Qualifying teammate battles seem to be of great interest to the current F1 community. While I’m a firm believer that Sundays matter far more than Saturdays, I can’t deny the growing importance of qualifying—especially with how tough overtaking has become with the latest generation of F1 cars. Track position is king, and starting ahead often means staying ahead. So while race day is where the points are handed out, Saturdays are playing a bigger role than ever in shaping the final results.
Analysis
Click to expand methodology
Methodology!
As with race pace, we can’t directly compare qualifying pace between races. Different tracks, lengths, and deltas make it tricky. To handle this, I standardized the data using a metric called symmetric percent difference. Without getting too technical, it’s a more robust way of calculating percent differences — hence why I chose it.
I calculated the symmetric percent difference for all qualifying sessions between teammates, keeping only the maximum session where both drivers participated. For example, if George Russell made it to Q3 but his teammate only reached Q2, I used the Q2 data for the comparison. If a driver couldn’t set a lap time in Q1 while their teammate did, I removed that session entirely. While this isn’t ideal, using equally comparable data points is crucial for a fair performance comparison. Negative symmetric percent difference values mean that a driver was faster than his teammate, while positive values mean that the driver was slower than his teammate. A difference of 0% means that both drivers were just as fast.
I calculated the values for each race for each team and plotted them as individual data points in the chart. I then calculated the median of these values for the season (so far) and displayed it the left side of the plot, next to the team logo. Smaller overall values represent that both teammates were more evenly matched during quali, while larger overall values show a greater gap between teammates.
Additionally, on the left-hand side of the chart next to the driver’s name, I also added the number of times a particular driver has been faster than his teammate in quali.
Finally, I added a gold-coloured diamond to show the median gap between teammates. This number will be equal to the overall value displayed on the left side of the plot, next to the team logo.
Issues!
One of the main issues when gathering data from multiple races is that the deltas will change depending on the length of each track. A delta of 0.1 seconds in a short track (say, 1:05 per lap) will be greater than a delta of 0.1 seconds in a long track such as Spa (~ 1:45).
One way we can standardize the data is by converting the deltas to percentages, but there is one big issue with this. The traditional way of calculating a percent difference is with the following formula:
$$ Percent\ difference = 100\times\frac{value1-value2}{value2} $$
The main problem is that this value is not symmetrical. This means that if I reverse the order of value 1 and value 2, the final percent difference will be different.
$$ Percent\ difference = 100\times\frac{80-90}{90}=-11.11\% $$ $$ Percent\ difference = 100\times\frac{90-80}{80}=12.5\% $$
You can see that the percentages are not reversible, even though in both cases we’ve changed the original value by 10 units.
One way we can solve this problem is by using the symmetric percent difference, which is calculated by using the following formula:
$$ Symmetric\ percent\ difference = 100\times\frac{value1-value2}{(value1+value2)/2} $$ This formula is reversible, meaning that regardless of the order of the values, we will get the same result. Because of this, I decided to use the symmetric percent difference formula as the basis for the analysis.
Quali delta between teammates (symmetric percent difference)
The results can change dramatically by switching between the mean and median as the key metric of interest. These numbers will eventually stabilize and converge as the season goes on.
After five races (and one sprint), the quali deltas have started to stabilize. This season, we have the anomaly of Lawson switching places with Tsunoda after just three races, which makes our usual analysis a little trickier. Normally, I’d just use the median as the key metric of interest since it’s more robust to outliers. However, in this case, the median might skew the average delta between Lawson and Verstappen.
To counter that, I’ve decided to include both the median and the mean qualifying deltas in this article. This approach might change in future posts, but for now, I think it gives us a more complete picture.
Regardless of which metric we look at, the largest gap between teammates is found at Red Bull Racing. If we use the median symmetric percent difference, Max Verstappen is currently beating Yuki Tsunoda by a whopping 0.968%. If we go with the mean symmetric percent difference, then the largest gap shifts to Verstappen outpacing Liam Lawson by an average of 1.034%.
These numbers are pretty significant. For reference, in 2024, Verstappen outpaced Sergio Perez by a median of 0.543%, while the largest gap that season—at Sauber—was 0.602%. Right now, Verstappen is outpacing his teammates by around 80% more than that.
At the other end of the spectrum, the smallest delta is found either at McLaren (0.065% based on the median symmetric percent difference) or Haas (0.113% based on the mean symmetric percent difference).
It’s important to note that most teammate pairings have been fairly competitive so far, with a few exceptions—including Russell vs Antonelli, Gasly vs Doohan, and, of course, Verstappen vs Lawson and Verstappen vs Tsunoda.
Qualifying stage appearances
This chart was exported in very high resolution. If the text appears a bit too small, feel free to zoom in to see each individual bubble more clearly.
Click to expand explanation
I’ve often seen tables showing how many times drivers reached Q1, Q2, and Q3, but I’ve never been fully satisfied with them. Tables tend to have too much text while still missing key insights. To address this, I created a bubble chart.
Each bubble represents a driver’s qualifying or sprint qualifying appearance throughout the 2025 F1 season. The bubble’s size reflects the driver’s final qualifying position, with larger bubbles indicating better results. The actual position is displayed as a big number inside the bubble, and the colors indicate the qualifying session reached.
As of the fifth race of the 2025 season, the biggest difference in qualifying stage appearances is at Alpine. While Pierre Gasly has reached Q3 three times, Jack Doohan has yet to make it past Q2.
Another interesting contrast is at Aston Martin. Fernando Alonso has consistently made it to Q2 in every session he’s taken part in, while Lance Stroll has been knocked out in Q1 three times. That said, Stroll is also the only Aston Martin driver to make it to Q3 this season.
Most of the remaining teammate battles have been fairly even so far. One standout is Oliver Bearman, who’s been holding his own against Esteban Ocon—a driver known for his strong one-lap pace. Matching Ocon in qualifying is no easy task, which makes Bearman’s performance all the more impressive.