© Getty ImagesStrategy Scout: Emilia Romagna Grand Prix 2022 Oracle Red Bull Racing’s strategy team look ahead to the season’s first race in Europe.
ThisweekendwereturntoImola,ortogiveititspropertitle:AutodromoEnzoeDinoFerrari,whichfirsthostedanofficialGrandPrixin1980whenitwrestledthe‘ItalianGrandPrix’awayfromMonza.
Monza quickly retook the title, but Imola stayed as the ‘San Marino Grand Prix’ until 2006, when it was removed from the calendar. The anticlockwise track is an adrenaline-pumping thrill ride and when it returned in 2020, the current crop of drivers loved it instantly.
With that in mind, we asked Hannah Schmitz, Oracle Red Bull Racing’s Principal Strategy Engineer how best to deal with this old school-style track.
Hannah Schmitz On The Pit Wall© Getty Images
During a race the Strategy Team is split between the track and Milton Keynes in the Operations Room, where they will be analysing second-by-second data and seeing if the strategy needs any adjusting. “Whoever is trackside, is in charge of strategy,” explained Hannah. “We decide when we’re going to pit, what tyres we’re going to put on the car and coming up with ways of winning the race.”
Not everything has to wait until you’re at the track, however. As principal strategy engineer, Hannah and her teammates analyse key factors by testing billions of scenarios and combinations using Monte Carlo simulations running on Oracle Cloud Infrastructure (OCI), all to give Max and Checo the best chance to stand on the podium.
Diving Deep Into The Data Is Essential When It Comes To Race Strategy© Getty Images
“Data goes into every decision we make,” Hannah says. “Before we even get to the track, our simulations will have what we expect the tires to do, what we think the overtaking will be at that track, and all the paces we're expecting of our competitors and us. And then when we're at the track, we can use data to better estimate all those variables. Basically, we're constantly using the data and refining those models.”
Once the team is trackside, Hannah will analyse data from practice and qualifying, focusing on variables such as current track conditions, the pace of the car, and tire degradation to further evolve the team’s strategy and map out pit stops.
By leveraging a modern technology stack on OCI, the Team last year was able to increase by 25% the number of Monte Carlo simulations it could run, allowing the team to explore more variables and increase the accuracy of simulations.
Last Time On Track At Imola© Vladimir Rys
Although, as Hannah explains, there are some things you can’t always plan for. “During the race there are things out of our control, such as safety cars, wet weather and red flags. So, when any of these happen it comes down to adapting to those factors and then finding the best strategy.”
Before Imola returned to the calendar, the Team only had two years’ worth of data, so the cars were vastly different. And when we returned in 2020, it wasn’t always plain sailing.
“Imola is a track that we’ve only recently come back to in the last couple of years, so we don’t really have a lot of historical data to rely on, which can make it more difficult to predict what’s going to happen. Last year the race also started wet so that gives us even less data on normal dry, track conditions,” Hannah said, before concluding by adding: “The year before the wet race, we saw that the tyres had very low degradation and there wasn’t a lot of pace difference between them. That means that the undercut or overcut can come into play during the race, and to win we just need to be on it to decide which one to do!”
Imola May Be A Historic Track But It's Only Just Made Its F1 Come Back© Getty Images
