But how to make any use of this? There are too many factors to visualize the full equations in a simple way. But at all three ground clearance levels 0-60 was a critical predictor. So, I found a different equation based solely on 0-60 time for each clearance height. It's a less accurate equation, but I it becomes useful when I stack all three lines on the same chart so you can eyeball a rough break-even time based on 0-60. For example, your LOW clearance car with a 3.0 second 0-60 time should be competitive on this course with a MED clearance car with a 5.6 sec 0-60 time. Grip will add variation, but this chart gets you in the same ballpark.

# What the Data Says About City Streets Small

RexKwonDo
Posts:

**63**✭✭✭
Thanks for the warm welcome to this forum. As there was some interest in the data I collect, here is my first official post outside of the IG forum.

City Streets Small is the last of the courses I've analyzed from Japan Atsugi Track 6. It's a very common course in Top Drives, and we've all cringed at one time or another when this course pops up and our hand is full of low ground clearance cars. The question I've had is whether I could find a simple way to know whether my low clearance car can compete with a medium or high clearance car.

So, I recorded course times for 88 low clearance cars, 79 medium clearance cars, and 58 high clearance cars and began analyzing this data. It's no surprise that low clearance cars get hung up on speed bumps so they will have one mode of behavior. I thought about treating medium and high clearance as the same group, but a test for equal variances and a 2-sample T-test showed that each group behaves differently. It may be due to so many high clearance cars being in the low 0-60 and low grip ranges. Regardless, the data suggested I should treat high and medium as different. The result is that on this course there are three models to predict course times, one each for low, medium, and high ground clearance.

For each level of ground clearance I ran the data through regression analysis to determine which of the main stats found on the cards are significant predictors of the results. With that information I then built a useful equation for each of the three ground clearances to predict course times. The equations (found at the bottom of this post) are a bit complex but they are very accurate for predicting. It is natural to have variation in actual times vs. the model since there is information about each car that we don't see on the cards. However, 97% of my actual times are within 0.5 seconds of the predicted times. 72% are within 0.2 seconds.

City Streets Small is the last of the courses I've analyzed from Japan Atsugi Track 6. It's a very common course in Top Drives, and we've all cringed at one time or another when this course pops up and our hand is full of low ground clearance cars. The question I've had is whether I could find a simple way to know whether my low clearance car can compete with a medium or high clearance car.

So, I recorded course times for 88 low clearance cars, 79 medium clearance cars, and 58 high clearance cars and began analyzing this data. It's no surprise that low clearance cars get hung up on speed bumps so they will have one mode of behavior. I thought about treating medium and high clearance as the same group, but a test for equal variances and a 2-sample T-test showed that each group behaves differently. It may be due to so many high clearance cars being in the low 0-60 and low grip ranges. Regardless, the data suggested I should treat high and medium as different. The result is that on this course there are three models to predict course times, one each for low, medium, and high ground clearance.

For each level of ground clearance I ran the data through regression analysis to determine which of the main stats found on the cards are significant predictors of the results. With that information I then built a useful equation for each of the three ground clearances to predict course times. The equations (found at the bottom of this post) are a bit complex but they are very accurate for predicting. It is natural to have variation in actual times vs. the model since there is information about each car that we don't see on the cards. However, 97% of my actual times are within 0.5 seconds of the predicted times. 72% are within 0.2 seconds.

For any who want to see my full regression equations, here they are:

- City Small, LOW Ground Clearance (R-sq=99.31%): 47.105 + (2.022*0-60) - (0.12534*Grip) - (0.00259*Weight) - (0.04804*(0-60)^2) + (0.00000067777*Weight^2) + (0.000209*0-60*Weight)
- City Small, MED Ground Clearance (R-sq=99.34%): 50.27 + (1.263*0-60) - (0.2956*Grip) + (0.687*Width) - (0.00435*PeakPower) - (0.01993*(0-60)^2) + (0.000985*(Grip)^2) + (0.000515*0-60*PeakPower)
- City Small, HIGH Ground Clearance (R-sq=99.79%): 48.50 + (1.7303*0-60) - (0.2967*Grip) + (0.001222*PeakPower) - (0.03851*(0-60)^2) +(0.001039*(Grip)^2)

Anyway, I hope some of you will find this helpful.

Post edited by RexKwonDo on

## Comments

535✭✭✭✭969✭✭✭✭✭Any interesting outliers in the cars you tested, good and bad?

63✭✭✭Looking again, using the full equation I guess 97% of my cars met the 0.5 second threshold and 72% were within 0.2 seconds. No sure how I managed to fat-finger that one so well. I've gone back and edited the original post to correct the number.

For medium clearance cars the grip actually adds more information to the equation than 0-60 does. For low and high clearance it adds a lot less.

63✭✭✭Surprises for me included the Camaro Convertible. It's still fast, but based on the equation it should have been even faster. And then the AMG S 55 was my second fastest B car, only 0.03 seconds behind the Camaro. With a grip of 82 I didn't think it had any business being in there, but that car is always surprisingly good.

1,714✭✭✭✭✭Very interesting one again. I guess city streets medium is where grip matters much more, the small one is more about speed.

Surprised to see that med and high ground clearance can make a difference. Even more surprising is that the chart above (and the equations also) suggests that med ground clearance is faster (although not by much) than high.

Can't imagine how much time is needed to do so much testing.

6,904✭✭✭✭✭777✭✭✭✭✭1,714✭✭✭✭✭777✭✭✭✭✭63✭✭✭2,713✭✭✭✭✭459✭✭✭✭Regarding the collection of times, I'm sure a few of us wouldn't mind helping you crowd source times to help with your research. A number of us keep track of times, although historical data gets wiped when physics updates change, so please do shout.

666adminIn terms of City Streets Short vs. Medium, back when they had an indistinguishable name you could tell it was Short if the highlighted blue tip was only on 0-60; for Medium it highlights both 0-60 and handling!

459✭✭✭✭6,904✭✭✭✭✭459✭✭✭✭63✭✭✭Perhaps I could ask the group for specific data at times when I'm researching a particular topic in which I see a gap in my own garage? For example, I'm halfway through some data collection on drag times on wet asphalt to compare with dry asphalt. But, I only have one Slick car so maybe the group would be willing to share specific track times for their Slick cars. In those cases I could supply a link to a google sheet for those that were willing to share that specific set of data.

6,904✭✭✭✭✭63✭✭✭https://docs.google.com/forms/d/e/1FAIpQLSfD5tD2sdY_gJWkNh_1SbJaDZhdkcF6Y0rzRJ3CVn9Qfgcw0A/viewform?vc=0&c=0&w=1&usp=mail_form_link

969✭✭✭✭✭Submitted times for the 911 RSR and the XJS as those are the only Slick cars I have.

Interesting that the Jag is quicker on the drags so I assume the lower power/weight ratio helps get more traction on the ground.

Be interesting to see what the regression analysis will say, hopefully, the sample size will be big enough.

2,233✭✭✭✭✭133✭✭✭63✭✭✭63✭✭✭3,076✭✭✭✭✭1,910✭✭✭✭✭I was wondering if you would be interested and could have a look on race times on some wet track in relation to 3 groups of cars:

1. No ABS and no TC

2. ABS but no TC

3. ABS and TC

Wet twisty road could be used since you already have plenty on data for that.

im really curious how big/small impact ABS and TC really have.

6,904✭✭✭✭✭359✭✭✭✭63✭✭✭63✭✭✭I've avoided RQ as a predictor of course times for a couple of reasons. First, it appears to be sort of a subjective number (as evidenced by the RQ changes that happen at updates due to some cars being misclassified) so I don't trust it to be reliable. Second, just from a data perspective, RQ almost always flags in my model for high multicollinearity. In other words, RQ highly correlates with 0-60, grip, and Peak Power (and even height if it's in combination with the others) - together they all predict RQ rather than RQ being the factor that does the predicting of results.

However, it would be nice if you could just have a simple RQ gauge to go by. It would really simplify things. Looking at RQ by itself, there is a definable relationship between RQ vs CSS results. Here are three charts --one for each ground clearance-- if you want to generalize a "cost" to the lower RQ on the course.