How to measure the absolute performance of 2021 F1 cars

The 2021 season will certainly be remembered for years to come, and one hopes the lasting memories will be of the competitive fights throughout the field rather than some of the more controversial aspects.

It is perhaps inevitable that a close battle will lead to more occasions when driving standards and even regulatory procedures become the focus of attention and, when the battle is close at the front, it is inescapable that polarised opinions will be formed. But let’s put that aside for a moment and examine how the teams performed over the course of the year, in terms of the absolute performance of their cars.

It might seem simple to determine the performance of the cars each weekend, but it is in fact remarkably difficult. Looking at qualifying times does not give a complete answer. Even in the top 10 it is extremely unlikely that even one driver from each team will actually get a perfect lap, so should one take the best sector times and add them even if they were not set on the same lap?

How do you equate the performance of the cars eliminated in Q2 from those in Q3 when a track is evolving? Also, it is often the case that the faster cars will use a less performant tyre in Q2, to allow a better race strategy, which really skews the assessment of overall performance.

Some cars will also go better than others on certain types of track, which can distort the underlying development progress. For example, we could see early in the season that Ferrari appeared to have good performance in slow corners and sure enough was most competitive in Monaco – in absolute vehicle terms, if not operational ones…

PLUS: What the data tells us about the F1 2021 title fight

With all these caveats, probably the best way of establishing performance is by matching simulation to actual track data. This is done by comparing the speed profile of a virtual car with that measured during the race weekend. By adjusting parameters such as downforce, drag and engine performance one can start to eliminate some of the unavoidable variables found in raw data.

Significant caveats are required to calculate the accurate pace of cars on any given weekend

Photo by: Glenn Dunbar / Motorsport Images

It is a mathematical fact that in order to determine any number of variables one needs at least one more equation than there are variables, and this leads to a problem in this case. Some of the variables, while very different in themselves, produce similar effects. For example, drag and engine power both determine top speed; grip and downforce both determine cornering speed.

This makes it difficult to separate all factors, but over a season an iterative approach allows a reasonable degree of accuracy in determining performance. Certain aspects can be regarded as constants. For example, one would not expect engine performance to vary unless a new engine or a new fuel was introduced. As these types of events are known, they can be inspected separately.

A team might perform well one weekend only to fall behind the next, and the reason for this is nearly always to do with management of tyre temperatures and their subsequent impact on performance

With very few significant improvements made to suspension these days one might think that tracking performance through the season would now show clearly how each team’s aerodynamic research was paying off, as this is by far the largest determinator of performance. With such constant evolution as a windtunnel brings, almost linear changes in performance might be expected.

Unfortunately, changes in performance – and specifically relative performance to other teams – are anything but linear. A team might perform well one weekend only to fall behind the next, and the reason for this is nearly always to do with management of tyre temperatures and their subsequent impact on performance.

With these caveats in mind, what does the simulation and analysis reveal? Considering first the top three teams, we see that Red Bull started with a reasonable performance advantage over Mercedes, and generally held this advantage until mid-season, when Mercedes started to gain competitiveness – finishing the year pretty well even with its main rival. Ferrari, after flattering to deceive in Monaco, generally drifted further and further from the top two.

PLUS: The F1 compromises Mercedes battled to make ‘monster diva’ W12 a winner

In midfield we saw very similar development rates between McLaren and Alpine, albeit with Alpine generally behind on actual lap time. These development rates matched that of Ferrari, but all fell short of AlphaTauri – which effectively maintained a constant deficit to Mercedes and Red Bull, suggesting the Red Bull junior team was matching the development rate at the front.

PLUS: The changes edging McLaren closer to an F1 title challenge

Further back there was little to choose between the development rates of Aston Martin, Alfa Romeo and Williams. Haas, although firmly anchored to the back of the grid, was rather erratic in absolute terms. This is likely due to that team struggling more to handle tyre temperatures while running two rookie drivers.

AlphaTauri's rate of development with its 2021 racer was impressive

Photo by: Charles Coates / Motorsport Images

What is particularly noticeable with the teams contesting seventh to 10th in the championship is that they fell further behind from September’s Dutch Grand Prix onwards. This is very likely to be because of focus turning firmly to all-new 2022 car designs, leaving scant resource spare to continue developing 2021 models.

The constructor status enjoyed by the teams in Formula 1 is now unique in professional single-seater racing, and it is this that does so much to drive costs. This explains, in part, the difference between running an F2 team for around £4m a year to running an F1 team with engineering and racing costs of over £100m. But it is this status that does much to ensure there is always interest and intrigue at a technical level, and adds a dimension that other formulae are now unable to emulate.

Ferrari team boss Mattia Binotto saw his squad climb to third in 2021, but can it bridge the performance gap to the top two this year?

Photo by: Ferrari