MotionIQ – the How of MTB Suspension Data Analyticsnate collins
OK, you read the “why” about mountain bike suspension data acquisition (if you didn’t check out BikeCo Pro Rider Cody Kelley, Joe Binatena and Rob Pryzkucki from Motion Instruments discuss it here) let’s now look at the “how” of the Motion Instruments MotionIQ system.
Those who’ve read a lot of BikeCo’s content know I love formulas and data. Everything is just easier when you can minimize variables with facts. So suspension data acquisition would be right up my alley right? Well sort of.
I’m also somewhat of a cynic. I’ve questioned earlier systems for a variety of reasons. Some concerns admittedly bigger than others but valid, in my opinion, none the less. Of the larger concerns particular issues in my mind: rear shock data credibility, outlier data issues (more on that later) as well as front and rear comparison.
Joe mentioned he planned to work with Cody Kelley and Motion Instruments after Crankworx Whistler and prior to the EWS Northstar round. I had sort of forgot about it until an overheard phone call peaked my interest. While driving to lunch one day Joe took a call from the engineer at Alchemy Bicycles who would be sending Motion Instruments leverage ratios and geo for the test. Wait, the testing system is sophisticated enough to need leverage input? Well, now we’re speaking my language.
Without understanding a specific rear suspension’s mechanics interpreting data is kind of like divining water. Ya, someone might be able do it – no, it’s probably not me. Understanding a frame’s rear suspension means you can quantify what’s happening and when. Instant credibility increase.
Well fast forward a bit and Cody’s testing goes really well. The data illuminates issues some changes are made which he embraces. Goes off and finishes a career high 7th place at the EWS Northstar. I get a call from Joe to get some content together highlighting what separates Motion Instruments. Puts me in touch with Rob one of the founders of Motion Instruments. OK. Let’s dig a bit deeper.
For full disclosure: I’d first heard about the team from Motion Instruments from BikeCo Pro Rider Brian Lopes some time ago. Brian and Joe did some testing and analysis with Motion Instruments. While I wasn’t really involved with that project I’ve known Brian a lot of years now and he is extremely analytical. If Brian’s working with you there’s a reason.
Rob was kind enough to exchange emails and calls with me providing awesome insight to his system.
First to my concerns. OK so I like data, am a cynic, and want things my own way. Learning a lot about me.
Rear Shock Data Credibility
Rob: MotionIQ analyzes a bike, not just a damper by itself. To set up a bike, you need a bike file we provide. It has all of the details about the bike including geometry and leverage curve.
This makes a ton of sense. I can’t take my shock off my current bike and bolt it onto another design and expect it’s settings to work perfect. So how can telemetry be useful without being bike specific? So what about outlier data…
Rob (continuing about the front / rear relationship. OK so I want things my way but often have to bend hahaha): From this (MotionIQ rear damper data), we compare front and rear axle motion. Here’s a screenshot of Cody’s front/rear balance on compression. The blue line is fork, the orange is shock. The colors were chosen for folks who are colorblind.
Rob (con’t): Next, if you recorded with our GPS, we can upload tracks to Strava. Then we pull the trail segments from Strava that you rode. So if you are an enduro rider like Cody, you can analyze your tracks on any of the Enduro courses.
Hook. Line. And Sinker. I’m loving all of this, even if he answered my questions out of order. One of the real holes in suspension analytics is the lack of correlated front and rear data. Being able to see the performance on trail as well as overlaying the graphs of both of your bike’s dampers is it. I’ve always wondered if singular testing riders end up focusing on the end of the bike the data acquisition is on? Even if it was subconscious. Like when you stare at the rock you’re trying to miss until you hit it?
But back to it. Outlier data. How does MotionIQ allow you to highlight special moments?
Mark your Data
Rob: We have integrated a unique handlebar button that the rider can push while riding the bike. This places markers in the data (map, and waveform data). This helps you go back to see what your bike was doing when something didn’t feel right. Super helpful, lots of great reviews from pro and novice riders on this feature.
I can imagine. From my experience I imagine the pro’s place markers where they noticed an inefficiency in performance. I might have to place a marker where I hit the biggest feature in the trail head on (on accident) so that I can negate the outlier data from my sets…
Rob: With any system, junk in = junk out. So we’ve incorporated a bunch of features to let you analyze data that really matters. With that same push button, you can drop multiple pins, then analyze an section of the recording between any 2 pins. This lets you just record all day, and lets you isolate the sections of trail that really matter when you are in the pits. This saves a lot of time and headache. It also gives you a view of your bike when it matters, steep and deep…
And, off topic, if my phone is so amazingly powerful how come it CONSTANTLY calls the wrong people when I use voice control? Like “Call Katie” at nine at night gets my phone to respond “Calling Tom from Ibis” and it’s like no, no, shit where’s the cancel button?