Featured image of post 2024 Monaco GP: Quali session - Leclerc vs Verstappen

2024 Monaco GP: Quali session - Leclerc vs Verstappen

Maybe you don’t remember, but when I was using my previous site (F1bythenumbers) I worked using the telemetry data. For a very long time I stopped working with that type of data mostly because, well, it has many quirks. Believe it or not, all of the analyses out there are using data that 1) isn’t properly synced and b) has many inaccurate interpolated values. In some cases, the distances calculated are wrong by as much as 100 meters or even more. In my opinion, this is completely unacceptable. The simple truth is that the raw data obtained by most sources out there is just not up to the task of analyzing runs that require millisecond precision.

It wasn’t until a few weeks ago that I decided to give telemetry data a chance. I worked hard for dozens of hours to properly process the raw data and obtain a dataset that was accurate enough for my high standards. As far as I’m aware, this is the first and only analysis out there that uses corrected data.

I will be using this newly corrected data to give you more detailed analyses that you can trust, so hopefully, you’ll enjoy them.


For this analysis, I will be working with data from the qualifying session of the 2024 Monaco GP. In this analysis, I will compare the fastest lap done by Charles Leclerc (1:10.270) vs the fastest lap done by Max Verstappen (1:10.567).

This analysis is only possible after doing extensive post-processing of the raw telemetry data. The data points are properly synced and interpolation has been kept to a minimum. When interpolation was necessary it was done in a way that reduced the margin of error to the maximum by using complex statistical models that provide increased precision over simple interpolating techniques. I’m willing to put my head on the line here and assure you that this data is reliable and should provide proper, real, conclusions from what we saw in the qualifying session

My data won’t exactly match the data shown by other sources. I’ve extensively post-processed the raw data to get a dataset that is up to the task.

Time delta

Time deltaCumulative time delta

The two charts shown in this section work in tandem. The time delta chart shows the time gap between both drivers at different points of the lap, while the map shows the same cumulative delta over the course of the lap. The time delta chart has higher precision than the map, but the map shows a good overview of how the lap developed for both drivers.

Do not confuse this map with the track dominance graphic provided by AWS. My chart shows the cumulative time delta throughout a lap, while their graphic shows who was faster on predetermined sections of the track.

Both of these charts use only positional data, with minimal interpolation required to perfectly match the position of both drivers. The precision of this analysis should be well under 1 hundredth of a second.

Unlike FP2 where we saw Leclerc easily outpacing Max, the session was much closer. Verstappen was particularly strong in sector 1, outpacing Leclerc by just over 1 tenth. The data shows Max was able to gain an advantage on turns 2 and 3, and then increase the delta by carrying more speed through turns 5, 6 and 7. Unfortunately for Verstappen, the rest of the lap was not nearly as good for him.

After T8 (Portier), Max lost his time advantage over Charles, and this trend continued until T16 when Max was able to reverse the trend and give himself a fighting chance. However, it is clear that Leclerc managed to carry much more speed on T17 (La Rascasse) and then had much more traction out of T18 and 19. The time delta between both drivers went from around 0.075 seconds in favour of Max to the final 0.297 seconds in favour of Charles in the span of around 400 metres.

Speed telemetry

Speed telemetry

To better understand how Charles managed to get such a commanding lead over Max, we have to analyze the speed telemetry chart. The data shows the recorded speed of both drivers at different points during the lap.

This chart interpolates some speed data, but the interpolation was done with statistical models that produce far more realistic data points than simpler algorithms. Although the telemetry’s low refresh rate causes some “blockiness”, the data should be smoother and more accurate than that provided by other sources.

The speed telemetry confirms what we just saw in the delta and map charts. Max was particularly strong between the 600 and 800-metre mark and then was able to slow down the car less in T7 after completing the hairpin.

Many people attributed the lack of top speed that Max showed in FP2 to a lower engine mode, but this trend continued during the quali session. While the delta wasn’t as pronounced, the RB20 did not have the top speed that the Ferrari showed in the tunnel section. I still believe that Red Bull was running slightly more downforce than Ferrari, which could’ve caused this phenomenon.

In the final section of the track, Charles reached T12 (Tabac) with a higher top speed than Max, but then slowed down way more than Max did, costing him valuable time. Max looked strong between T12 and T17 (La Rascasse) but then struggled in T18 and 19. Max was ~ 10 km/h slower through this section, which completely swung the delta in favour of Leclerc.

Final remarks

Charles Leclerc had a stronger session than Max Verstappen did. Yes, Max made a mistake and couldn’t get a proper final lap, but Charles would’ve most likely still taken pole position. Charles gained around 1.5 tenths between his second to last run and his final run. If we assume that Max could’ve matched that, he still would’ve finished behind the Monegasque, although he could’ve possibly placed his car on the front row for tomorrow’s race.

Support me!

Hopefully, you have enjoyed this detailed analysis. I want to write more and create more personalized analyses, so I’m excited about the possibilities now that I have proper telemetry data. As I mentioned, my data won’t match the one provided by other sources. This data has been reworked to be more precise, allowing me to delve into the world of telemetry analysis. This process took at least 30 hours of hard work, at least based on rough estimates, but I think the result was worth it.

If you enjoyed this article, please support me and my project. Keeping this site going takes many hours of energy and effort. Trust me, maintaining a project like this one is no easy task. If you want to donate some money to the cause, please click on the “BUY ME A COFFEE” button. If you don’t have money to donate, please share the content with other people so that this project can keep growing. Thank you.

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