Round 5 F1 GFT AI Driver Rankings: Verstappen Gains with Miami GP Win

9 May 2022
By Bob Francis, Managing Editor
Go Full Throttle Racing News

Very little change in the F1 Go Full Throttle AI Driver Rankings after Round 5 in Miami. Defending F1 champion Max Verstappen earned 26 Driver Championship points for the win and Fastest Lap. After 5 races, Verstappen now has 3 wins and has led 117 laps. However, his 2 DNFs hurt him in the F1 Driver Points where Ferrari’s Charles Leclerc holds a 19-point lead and a 28.5 point lead in the GFT AI Score. By scoring the maximum points the past two races, Verstappen continues to chip away at Leclerc’s lead.

Formula 1 GFT AI Driver Rankings after Round 5 in Miami, FL USA (Image: GFT Digital / gofullthrottle.net)

Verstappen’s Red Bull Racing teammate Sergio Perez is P3 in this week’s rankings after his 4th place finish in Miami. Mercedes driver George Russell is P4 after his 5th place finish and Carlos Sainz from Ferrari P5.

Hamilton In Trouble
7x F1 Champion Lewis Hamilton is falling farther behind each week. Coming out of Miami, Hamilton is 68 points behind Points leader Leclerc, and 49 points behind P2 Verstappen.

The Go Full Throttle F1 AI Driver Rankings are published weekly and updated 24 hours ahead of the Sunday GP.

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.

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Bob Francis - Go Full Throttle

Go Full Throttle editors and reporters bring you news & commentary on NASCAR, F1, IndyCar, and World of Outlaws. Member: National Motorsports Press Association