Week 2 NASCAR GFT AI Driver Rankings: Cindric holds on to P1
The Go Full Throttle NASCAR Cup Series AI Driver Rankings for Week 2 were released today. After the Wise Power 400, race 2 of the Cup season, from Auto Club Speedway, Austin Cindric, driver of the № 2 Ford Mustang from Team Penske holds on to the top spot after finishing P12 on Sunday.
The Big Movers
With his 3rd place finish in Fontana, Petty GMS Motorsports driver Erik Jones jumps from P24 all the way up to P7 in this week's rankings. Also moving up is Auto Club Speedway race winner Kyle Larson who jumps 15 spots to P3 and Ryan Blaney who also jumped 15 spots to P5. 2nd place finisher Austin Dillon moves up 13 spots from P22 to P9. Falling in the rankings this week is Brad Keselowski down 10 spots to P12.
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, and freshly updated with results and data from the Wise Power 400 in Fontana, our algorithms went to work crunching data. 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).
How do the GFT AI Driver Ranking 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.
What’s next? Onto Las Vegas Motor Speedway
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 winged Sprint Car series.
We are off to Las Vegas Motor Speedway