The field is finally set for the 2019 Daytona 500, but before we dive into my driver-by-driver breakdown, I want to get out my yearly NASCAR DFS strategy article for the Daytona 500. In this article you’ll find facts and stats based off past Daytona 500 races, which, if the underlying assumptions of past Daytona 500 races hold true, gives us game theory optimal DFS exposures for each starting position. Then I’ll put all that together to give you some rules of thumb, and some strategy for this year’s Daytona 500 race. Let’s dive into the numbers!
Historical Incident Rate
Since 2005, the Daytona 500 incident rate is 32.5 percent, but since 2013 that’s crept up to 35 percent. Also, the incident rate seems to affect cars pretty equally. If I plot previous year driver rating vs. incident rate, it’s essentially flat at around 30 percent for all drivers above a driver rating of 50 the prior year. Then it trends up approximately linearly to 60 percent for drivers with a previous year driver around 25 percent. In other words, everyone but the worst possible cars has a long-term DNF rate of around 30 percent, including race favorites and dominators.
That means you should have a maximum of 70 percent exposure to any driver, simply based off the fact that they have at least a 30 percent chance of being caught up in an incident. And in reality, even the best restrictor plate driver of all time, starting dead last shouldn’t even be 70 percent owned. He might not win the race, and he may only finish 12th or 18th, while six other drivers get larger place differential and/or dominate and finish well.
My advice would be not to have more than 55-60 percent exposure to any driver, even Brad Keselowski who starts 35th on Sunday.
Starting Position vs. DraftKings Points
Let’s look at a table of the top six DraftKings scoring drivers per race at the Daytona 500, listed in order by their starting position.
We can put some numbers to this pretty easily.
Number of drivers starting in the top 5
- Minimum: 0
- Maximum: 2
- Average: 0.43
Number of drivers starting in the top 10
- Minimum: 0
- Maximum: 2
- Average: 0.71
Number of drivers starting in the top 20
- Minimum: 0
- Maximum: 4
- Average: 1.43
Number of drivers starting 30th or worse
- Minimum: 2
- Maximum: 5
- Average: 3.71
Number of drivers starting 21-29
- Minimum: 0
- Maximum: 2
- Average: 0.86
As you can see from these numbers, place differential is king given the number of cars per race starting 30th or worse. However, I thought it was interesting that more drivers per race start inside the top 20 than from 21st to 29th. Even if we narrow that to the 40-car field era of 2016-2018, we see a total of four cars starting inside the top 20, and four cars starting 21st to 29th in those three races, compared to 10 cars starting 30th or worse, for an average of 3.33 per race.
If we translate this to driver exposures, then on average you’d want to have the following exposures:
- 1st through 5th: 43 percent
- 6th through 10th: 28 percent (for 71 percent total in the top 10)
- 11th through 20th: 72 percent (for 143 percent total in the top 20)
- 21st through 29th: 86 percent
- 30th or worse: 371 percent
That all sums up to 600 percent exposure, which makes sense for rostering six drivers (if you played one lineup, you’d have 100 percent exposure to each of your six drivers, for 600 percent total).
However, there’s a better mathematical way to approach driver ownership, and that’s by plotting starting position hit rate not just for the optimal lineup, but for all the past lineup combinations that place us in cashing position, then weighing by the dollar amount that pays us over our buy-in. So for the 2019 DraftKings $750,000 GPP, the top 20 percent get paid out, so we’d take the top 20 percent of past lineup combinations. First prize is $100,000, which is $99,990 more than your buy in.
A bit of fancy math, and voilà, we have optimal starting positions based off past races.
Not so fast. See, from 2005 until 2015, NASCAR used a 43-car field for the Daytona 500, while from 2016-2018 it has been only a 40-car field. So I had to weigh things appropriately for the field size. A lot of regression and math later, and I can present you Game Theory Optimal (GTO) exposure percentages per starting position.
Let me explain each of the columns.
- Start: The starting position
- Weight: The weighted GTO exposure of the 11 races with a 43-car field and 3 races with a 40-car field (so most of the weight is placed on the 43 car fields)
- Average: The average GTO exposure of the 43-car era and the 40-car era
- 40_Car: GTO exposures only using the three races from the 40-car era
- 40_Car_W: GTO exposures weighing the 40-car era 80 percent and the 43-car era 20 percent
Personally, I prefer either the average, or the weight column, but you may want to use different assumptions.
Additionally, I should add the disclaimer that these are not the ownership percentages you want to blindly apply to this year’s starting field. This is just an average optimal, for that particular starting position’s average driver. If we use the weighted 40th place starting position, it says we should have 27.7 percent exposure to that driver on average. However, I would use Brad Keselowski much higher than 27.7 percent if he started 40th, because he’s way better than the average driver. Similarly, I would use Cody Ware way less than 27.7 percent (probably little to none at all) if he started 40th, because he’s only finished one race out of nine in his career. This is just a guide for your average driver, based of the assumptions you think will apply to the 2019 Daytona 500. Will it look more like 2016-2018? Will it look like the 43-car field era? Do you want to weigh one more than the other, or equally? Those are all for you to decide.
You’ll see this all makes sense with the numbers above too. If we just use the 40_car era, the 30th-40th place exposures sum up to 365 percent, or 3.65 drivers per lineup. That’s above the 3.33 drivers per lineup. The reason for that is because we’re not just looking at the optimal lineup, but also the lineups that help us cash.
So now that we have some stats and numbers, let’s talk rules of thumb, and strategy.
Daytona 500 NASCAR DFS Strategy and Rules of Thumb
Rule 1 — Avoid the front row completely
Only once has a front-row starter emerged in the optimal lineup, and if we extend this to the top eight DraftKings scoring drivers per race (for the top 20 percent of the field, since the top 20 percent of DK lineups pay out), that number stays at one. So out of 28 tries (14 races times two drivers), there’s a 3.6 percent hit rate for the front row in a cashing position. I don’t expect this year’s front row drivers to end up in the optimal lineup. The Chevys of William Byron and Alex Bowman have qualifying speed, but the Ford have proven to be the dominant manufacturer throughout the 2019 Daytona Speedweeks.
Byron and Bowman will probably combine for like 10 percent exposure at least, just from people who don’t know what they are doing, so there’s 10-plus percent leverage on the field right there.
Rule 2 — Use no more than 2 drivers inside the top 10, but preferably one or zero
We’ve never had a race where three drivers inside the top 10 ended up in the optimal lineup. The closes we’ve come was 3rd, 5th, and 11th all in the optimal lineup in 2015. Additionally, the number of times we’ve had two drivers inside the top 10 is twice out of 14 races. That implies, if you multi-enter, about one-seventh of your lineups should have two drivers inside the top 10. The remaining lineups should be split approximately evenly between zero and one.
Rule 3 — Dominators are okay, but don’t overuse them
There have been eight times in the past 14 years (57 percent) that a driver led at least 40 percent of the race (80 laps). Of those eight times, only four ended up finishing. The other four ended up with crumpled cars. So four out of 14 races has had a major dominator end up in the optimal lineup. However, given what we saw in 2016, 2018, and so far here in 2019 Speedweeks, I think the likelihood of a dominator is more than 57 percent. If I had to venture a guess, it might be closer to 70 percent. With the historic incident rate at around 35 percent, that implies that around only half your lineups, give or take a bit, should have a single dominator in them (you can still have two potential dominators starting in the top 10, hoping one hits and the other finishes well. That won’t violate rule 2).
Rule 4 — Don’t use too many drivers starting in the 16-25 range
Only seven drivers starting 16th to 25th have ended up in the optimal lineup. Drivers in this range tend to be drivers that didn’t finish very well in their Duel race, but still finished without a problem, whereas drivers 26th and worse typically had problems in the Duels, or are just bad cars. Additionally, 26th-40th offers more place differential potential, so even mediocre cars starting far back are better than mediocre cars starting 16-25.
These cars also typically aren’t dominators or winning contenders, since they didn’t perform well in their Duel. That’s why we see top 10 drivers have a higher rate in the winning lineup (0.71 per race) than the 10 starting positions from 16-25 (0.5 per race).
There has been only one time where two drivers in this range ended up in the winning lineup, but it was last year. Don’t use more than two from this range, and even when you do, make it a rare occurrence.
Beyond those rules, and the exposure guidelines at the top regarding incident rate and GTO exposures, the main thing is to find good leverage spots and play the ownership percentage game. If you think Brad Keselowski will go 65-70 percent owned (ownership projections will be out in the driver-by-driver breakdown), it’s okay to play him a bit less than that 55-60 percent max range I talked about for any one driver if you want some extra leverage. Even if you play him in that 55-60 percent range, that’s still leverage on the field if he’s 65 percent owned.
If you want to place that extra few percent you’re not using on Keselowski, don’t place it somewhere else chalky, place it on a lower owned driver that has big upside (usually starting in the back) like Casey Mears or Tyler Reddick.
Most of all, stick to what the past facts and stats say, which inform the rules of thumb and GTO exposures, and have fun!