Digging around looking for stats and data relating to the first Formula One Grand Prix of the new season, I came across some interesting looking technical info on the Race Car Engineering website (Formula 1 2009: Round 1 Australia tech data), as well as details of the staring weighs of the vehicles following qualification (post-qualifying car weights).

Assuming that the weight of the fuel is the post-qualifying weight of the car minus the minimum weight of the car, it should be possible to have a guess at when the teams are planning their first pit stop. So I started doodling a spreadsheet that could be used to try and work out fuel’n’pitting strategies (albeit very simplistically).

If you’re interested, you can find it here: Race Day Strategist Spreadsheet:

I’ve made a few assumptions about how to calculate how far the fuel will take a car, so if you can tell me if/where I’ve made any mistakes/errors/bad assumptions, please post a comment.

I’ve tried to make the working clear, where possible:

I also put together a ‘quick calculator’ that could be used to play-along-a-strategist while watching the race.

All the formulae were made up on the fly (“hmm, this could be interesting?”) so when I get a chance, I do a little reading to find out how other people have addressed the issue. (I’ve already found links for a couple of things I probably ought to reqad: Practice Work – Optimization of F1 – PIT STOP TACTICS (which may contain some interesting ideas) and the rather more involved Planning Formula One race strategies using discrete-event simulation (subscription required – so OU folks should be okay through the OU library. If there are any other things you think I should add to the list, please pop a reference to them in the comments.)

This spreadsheet could obviously go much further – addressing other pit stop timing delays, tyre considerations etc. Being able to pull in live timing data – e.g. time intervals between the car of interest and other vehicles – and predict car lap times would also add a little more intrigue when trying to decide whether or not to pit.

But it’s a start, and it got me asking a few questions that might not otherwise have come to mind ;-)

All I need to do now is work in the visual angle, maybe taking a little inspiration from Visualising Lap Time Data – Australian Grand Prix, 2009…