Hello army! Now that the first 6 races of the 2018 season are in the books, I wanted to dissect the results and show you guys/gals what worked, why it did, and how it goes hand in hand with what I talk about with lineup correlation. While there are only a few of examples here, the results tend to be very similar over time and are similar to what will be presented below (except for Blaney’s 118 lead laps at Daytona…that’s not normal, but we’ll get to that). I built a model to keep track of everything going on during the season, and this is part of what’s in it. My data is your data, so let’s get to it!
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First off, don’t focus on the names. Focus on the numbers. Study them while thinking about lineup correlation. Alright, let’s break down each category!
Race setup
Starting at the top you’ll see each race, the amount of laps recorded by NASCAR, and how many drivers participated. Simply put, more laps + more drivers = more available DKFP. The amount of laps available will influence the maximum DKFP the most since both lead & fastest laps are increased, and the extra last place finishes only add a small amount.
Driver stats
Each driver has their stats broken down here. You’ll see their salary, starting/finishing positions, +/- place differential, how many laps they led, how many fastest laps they earned, their total DKFP, and their value multiplier. For the laps, you’ll also see a percentage. This is showing how much was earned from the total amount available. For example: if they led 33 laps of a 200 lap race, they led 16.5% of it.
Totals
This is the sum of all 6 drivers. The green box under DKFP shows the total amount the lineup earned, while the purple box shows the total maximum available for the race. The grand total, directly below, is the percentage of maximum available DKFP that each lineup earned.
Note: if you divide the total available by the total earned, you’ll get a different number than what the model shows. This is because I take into account the amount of place differential earned. If you recall, it’s always equal to zero since drivers take it away from each other, so it’s an important factor to monitor as it’s essentially “bonus” DKFP.
Percentages
The top row here shows how much of each category’s total was earned. For example, if the lineup had 121 lead laps in a 207 lap race, it had 58.5% of the total lead laps.
Now, the bottom row is where things get interesting! This is taking the amount earned of each category as a percentage of the total maximum available for the race. You should notice that while the finishing position percentages are fairly close, the other three are wildly different. This is directly related to proper lineup correlation.
Putting the data to use
We need to earn as much as we can from every source, but this is showing us the diminishing returns of focusing too much on laps/place differential. This is why I stress over using the fewest amount of dominators required to lead the majority of laps, and to focus on finishing placement + place differential with the rest of the lineup.
Notice how every lineup has 4-5 drivers with a top 10 finish, and how much bigger that percentage (bottom row) is compared to the rest? Finishing position is king! Place differential is great, but it’s a bonus we want to grab along the way to a strong finish. The priority is to get BOTH, but if there isn’t a clear path to a significant amount of place differential, focus on the finishing position (which is the key to Xfinity races).
Let’s next look at specific scenerio; Martin Truex Jr’s results from the 2/25 Atlanta race. He finished in 5th place with +30 place differential. That was worth paying up for instead of taking the savings of a $9k driver who may have started 20th and finished 5th. A $9k driver giving you a 6x return is nice, but a $10.4k driver giving you 7x return is even better. Pay up for studs that are in a position to give you that kind of return.
Next, compare a couple of cheap plays from the Las Vegas races. Xfinity’s Vinnie Miller vs Monster Energy’s Chris Buescher. Both are around the same price with +13 place differential, but look at how much more DKFP Buescher earned. Miller had a higher ceiling, but wasn’t in a fast enough car (and not as skilled of a driver) to move up in the field like Buescher was able to. Had they been in the same race, that would have been the difference between min-cashing and winning a GPP.
Comparing the Daytona results
Now that the numbers are explained, let’s compare them to one another. There are some things to take note of that will help you approach each race and determine how to construct/correlate your lineups.
First, let’s go over the Daytona results. As I mentioned at the start of the article, Ryan Blaney’s 118 lead laps are not a normal occurrence for a plate race. Traditionally, there are multiple lead changes and no significant amount of lead laps are earned by one driver (see the Xfinity results). However, do you find it odd that even with that many lead laps, the Monster Energy lineup only outscored the Xfinity one by 9.75 DKFP?
At first glance, yes. But look at how the numbers break down into percentages and compare the finishing positions. The Monster Energy lineup had mostly 5th through 11th place finishes, while the Xfinity lineup had all top 5 finishers and +17 place differential. Again, finishing position is king!
Consider the possible outcomes for Ryan Blaney in that race:
- He retains his lead laps but finds himself in one of the many crashes at Daytona. Instead of finishing 7th he finishes 30th, and drops from 65 to 42 DKFP. He’s no longer in the winning lineup and the lead laps go to waste.
- He starts from the pole but falls back after a few laps (which is what everybody thought would happen, as it often does at a plate race). He still finishes strongly in 7th place, but with negative place differential and no lead laps earned, he only gives us around 35-40 DKFP. Again, not in the winning lineup.
- He crashes very early and finishes last. He’s now the lowest scored driver of the race.
- The race plays out exactly as it did. He starts up front, leads a bunch of laps, and finishes in the top 10. He’s in the winning lineup.
The moral of the story here is to pay up for dominators who can get out front, lead a bunch of laps, and win/finish strongly. If you take an expensive driver starting up front, they WILL NOT return value if they fall back and don’t lead any laps. They need to be able to perform well when they are in a scenario that offers a high ceiling, which is why we pay up for drivers who can do just that. Most drivers won’t have the same high ceiling opportunities as a few will each week, so pay attention and zero in those who do. If you don’t believe that they can perform well in those situations, spend the salary elsewhere.
Other findings
There are a few other trends you have probably noticed as well. Primarily, the fact that every lineup gets right around 33% of the total available DKFP. This is something I am keeping a close eye on, but I don’t expect it to change much over the course of the season. I’m working on a tool (excel sheet) to take advantage of this, so stay tuned for that.
Next, look at the lead laps vs fastest laps in the Atlanta & Las Vegas races (disregard the plate races; different physics come into play there). You’ll notice that drivers with a low amount of lead laps tend to have a pretty low number of fastest laps, and the ones leading a lot of laps have a lot more. This is another reason why you pay up for dominators who can get out front and lead a lot of laps. It’s hard to pinpoint where fastest laps come from when it comes to non-dominators, so take the ones you can get by default. Don’t go hunting for fastest laps, focus on the other three sources. They will come naturally with the fast cars that are finishing strongly.
Finally, take a quick look at how many laps were led by the primary dominator in the Atlanta/Las Vegas races compared to the other studs in those same lineups. This is why it’s important to first determine how many dominators you need, because if a stud isn’t leading laps, they need to return value in other ways. Otherwise, you’re better off looking at a different one in a better situation.
That’s all for now! Hopefully this article helped you all to put some more pieces of the puzzle together. As always, hit me up on Slack @nillyJay if you want to talk more. See you there!