Does the Lead-Change Metric Determine a Good Race?

People often cite the number of lead changes in a race — the lead change metric — and suggest that a big number means a good race. The metric is simple, easy to get and elegant in a fundamental way.

It’s also misleading.

The simpler a statistic is, the more information it buries under the rug. That’s true with everything from letter grades in school to sport team rankings. Let’s delve into the lead-change metric. What is it? What does it measure? And is it an objective measure of how good a race is?

What Does the Lead Change Metric Measure?

That might sound like a dumb question, but the lead-change metric is not as simple as it seems. Let’s consider two cases.

Case 1: At the start/finish line, driver A is ahead of driver B. During the next lap, driver B passes driver A so that when they return to start/finish, driver B is in the lead.

I won’t even ask you if that’s a lead change because it clearly is.

Case 2: Start with the same situation: driver A leads driver B at the start/finish line. In the next lap:

• Driver B passes driver A in Turn 2
• Driver A passes driver B back again in Turn 4.

Is that a lead change?

Lead Change vs. Green-Flag Passes for the Lead

NASCAR’s lead change metric tallies the running order only at the start/finish line of each lap. By that definition, Case 2 — a pass and then a pass back — does NOT count as a lead change because Driver A leads at the start/finish line for both laps.

Before you decide that’s a dumb way to count, it’s a question of continuity. Back in the day, NASCAR didn’t have transponders and scoring loops around the track that allowed officials to get intermediate running orders. They literally had people counting cars at the start/finish line. This definition allows for consistency between today’s races and past races.

Today, NASCAR has scoring loops that generate loads of loop data. That data produces another, less publicized metric called Green-Flag Passes for the Lead. While the straight Lead Changes stat covers all passes at the start/finish line, the GFPL (as I call it for short) registers car order at every scoring loop, not just at the start-finish line.

The GFPL is not an all-encompassing metric either because it depends where the scoring loops are located. If Car A passes Car B and Car B passes car A back again within a single loop, neither of those count as a lead change, either.

That neither metric measures the “true” number of passes doesn’t matter so much. What matters is that you understand what each one measures and that you always compare apples to apples. You can think of the GFPL as measuring how racy things are during green-flag laps, whereas the lead change metric compares laps, whether there are yellow or green flag.

And here’s the perfect use case for a Venn diagram! The figure below shows all lead change (any flag, anywhere on track) as a large light-blue circle. The circle on the left (inside the large circle) is the lead-change metric and the circle on the right is the green-flag passes for the lead metric.

The figure shows that the two metrics overlap in that they both measure green-flag lead changes at the start-finish line, but each also measures other things. The lead-changes metric includes passes under yellow, and the GFPL includes green-flag passes that occur at loops other than the start/finish line.

Comparing the Lead-Change Metric and the GFPL

Let’s dig into some concrete numbers and examine the two metrics for this year’s races. The table below shows both metrics, along with a third column that displays the ratio of the lead-change metric to the GFPL. The purpose of the third column is to quantify how the two metrics compare.

The GFPL is usually greater than the lead-change metric, which means that their ratio is usually less than one.

I’ve highlighted the races where the ratio is less than 0.5. At these tracks, which are usually large and often superspeedways, GFPL can be three to four times greater than lead changes. In addition all five superspeedway races, this year’s Las Vegas race fit into that category. It does, however, have the highest ratio (0.39) in the group. These are tracks where there is a lot of passing all over the track, not just at the start/finish line.

At the other extreme are places where the GFPL is smaller than the lead change metric. I’ve highlighted those in green. In addition, there are three races (Phoenix, Sonoma and San Diego) where the lead change metric is exactly equal to the GFPL.

Take a look at Darlington II (last weekend) and Richmond. They have the same lead-change metric (29), but the GFPLs are radically different: 55 at Richmond and 26 at Darlington. There were nearly two green-flag passes for the lead at Richmond for each lead change.

This tells us that the lead-change metric by itself is not sufficient to tell us much about a race.

Breaking Down the Lead-Change Metric Earned vs. Unearned

Let’s break down last weekend’s Darlington race, taking into account that not all lead changes are the same. They count the same for the driver, of course, but would you rather watch a driver get the lead because the leader pit and the driver stayed out? Or do you prefer watching that same driver make a green-flag pass of the leader?

Out of the 29 lead changes at Darlington last weekend:

• 7 were green-flag passes
• 1 was Daniel Suarez taking the lead from polesitter Tyler Reddick on the very first lap
• 5 were leads taken on pit road under yellow because a driver’s crew got him out first.
• 1 lead change happened during GF pit cycles, when Chase Briscoe led at the end of a pit-stop cycle that started with Reddick as leader.

These 14 lead changes are what I call ‘earned’ lead changes. The driver who look the lead had to do something to get it away from the previous leader. But what about the others?

• 12 lead changes happened when the leader pit under the green flag and someone else became leader.
• 3 lead changes happened when the leader pit under yellow and someone else stayed out and became leader.

I call this latter group “unearned lead changes” because the new leader basically inherited the lead without having to pass anyone.

2026 Earned vs. Unearned Lead Changes

In the table below, I break down this year’s lead changes into the percentage of earned and unearned lead changes. This analysis requires that I check every lead change in every race. I’m not going to claim that I am exactly perfect in that count, but if I am off, it’s by one or two, not ten.

The percentage of earned lead changes ranges from 91.5% to 12.5%. I’m not one for judging a race as ‘good’ or ‘bad’, but a lot of people do exactly that. Do these numbers correlate with your enjoyment of races?

Confounding Variables and Conclusions

One main problem with trying to cite a single number as ‘proof’ of a good race is that none of there numbers exist in isolation. For example:

• A yellow flag usually produces at least one lead change. Lap-down cars must wait to pit until the lead-lap cars have pit, so the first car laps down usually inherits the lead. When those cars pit, the first of the lead-lap cars takes the lead. That car may or may not be the car that was leading coming into the caution.
• A green-flag pit cycle produces an average of three to five lead changes, depending on the length of the cycle and varying strategies.

Because of this, a race that is more of a wreckfest will have a lot of cautions and thus additional lead changes. Every stage caution basically results in a lead change.

Fewer cautions mean more green-flag pit stops, which means even more lead changes

The 2024 spring Bristol race, where tires were lasting 30 laps and teams couldn’t afford to wait for cautions had a huge number of lead changes, but that wasn’t due to passing: It was due to all those pit stops.

The lead-change metric by itself isn’t a good way to judge a race as ‘good’ or ‘bad’. It’s only when you break down the data and start getting into the weeds that these numbers gain meaning. When you hear people citing statistics, make sure you understand exactly what those statistics measure before you buy their arguments.