Week 3- F1 GFT AI Driver Rankings: Leclerc Builds Lead with AUS Win
11 April 2022
By Bob Francis, Managing Editor
Go Full Throttle Racing News
Ferrari driver Chales Leclerc builds his points lead in F1’s Driver Standings (now at 71) to a 34 point gap to over P2 George Russell (Mercedes) following the Grand Prix in Australia where Leclerc wins and Verstappen gets his 2nd DNF of the season. When taking into account all 8 inputs into our models, the Go Full Throttle F1 AI models have Sergio Perez (Red Bull Racing) up two spots at P3, Carlos Sainz (Ferrari) dropping 2 positions to P4, Lewis Hamilton (Mercedes) at P5, and current F1 Champion Max Verstappen at P6, down 3 from last week.
The data says Leclerc continues to have the best odds for the win, however Max Verstappen has a strong resume at Imola as well as in the Sprint qualifying format which debuts this weekend in Italy. While “Mad Max” is P6 in the rankings, he is P2 in the race prediction models. Bet accordingly!
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)
Algorithms
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, 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.
