The ranking can also be used as an alternative to FIA's Drivers Championship. The difference is that positions of active drivers are now determined by their performance over an entire career, rather than over one season.

This provides a more interesting perspective.

Standings as per mid season

To illustrate the dynamics of the ranking, below the progress of the relevant actors during the 2025 season.

After GP Italy 2025

These dynamics have had consequences for several drivers in the ranking:

After GP Hungary 2025

Hamilton plummets from his best 5th place to 9th place, as Mercedes loses its competitive edge in 2022. His move to Ferrari is starting to take on dramatic proportions, prompting Bernie Ecclestone to send him a retirement message.
Since 2021, Verstappen skyrockets towards the Top 10 with a superior Red Bull, but by mid-2024 Red Bull begins to falter, car and team alike. His loyalty to Red Bull keeps him out of the Top 10 for now.
When Vettel moves to Aston Martin in his pre-retirement days, he rapidly loses his spot in the Top 10.

Alonso reaches his highest ranking -12th- with Renault in 2006. With Ferrari, he drops out of the Top 25; with McLaren, Alpine, and Aston Martin, he ends up in the midfield.
McLaren pushes both Piastri and Norris up in the rankings. Piastri will probably enter the Top 25 this year.
Antonelli started his career by threatening Russell, but the threat does not last for long.
It is unlikely that Sainz will break into the Top 25.

Methodology

There will always be differences of opinion. These differences aren't about drivers, but about the criteria used. This is the subjective element of all so-called objective lists. Moreover, we tend to rate current drivers higher than those of the past. Food for thought for psychologists.

Drivers have different favorites than fans. Alonso scores highly among drivers. Bernie Ecclestone -not just anyone- puts Prost at the top of his list. He must have his reasons.

It all comes down to the criteria used. Is it fair that Fangio is at the top? He is the only one who won his titles with four different constructors. And not because there was less competition back then.

That myth is quickly dispelled when measuring the levels of competition over the past seven decades:

Level of competition per decade
The trendline speaks for itself

FIA uses one criterion for the championship -points. This criterion is not fit for this "Best-of-all-time" ranking, as FIA has used 6 different points systems over the past 75 years.

OneFormula uses three different criteria for its ranking:

Wins - in both sprint races and regular races.
Poles - in both sprint shoutouts and qualifying. A driver who achieves a pole position retains it, even if he drops back on the grid due to technical reasons or infringements in a previous race.
Podiums - in both sprint races and regular races, but only second and third places, to prevent double counting of wins.

Weighing factors

The following weighting factors are applied to these criteria:

Wins factor 3
Poles factor 2
Podiums factor 1

This can lead to some discussion, but the end result is only minimally influenced by these factors.

Hamilton, champion of absolute numbers

Percentages

Wins, poles and podiums are not counted in absolute numbers, but in percentages of all Grands Prix completed. After all, this is a "Best-of-all-time", not a "Longest-of-all-time" ranking.

Below is an example of the difference between absolute and relative numbers.

Absolute vs relative

As per end 2024

DNF

A second characteristic of this ranking are technical DNFs*. By "technical," we mean car- or team-related DNFs. If a driver doesn't finish a race for these reasons, that race doesn't count towards his score.

*did not finish

This is relevant in a ranking of drivers. Jochen Rindt -undisputed champion of DNFs- did not finish 53% of his races due to technical issues. It boosts his percentages and position in the ranking. Rightly so, because this is a ranking of drivers, not constructors.

Should this race count towards Ricciardo's Best-of-all-time ranking?

In the 1960s, close to 50% of cars failed to finish due to team or technical reasons. See the chart below:

Hence, a driver's score is calculated based on the total number of GPs minus the races in which the driver did not finish for team or technical reasons.

With and without technical DNF's

Races in which a driver does not reach the finish, due to spins, collisions or other driver-related issues, obviously do count.

Competition

Comparing apples with apples

If a driver has faced more competition than others during his career, this must somehow be reflected in his scores. But how do you measure the level of competition in Formula 1?

Quite a few articles have been published on this topic; see "References" below. I spoke with most of the authors and consulted with several statistical experts.

Ultimately, the following methodology was developed:

Calculation of competition level per season - C-level F1
Calculation of C-level per driver

Calculation of C-factor per driver
Inclusion of C-factor in the final formula.

C-levels

There are many options to calculate the C-level:

Points scored per season. This requires a uniform points system for all 75 years, not six different ones as used by FIA.
Time differences at the finish. These are not suitable because they vary by circuit.
Differences between qualifying times. Not suitable since it does not include race data.
The average number of leader changes during the race. Unusable due to pit stops.
Difference between starting and finishing positions. This is unreliable, partly due to grid position penalties imposed by the FIA.

In the end, I have opted for option 1, but with a uniform points system from 1950 to the present, for both races and qualifying.

This points system is exclusively intended to determine the C-levels.

Uniform points system

The points system is applied to the scores of the top 6 drivers in each season since 1950. This group includes practically all drivers who have won Grands Prix and have achieved pole or podium finishes.

Below two examples:

The next step is to select a tool that measures the differences between points scored. This would indicate the level of competition between the 6 drivers. I'll mention just a few:

The Gini coefficient
Herfindahl-Hirschman index
Absolute mean deviation
Standard deviation
Points winner compared to total points of the top 6
Difference between No. 1 and No. 2
Difference between No. 1 and No. 2 and No. 1 and No. 3

Option 7 is added since often the first two drivers in F1 are team mates. This may not matter in the case of Senna/Prost or Hamilton/Rosberg, but with Schumacher/Barrichello, Hamilton/Bottas and Papaya variants, one measures unreliable results due to team orders.

After trial calculations with all 7 options, I have opted for the standard deviation. Differences between the various options are minimal.

The result is inverted -dividing 1 by the standard deviation. The higher the standard deviation, the lower the level of competition.

Below the C-levels 1950-2024:

First step is to take average of all C-levels = 0.452

The average changes every year. That's why scores of inactive drivers as well change slightly.

Next, the average of the C-levels of all years in which a driver is/was active is calculated. This results in a C-level per driver.

Below some examples:

C-factor

In the final step of the process, the C-level of each driver is divided by the average of C-levels 1950-2024, resulting in a C-factor.

This limits the effect of this criterion to an acceptable level.

The Formula

In the final step of the methodology, the outcome of a driver's percentage of wins, poles and podiums is multiplied by his personal C-factor.

Below the final formula with some examples:

where

ds = driver score
wi = wins/net races
pp = poles/net Q's
pd = podiums/net races
cf = c-factor

The final score is multiplied by 100 and converted to absolute number.

Examples

Calculations as per 2024

Scores as per 2024

References

Stats F1 is used as the preferred database for the OneFormula model.
Peeters, R., Wesselbaum,D,.(2023) Competitiveness in Formula One, Sports Economic review
Bell, A., Smith, J., Sabel, C. E., and Jones, K. (2016). Formula for success: multilevel modeling of formula one driver and constructor performance, 1950–2014. Journal ofQuantitative Analysis in Sports, 12(2):99–112.
Bol, R. (2020). How to win in formula one: is it the driver or the car? The Correspondent.
Budzinski, Oliver and Feddersen, Arne, Measuring Competitive Balance in Formula One Racing (March 16, 2019).
Burkner, P.-C. (2017). brms: An R package for bayesian multilevel models using Stan. Journal of statistical software, 80(1):1–28.
Eichenberger, R. and Stadelmann, D. (2009). Who is the best formula 1 driver? An economic approach to evaluating talent. Economic Analysis & Policy, 39(3).
Elo, A. (1978). The rating of chess players, past and present. Arco, New York.
Henderson, D. A., Kirrane, L. J., et al. (2018). A comparison of truncated and time-weighted Plackett–Luce models for probabilistic forecasting of formula one results. Bayesian Analysis, 13(2):335–358.
Ingram, M. (2021). A ﬁrst model to rate formula 1 drivers. accessed March 2022).
Phillips, A. J. (2014). Uncovering formula one driver performances from 1950 to 2013 by adjusting for team and competition effects. Journal of Quantitative Analysis in Sports,10(2):261–278.
Van Kesteren, E.-J. and Bergkamp, T. L. G. (2022). Code Repository: Bayesian Analysis ofFormula One Race Results.. Quant. Anal. Sports 2023; 19(4): 273–293
formula1points.com visitors can select from a number of criteria and their weighting factors. Based on the selection, the site produces a ranking. It uses criteria similar to the OneFormula Top 25.

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