Forward of a grand prix weekend, most of us wish to share predictions or try to guess who will come out on prime on a Sunday. Knowledge scientist Mariana Antaya took these chats one stage additional and constructed a machine studying mannequin to try to predict F1 race outcomes. To date, her mannequin has accurately known as the winners of three grands prix this season.
“I am a very large Method 1 fan,” says Antaya when talking with Motorsport.com. “Machine studying and all these algorithms are actually extensively utilized in Method 1 by the groups. I do not assume as many individuals know, however the race engineers are utilizing this for his or her technique in actual time.
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“So, I needed to attempt to predict the winner as a enjoyable train, simply to see, like, how good we are able to get with the information that is obtainable.”
To do that, Antaya began constructing a mannequin of her personal. Armed with lap instances from final yr’s Australian Grand Prix, which was sourced from the FastF1 API information retailer, Antaya set about evaluating the 2024 race outcome with qualifying performances in 2025.
As soon as the rookies have been faraway from this system, which Antaya admits is the one issue she “interfered with” as there was no information to benchmark in opposition to, she started coaching her mannequin. Utilizing a gradient boosting device, Antaya predicted the lap instances for the race in Albert Park, and her program accurately picked because the winner.
“I stated on the finish of the video, that is clearly a easy mannequin, and I did not realize it was going to foretell proper,” Antaya says. From there, the venture began rising because the F1 group gathered round to see what number of extra races Antaya might accurately name.
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“I needed it to be a crowdsourced kind of factor,” she provides. “So, all the viewers might say ‘I actually need you to incorporate climate information in it,’ or ‘I actually need you to incorporate the observe classes within the mannequin.’
“I needed folks to inform me what different options they needed so as to add to the mannequin to enhance it over the course of the season.”
Method 1 Fan Mariana Antaya
Method 1 Fan Mariana AntayaMariana Antaya
Mariana Antaya
And enhance it has, because the machine studying mannequin is continuous to foretell race winners accurately. This doesn’t imply it’s excellent, nevertheless, and Antaya is now including extra datapoints to this system to assist enhance its accuracy.
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“Having extra information goes to assist the mannequin be taught extra and it is going to have the ability to make higher predictions,” she explains. “In the event you solely have a lot information, it will have a really small thoughts, I suppose, and it will not have the ability to perceive as a lot.”
As a way to broaden the thoughts of her mannequin, Antaya added climate information forward of the Japanese Grand Prix, which included the possibility of rain through the race and observe temperatures at Suzuka. Along with this, wet-weather efficiency of the drivers was additionally added, and this system used this to accurately predict ’s victory on the race.
The following large step for the mannequin got here forward of the Saudi Arabian Grand Prix this weekend, when it was skilled on every staff’s efficiency thus far this yr. Antaya defined that the additional strand of knowledge would assist her program perceive that groups like and have made a step ahead in 2025, whereas others reminiscent of Crimson Bull aren’t performing persistently in addition to they have been in 2024.
“Now we’re bearing in mind extra of a holistic image of how properly the automobile and the staff is performing,” she explains.
‘Stunned’ by the collection
and TikTok has been rising in recognition with every successive add, and the clips have even reached Method 1 itself. A handful of engineers from F1 groups on the grid reportedly reached out to Antaya after she began importing, and she or he’s now trying ahead to discovering out how shut she bought to the prediction fashions used within the collection.
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“I have been shocked [by the response]. I have been actually, actually shocked,” she says. “I actually don’t know [how the teams do it]. That is a black field to me, I want I knew. However I hope I am doing it accurately or one thing related. They’re utilizing, most likely, far more advanced fashions and far more information that they’ve on the automobile although, for certain.”
Hannah Schmitz, Principal Technique Engineer of Crimson Bull Racing
Hannah Schmitz, Principal Technique Engineer of Crimson Bull RacingPeter Fox – Getty Photos
Peter Fox – Getty Photos
With three out of 5 race winners accurately predicted, Antaya is not resting on her laurels as she hopes to make the predicter much more correct. Forward of the Miami Grand Prix, the information scientist says she needs to begin experimenting with extra advanced machine studying processes to extend the accuracy of her predictions and cut back the imply absolute error of the mannequin, which will be regarded as the typical distinction between the mannequin’s predictions and the race outcome.
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However whereas the accuracy of the mannequin might enhance due to extra datapoints and new processes being applied, Antaya is conscious that in F1 there’ll all the time be unpredictable components.
“I feel there’s all the time going to be that barrier,” she provides. “It is actually laborious to have the ability to inform that there is going to be a security automobile this lap, and that that is then going to set off another stream of occasions.
“Possibly we might pull previous information on crash proportion through the race, and that is one thing that we are able to add as one other function. Nevertheless it’s additionally a sport, so it isn’t like we are able to look into the long run and see what is going on to occur on a regular basis.”
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