Thirteen races down, nine to go and, at face value on the points table, it looks like the 2022 Formula 1 season is heading in the direction of Max Verstappen and Red Bull. But how big an opportunity has Ferrari missed and, more importantly, is there time to pull it back?
For the first half of the season, it really has been a bit of a cross between Red Bull and a fully reinvigorated Ferrari. Both have had some reliability issues, but Ferrari is the team that has consistently stumbled. The battle between Max Verstappen and Charles Leclerc is about who does well on a given weekend, but as a team Ferrari have made it difficult for the young Monegasque.
Red Bull has gone about its business in its normal, professional manner and has left no stone unturned. There have been withdrawals, most notably the fuel cavitation issue that sidelined both cars in Bahrain and Verstappen’s damaged fuel line in Australia, but the RB18 has been a car for every circuit. But in terms of overall car performance, Ferrari are up there and have often had the upper hand with eight of the 13 pole positions.
Let’s take a closer look at the data. The “super times” method takes each team’s fastest individual lap each weekend, calculated as a percentage of the fastest and then averaged over the season. This means that each of the 13 events is equally weighted, with 100,000% of the best possible average, but only in the unlikely event that a team was the fastest every weekend. Also included is each team’s best and worst performance, with the delta between them.
|team||Average (%)||Better (%)||The worst (%)||Delta (%)|
Obviously, the goal is to be as high up on this chart as possible, but you need the tools to do that. As a race team, all you can do is extract the maximum potential each weekend from the package you’re given. The delta column is an important reflection of how successful you have been in doing this.
Minimizing randomness here means that if one day your design group produces a fast car, your race team will know what to do with it. Yes, it may come down to a bad weekend compared to a good weekend, but it shows that Aston Martin and Haas in particular need to focus on that consistency.
But we can also bring some additional data to this analysis. This year there have been 10 qualifying sessions in the dry and three in the wet, with Imola, Canada and Great Britain affected by the rain.
For this next data set, only Q1 times are used. That’s because we know all 20 cars are out and running at roughly the same time and in identical track conditions. As the track climbs further through qualifying, it can skew the data and make cars that make it to Q3 look much more competitive than those that are eliminated in Q1 or Q2.
Of course, the faster cars won’t necessarily have pushed as hard or even completed two runs in Q1, but any data set is imperfect and this still produces some interesting numbers.
Q1 supertimes 2022
|team||Average dry (%)||Wet medium (%)||Delta (%)|
|Ferrari||100,060||100,444 (2)||+0.384 (2)|
|Red Bull||100,272||100,211 (1)||-0.062 (1)|
|Mercedes||100,806||101,314 (3)||+0.508 (5)|
|alpine||100,975||101,444 (4)||+0.469 (4)|
|McLaren||100,982||101,816 (6)||+0.834 (7)|
|Alfa Romeo||101,050||101,485 (5)||+1,278 (10)|
|AlphaTauri||101,111||102,389 (8)||+0.435 (3)|
|Haas||101,125||101,857 (7)||+0.732 (6)|
|Aston Martin||101,523||102,672 (9)||+1,149 (8)|
|Williams||101,746||102,968 (10)||+1,222 (9)|
The first column above is more representative of the car’s true performance in dry weather. Yes, the teams at the back throw everything they have at trying to progress, while the teams at the front are probably a bit more reserved. But still, it shows that the guys behind the scenes are still doing an impressive job.
The second column shows each team’s performance in the wet, with their position in parentheses. Red Bull is the only team that improves in the wet compared to the others, so it shows that their car, or at least the team’s understanding of how to optimize it in the wet, is quite solid
The third column is the difference. I’m surprised Mercedes’ drop is as big as it is. Their bounce and porpoise issues should be reduced with the larger diameter rear wet tires and their drivers are usually up there in these types of conditions.
Perhaps this column simply shows how some of the cars, including the Mercedes, have to be run with a very stiff suspension setup to reduce porpoise. This has never been good in the wet.
Analyzing performance pace versus race pace is more difficult due to the number of variables at play. To compare overall performance to race performance, I’ve created our own “first F1 car after post” championship.
It awards points like the current championship system of 25 for the fastest and one for the slowest based on performance. So from this we can compare the fastest lap in Q1, when the target for all is quite similar (first column) with the same points awarded based on each team’s first car to the flag to checkered career.
First pass after 2022 points
|team||Q1 super time||Leading car in race||delta|
You may have the fastest car but race day is pay day and let Ferrari bravely go into each race weekend not realizing what has happened that cost them considerable points from previous races it’s a pretty stupid thing to do.
Statements about it being all about performance and not strategy and race reliability make no sense to me.
Ferrari need to realize the obvious, that despite winning four races this year it has been their worst performance of the season based on car pace compared to race results. If it is ever to win a championship again, that has to change and change fast.
He has nine races to show his understanding of how best to run a race weekend and try to claw back at least some championship points. Otherwise, I’m afraid the heads will be on the table in Maranello.
#Gary #Anderson #True #Scale #Ferrari #Underperformance #Exposed #Race