2021 Season quali battles: Rounds 1 to 11
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We’re at the mid-season break, so let’s take a look at how the intrateam quali battles are developing so far in this 2021 Formula 1 season. I will make this article every one or two races so that you can stay updated on how the drivers are faring against their teammates so hopefully, you will enjoy it.
I am completely shot mentally. Life feels like a mess and I’m feeling very down right now. I haven’t done an article in a while so I will try to write a short article. I know I don’t have to justify myself to anyone, but I feel like I do. This project is great and I like it, and I think some of you do too, so I will do my best to keep going.
Methodology
This analysis is quite similar to the one about Perez that I did a while ago, but comparing performance between teammates for all the teams. As before, the main challenge is comparing performance between drivers in different tracks. Some tracks will have higher dispersion in quali times, while in some tracks you will see very similar lap times all across the grid. To overcome this issue I decided to standardize the data.
The process is quite simple. First, I obtained the average time done by all the drivers in every quali session analyzed. Eg, for the 2021 Emilia Romagna GP, I obtained the average lap time done in Q1, Q2 and Q3. This includes the lap times done by every driver who participated in each session. Second, I subtracted this average time from all the lap times done in that session. Finally, I divided that resulting number by the standard deviation to end up with the standardized lap time.
An example of the standardization process is shown in the table below. If you like formulas, this one should help you to understand a bit better how this process works.
The second challenge with this analysis is how to compare performance when not all drivers qualify to all quali sessions. For example, I can’t compare the lap time of a driver in Q3 vs the lap time of his teammate in Q1. These numbers are just not comparable due to track evolution. The reality is that there is no proper way to do this. Due to this problem, I only compared quali sessions that both teammates had in common. Eg, I only compared the Q1 and Q2 sessions of Lando Norris and Daniel Ricciardo from the Monaco GP. This means I compared Lando’s best time in Q1 with Daniel’s best time in Q1 and got the delta between them. I did the same for Q2. Since Danny Ric didn’t qualify for Q3, I didn’t utilize Lando’s lap time in Q3 for this analysis.
An analysis like this has the main limitation of not telling you if a driver is consistently missing qualifying to Q2 or Q3. I decided to represent this data with a simple bubble chart that I will show in a while.
Finally, if you want to take a look at the detailed data, I will add a table with all the information at the end of the article.
Standardized lap times
Interpretation
How do we interpret this chart? Some important pointers must be considered. First, the x-axis has no traditional units. The units shown here are not seconds or milliseconds, but standard deviations above or below the mean. Second, a standardized lap time of 0 means that it was exactly the average time done during that particular quali session (Q1, Q2 or Q3). Negative times—dots shown to the left of 0—represent faster lap times than the mean (this is good!), while positive times represent slower lap times than the average.
The gradient bands shown stand for high or low-density areas. Darker areas show where most of the laps were recorded, while lighter areas show the opposite.
The horizontal coloured lines represent the 66% and 95% quartiles. The thick line around the middle contains the middle 66% of the laps, while the thinner line spans 95% of the lap times done by each driver. Laps outside any of these two intervals could be considered as anomalies, that is laps that were perhaps a bit faster or slower than you would normally expect.
Analysis
It’s mid-season, so the gaps should be fairly stable now. Or so I thought. The reality is that the gaps between drivers have continued to be quite variable, and the deltas have changed suddenly from race to race.
Currently, the smallest gap between teammates is found at Aston Martin. Stroll was leading for most of the season, but Vettel has now been able to adapt to the car. The standardized delta of 0.03 is quite minuscule though, with both drivers being pretty much even at the moment.
The delta at Ferrari and Alpine has continued to decrease too, especially with Alonso’s latest strong performances. On the other hand, the delta at Mercedes, and especially at Red Bull, has widened in the past few races. On the session-by-session table, you will see that Verstappen has been very strong against Perez in the previous three races. This has caused a massive increase in the gap between both drivers.
One of the most interesting battles has been happening at the worst team on the grid, Haas. Yes, the gap is still quite big. Yes, Mick Schumacher is yet to be beaten by Nikita Mazepin. Having said that, the delta between both drivers has been considerably smaller in the past 5 races. For the 4 qualifying battles, the delta between Mick and Nikita was of 1.12 standard deviations, in favour of the German driver. In the last 5 races, this gap has narrowed down to 0.64 standard deviations.
Standardized lap times: Session-by-session
The following table presents the information that has been shown before, but on a quali by quali session basis. Every quali session was considered to be a battle, with a driver crowned the winner by a certain margin (delta).
How is this different from the previous chart? The previous analysis considered the whole season to be a battle, while this chart considers each session as an individual competition. I am a fan of the season-long analysis, but the more granular race by race, session-by-session analysis provides some interesting information about the performance of the drivers.
Just as before, there is no way to compare the performance of the drivers if one of them classified to Q2 or Q3 while the other one didn’t. Because of this, you may not see a driver in any of these two columns even though he advanced to that particular session. I can’t declare a winner between for example Perez and Verstappen at the Q3 session of the 2021 Emilia Romagna GP since Perez failed to advance from Q2 to Q3.
Remember that the units that are being used here are NOT seconds, but standard deviations. These units are harder to interpret than pure seconds, but allow you to compare performance between different tracks. Seconds are easier to interpret, but the comparison between different tracks is misleading at best, so I decided not to use them for this analysis.
Appearances in quali sessions
Interpretation
This is a quite simple chart to interpret. Each big bubble represents a team. The bubbles inside each big bubble represent each driver in each team. The little, medium and slightly larger bubbles inside show the appearances in each quali session of the season. Take a look at the size of Daniel’s bubble compared to Lando’s bubble. As you can see, it is smaller due to him having only five Q3 appearances, compared to Lando’s 11.
If you want a hi-res png image of this chart just click here.
Analysis
One of the main issues with the standardized lap times comparison is that it doesn’t consider races when one driver moves into Q2 or Q3 session and the other didn’t. There is no way to compare times between quali sessions since track evolution has great influence over a lap time. This bubble chart tries to put the number of times each driver has advanced to Q2 and Q3 in perspective.
Take, for example, McLaren. The standardized delta between both drivers is 0.67 in favour of Norris. However, the bubble chart also tells us that Ricciardo has qualified to Q3 only on 5 occasions. His teammate, Lando Norris, has been able to get into every single Q3 session available so far.
Something similar is seen at AlphaTauri. Pierre Gasly has taken the AT02 to Q3 on 9 different times. Yuki Tsunoda, on the other hand, has only qualified to Q3 three times this season.
While the gap between drivers is pretty important, I would argue that maximizing performance and getting into Q2 and Q3 sessions is perhaps just as important.
Detailed data
This is a simple table that should be pretty much self-explanatory. The table shows the number of appearances in each quali session, the average position in each particular session, and a tiny sparkline chart with the range of the previously mentioned average position.
Analysis
This is a simple table that should be pretty much self-explanatory. The table shows the number of appearances in each quali session, the average position in each particular session, and a tiny sparkline chart with the range of the previously mentioned average position.
Final remarks
I hope you have enjoyed this post. Working on articles like this one is no easy task, and takes quite a bit of time and effort. If you enjoy visiting my site, please consider sharing my posts on social media or with friends and family. If you want to support me, I would also greatly appreciate a donation.
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