Your driver is running in the top five when he gets caught speeding on pit road. While early penalties can sometimes be overcome, late penalties can eliminate any chance to win.

In most competitive sports, from baseball to chess, the more experience you have, the less likely you are to make mistakes. Can we say the same thing about NASCAR?

## An Overview of 2018 Penalties

With 34 races complete, NASCAR has assessed 376 in-race penalties in 19 categories to 56 drivers. No one in the top 20 has made it through the season without at least one penalty.

But some drivers are making more of a contribution to the total than others. As usual, my data is from racing-reference.info.

## Comparing Apples to Apples

Not all drivers run the same number of races. We can’t really compare the driver who gets two penalties in two races to the driver who gets two penalties in two races.

Part-time drivers ran a total of 275 races while full-time drivers ran a total of 1018 races. So the part-time drivers ran 21% of all and the full-time driers account for 79% of all races. This would suggest that part-time drivers should be responsible for 21% of all the penalties.

Part-time drivers were responsible for 109 penalties, while full-time drivers were responsible for 267 penalties.

- Part-time drivers
- Accounted for 21% of the races
- Committed 29% of the infractions
- Had a penalty per race average of 0.4

- Full-time drivers
- Accounted for 79% of the races
- Committed 71% of the infractions (267)
- Had a penalty per race average of 0.26

Part-time drivers, on average are more likely to be penalized than full-time drivers.

## Which Full-Time Driver Has the Most Penalties (So Far)?

The graph below shows total number of penalties for the 29 full-time drivers competing this year. I’ve highlighted the top four drivers in red and the next four drivers (the ones who are still in the running) in green.

Side note #1: I was curious whether 29 is a low number of full-time drivers. It’s on the lower end of the ten past years, but not anomalously. It’s difficult to count because you’ve got a number of drivers who meant to be full time, but missed races due to injury or suspension.

My working theory was the the drivers with the most number of penalties would be those with the least experience. So this result made me go back and double check that I hadn’t done something squirrely with the data.

Right up at number one is not only a very experienced driver, but last year’s champion: Martin Truex, Jr. with 17 in-race penalties.

There goes my theory, right?

Side Note #2: Did the Furniture Row team closing announcement have anything to do with the large number of penalties? Four penalties were from the races after the of them. They had two penalties at Daytona in February and 5 at Bristol in the spring.

- There were 4 penalties in the 9 races after the announcement (0.44 penalties per race)
- There were 13 penalties in the 25 races before the announcement (0.52 penalties per race)

### All Penalties are Not Created Equally

NASCAR levied 19 different types of penalties — but not all of them can be blamed on the driver.

We could quibble about some of the non-driver attributable penalties. Removing equipment, for example, could be driver’s fault or could be the pit crew’s fault. I erred on the side of only blaming the driver for things we could be pretty sure he or she was responsible for.

- Considering all drivers:
- 51.6 of the penalties were non-driver attributable
- 48.4% of the penalties were driver attributable

- Considering only full-time drivers
- 51.7 of the penalties were non-driver attributable
- 48.3% of the penalties were driver attributable

So, about the same fraction regardless of which group of drivers we consider. Wondering what exactly those penalties were? Here’s a breakdown of the driver-blameable infractions:

Too fast entering pit road and too fast existing pit road together account for 79% of all driver penalties. We see something similar when we look at the non-driver penalties:

Tire violation, too many men over the wall and crew member over the wall too soon (all of which are pretty hard to blame on the driver) combine to account for 84% of the crew-attributable infractions.

These distributions remain pretty much the same if you only consider full-time drivers with the following note: No full-time driver got ticked for going above the blend line exiting pit road, passing the caution car, or jumping the restart.

## Breaking Out the Blame

So if the driver is only responsible for about half of the total violations, that would mean Martin Truex, Jr. was only responsible for eight or nine of the 17 violations, right?

Here’s the same chart as before, but I’ve put the driver-attributable penalties in yellow and the non-driver-attributable penalties in green.

MTJ is not responsible for seven violations. He’s only directly responsible for three. His pit crew got caught five times with too many men over the wall at Bristol in the spring. They had seven penalties in the first eight races – one more than the had in the next 17 races.

## So Penalties Really Do Correlate with Experience?

Although all these drivers were full-time this year, they weren’t always full time. To get an equal measure of experience, I divided the total number of cup races each driver has won by the number of seasons. This gives us a ‘equivalent years of experience’ I thought would be a fair measure. So let’s plot penalties vs. driver years of experience.

This is pretty much random, signifying that there’s no correlation between experience and penalties; however, I did use the total number of penalties and we’ve seen from the MTJ case that this isn’t really fair to the driver. So let’s plot driver-only penalties and look for some patterns.

Hmm… absolutely no correlation here, either. It’s always good to go back the original data, so let’s see if there are any patterns in the data if we just plot the number of driver penalties for the full-time drivers.

Again, the top four drivers are in red, the second four are in green. Now a pattern begins to emerge. The top drivers are all in the four-or-less portion of this graph. That includes Erik Jones, with 2.0 effective years and Chase Elliott with 3.1 effective years, as well as Harvick (17.9 effective years) and Kurt Busch (also 17.9 effective years)

At the same time, the most penalized drivers included Suárez (1.9 effective years) and Wallace (1.1 effective years), but also Newman (17.1 effective years) and Jimmie Johnson (17.0 effective years). So experience is not the relevant variable here.

## Then What Is the Relevant Variable?

I plotted out a number of possibilities until I happened to look at the raw data in a table and saw the correlation that way

This is the strongest correlation I found. If you exclude the first two drivers, the number of penalties is most closely correlated to their ranking in the driver standings. Kyle Busch (4) and MTJ (3) are 1st and 2nd and have more penalties than the 3-6th drivers, which suggests perhaps that they take more chances: they get caught more often, but it seems to pay off because their rankings are the two best.

Does this mean that worse drivers make more mistakes? Or that making mistakes pulls them down in the standings? Hard to tell from this data.

Just out of curiosity, I plotted total penalties vs. standings.

And found no correlation there, either. Consistent with the driver’s behavior not necessarily being represented by the total penalty numbers.

## What About Crew Penalties?

MTJ’s wasn’t responsible for 14 out of the 17 penalties. What about the other teams?

The 78 team had twice the number of non-driver attributable penalties than the next highest teams (The 17 and the 20 tied at 7 penalties each.) But plotting the data this way doesn’t take into account the total number of penalties because there are cases in which the driver made the lion’s share of the mistakes.

So here’s another way of looking at the numbers. I plotted the ratio of driver mistakes to non-driver mistakes. If the ratio is one (which I’ve indicated with a red line), it means that the driver and the crew made the same number of mistakes.

If the number is greater than one, the driver is contributing more than his share. Those bars are above the red line. If the number is less than one, the crew is making more mistakes than the driver. Those are the bar below the red line.

David Ragan was penalized 7 times (all for pit-row speeding) while his crew only had one penalty (for not meeting minimum speed). On the other end, Kyle Larson only had one driver-attributable penalty and six crew-leaning penalties.

But this still doesn’t give us all the information in one graph, so we need to move to graphs that can handle 3D data. Like Bubble Graphs.

This graph plots the number of driver penalties vs. non-driver penalties with the size of the bubble proportional to the total number of penalties. The red line represents a 1:1 ratio: the driver and the crew made the same number of mistakes. Below the line means that the driver made more mistakes, while above the line means that the crew made more mistakes. You can see more clearly that the drivers who made the most mistakes tend to be the lower-ranked drivers.

## Miscellaneous Facts & Figures

- Most penalties for too fast entering: Newman (6)
- Hamlin: 5
- Suárez: 5
- McDowell: 5

- Most penalties for too fast exiting: McDowell (6)
- Stenhouse, Jr. : 5

- Most penalties for too fast on pit road anywhere: McDowell (11)
- Suárez: 9
- Stenhouse, Jr.: 7
- Newman: 6

- Most commitment line violations: Dillon (3)
- Most tire violations: Truex Jr. (6)
- Stenhouse, Jr. : 4
- Byron: 4

- Most penalties for too many men over the wall: Truex, Jr (5)
- McMurray: 4

- Most penalties for crew member over the wall too soon: Larson (3)
- Most penalties for removing equipment: Jones (2)

Thank you for the interesting information. When I get the time, I will come back to this info to see if there is a difference of non-drivers errors between big (well-funded) teams and small (lesser-funded) teams (I wonder if the bigger resources of big teams translates to fewer non-driver errors for big teams compared to small teams).

Great idea. Especially since we’ve had some unique situations like a very good driver (Kahne) driving for a less-well-funded team. Let me know what you find!

Dr. Diandra, very interesting look at penalties, thank you so much for putting this together! Hear you every week with D Moody, always enjoy your scientific look at things. Much can be learned from compiling & analyzing data on this and many other NASCAR statistics. Would love to see a similar approach toward driver age vs wins & overall performance. Thanks again for this very eye opening look at penalties!

Thank you so much for listening! I have looked at driver age before, but it’s time for a redux!

Diandra,

Love the colored graphs for the 10% of us that are “hue” challenged.

Bob

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