Laptime Analysis – Unmasking Mercedes’ advantage
Lewis Hamilton dominated the Italian Grand Prix, but as I’ll try to explain, Mercedes’ advantage is even greater than the result showed.
Sebastian Vettel pointed out, after the race, that Lewis had the least tyre degradation in the first stint. In this analysis we’ll aim see if Lewis had a tyre wear advantage in his first stint because of a possible under-inflation, and how much faster he could’ve gone on raw pace.
The two orange lines in the graphs below are the results of 920,000-ish active cells in a spreadsheet I’ve been working on/off since pre-season. It essentially generates lap times given certain track, car, driver, fuel, tyre data etc. They are the “predicted” races for the drivers. I say “predicted” because I calibrated various data to ensure it is as close to representing the real times as possible for the purpose of this investigation.
Here are the lap times of the front runners, Lewis and Sebastian. Both drivers spent most of the race in clear air, so tyre degradation was least affected throughout.
We can fuel-correct the lap times, and purely focus on time lost due to tyre wear and driver consistency:
Looking at these graphs we can see that at the end of both stints, Lewis was able to reduce his lap times and was very impressive to be in the low 1:28’s before his pit-stop, whilst Vettel was in the mid 1:29’s.
Lewis in the second stint followed a consistent curve, except for laps 34-36 and, of course, when he was commanded to push at the end. For now, we’ll look at this steady curve.
It’s interesting to see that Vettel had a higher wear rate than Hamilton on the option tyre, but a lower rate on the prime compound. Cars respond to the tyres in different ways. Differences in performance going from compound-to-compound is expected. If only Rosberg wasn’t stuck in traffic and dirty air so we could cross-compare between two of the same car…
But wait, Rosberg did a stint on the option tyres during FP2. He started his long run with 6 lap old tyres so we’ll take that into account.
Unfortunately, Nico’s FP2 stint was only 12 laps long, but from the degradation shown it is likely that both follow the same trend line. From lap times, we can’t be certain to confirm or dismiss an advantage, but it looks unlikely. Either way the result wouldn’t have changed at least.
Now, why Mercedes are even further ahead than it seems. Hamilton won the race by 25 seconds, but it would’ve been more if he had been pushing as much as Vettel.
On lap 30 Hamilton is told over radio “Gap to Vettel 18.6. We want to open that out to a pit stop gap so we’ll just eke it out a little bit.” Lewis does three fast laps and opens the gap to one pit-stop.
On lap 38 he asks “Should I turn down the engine?”, and it becomes clear Lewis is cruising. How fast could he have gone?
Sebastian Vettel and Kimi Raikkonen averaged 1.25 seconds faster with the option compound in practice, but only 0.8 seconds in race pace. This decrease of ~30-40% is a common occurrence for all teams. At Monza, Mercedes’ prime-option gain was 1.0 seconds on low fuel but, for Lewis, 1.21 seconds on high fuel. This shows Mercedes potentially had another half-a-second per lap advantage on the prime tyre that wasn’t shown for the majority of the stint.
The graphs below shows the race completion times for different pit-stop laps. The left graph is for the “predicted race” that we have been previously analysing. The graph on the right has Lewis pushing for the whole race, with tyre wear increased accordingly. The black markers indicate the actual lap they pitted on.
It’s interesting to see that Lewis’ shortest possible race, driving to the predicted times, was to pit on lap 27/28 (which is probably why he had the grip to post some low 28’s at the end of his first stint). Once he is pushed, his prime tyres are only 0.64 seconds slower per lap than his options and it is worthwhile to spend more laps on them, hence why Lewis’ curve closer matches Vettel’s when both are pushing.
The forecast shows Hamilton winning the race by a further 10 seconds.