Week 5 NASCAR GFT AI Driver Rankings: Logano P1 after Atlanta
NASCAR Cup Series Week 5 at Atlanta Motor Speedway sends Joey Logano back up to P1 in the Go Full Throttle AI Driver Rankings. Logano’s 9th place finish, William Byron’s win, and tough days for Kyle Larson and Kyle Busch sends our algorithms into overdrive and our AWS bill soring. Chase Elliott moves up 3 spots to P2, and Atlanta Folds of Honor 500 winner William Byron from Hendrick Motorports jumps 13 places to P3. !3 places? How is that possible? The weighting for a win is the strongest factor in the overall score calculations by the GFT algorithms. Just as Chase Briscoe jumped 11 spots after Week 4 of the Cup Season with his win in Phoenix.
The Big Movers
Byron’s win and the GFT algorithms make him this week’s top mover, up 13 spots. The largest decline in the Top 25 this week was Kyle Busch falling 10 spots to P14. Austin Dillion falls 7 spots to P20.
Predictions for COTA?
The data says Joey Logano is the favorite for Sunday’s first road course race of the Cup season. However, our AI models were data starved to meet a solid confidence level again this week with the lack of data on the Generation 7 car at Circuit of the Americas.
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 from The Clash at the Coliseum, the Duels at Daytona, and all the data from Weeks 1–5 of practice, qualifying and racing, our algorithms went to work analyzing and learning. The complex math also includes inputs such as top speed, qualifying position, stage wins, laps led, and in Super Speedway races — the number of cars each manufacture has entered (likely drafting partners, especially for green flag pit stops).
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. (Image: royalty free via Digital Soup)
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 NASCAR live leaderboard with lap times during practice or qualifying results, laps led on race day, and stage points.
What’s next?
In 2022, our goal is to continue to improve the accuracy of the current Go Full Throttle AI Driver Ranking models for F1 and NASCAR Cup that will be published weekly, usually on Saturday to contain the most up to date information ahead of the races on Saturday night or Sunday. We are also in the process of building GFT AI Ranking Models for IndyCar and the World of Outlaws Sprint Car series.
Follow it all on our website https://gofullthrottle.net/ and get regular updates via our Twitter feed.
