Introduction

Data! Our app generates a ton of it. If you are like most people, the data will be a little intimidating at first. We designed the system to be collaborative. One way to collaborate with others is on our Reddit site for our app, MotionIQ. We are encouraging our customers to go here to post up screenshots of their app and ask about setup procedures. We will be monitoring Reddit and giving our advice.

Let’s dive into some data and show you what we look at when setting up our bikes. Our philosophy is not to start turning a bunch of knobs, etc. It’s all about fixing the most obvious thing and then working your way to more tedious stuff. 

First Things First

Before you go out and start testing, have you checked your sag? Is it where your bike manufacturer wants you to start out? Measure your sag. In our app, we’ve attempted to make this simple. 

• Shake your bike to wake up the sensors
• Go to the Record Screen, tap on “Live” mode
• Tap the Sag button
• Get on your bike, lean slightly against a wall holding yourself up as vertical as you can with your elbow. 
• Jump up and down, let your bike settle
• Then hit done
• That’s it, you’ve recorded sag

It’s easy to see your sag measurement in terms of % or actual displacement in mm. 

Is your fork at 50% sag? Or 5%? Or is it somewhere between 9-15%? Your bike manufacturer will state where they want it, but for Pro DH or Enduro riders, this number is ~9-11% for the fork for example. Average trail riders are 20-30%. Just make sure you record it because it’s an easy thing to check once you get your bike dialed in. Loss of air pressure is normal in your shock and fork  so check your sag often. 

Go hit some hard trails at your aggressive speed

Once you have your sag set, go hit some trails. When looking at your bike data, you want to make sure you aren’t analyzing junk data, IE flat riding. This will skew the data a bit on the position histogram and average position calculations. We’ve made it easy to give you methods to focus your results to trail segments that matter. You can drop pins from our handlebar button as you are riding. Drop one before you hit a gnarly long downhill, then drop one after. You can isolate all of the data in the app between those two pins by setting up a Trace Filter. Another way is to upload your MotionIQ run data to Strava. Once MotionIQ pushes your data to Strava, your Strava segments will automatically be downloaded. You can easily pick the tough sections by choosing a Strava segment. If other riders think that piece of trail is worthy of a segment, choose it. Don’t pick the roadie uphill climbs…

What to look at first

We ignore most of the data in the app for the first couple of runs.

• Don’t focus on balance
• Ignore speeds for compression and rebound
• Ignore vibration stats

Do look at:

• Max position
• Average position
• Position histogram

For max position, are you getting 50% of your travel? 100%, or somewhere in between. Typical aggressive riding should yield 85% of max travel or greater. There is that 1 in a 1000 situation where you will bottom out so you want to make sure you’ve got some headroom to deal with this. If you’re max is like 50%, then your preload is too high, or you are not riding on tough enough trails. If you bought this system, you are probably not just coming off the couch. 

Here’s some data from a customer on his first run. Note: He's 125 lbs. Keep that in mind as you look at his data.

We’ll ignore the speeds for now, but notice his Maximum Axle Position is 85%. This is a good spot in our opinion. But then look at the Average, 23%. This looks a little stiff for the average trail rider pushing aggressively. 

The next thing to take note is the position histogram. We sample at 200 samples per second. Depending on the position of the sample, we toss it into a bucket. From our user guide, here’s a decent description of a histogram. 

First thing, what is a histogram? It is a simple chart that shows you recurring events indifferent measurement ranges. This is a really powerful way to get a macro view of a large data set. 

In the preceding diagram, you will see a signal in the time domain. Samples are taken in a periodic time interval. On the y axis, 3 discrete position ranges were defined. For now, let’s call them bottom, middle, and top. On the right graph, we’ve taken those buckets and placed them into a histogram. On the y axis, this is simply the number of samples taken per bucket. On the x axis, each bucket has a starting and ending point in mm. So a histogram is simply a chart organized with a series of buckets. Each bucket contains a number of samples that were recorded within that bucket range. Going forward, we’ll refer to a histogram as buckets and samples. The samples could be position, stroke velocity, or other metrics we track. 

For analyzing suspension and bike dynamics, the shape of these histograms will yield a lot of information. It’s one of the best macro charts to convey information of large data sets. Now that you know what a histogram is, let’s look at some data.

You can change the shape of this histogram through the following methods:

• To move the entire graph to the right, let air out
• To move the entire graph to the left, add air
• To change the shape of the roll off to max position, add or remove tokens

From the data snippet above, it looks like the ramp is too progressive and may need to take a token out. There are a couple of other things glaring in this data:

• Max compression speed looks OK for a Trail rider
• Rebound max speed is horribly slow. This is an obvious problem we’ll cover in a future blog. I can’t imagine riding this bike with rebound that slow.

Let’s take a look at the back of the bike. 

Houston, we have a problem. First off, max position is 65%. Next, the average position is less than 20%. WOW, that's a stiff rear end! RedBull rampage here we come. Seriously, we need to lighten things up here. 

Now look at the position histogram. Clearly we need to spread things out a bit here. Notice there is no data in the Deep Axle Position Histogram. This is a close up view of the top 25% of the Position Histogram above. No data here = crappy ride. 

This bike is over damped and over sprung on the rear. His fitness may not be holding him back from the Strava KOM, but his bike setup is for sure. Also, his rebound speed is in the death zone, sub 1000 mm/s. This means his bike has to be packing. Packing happens when you compress, and your rebound is so slow that the bike never gets back into position to absorb the next bump. So you feel a gnarly THUD-THUD-THUD...

Conclusion

We haven’t earned the right to dive into bike balance yet. We need to fix the obvious things first. Once we get some movement in the rear, we can start looking at speeds and balance. The key takeaway from this very limited set of data:

• Front, not bad, may be a little too progressive, but movement is ok
• Rear, serious issues, too stiff, over sprung
• Front and rear are clearly over damped on rebound. This bike must make a huge hissing sound on every rebound stroke. That is not a good thing.

Our recommendations:

• Start by releasing some pre-load from that shock spring
• If that still doesn't get you some more range, go to the next lighter spring
• Once you are getting decent motion from front and rear, start tuning the damping

Light riders are typically outside of the sweet spot for standard OEM tunes, especially on rebound. But don't take our word for it, see for yourself with your own data.

We will be tacking issues like this on our Reddit page so please post up your questions and concerns there. 

One last note, in no way was any of this critique on the rider. How would he know what was going on with his bike,  especially on the rear shock? Since this is a coil shock, he could have spread some orange grease on the shock shaft to see how far it went during the ride, but that's not an obvious trick. His fork looked good and the o-ring would probably give you enough information to keep it as is. We will get things figured out for this rider and along the way, you may learn something too.