F1 Preseason GFT AI Driver Rankings: Verstappen P1, New Names in Top Ten
Bahrain International Circuit — 20 March 2022 -The defending F1 Champion Max Verstappen of Red Bull Racing ranks P1 in our F1 Preseason GFT AI Driver Ranking ahead of the season opener today in Bahrain. Admittedly our algorithms were starving for data with so many changes in the F1 car, so little preseason testing time, and some major surprises during the Friday and Saturday practice sessions and qualifying. Our F1 staff has been tracking lots of chatter that the Ferrari’s had greatly improved speed and handling and that appears to be case based on qualifying results- LeClerc P1 and Sainz P3.
News Names in the Top Ten
While seeing Valtteri Bottas in the top 10 is not new, many analysts questioned if Alfa Romeo with the Ferrari power would perform at the level Bottas had when driving for Mercedes. The surprise of the qualifying session was clearly the performance of the Hass driver “K-Mag” Kevin Magnussen at P7. George Russell also showed that he has ability and the car, placing his Mercedes P9.
How do the Go Full Throttle AI models work? (Repeated for context)
Algorithms
The GFT AI Driver Rankings use 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 as well as qualifying for the Bahrain GP, our algorithms went to work crunching the data and learning. The complex math also includes inputs such as top speed, and qualifying position.
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.
