High vs. Low Tire Pressures: Which Is Faster?

We all know the theory: lower tire pressures mean more grip, and higher pressures roll faster. But when it comes to real-world speed, which one really wins? I set out to answer this with 30 timed runs down the same track.

◾ The Experiment

Two sets of tire pressures were chosen for my 88kg (194lbs) weight: 25/28 psi (front/rear) for the higher pressures and 18/20 psi (front/rear) for the lower pressures. These pressures maintain a consistent 0.9 front-to-rear ratio, with the high pressures aligning with recommendations such as those from E13.

After three warm-up laps, each tire pressure setup was tested over 15 runs, resulting in 30 total laps. The runs were performed in batches of five with high or low pressures selected at random and maintained for the current batch. An automatic timing system, Freelap, was used to time the runs, with a reported system accuracy of 0.02s.

◾ The Track

The upper section of Mondini Downhill, a blue flow trail in the south of Switzerland, was used for testing. It has a rock roll-in followed by three flat to medium banked corners with just the right gradient that your tires begin to break traction if you don't pedal or touch the brakes. This creates the perfect testing playground to consistently push the limits of grip. Testing just the roll in and the first three corners, rather than the whole track, meant the effects that other factors such as mistakes and fitness may have had on the results were reduced.

In other words, the longer the test track, the less sure we could be that the variations in time we saw were due to the changes in tire pressure, and not something else, such as fatigue or mistakes. This approach does come with some downsides. For example, to understand how the tire performs across a range of conditions, many smaller runs would need performing - something we hope to do in future tests.

◾ The Test Rig

The test bike of choice was a Raaw Madonna. At 188cm (6' 2"), I ride the size large. The geometry of this bike feels great, with the high stack and well-proportion chainstays creating intuitive handling that makes placing weight between the front and rear tires effortless.

Dual 29 x 2.4" Michelin Wild Enduro Racing Line tires were chosen for this test. It is a tire I have a lot of experience with, and I believe it is well suited for the terrain frequently found in the south of Switzerland. Inside the tires was a set of Cushcore pro inserts.

◾ The Results

Average Performance

Let's just jump straight to the answer you are probably itching to hear: on average, factoring in the accuracy of the timing system of 0.02s, there was no significant difference in performance between the higher (10.81s average) and lower (10.78s average) tire pressures.

However, there is more to the story than just looking at averages. If we overlay the distribution plots for the different pressures from the table (which show how times are spread across all the runs), there is a difference between the high and low pressures.

Here, we can see that the highest tire pressures produced not only the fastest times (the left tail of the yellow distribution) but also the slowest times (the right tail of the yellow distribution). The lower pressures, on the other hand, produced more consistent results, as seen by the tighter band of results around the 10.8s mark in the purple distribution. Another way to visualize this is to take the five fastest and slowest runs across all tire pressures and count how many appear in each group. Here we see that eight out of the ten fastest/slowest runs were on the higher tire pressures:

These results match my experience during the test. While the lower tire pressures rolled slower, they offered more grip. This made placing them precisely where I wanted easier, and as a result, I could more consistently find the line I wanted. The higher tire pressures, on the other hand, were more likely to slip off line, resulting in mistakes. But when the line was found, they were faster.

◾ Learning Period

Looking at averages and consistency across the whole testing period is important to do as we typically only get to ride a line once, or maybe a handful of times, during a ride or race. So, understanding how the tires perform from the first to the last effort is important. But, for most of us (myself included), there is a learning period as we ride a track. To see the learning period during this test, let's plot the time of each run over the course of testing:

We can see that, on average, the times got faster as the testing progressed and then plateaued and became more consistent toward the end of the session. This learning period is probably due to the simple fact that I got better and better at the track the more runs I did. To control for this, let's remove the first ten runs and replot our distributions of times:

The story changes! Like before, the lower tire pressures still prove to be more consistent, as shown by the tight band of the purple distribution. But unlike before, a higher number of faster laps, and a lower number of slower laps were observed for the higher pressures. I interpret this to mean that once you have mastered a track, the improved rolling speed of the higher pressures becomes advantageous.

◾ What's The Bottom Line?

My takeaway from this testing is that slower tire pressures offer the advantage of consistency. For the casual racer or weekend warrior, I think this should be an important consideration. Because unless you are Loic Bruni and can hit the perfect line the first time, every time, you often don't have the luxury to hit the same section of track 30 times to find the perfect line. If you do, then great! Rock the higher tire pressures, as there seems to be an advantage in speed.

But take these insights with a pinch of salt. They are specific to the combination of tires, rider, track and conditions. Would the test yield the same results on a wet day down Val di Sole? Possibly. Possibly not. For that, we need more testing. For now, consider how you might use these results to better tune your bike for your next ride.

The code and data are open-source and can be accessed here.