Can a Champion Come from Outside the Top-Six Seeds?

Within weeks of NASCAR announcing a re-formulated version of The Chase for 2026, the word around the garage was that the future champion would have to enter The Chase as one of the top six seeds. Yet the current top-four-ranked drivers started The Chase ranked seventh, first, ninth and sixth.

Where did that ‘top-six seed’ prediction come from? And does it still hold?

The Chase, So Far

The table below summarizes the standings at the start of The Chase and after each of the three races. I used car numbers to make the table a little clearer. Race winners are shown in bold.

Rank	Initial Seeding	After Darlington	After Gateway	After Bristol
1	11	11	11	5
2	12	20	5	11
3	45	12	20	22
4	54	45	12	20
5	19	19	45	54
6	20	54	54	12
7	5	5	22	45
8	9	22	19	77
9	22	9	77	19
10	17	23	23	23
11	17	17	9	2
12	7	77	2	9
13	77	7	17	24
14	24	2	60	60
15	2	60	24	17
16	60	24	7	7

There has been quite the shake-up in rankings at the top of the standings in the first three races.

• Points leader Kyle Larson started The Chase seeded seventh.
• Joey Logano, currently in third place and only 16 points from Larson, started The Chase seeded ninth.
• Chase Briscoe, who started as fifth seed, is down to ninth.
• Tyler Reddick, who started the season with never-before-seen domination, entered The Chase ranked third, but is now seventh.

So a Winner Can Come from Outside the Top Six?

Yes.

In fact, Ryan Preece, the original 16th seed, could win the remainder of the Chase races and become the 2026 Champion.

The important part here is in words like ‘could’, ‘will’, ‘likely’ and ‘must’. Statisticians use these words carefully, but a lot of people don’t. A message transforms as it moves from stats experts to those less familiar with the strict rules of numbers.

Somewhere along the way, the original message — that the eventual winner would most likely come from the top six seeds — turned into something more like ‘You can’t win the championship if you’re not among the top six seeds.”

The Experts Said…

Racing Insights is a statistics organization that provides information to NASCAR and media outlets that subscribe to their services. On NASCAR’s Hauler Talk podcast, Russell Wenrich explained how Racing Insights helped NASCAR decide on a new championship format by running simulations of different scoring systems. Those simulation results helped NASCAR pick a format that was — statistically — most likely to produce a strong 10-week competition.

In the 25,000 simulation runs of seasons using the 2025 format, Wenrich report that following:

• In more than 35% of the simulations, the first-seeded driver won the championship.
• One of the top-three seeds won the title in 69% of the simulation runs.
• Eighty-five-percent of the time, the champion came from one of the top-six seeds.
• The champion is the top points scorer for last 10 races in 70% of the simulations.

That third bullet point is the one that got the most traction with drivers and the media, but you probably heard it first from a driver who said something like ‘You have to finish the regular season sixth or better to have a shot at winning the championship.”

That’s not really what these simulations said.

What are these ‘Simulations’ You Speak Of?

NASCAR’s championship format was decided using mathematics originally developed for the Manhattan Project: The United States’ secret World War II-era research program into atomic weapons. In fact, much of sports analytics and gambling relies on these type of simulations.

Polish mathematician Stanislaw Ulam was one of many European academics who fled to the United States as Hitler overtook their countries. Ulam was my kind of math guy. Although he was interested in pure mathematics, he was also anxious to develop math that could be used to solve practical problems.

Ulam first conceptualized the Monte Carlo simulation while playing solitaire. Being a mathematician, he didn’t play normal solitaire. He played a version called Canfield or Demon solitaire, which hwas very hard to win.

Ulam got to wondering — as sick mathematicians playing solitaire do — what the probability of winning the game actually was. Existing mathematicalmethods didn’t offer a solution, so he wondered if he could simply play the game over and over until he figured out the probability. Being a practical man, he realized that this wasn’t exactly a problem of major import.

However, he quickly realized that his card problem was analogous to more relevant issues like neutron diffusion, which was critical to post-war work on atomic weapons at Los Alamos. They needed a code name for the project. Ulam had an uncle who used to borrow money from relatives to gamble in Monte Carlo and thus the Monte Carlo method was born.

Monte Carlo simulations are something of a last-ditch approach: A way of attacking problems that are too complicated to solve any other way. They are ideal for situations where chance plays a large role and there are many possible outcomes.

The idea is that you simulate a situation so many times that you explore all possibilities. Then you tally up how often each outcome happens and that gives you a probability of each final result.

For Example

Consider flipping a coin ten times. The probability of each coin flip is one half, no matter how many times the coin is flipped. It is possible to flip a coin ten times and get ten heads, or to get ten tails. But the far more likely outcome is to get five heads and five tails, or six heads/four tails or six tails/four heads.

The probability of getting ten heads in ten flips is 0.0977%. In order to have a 99.9% chance of having that outcome, you’d have to repeat 10 coin flips almost 9,500 times. You can see why the development of these simulations proceeded apace with the development of computers.

Simulating NASCAR Season

The easiest way to simulate a race is to simulate each driver’s lap times. Add up all those lap times for each driver and you end up with a finishing order.

How you simulate lap times determines how accurate your simulation is because a LOT of things impact driver lap times. For example, a good simulation might include:

• Base lap time due to car quality + driver skill
• Impact of tire degradation, which changes every lap
• Fuel-related lap-time changes: fuel level changes the car’s mass and balance
• Changes in the track with time
• Changes due to weather
• The effect of any damage
• Whether the car is in traffic or not

Adding up all of these numbers is easy. Getting them is hard.

Tire degradation isn’t the same for all drivers because some are better at managing tires than others. Some drivers are more likely to be involved in accidents than others. Passing some drivers is easier than passing others. A car that typically leads laps will encounter very different traffic than one that is perennially back in midfield. The dynamics of superspeedways are very different than the dynamics of a short track.

There are up to 40 drivers in each race, 36 races in each season, upward of 20 tracks per season. And they’re not always the same tracks every year. But NASCAR has extensive data that allows them to make models of all of these effects.

Probability and Possibility

The graph below is a conceptual representation of the simulation results Wenrich described on Hauler Talk. The horizontal axis shows driver’s initial seeding. The vertical axis shows the percentage of simulations in which that seed won the championship. Note that they did these simulations ahead of the 2026 season and without attaching specific names to the simulations.

This graph says that, if we had 25,000 NASCAR multiverses, the number one seed would win the championship in around 8,750 of them. Having the top-ranked seed win the championship only a little more than a third of the time is actually a surprisingly low number to me. Consider how often tennis tournaments, for example, are won by the top-ranked seed.

Then again, you generally don’t have one tennis played wrecking another player’s racquet in the middle of the game.

So Why Bother with Sixteen Seeds?

It’s a legit question. If the 16th-seeded driver has virtually no chance of winning the championship, why have 16 drivers?

Because, although the chance of the 16th seed winning the championship is very small, it is not zero. Recall that Tony Stewart entered the 2011 Chase as the ninth seed, but went on to win the championship. Stewart winning five of the 10 Chase races wasn’t a probable outcome, which is why that championship race was so exciting.

One More Caution

Because points reset at the start of The Chase for the top 16, we’re back to the issues of small numbers. Everyone competing started with 2000 points plus a bonus for where they finished the regular season. But those 2000 points are only so that the Chase competitors stay ahead of the rest of the field.

Between those 16 drivers, the only thing that matters is the delta to the current leader. And those numbers are small, just as they were at the start of the season.

It’s no accident that three of the top four drivers after three races are the first seed and the three race winners. What remains to be seen is whether we continue to have a diversity of winners, or if a handful of drivers dominate the next few races.

Or if, against all odds, one of the drivers in the lower quartile surges forward to surprise us all.