Formula 1 Races Analysis
A Brief Analysis of Formula 1 Races in The Last Six Decades
Formula 1 is a sport that relies on technological developments. When drivers race as fast as they can, they not only could depend on themselves, but also on the team strategy and the advancement of the cars they drive. Each car manufacturer team, known as constructors, put their efforts into improving the technology of the cars, so their representative drivers could be the ones who are the first to strike the finish line.
According to all of the Formula 1 races that have been held, are there any insights that we can derive? Is there any connection between the circuits and drivers? Is it possible for us to know any factor that can differentiate race winners and other drivers?
Where Does The Dataset Come From?
For this Formula One analysis, the dataset is taken from a complete dataset in Kaggle. This dataset contains complete data about all races spanning from 1950 until 2022. It contains the records and results of races and also includes quick information about the drivers, constructors, and circuits, which enables us to combine the information for analysis.
Which Constructors Have Ruled The Circuits?
Each circuit has its characteristics and challenges that drivers and constructors must battle. In this part, we are going to see which constructors have won the most in each circuit of the 2022 Season. For this season, there are 22 circuits used for races.
In terms of the number of circuits that the constructor rules, Mercedes has majored 11 circuits winning the most. Only in three circuits does Mercedes shares the number of wins with other constructors (which means the same number of wins). To be detailed, Mercedes has won 67 races in these circuits.
Meanwhile, Ferrari has conquered nine circuits, where four of them are shared among other constructors who have won the same number of times. Nevertheless, Ferrari has won 88 races in these nine circuits, which is higher than the number of wins for Mercedes in its respective conquered circuits.
Which Circuits Are The Most Challenging to Drivers?
Still speaking about the circuits, can we describe or measure in some way how challenging the circuit is to the drivers? In the meantime, for most of the races, most of the time not every driver could finish the races. Some of them had to retire earlier due to several conditions, such as accidents or malfunctions of some car parts. Here in this part, the number of DNF (do-not-finish) drivers is used to measure how challenging the circuit is for every 2022 circuit.
Here, we are counting the total number of DNFs for each circuit and its average. For the average measurement, the number of DNFs is divided by the number of seasons respective to the circuit, since a circuit will not be constantly included throughout the years.
In terms of the average number of DNFs, Circuit Paul Ricard (France) has the highest average, followed by Circuit de Monaco (Monaco) and Imola Circuit (Italy). But, in the terms of the absolute number of DNFs, Circuit Paul Ricard has a low number of DNFs.
It could be inferred that in a short amount of time, Circuit Paul Ricard the number of DNFs at the same level as Circuit de Monaco if interpolated.
Circuit Paul Ricard has been picked in 15 seasons and has actual number DNFs as 189 occurrences. In another circuit that was picked at a similar frequency (more or less) as Circuit Paul Ricard, the number of DNFs is far below Circuit Paul Ricard. For example, Bahrain International Circuit has been chosen 18 times and only has 68 occurrences of DNFs.
How Can We Distinguish Race Champions While Racing?
The race champion is indeed defined at the finish line, but while the race is still going on, is there anything that can differentiate champions and fellow racers?
During the Race Days (which include qualification days and actual competition days), there are many statistics and metrics available for viewers to know. In this part of the charts below, a group of metrics has been compiled and statistically tested whether the mean value is significantly different between race champions and fellow drivers.
Four metrics are statistically significant between race champions and other drivers. The first one is derived from the qualifications, called average qualification times. In qualification, each driver will record their time as fast as possible for one lap. When you see the final result of the qualification, the first ten drivers are the best ones who have gone through three times of qualifications for the race, while the other drivers are eliminated in the first two qualifications. To generate average qualification times, for specific drivers and races, the qualification times will be averaged. For this metric, the race winners on average recorded two seconds faster than other drivers in qualification.
The other three metrics come from the actual races. In terms of time, generally, race winners are 2–3 seconds faster than the others. For the average lap times, race winners are 3.4 seconds faster than the others, and their fastest lap times are two seconds fasters. At the fastest lap, for the speed record, race winners are 5 km/hour faster than the others.
