Week 7 GFT NASCAR AI Driver Rankings: Blaney moves to P1 after Richmond

9 April 2022
by Bob Francis
Go Full Throttle Racing News

Another crazy week in Go Full Throttle AI Rankings — the cloud based predictive analytics system that uses our proprietary algorithms, utilizing artificial intelligence and machine learning technology, to deliver Driver Rankings and Race Predictions. Huge moves in the Cup Series data following battle at Richmond Raceway where Denny Hamlin and Toyota finally get to Victory Lane. Mr. Consistency and multi time Busch Light Pole Award winner Ryan Blaney started P1 and delivered another top 10 finish in 7th place.

What moved the data? Of course, Hamlin’s win rocketed him up 10 places from P22 all the up to P12. Kevin Harvick and his № 4 SHR Ford finished 2nd at Richmond and that moves Harvick up 5 spots in the rankings to P11. Byron led a ton of laps and looked to be headed to Victory Lane before a great tire strategy call by Hamlin and Harvick’s teams gave them the advantage late, passing Byron at 5 to go. “Willy B” held on for 3rd. All that data and more resulted in Blaney at P1 in this week’s ranking, William Byron is P2, Chase Elliott P3, Ross Chastain P4, Martin Truex Jr P5.

Martinsville Picks
The data says put your money (or set your Fantasy league picks) on Blaney, Byron (who won the Truck Series race Thursday night), and Pole sitter Chase Elliott. Truex is ranked P5, but also has 3 wins at “The Paper Clip.”
*NOTE* While the algorithms rank Kyle Busch at P13, yesterdays Practice and Qualifying data from Martinsville Speedway says he is likely to be a factor at Martinsville under the lights.

Week 7 of the NASCAR GFT Top 25 AI Driver Rankings following the Toyota Owners 400 at Richmond Raceway on April 3, 2022. (Image: GFT Digital / gofullthrottle.net)

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. Data feeds into our system include our Pre-Season rankings and the data available from NASCAR and other trusted NASCAR Cup Series sources that include (but not limited to) inputs such as Driver points, Stage points, Stage wins, top speed, lap times, and laps led from all practice sessions, qualifying and the races.

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