The Grand Prix Scout team is here to bring you valuable analysis to enhance the MotoGP viewership experience. We study historical and current rider performance, various weather factors that impact road racing and circuit configuration and technical difficulty. The Grand Prix Scout team has put together a unique profile for each circuit currently include in the series. Within each profile you will find a handful of useful information including general stats, circuit maps, net predator/prey movement, technicality indexes, similarity rankings and the historically strongest riders for each sector.
Let’s elaborate on some of these analytical tools…
Less analytical and more summary, the general intro allows you to gain a big picture understanding of each circuit with total length, breakdown of corners and elevation change. In addition, we provide a full map that outlines the circuit.
Average Net Predator/Prey Movement Index
Then begins the fun… Next you will find the average net predatory/prey movement as a numerical value as well as a rank against all other circuits. This (new) index tracks the total average movement between the flags for each race 2015 – 2019. Total average movement refers to the rate of passing between riders from start to finish. A circuit with a high index indicates frequent passing and change in rider position from one lap to the next.
From this, we can infer that a circuit with a high net movement index is a more difficult circuit that holds less manufacturer advantage and rewards individual rider skill. For a complete average new movement circuit ranking list, click here!
Sector Technicality Index
Each circuit is broken down into 4 sectors and each sector has unique characteristics that affect road racing in different ways. We fuse these characteristics into a single quantitative value that allows us to present each sector in a ranked order. The sector technicality scale ranges from 0 to 4 with 0 being the least technical and 4 being the most.
The technicality indexes are unique to a circuit, meaning they allow you to compare all four sectors within any given circuit but not sectors from varying circuits.
Sector Similarity Rankings
As you may know, there are 20 circuits currently in the MotoGP series which means there are 80 sectors of study. Each circuit is broken down into 4 sectors and many of these sectors share similarities that are deeper than the eye can detect. With the sector clustering system, we are able to identify similarities and differences across all 80 sectors.
So aside from the technicality index, we also provide a “top 3 most similarly classified” sector list. The sector clustering system allows you to compare rider performance to a whole new variable that encompasses every single sector in the series.
Now you may have some questions…
Q: Why are circuit stats useful?
A: Not only do they allow us to classify each sector of each circuit, but they also allow us to forecast confidence levels for rider performance. A specific sector can make or break a race for any rider. Riders often have a territory on a circuit where they historically outshine their performance on the remaining three sectors and sometimes outshine their opponents. We are here to break it down and classify each sector of each circuit.
Q: What variables do you take into account when analyzing and classifying circuits and sectors?
A: The list is long! Picture a specific sector and try to imagine all the different elements that may affect how this section is ridden. Length of sector, number of turns, angles of turns, elevation changes, slopes of these fluctuations in elevation… need I say more? Compiling all these variables in such a way that can reflect a sector’s level of technicality can be complex, but that is why we are here! Raw data + Grand Prix Scout = applicable MotoGP analysis for race fans.
Q: How can I utilize this information when studying the series?
A: Our goal is to present a well-rounded library that encompasses some of the most important and influential components that impact race day. By cross-referencing the circuit stats with climate analysis and historical rider performance, viewers are able to dive into the series on a whole new level with new information to supplement other media sources. We are not here to replace any one data source but instead to offer unique, supplementary information to round out riders, teams and circuits.