I came across this well crafted write-up on data-analysis on another forum and thought that it should be shared, (with the permission of the author, Collin Mizeur).
Most posts that I have seen on the topic show the raw data, but a little thin in identifying how to use to improve performance. Collin's write-up provides some nuance into how you turn Traqmate data into faster lap-times.
Thanks again to Collin Mizeur (aka Hornswoggler) for the write-up.
Finding time around Road America using Traqmate data:
Just for example, this is how I use Traqmate data and their traqview software to find opportunities for going faster. The tools are slightly different but the concepts and goals can be the same. (not trying to compare the two data acq products, just talking through how I use data acq and what I look for..)
Same track: Road America. Data is from a month earlier (with NASA Midwest). Creating similar segments to yours, my difference from theoretical best lap (TBL) to best is also around 2 seconds per lap. Using TBL is the reference, we know the car can do it, and we know the driver has done it (atleast once, haha), so how do we identify those areas to focus on for next lap? Data can explain what happened!
The below screenshot is velocity (mph) vs distance travelled. I use distance instead of time because time can shift, but distance is fairly constant no matter the laptime. Red is my fastest lap of the session (2:41.251) vs my TBL that session (2:39.215). The question is this: where did those two seconds go??
I also add a graph called Time Gap, which you'll see at the bottom. Where velocity vs distance shows me where I was slower, time gap can help quantify exactly how much time was lost (or gained) due to the difference in mph at a given point.
Thanks to a higher min speed in turn 3 (59 mph vs 54 mph), I was able to carry a slight mph advantage down the straight heading into turn 5. Up until the braking zone, this was worth .2 seconds.
By starting my Turn 5 braking zone 50 feet later, TBL made the largest single gain of .6 seconds. This is why I find braking references so important... you can make or break a single lap by just the slightest inconsistency in where you begin braking. 0.6 seconds is HUGE! Data has made me a believer in braking late and braking hard!
The next big gain comes from getting a better corner launch out of turn 8. I carry that speed into and through the carousel. It is worth about .5 seconds.
Coming into the Turn 12 braking zone, I must have hit some traffic on TBL as I start slowing much sooner than usual, and not as hard on the brakes. This was worth about .2 seconds. (in favor of my fastest lap)
Carrying more speed (83 mph vs 79 mph) through turn 13 gained me .2 seconds carrying that momentum all the way to turn 14.
Summary against TBL: (in order of opportunity)
Braking 50 feet later into Turn 5 is worth 0.6 seconds
Higher Turn 8 exit speed is worth 0.5 seconds
Higher Turn 3 min speed (59 mph) is worth 0.2 seconds
Higher min speed for Turn 13 (83 mph) is worth 0.2 seconds
If I can remember the top three things on my list next sessions, I may be able to pick up 1.3 second! I still need to find another 0.3 seconds though to take first place in TTC... so I keep digging using other tools!
Next tool I use is lateral g's vs distance. This is where I look to see if I am using maximum lateral grip in the corners. For the slow stuff, this is pretty easy.. but it takes a pretty brave person to discover these limits without (or even with) data acq.
Looking at my lateral g's vs distance, I notice my right-hand turns can sometimes hit 1.2 g's. So, I look at what non-event corners (meaning corners not immediately after a braking zone) do I not hit 1.2 g's? Both Turn 1 and The Kink stand out as I only sustain about 1.08 g's in those corners. Both of these corners are hairy for pushing harder, but my data shows the tires can handle a little more speed.
In order to quantify how much time I might be able to gain in turns 1 and 11 (kink), I load up all my data from the weekend to see if I had even one "Superman" run through there. If so, I might be able to compare segment times vs best lap of the weekend. Turns out I never took turn 1 over 70 mph, so inconclusive using my own data. Next step is to use data from a better driver in similar car (sharing is easy with the traqmate) and was lucky enough to find someone who took the kink a bit faster (they also had different tires, so not exactly apples-to-apples). From a 98 mph kink min speed to 103 mph, there is gains of atleast .25 seconds.
Below graph shows my plot as blue, and a kind data sharing person in pink. Highlighted is the difference in kink speeds and lateral grip utilized:
I hope this post gets the wheels turning on ideas and ways to use the data for performance gain. Again, this is just me typing outloud what I look for and how I would adapt my driving after seeing the data.
Whichever of these data acq tools we choose to use, the power is there.. just gotta take the time to understand and interpret it. Data by itself is just data, the real value is the information you can derive from the data, which can be converted into real-world gains on the racetrack.
__________________Most posts that I have seen on the topic show the raw data, but a little thin in identifying how to use to improve performance. Collin's write-up provides some nuance into how you turn Traqmate data into faster lap-times.
Thanks again to Collin Mizeur (aka Hornswoggler) for the write-up.
Finding time around Road America using Traqmate data:
Just for example, this is how I use Traqmate data and their traqview software to find opportunities for going faster. The tools are slightly different but the concepts and goals can be the same. (not trying to compare the two data acq products, just talking through how I use data acq and what I look for..)
Same track: Road America. Data is from a month earlier (with NASA Midwest). Creating similar segments to yours, my difference from theoretical best lap (TBL) to best is also around 2 seconds per lap. Using TBL is the reference, we know the car can do it, and we know the driver has done it (atleast once, haha), so how do we identify those areas to focus on for next lap? Data can explain what happened!
The below screenshot is velocity (mph) vs distance travelled. I use distance instead of time because time can shift, but distance is fairly constant no matter the laptime. Red is my fastest lap of the session (2:41.251) vs my TBL that session (2:39.215). The question is this: where did those two seconds go??
I also add a graph called Time Gap, which you'll see at the bottom. Where velocity vs distance shows me where I was slower, time gap can help quantify exactly how much time was lost (or gained) due to the difference in mph at a given point.
Thanks to a higher min speed in turn 3 (59 mph vs 54 mph), I was able to carry a slight mph advantage down the straight heading into turn 5. Up until the braking zone, this was worth .2 seconds.
By starting my Turn 5 braking zone 50 feet later, TBL made the largest single gain of .6 seconds. This is why I find braking references so important... you can make or break a single lap by just the slightest inconsistency in where you begin braking. 0.6 seconds is HUGE! Data has made me a believer in braking late and braking hard!
The next big gain comes from getting a better corner launch out of turn 8. I carry that speed into and through the carousel. It is worth about .5 seconds.
Coming into the Turn 12 braking zone, I must have hit some traffic on TBL as I start slowing much sooner than usual, and not as hard on the brakes. This was worth about .2 seconds. (in favor of my fastest lap)
Carrying more speed (83 mph vs 79 mph) through turn 13 gained me .2 seconds carrying that momentum all the way to turn 14.
Summary against TBL: (in order of opportunity)
Braking 50 feet later into Turn 5 is worth 0.6 seconds
Higher Turn 8 exit speed is worth 0.5 seconds
Higher Turn 3 min speed (59 mph) is worth 0.2 seconds
Higher min speed for Turn 13 (83 mph) is worth 0.2 seconds
If I can remember the top three things on my list next sessions, I may be able to pick up 1.3 second! I still need to find another 0.3 seconds though to take first place in TTC... so I keep digging using other tools!
Next tool I use is lateral g's vs distance. This is where I look to see if I am using maximum lateral grip in the corners. For the slow stuff, this is pretty easy.. but it takes a pretty brave person to discover these limits without (or even with) data acq.
Looking at my lateral g's vs distance, I notice my right-hand turns can sometimes hit 1.2 g's. So, I look at what non-event corners (meaning corners not immediately after a braking zone) do I not hit 1.2 g's? Both Turn 1 and The Kink stand out as I only sustain about 1.08 g's in those corners. Both of these corners are hairy for pushing harder, but my data shows the tires can handle a little more speed.
In order to quantify how much time I might be able to gain in turns 1 and 11 (kink), I load up all my data from the weekend to see if I had even one "Superman" run through there. If so, I might be able to compare segment times vs best lap of the weekend. Turns out I never took turn 1 over 70 mph, so inconclusive using my own data. Next step is to use data from a better driver in similar car (sharing is easy with the traqmate) and was lucky enough to find someone who took the kink a bit faster (they also had different tires, so not exactly apples-to-apples). From a 98 mph kink min speed to 103 mph, there is gains of atleast .25 seconds.
Below graph shows my plot as blue, and a kind data sharing person in pink. Highlighted is the difference in kink speeds and lateral grip utilized:
I hope this post gets the wheels turning on ideas and ways to use the data for performance gain. Again, this is just me typing outloud what I look for and how I would adapt my driving after seeing the data.
Whichever of these data acq tools we choose to use, the power is there.. just gotta take the time to understand and interpret it. Data by itself is just data, the real value is the information you can derive from the data, which can be converted into real-world gains on the racetrack.
Collin Mizeur
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