Week 3 NASCAR GFT AI Driver Rankings: Larson Moves into P1

Week 3 of the NASCAR Cup Series at Las Vegas Motor Speedway produced another exciting finish as Alex Bowman holds off Hendrick Motorsports teammate Kyle Larson to win the Pennzoil 400. With the win, Bowman jumps 16 spots to P5 in this week's rankings and by finishing P2, scoring stage points, and leading 27 laps (among other ranking dynamics in the algorithm) Kyle Larson moves to P1. Last week’s leader Austin Cindric falls to P2, Martin Truex, Jr moves up to P3, and Joey Logano falls 2 spots to P4.

Week 3 of the NASCAR GFT Top 25 AI Driver Rankings following the Pennzoil 400 at Las Vegas Motor Speedway on March 6, 2022. (Image: GFT Digital / gofullthrottle.net)

The Big Movers
As you would expect, Bowman moves way up to P5 primarily based on how our models apply weighting for wins. Other big movers up the rankings include Ross Chastain from Trackhouse Racing up 14 slots to P21 and William Byron from Hendrick Motorsports up 11 slots to P20. Falling well down the rankings is Michael McDowell dropping 12 positions to P23 and four drivers falling eight positions- Blaney, Briscoe, Jones, and Buescher.

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 of The Clash at the Coliseum, the Duels at Daytona, the Daytona 500, the Wise Power 400 in Fontana, and freshly updated with results and data from the Pennzoil 400 at Las Vegas Motor Speedway, our algorithms went to work crunching the data 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.

We are off to Phoenix Raceway!

Follow it all on our website https://gofullthrottle.net/ and get regular updates via our Twitter feed.

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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