Week 2- F1 GFT AI Driver Rankings: Leclerc holds P1, Verstappen up to P3 with win in Saudi Arabia
29 March 2022
by Bob Francis
Go Full Throttle Racing News
The Red Bulls rebounded after the Week 1 disaster in Bahrain with World Champion Max Verstappen winning in Jeddah and Sergio Perez won the Pole Position and finished P4. Mercedes is still not on form as George Russell finished P5 and Lewis Hamilton was a distant P10. Ferrari continues to be on top of the field with Charles Leclerc finishing P2 and Carlos Sainz P3.
“Yes, it was great to rebound after the issues we had and what a great race. It was a very strategic race for Max, not taking too much out of the tires to make sure he had enough to attack at the end, and some great racing between him and Charles; thankfully he had enough to hang on at the end,” said Red Bull Team Principal Christian Horner.
With the addition of all the data from Jeddah (FP1, FP2, FP3, Qualifying, Race) the Go Full Throttle AI Driver proprietary algorithms went to work to produce the updated rankings for Week 2.
Ferrari Still on Top
No change at the top as Leclerc holds P1 and Sainz P2, however Max Verstappen’s win vaults him up to P3 in this week's rankings. Mercedes driver George Russell holds at P4 with his 5th place finish in Saudi Arabia and Sergio Perez jumps 3 spots to P5 with his Pole, laps led, and 4th place finish.
The Go Full Throttle AI Driver Rankings is a cloud based predictive analytics system that uses our proprietary algorithms utilizing artificial intelligence and machine learning technology to dynamically tune and improve accuracy over time.
How do the Go Full Throttle AI models work? (Repeated for context as we have new subscribers joining each week)
The Go Full Throttle AI Driver Rankings is a cloud based predictive analytics system that uses our proprietary algorithms utilizing artificial intelligence and machine learning technology to dynamically tune and improve accuracy over time. Based on our Pre-Season rankings and the results of F1 testing, Practice sessions 1, 2, and 3, qualifying and the race results from Bahrain and Saudi Arabia, our algorithms go to work crunching the data and learning. The complex math also includes inputs such as top speed, lap times, and laps led.
How do predictive models work?
Can artificial intelligence and machine learning algorithms really make accurate predictions? YES! In fact, our proprietary models accurately predicted 8 out of 10 F1 race wins in 2021, including Max Verstappen’s Driver Championship over Lewis Hamilton. Our NASCAR model was equally as accurate correctly predicting 7 of the drivers making the Round of 8 in the 2021 Cup Playoffs as well as predicting Kyle Larson winning the Cup Series Championship. These models will only get “smarter” in 2022 as more data and “learning” will improve accuracy.
Context is key!
“Artificial intelligence refers to the general ability of computers to emulate human thought and perform tasks in real-world environments, while machine learning refers to the technologies and algorithms that enable systems to identify patterns, make decisions, and improve themselves through experience and data” according to Columbia University’s School of Engineering. But Microsoft’s definition breaks this complexity down even more: “AI and machine learning enable companies to discover valuable insights in a wider range of structured and unstructured data sources. For better, faster decision-making, data scientists use machine learning to improve data integrity and use AI to reduce human error — a combination that leads to better decisions based on better data.” For us motorsports fans, we might use the analogy that artificial intelligence (AI) is the car and machine learning (ML) is the engine — you need both to win.
Dynamic tuning to improve accuracy
When we say “dynamic” we are referring to “near real time” data continually feeding the models. Besides the obvious final race results, as an example, our system will “watch” a number of data feeds looking for trusted information, such as the F1 live leaderboard with lap times during practice or qualifying results, laps led on race day, and final results.