Week 6 GFT NASCAR AI Driver Rankings: Chase Elliott P1 after COTA
By Bob Francis, Managing Editor
March 31, 2002 — Go Full Throttle Racing News
Another first-time winner in the NASCAR Cup Series rockets up the GFT Rankings and sends our algorithms into overtime. Ross Chastain’s final 2 laps of beating and banging for the win against AJ Allmendinger and Alex Bowman at Circuit of the Americas on Sunday was an absolute thriller. Chase Elliott’s 4th place finish at COTA sends him to the top of the rankings. For Chastain, driver of the № 1 Trackhouse Racing Chevrolet, the win moves him up 7 spots from P11 to P4.
Week 6 Big Movers
As it should, our algorithms place significant weight on a win, thus Ross Chastain’s jump to P4. The other big mover up the rankings was Joe Gibbs Racing’s № 20 Toyota driver Christopher Bell. As has been the case for many of the Toyota’s so far in 2022, Bell has had a tough early season, but his 3rd place Sunday jumps him up 6 spots (P29 to P23) making his first appearance in our Top 25 this season. The ranking models were not as kind to drivers who had poor finishes at COTA with last week's top ranked driver Joey Logano falling 5 spots to P6 with this 31st place finish and Kyle Larson who also dropped 5 spots with a 29th place finish.
Chevy Continues Winning — Toyota Continues to Struggle. Why?
From a manufacturers point of view, the top ten finishers at COTA told a familiar story- Chevy wins, Trackhouse looks great for a new Cup Series team, and the Toyota camp is still winless. At points Sunday in Austin, each of the Toyota’s showed possibilities and speed, but Bell’s 3rd and Truex Jr’s 7th was all they could deliver in the end. Denny Hamlin finished P18, Kyle Busch P28, Kurt Busch 32nd, and Bubba Wallace 38th. It was double pain for Wallace after his № 23 car lost a wheel on Lap 45 out of 69 in the EchoPark Automotive Grand Prix. On Tuesday, NASCAR’s competition officials handed down four-race suspensions to 23XI racing crew chief Robert “Bootie” Barker and crew members Caleb Dirks (jack) and Adam Riley (rear-tire changer).
Top Ten at COTA:
*THIS SECTION IS REPEATED EACH WEEK FOR OUR NEW SUBSCRIBERS
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 1–6 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.
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.
