Comparing Data – 2 riders, same lap time

I’ve heard from a couple of people in the paddocks that they don’t think it’s worthwhile to compare data from another rider who is at a similar pace or even if the faster rider is looking at data to look at someone who has a slightly slower lap time.

On the surface, this might seem true but if you dig in a little bit, you can almost always find opportunities for improvement for both riders. As I’ve stated in previous posts, we need to make sure that the rider/driver with whom we’re comparing data is doing things correctly, i.e., good lines, slow points of the corner to maximize what each corner has to offer, technically correct in terms of controls (brakes to or past the apex on entry corners, throttle at or past the apex on exit corners, etc.). If you have accompanying video, this makes it easy to verify. In this case, I had video for both riders and was thereby able to confirm technique and conditions.

Technical Aspects

  • Vehicle Direction – placement of the bike, hitting apexes
  • Slow Points – the slow points should correspond with the type of corner to maximize acceleration and braking for each type of corner (entry corners = end of braking/beginning of acceleration somewhat past the apex, exit corners = end of braking/beginning of acceleration slightly before the apex), slow points also tie in to safety
  • Control Timing – ties in to slow points, what controls you use when

Data Source
In the example below, we’re looking at Sonoma Raceway 2022, similar weather conditions, both riders on a 2020 Triumph Daytona 765 using an AiM EVO4s data logger, enhanced ECU profile, suspension potentiometers, and brake pressure sensors. The rider in blue is an accomplished club racer with years of experience but it was his first time riding this bike and he had some traffic that seems to have impacted his turn 7 entrance. The red rider is primarily a track day rider who is working to improve his riding through study and practice and professional coaching. The lap times were within 0.3 seconds of one another. For this purpose, we’re just going to consider GPS speed and other data available from an AiM Solo 2 (not the DL version). The bike has much more data available which can later be used to dissect and/or confirm some of the observations.

Sonoma Raceway, Triumph Daytona 765, nearly identical lap times, good technique from both, but still different approaches, the blue vertical line represents TC/WC engagement

Looking through turn by turn, we see the following:

  • T1 – blue carries more roll speed and his slow point is slightly later, which demonstrates that he has maximized his braking since he picks up the throttle closer to the apex
  • T2 – blue carries a bit more speed up the hill on the way in, red, while slower, has a slightly more defined slow point and is able to accelerate more on the exit
  • T3 – probably the biggest difference here, blue carries considerably more speed through this complex (T3 is left with a quick turn to the right over a blind rise); this is a definitive opportunity for red
  • T4 – quite similar, slightly earlier slow point, not enough difference to focus on
  • T5 – rider blue accelerates out of T4 more but has to roll out more for T5 whereas red builds throttle continuously and longer, in terms of lap time, it’s pretty much a wash
  • T6 – The Carousel – there are a lot of different approaches here and it changes based on the frequently changing surface conditions and the ultimate difference here is not significant; both have good exits
  • T7 – This is where blue had the biggest traffic situation which very much impacted his slow point so we’ll leave this one off the table
  • T8 – blue accelerates appreciably longer and deliberately and carries more speed through to the slow point; red accelerates longer on the exit which makes up for part of the difference
  • T9 – similar rates of deceleration but blue slows a bit less and accelerates a tiny bit between 9 and 9a, similar acceleration out
  • T10 – blue rolls off more than red to turn the bike, enough to shed some speed; red reduces the rate of acceleration to still turn the bike but accelerates more past the apex
  • T11 – both brake at nearly identical rates and slow points are virtually identical and rate of acceleration is the same; worth noting here is that blue is hitting traction control/wheelie control quite a bit more, which could indicate using lower gears but not being able to take advantage of the acceleration

Overall takeaways:

  • Blue is more comfortable with higher roll speed at the slow point of slower corners, turns 3 and 9 reflect this, blue also carries more speed into T8; opportunities lie in going to more throttle out of turns 5 and 10
  • Red is more comfortable with more acceleration out of higher speed corners; opportunities lie in more speed through slower corners, review throttle application of blue in T3 complex, continue building speed out of T1, carry the throttle longer out of T7 into T8

If you want to dig in deeper, and this is only using the built-in sensors on any of the AiM lap timers or data loggers, including the base Solo 2, we can add in virtual braking by looking at longitudinal deceleration. I use 0.3g to reflect as actual braking because 0.1 – 0.3g is about what I’ve seen on engine braking alone. There may be some minor peaks which can be caused by engine braking plus scrubbing off speed in an uphill turn (think T2 at Sonoma) but it’s still data you can work with.

Same lap, adding in deceleration force measured in longitudinal g

Here we can see a little more detail into how each rider uses the brakes. In some of these areas, if a rider is carrying more speed than the other, we will expect them to use more braking force to slow for a corner. For instance, braking into T3, T6, T9, and T11, red is carrying more speed later so additional braking force is warranted. The braking force of blue into T9 is of interest as he adds more brakes later and carries more speed into T9/9a.

Another thing we can look at is lean angle, which is a fairly simple math channel in Race Studio Analysis. In this example, I’m also adding the slightly more complex trail braking math channel. This is an area that I’m always working on in my own riding. Again, this is using data available with just an AiM Solo 2.

Same laps, now adding lean angle and trail braking force

Here we can see that lean angle and timing is not appreciably different between the two riders (other than the T7 outlier). In this particular example there may not be a lot of useful data but depending on the riders, this is also a great way to look for potential risks, such as adding more lean angle while the GPS speed climbs. Neither rider is using absurd lean angle but not insignificant. There are some differences in trail braking, mostly opportunities for the red rider who uses slightly less trail braking, which is to be expected as he has less experience and developing the feel for traction often takes years of practice.

Conclusion
In sum, yes, you can absolutely find opportunities without having comprehensive data logging and riders at a similar pace, both executing reasonably well. Even if another rider on similar hardware is only a second or two slower, it’s worth comparing notes. I’ll mention it again because it’s so important–you really want to make sure you’re comparing riders executing similar technique. I’ve got loads of data of other riders who are very quick but are not necessarily executing with as much precision (lines, control timing, etc.) and since I’m trying to keep the bike upright, I’m studying this in a way that helps me achieve that goal.

Bonus Section
Since we do have comprehensive data logging capabilities on this bike, we can review throttle and gear data to look at some more things. The throttle data definitely shows big opportunities for both riders. Gear selection makes a difference too. Because red often short shifts, he’s able to get to more throttle sooner. Red’s average throttle through the lap is 35% versus blue’s 29%. Even though the bike isn’t making peak power, it’s often making enough that it out accelerates the same bike in a lower gear trying to feed in more throttle.

Same laps, this time looking at gearing selection and throttle position. This requires more comprehensive data logging capabilities.
  • T1 – red goes to 2nd gear which, combined with too much brake force, slows the bike more which is probably part of why blue carries more speed using 3rd gear
  • T4-5 – blue downshifts to 2nd gear which explains why he is able to out-accelerate red with less throttle but red stays in 3rd and short-shifts to 4th before T5 which allows easier throttle modulation and is able to build to more throttle on the exit of T5
  • T6 – blue downshifts from 4th to 3rd which will put the bike in the meat of the power band but being in 4th, red is able to build more throttle faster. Because T6 is a fast downhill corner the acceleration result is the same (to note, on this lap red rolled out briefly during the exit because he was approaching the outside exit faster than he was comfortable with so reducing throttle helped turn the bike back in)
  • T7 – blue downshifts to 2nd gear, again putting the bike at higher engine RPMs which results in more aggressive acceleration but it’s harder to get to throttle; this was also a traffic situation for blue so it’s not worth dwelling on
  • T9 – blue goes to 2nd gear and is more comfortable with the bike at higher RPMs
  • T11 – blue has significant TC/WC intervention coming out of T11. We see that his throttle graph is smoother but his acceleration is likely hindered due to the TC keeping the front of the bike down. Red is modulating the throttle before the TC kicks in. The net result is identical acceleration. This is red’s bike so he’s more familiar with the power output of the bike which is likely why he doesn’t hit the TC but accelerates at the same rate.