2020 Spanish GP: HAM vs VER per micro-sector

Lewis Hamilton won the 2020 Spanish Grand Prix in dominating fashion. Where did he get the upper hand against his closest rival, Max Verstappen? Let’s take a look at the numbers.


I started by obtaining data from the “telemetry” provided by the Formula 1 live app. The data contains information about the speed and position of each driver from the entirety of the race. I then decided to divide the track into 100 micro-sectors, each of about 100th of the length of the track.

After getting this data, I made a spatial analysis to classify each of the data points provided by the timing app into the just created micro-sectors. This meant that I would get the information from all 66 laps divided by micro-sector.
Since the idea was to compare the speed of each driver for each micro-sector, I had to make sure that all the laps that I would use would be comparable between drivers. To get a valid comparison, I removed all the laps where either driver was in the pits or the lap after going into the pits.

Just to be completely sure that the laps were comparable, I ran an anomaly analysis to remove laps that could have perhaps problems with the telemetry. The analysis, however, found no problems, so I could continue with the rest of the process.

I grouped the data by micro-sector and compared the average speed achieved by each driver in that micro-sector. To get the difference in speed between both drivers, I subtracted the speed of the fastest driver minus the speed of the slowest driver. E.g., let’s say that in the micro-sector 25 Max had a speed of 250 km/h, and Lewis one of 245 km/h. The difference in speed would be calculated as 250 – 245 = 5 km/h in favour of Max Verstappen.

Remember that this average speed was calculated by using the telemetry from all the laps of the race (minus laps with pit stops and anomalies as previously explained).

Finally, I created a map of the track with all of the 100 micro-sectors and coloured them according to the calculated difference in speed between both drivers. Areas with blue colour represent sections in which Max was faster than Lewis, while areas with a green-ish colour represent sectors in which Lewis was faster than Max. The darker the colour, the greater the delta in speed between both drivers. Areas with white or white-ish colour represent micro-sectors in which both drivers were evenly matched.

For the map that uses the qualifying data, I followed almost the same process as for the one for the race data. The only difference is that for the quali chart I only used the data for the fastest lap done by each driver during the qualifying session.

Just as a note, the finish line is represented with a cross and a circle, so that you can see where each lap starts.

Delta per micro-sector for the qualifying session

Important note

I’ve added two different images that show the same information in slightly different ways. The first one shows the colours with a symmetrical scale that goes from -20 to +20 km/h. The second one shows the same data but with an asymmetrical scale that goes from -10 to +20 km/h. The asymmetrical scale is very good at showing the difference in speed between both drivers since it creates a greater difference between the colours. The first scale doesn’t show the differences as markedly as the second one but has the advantage that it can be compared between charts. This means that the colours will remain constant when comparing the chart that has the data from the quali session with the chart that has the data from the race.


As we can see, Lewis was faster than Max in most micro-sectors of the track. The Britishman completely dominated in quali, and outpaced Max in more than 80% of the micro-sectors that were analyzed. He seemed to be faster in the straights and most corners, with the exception of turns 2, 8, 12 and perhaps T14. Hamilton had his best micro-sector just before T4, where he had a whooping speed advantage of over 20 km/h over Max.

The Dutchman had his best moments in T12 and right before T14. His speed advantage was however of around 10 km/h over Lewis, and as we all know it certainly wasn’t enough to overcome the deficit accrued over the rest of the track.

Delta per sector micro-sector for the race

Remember what I said about the scales? Here we can see the differences. The first image of the carousel shows the colours with a symmetric scale. While the differences are not so easily visible (the colours look a bit faded), they are comparable to the colours shown in the previous chart. The second map with the asymmetrical scale allows you to better see the differences in speed between both drivers. Its main downside is that you cannot compare the colours between charts. Just something to keep in mind.

It’s quite easy to see that the race shows a similar but less extreme version of the quali session. Lewis still had a significant advantage in more than half of S1 and S2, and some areas of S3. The greatest difference is seen in the micro-sectors of the long T3. In quali, Lewis completely dominated in this area, but during the race, Max was able to keep up with the Mercedes driver.

Another one of the differences is seen in T5. While in the quali session Lewis had a speed advantage over Max, the race shows us a different picture. If you go to the second picture of the carousel you’ll see that Max had his best micro-sector in this section of the track, outpacing Lewis by over 10 km/h.

Finally, something that caught my attention was the little difference in speed between both drivers at the main straight of the track. Mercedes is seen as a car stronger in the straights, but weaker in the turns. The reality is a bit more complex than that. From this simple analysis, I would argue that Mercedes worked on a strong aerodynamic setup. With a strong power unit, the German team was able to sacrifice speed on the straight while increasing the performance on the long turns seen at the Circuit de Barcelona-Catalunya. Clearly, this strategy played out in their favour, with Hamilton taking an easy victory over the rest of the field.

Final remarks

Mercedes’ reputation of being fast on the straights and slow in the corners is not 100% accurate. The Circuit de Barcelona-Catalunya is a twisty circuit that supposedly favoured Red Bull, but as we saw, the weekend was dominated by Mercedes. After Mercedes’ troubles in Silverstone, they came back with a vengeance and optimized their setup for a circuit with long corners and high degradation.

Red Bull is doing a great job in staying within range of Mercedes, but right now it is hard to see them challenging for the World Championship. The Austrian team was able to capitalize on Mercedes’ problems at the 70th Anniversary GP, but once again couldn’t compete at the Spanish GP. They will need to improve their performance not only on the straights but also on the slower sections of the track in order to fight for more race victories.

In any case, I hope that you have enjoyed this article. I’ve been working hard to get these new analyses for all of you. If you enjoy them, please consider a small (or big!) donation and remember to share my site with your friends. Any comments or questions are greatly appreciated too.


  1. aapp

    Excellent job!
    As far as I know, the micro-sector shown on TV (the updates of the gap between drivers) is long about 200m. I don’t know if the micro-sectors of the Android app are the same, but I suppose so…
    I would like to have a look at some of your code snippets. Do you plan to make a repo Github?
    For example here is a collection of snippets of R and Python code from FiveThirtyEight which I’ve found quite interesting (https://github.com/fivethirtyeight)

    • admin

      Hello aapp

      Thanks for the nice comment. Yes, the micro-sectors created by my analysis are different from the official micro-sectors. My analysis divides the length of the track in 100 parts, while the official micro-sectors are created by dividing each sector in n micro-sectors. The android app doesn’t include the information from these micro-sectors though, just the information for each sector (S1, S2 and S3). The only way to see who was the fastest in each official micro-sector is to analyze the video feed provided if you are a suscriber of F1 TV.

      I’m not too interested in getting a repo right now. I can barely keep up with this season since I got a job and we keep getting triple headers. To be 100% honest, the scripts are functional but I wouldn’t consider them to be efficient or “nice”. They get the job done, but with more time I’m sure they could be better.

      Regarding FiveThirtyEight, my theme is actually inspired by theirs. I made some modifications though, but I do enjoy their analyses. They do much more advanced modelling though, while I mostly focus on processing the data and making it easy to understand via descriptive statistics and simple visualizations.


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