Round 4 F1 GFT AI Driver Rankings: Leclerc holds P1, but Max Jumps to P2 with Imola win
26 APRIL 2002
By Bob Francis, Managing Editor
Go Full Throttle Racing News
Things were not looking good for the defending champion Max Verstappen after his Red Bull Racing car had mechanical issues and resulting in a DNF in Australia. But it was the complete opposite story after Round 4 in Imola, Italy and the famed home of Ferrari. Verstappen put maximum points on the F1 Driver Standings leaderboard and in our Go Full Throttle AI Driver Rankings, jumping 4 positions to P2 after winning both the Spring Qualifying race and the Grand Prix as well as posting Fastest Lap- the points trifecta.
With his 6th place finish, Ferrari’s Charles Leclerc still has a significant lead, but Verstappen’s win and points bonanza moved him back into contention at P2 with teammate Sergio Perez holding at P3 with his impressive 2nd place finish at Imola. The F1 world is still buzzing about how off Lewis Hamilton’s performance was, finishing a lap down at P13. While Mercedes has been quick to admit their 2022 cars are struggling for both speed and handling, the fact remains that Hamiton’s teammate in the same equipment, George Russell, finished P4 at Imola and sits P4 in the Driver Standings with 49 while Hamilton is P7 with only 28 points on the season so far. Lots of questions and even more pressure for Lewis Hamilton as F1 goes to Maimi for Round 5 — FORMULA 1 CRYPTO.COM MIAMI GRAND PRIX 2022.
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, 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.