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Can a Formula be used to create Driver Ratings for Formula E Drivers?

Written by Olly Radley, Edited by Vyas Ponnuri

Credit: Handout / Jaguar Racing / Getty Images

Every year, Codemasters, with the support of EA Sports, release their Formula 1 video game; within the said game, there’s a career mode, where each of the 20 drivers, as well as the F2 class below them, have a “rating”.

This rating comprises four main attributes: experience, racecraft, awareness, and pace. These four scores are then all considered in order to come to a final rating of the driver. For example, the highest rating in the game is Max Verstappen at a 96 (85 experience, 98 racecraft, 86 awareness, and 98 pace) whereas the lowest is Logan Sargeant at a 71 (63 experience, 73 racecraft, 74 awareness, and 71 pace).

With this in mind, as a Formula E fan, I decided to compile several different stats, and use them to create a formula that can determine a “driver rating” for all 22 Formula E drivers from Season Nine.

Firstly, in order to create this formula, I needed to decide on what stats would be considered in the rating. Unfortunately, there isn’t too much specific Formula E data and statistics available to the average viewer, so any numbers I used would have to be general, and any chalkboard stats I wanted would need to be calculated by me.

The final formula would be an average of several decimalised statistics, multiplied to set a maximum driver rating, and added onto a base rating to set a minimum driver rating. So, in order to get 22 driver ratings, I needed to:

  1. Collect the data

  2. Set a baseline

  3. Set a multiplier

Throughout this process, I will use the Envision pairing of Sebastien Buemi and Nick Cassidy, to show you how the numbers are being created.

The Envision Pairing of Cassidy and Buemi; Image Credits - Formula E

Now then, step 1, collecting the data. For the obvious baseline stats such as wins, podiums, poles, or fastest laps, I decided to create a combined number to add to the average, rather than treating them as individual figures.

For the aforementioned simple four stats, I simply converted them into number per race entered, so wins per race, podiums per race etcetera. With our two example drivers, Buemi scored 0 Wins/Race, 0.06 Podiums/Race, 0.125 Poles/Race, and 0 Fastest Laps/Race. Cassidy meanwhile, clocks in with 0.25 Wins/Race, 0.5 Podiums/Race, 0.06 Poles/Race, and 0 Fastest Laps/Race.

While teams like Envision, who'll be achieving wins and podiums regularly, will be helped by these kinds of stats, they don't take into account the likes of ABT CUPRA or Mahindra towards the back of the pack, who's drivers can't achieve the likes of wins and podiums as a result of their car's poor performance.

Therefore, to combat this, I also introduced a Points per Race Entered metric which benefits the midfield teams, and even the teams at the rear of the field, as this is the highest figure for them.

However, because we're working with decimals, the points per race number was multiplied by 0.04, given that a maximum of 25 points are available from race finish alone to each driver, and 1 divided by 25 is 0.04.

Using our examples, Buemi, who has 105 points from 16 races entered (6.6 points per race) has a decimal of 0.26. Cassidy on the other hand has 12.44 points per race, giving him a decimal of 0.4975. These decimals, combined with the other 4 in its section, will give each driver a score.

Some of the top drivers, like Nick Cassidy, will have a score above 1, which may sound like an issue, but the other decimals in the second section will bring that average back below 1, and prevent these top drivers breaching the maximum rating that we set. With all that said and done, Buemi scored 0.45 from the first section, while Cassidy had an impressive 1.31.

Next, I delved into some of the more specific, chalkboard stats. Some were still general, but to represent the overperforming drivers at worse teams, more relative and comparable stats were also used.

The first stat of this second section was Average finishing position. This stat, like the next one, is basically what it says on the tin, except to put it into decimal form, I had to take it away from 23, and then multiply it by 0.045 (1/23). In this stat, Buemi, with an average finishing position of 8.5, had a score of 0.654, and Cassidy, with an average finishing position of 5.67, had a score of 0.78.

As you may notice, in this section, the closer to 1, the better your rating at the end. Next is average qualifying position, which, as you may have guessed, works the exact same way as average finishing position. On this stat, Buemi's average quali position of 7.5, becomes a decimal of 0.69, and Cassidy's 7.4, becomes 0.7.

With the more general stats of this section out of the way, we've got two final relative stats to create a fairer picture for midfield and backmarker teams.

Firstly, the simpler stat: Percentage of Team's Points Scored. This is very simple to explain, as it is very simply what it says; the amount of points you scored as a percentage of how many points your team scored. With our duo, Envision scored 304 points — 199 for Nick Cassidy and 105 for Sebastien Buemi — therefore Cassidy's percentage (in its decimal form) is 0.65, while Buemi's is 0.35.

Finally, to round off the stats, we have the average race finishing gap to teammate, which is your average finishing position compared to your teammate's average finishing position. This stat is unique in the way that, if you are outperformed by your teammate on this metric, then your decimal will be a negative, and your teammate will have the exact same decimal, but positive.

For every position you are infront or behind your teammate on average, your decimal goes up or down by 0.045, the same way as average finishing position and average qualifying position.

For our Envision pair, Buemi was on average, just under three positions behind Cassidy, and has a decimal of -0.126, while Cassidy benefits from this, and has a 0.126. Finally, the only stat that's used but isn't included in the average, is Accidents or Collisions resulting in a DNF.

For every accident or collision (whether its the drivers fault or not), the decimal will go up by 0.0625 (1/16) and instead of being included in the average, this number is taken away from the final average, before its multiplied and added to the baseline. For Buemi and Cassidy, they each lose 0.0625 for their 1 race-ending accident each.

Now that all data is collected, I simply needed to decide on the multiplier and baseline. For the baseline, I decided that 65 was fair, considering that certain stats I used were differentiating drivers, but lowering their averages in the process, making it difficult to breach an average of over 0.5.

The maximum, I set at 85, considering that's what the F1 game determines the ability of F1's midfield drivers. While some may disagree, I'd argue that the crème de la crème of Formula E would be able to contest with F1's midfield ranks. With the maximum at 85 and the minimum 65, that means the multiplier is 20. That's it then, all that's left to do is tell you how everyone faired, but before that, here's the formula.

So, with everything considered, here are the ratings:

Jake Dennis, season nine champion, garnered the highest rating among all drivers; Image Credits - FIA Formula E

Jake Dennis - 83

Mitch Evans - 80

Nick Cassidy - 79

Max Gunther - 76

Jean-Eric Vergne - 75

Pascal Wehrlein - 75

Sam Bird - 73

Norman Nato - 73

Antonio Felix da Costa - 73

Sebastien Buemi - 73

Jake Hughes - 72

Lucas di Grassi - 72

Rene Rast - 72

Dan Ticktum - 71

Nico Muller - 71

Stoffel Vandoorne - 71

Edoardo Mortara - 70

Sacha Fenestraz - 70

Sergio Sette Camara - 70

Robin Frijns - 69

Oliver Rowland - 69

Andre Lotterer - 68

Roberto Merhi - 66

So then, what are your thoughts? Do you think these ratings are fair? Would you like to see the formula applied to a different series? Give us your thoughts in the comments section below. That's it from me, though, so goodbye for now.


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