top of page
Search
  • MS

2020 Turkish Grand Prix [R14]: Lap Time Distribution

Updated: Apr 8, 2021

This work displays a representative race lap time distribution comparison for the top 5 finishes in the 2020 Turkish GP. In having to present this data some “outliers” have to be taken off from the raw lap times that are recorded. A data treatment process was first used and then the filtered data is plotted as shown in the ridgeline plots below.


Fig 1. Interquartile Method (IQR)

Outliers in this context are laps that are vastly different from the average lap time per individual driver. These include but are not limited to the 1st lap, safety car laps, laps going into and out of pit stops, etc. While generally the higher variance is limited to these factors, there also is a possibility driver/car errors resulting in longer lap times. To best accommodate these outliers, I’ve used a modified IQR (Interquartile Range) method based off the average lap time (50th percentile) of each driver. For the upper outlier cutoff limit, I’ve used the a 1.7*IQR scaling (IQR being the difference between the 25th and 75th percentile) as opposed to the standard 1.5 equal factor to possibly include any naturally slow laps without skewing the data too much. The number of outliers are marked in the notes of each plot along with the IQR scale used to obtain the current filtered data. As for fast laps (lower time limit), no such cutoff limit was set (cutoff set to be large enough to include all fast laps) as this would practically be improbable. This takes to the fact that a fast lap, however much faster than the mean lap time, cannot be discarded form the representative data as such data would indicate a significantly better lap from a driver. IQR method has been briefly summarized in Figure 1 for clarity in data selection. However if pit stops (in & out laps) and VSC laps don't fall outside of the outlier limit, they have been manually removed from the data in the plots below.


Hamilton with another great race, this time also securing his 7th World Title. He had good grouping of data all lying within the outlier limits and producing a standard deviation of 4.72s. Right off the bat, we see Leclerc with a higher concentration of faster laps and a smaller standard dev. This however has to be considered with the fact that he does have a significantly larger number of laps outside of his outlier zone (10 laps) -- essentially limiting his grouping. The slower laps for Leclerc have been primarily on his short 1st stint where all 6 laps were considered to be too slow before his pit stop. As we saw towards the end of the race, the McLarens seemed to have some positives both displayed through Sainz's finish and a couple of stringed fastest laps for Norris. Also is of note the faster laps distribution achieved by Sainz in comparison to the top 5 finishers.



97 views0 comments

Comments


bottom of page