. “They see many of the key telemetry and data points working in their vehicle.”
On the way to a smarter venue
In terms of technology, Bennett Indart, vice president of SMART World Solutions at NTT, calls the partnership “a business-centric approach” to “improve the fan experience, encourage new fans to the sport, and provide that forum for enriching Indycar in Indycar data.” .”
For this purpose, NTT also uses data to improve the fan experience at the venues. It deployed its Smart Venue solution at the Indianapolis Motor Speedway (IMS). Taking inspiration from efforts to create smart cities, the app treats the venue, which attracts more than 350,000 fans on race day, as a mini-city.
“We’re thinking more of the idea of a city mobilizing and planning for a day, everything from moving people to getting supplies through emergency services to being able to see around the corner where we might want to send someone before it.” an incident happened,” says Luedtke.
For Indycar, the Smart Venue’s AI provides full visibility of the venue, with data calibrated every 30 seconds with greater than 90% accuracy. AI-enabled optical detection technologies combined with real-time flow data at the entrance gate enable:
- Crowd and traffic monitoring, including real-time analysis and alerting
- Number of people and insights into congestion for specific gates and tunnels using predictive analytics
- Faster response times to potential problems and risks
For fans, the Smart Venue offers insight into the fastest and least congested routes through the world’s greatest sporting event.
“It’s the second largest city in Indiana on any given race day,” says Indart. “You can imagine 350,000 people trying to get onto the Indianapolis Motor Speedway. Over the past few years, we’ve helped the operations team understand where the bottlenecks lie. This year we even added a feature to give this to fans themselves on their mobile devices.”
“It’s all about data and data-driven approaches to solving business cases,” adds Indart.