NASCAR 101: An Adventure in the Wonderful World of Loop Data

Since 2005, following every Monster Energy NASCAR Cup Series race, NASCAR has released what it calls loop data to the general public.

Loop data is a form of advanced statistics that calculates what position every driver is running at at the conclusion of every lap of the race and who had the fastest lap. NASCAR then calculates a number of statistics, such as how often a driver passes, gets passed, how many laps they were in the top 15 and the overly complicated driver rating.

There are a number of different functions for these statistics. NASCAR likes to use the passing statistics in particular whenever putting out a press release or tweet praising the race quality (“Since adopting the new blah-blah rules package, passing has increased by blah-blah percent”).

Loop data is also a great way to see flukes for what they are. Justin Haley’s win a couple of weeks ago will go down in the record books as a win, but so will his average running position (ARP) of 31st.

Probably the best use of loop data, and yet also its biggest mystery, is to use it to compare drivers. It’s like getting a box of LEGO without any instruction booklet or pictures to show what to make with it. Everything is here, there’s just no guide on how to use it.

One thing I’ve always appreciated in general sports are “clutch” athletes, the ones that are at their best when the game is on the line. Football has fourth-quarter comebacks or game-winning drives for quarterbacks. Baseball has saves for closers. But in racing, it’s hard to define what makes a good closer.

Sure, you can look at where a driver is at the final restart and compare their position there to where they finish. But that really doesn’t tell the whole story. What if the team took a gamble on strategy and they blow by everybody on the restart? Or what if the final stage restart is the final restart of the race and it becomes a fuel mileage race?

So instead, I’ve taken loop data and have attempted to come up with at least one statistic to figure this out. Racing Reference has average finishing position (AFP) down to a tenth of a percentage, but the NASCAR-operated website doesn’t list ARP.

ARP is actually a very vital statistic. With it, it’s easy to find out who really has speed throughout a race and how they stack up to the rest of the field. Of course, it has the same problems another loop data statistic NASCAR publishes (position mid-way through the race) has in that sometimes it’s strategy not to just be up front unlike with general sports.

Some drivers wait near the rear of the field at superspeedway races before drafting up through the pack near the end. Other times, teams will short pit and fall near the end of the running order until pit stops cycle their way through.

But unlike with the mid-way position, ARP is just that… ARP. A pit stop cycle isn’t going to necessarily ruin a driver’s ARP, especially in today’s NASCAR where we might see three at most in a race. It definitely affects it, but not in a super meaningful way.

I went through and calculated the 31 full-time Cup Series driver’s ARPs, along with Landon Cassill’s and Ross Chastain’s, through the first 19 races of this season. After rounding to the nearest tenth of a percentage, the ARPs were then subtracted by the driver’s AFP to form what I’m informally referring to as their “Pearson Grade”.

Basically, it’s the difference between where a driver usually ran in a race and where they ended up actually finishing. It’s named after Hall of Fame driver David Pearson, who was famous for showing up out of nowhere at the end of races to finish strong. The total number of fastest laps a driver has had this season was also included in order to help determine just how much raw speed a driver can have at any one time in a race. Finally, how many races a driver has finished ahead of their ARP in a race out of their total number of race starts were also recorded.

The data and the spreadsheet I created with it can be found at this link. It doesn’t answer everything as far as to how each driver stacks up, but it does raise some interesting points.

The top five drivers in Pearson Grade were:

Driver	Grade
Ryan Newman	3.6
Corey LaJoie	3.2
Kurt Busch	2.8
Ross Chastain	2.2
Ty Dillon	1.9

Yeah, not exactly the names you’d think would be up there. LaJoie, Chastain and, to a lesser extent, Dillon benefit from the natural advantage the drivers lower on the totem get from this metric. As attrition builds during a race, it creates opportunities for slower cars to get decent results.

Newman and Busch’s grades, however, are very impressive. Newman had an ARP in the top 10 at just one race this season but has seven top-10 finishes. Meanwhile, Busch might well be a championship contender this year with that high of a number in addition to his raw results.

Meanwhile, here’s the bottom five:

Driver	Grade
Chase Elliott	-2.0
Clint Bowyer	-2.1
Kevin Harvick	-2.2
Austin Dillon	-3.7
Ryan Blaney	-4.5

All five of these drivers, along with Joey Logano, have been the biggest beneficiaries of stage points this season. Blaney, in particular, would be in danger of being out of the playoffs instead of being comfortably in. Dillon finished ahead of his ARP just seven times in 19 races, a series low. His slim hopes at making the playoffs are going to start dimming even more if he doesn’t start finishing these races.

It’s not a perfect metric at all, and while this was a fun little adventure, I can’t really call it a complete success. Kyle Busch has a grade of 0.7, which is a good grade compared to the rest of the field who average in the low negatives. But it’s a little underwhelming, and it’s primarily because his ARP is a mind-bogging 7.8, a full position ahead of Logano in second and nearly three positions ahead of third.

Pearson ratings reward a driver for, well, driving like Pearson. But that’s really the great thing about loop data. It really is the LEGO of the NASCAR world. The only limits are your imagination and how big of a nerd you want to be.