2014 Motocross | High Point

Photo: Cudby/racerxonline

We are evolving here at the Roost'r camp in ways I hadn't anticipated.  My interests have been progressing more into the periphery of the "roosty" sport of dirt bikes, make no mistake though the racing and the bikes still drive my passion.  I've tried to keep a balance between quantitative and qualitative analysis but lately the numbers seem to be winning the motos.  It's no surprise, numbers flash at me 8 hours a day and uncovering a new way to enjoy my favorite pastime keeps my wheels on the ground.

Statistics is not unlike riding a new track; trust your instincts, give it a couple of test runs then twist the throttle and hope you don't crack your dome.  Alpha in my industry is the driving force behind many of our decisions.  It's a factor in determining the value of a portfolio given a level of risk and only when we've identified significant alpha will we deploy capital.  This week I decided to put my "El Capitán" hat on and talk about how one might employ statistics to identify the M.U.V.R. or most undervalued rider.

My buddy, I'll call him Jimmy Jack, asks me why are you taking all the fun out of motocross?  My reply, "because I can."  All joking aside, the business side of the sport can be equally exciting with non-stop maneuvering behind the scenes creating a unique and dynamic season year after year.  Billy Beane couldn't stand to watch a pitch but he absolutely loved the sport of baseball.  A live game was only confirmation of a game he'd already played on paper and since there is not much attention being paid to the subject in motocross I thought I'd concentrate my efforts here.

The best I can do as a casual observer is to simulate what I might do as a team manager to uncover the MUVR.  Alpha should at the very least assist in identifying value in motocross and only a combustible mix of statistical analysis and applied mathematics can rut it out.  So what's the alpha generator in motocross? Having pondered the question for some time I've come to the conclusion that there are three main factors to consider.  Obviously part of the equation lies in the rider and his abilities.  Now he doesn't run around the track so another factor to consider is the equipment and the support he receives.  Finally there is the level of competition he faces and to a lesser extent the track itself.

Of course one moto or one race is not enough to come to any kind of conclusion so historical data and a keen eye are critical.  Given my time constraints I doubt I'll be able to provide any meaningful results in this post but at least you know what's in the works.  I understand alpha looks great on paper but it ultimately comes down to execution and that's really where the nobby meets the dirt.  In the meantime, below are two traps from High Point.  A TRAP for those not familiar is my proprietary scoring method for evaluating individual performance.

A quick glance at moto 1 of the 450 class revealed a lot of parity with 31 riders all scoring within tier 2 and 3.  Roczen was the top performer followed closely by Grant.  You may have also noticed Fredrik Noren from Sweden clawing his way up the rankings, now sitting 13th in points.  Another glaring fact is that KTM has officially arrived with some very impressive showings.  In moto 2 of the 250 class I had 3 riders scoring in the top tier, 2 of which I had never heard of; Dylan Slusser of Butler PA and Brandon Riehm of Annadale MN.  The rest of the field held their own in tiers 3 and 4, Matt Lemoine being the only rider scoring in tier 2 but just barely.

In the off season I hope to score every moto in every race so I have one full season of stats to work with.  I can't say how this will translate to supercross but then that's why I do this.  Muddy Creek profile up next, till then enjoy Budds Creek.

The Roost'r