Marte Berg Edseth

Marte Berg Edseth is a professional bike-rider from Norway. Marte Berg Edseth is contracted at Uno-X Mobility and was born on October 6 1998. Marte Berg Edseth weighs 0 kg and is 0 cm long. More info on Marte Berg Edseth will be avaialbe soon. Please take look at the skills of Marte Berg Edseth at the rider-card at this page, those will be updated daily.

Current scores of Marte Berg Edseth

We keep track of all indicator-scores of Marte Berg Edseth (and all other pro-riders) based on results in UCI-races in the past 3 years. Stats are updated every day in order to provide up-to-date scores. It gives you the possibility to check current rider-specialties of all riders. Here you can find the scores of Marte Berg Edseth.

• Marte Berg Edseth has an average strength of 77 points.
• Edseth scores 79 points on riding on cobbles.
• Marte Berg Edseth scores 76 points on hills.
• Edseth gets 49 points on mountains.
• Marte Berg Edseth has 44 points on riding General Classifications.
• Edseth is ranked at 42 points in time trial.
• Marte Berg Edseth scores 64 points on sprinting.
• Edseth gets 67 points on riding on the flat.
• Marte Berg Edseth indicates 91 points on doing a leadout, meaning the rider belongs to the best leadout-specialists.
• Edseth gained 83 points on riding one-day races.
• Marte Berg Edseth has 20 points on racing prologues.
• Edseth gets a score of 20 points on riding short time-trials.
• Marte Berg Edseth scores 40 points on riding long time-trials.

About CyclingOracle.com

CyclingOracle.com is created by six cycling-addicts who found each other in their shared passion for cycling. Tom Nederend (@TomNederend), Arjan Zoer (@ZoerCyclingStat), Daniël Herbers (@StatsOnCycling), Thomas Zwetsloot (@zwetmas), Fleur Kok (@fleurrkok) and Stef van Zon (@stefvanzon) invest a lot of their free time in making content for the website and developing the computer algorithm predicting professional cycling races.

Computer-model of CyclingOracle.com

Arjan Zoer is the mastermind behind the smart computer-algorithm. Arjan developed the model and is working on improvements of the model on a daily basis. We will not share the depths of the model publically, but can give some insight in how it works. The model is based on results of riders in the past 3 seasons in which more recent results have a larger impact on the outcome. The model runs for every male and female rider in all UCI-races. That’s a lot of data. The result of race, combined with the profile, quality of the startlist and the UCI-classification of the race, determines on which skills a rider gets ‘points’. Riders score points between 20 and 100 on 13 different skills (categories), being: spring, flat, mountain, hills, time-trial, ITT-long, ITT- short, prologue, cobbles, leadout, GC, one-day races and stage-races. In addition, a rider gets points for his current shape (good results in recent races).

Some examples:

• A rider wins a bunch sprint in Tour de Rwanda. He gets points awarded for ‘flat’ and ‘sprint’, but these points will make less of a difference compared to a bunch sprint-victory in Tour de France given the UCI-classification of the race (2.1) and weak field of participants.
• A rider wins a bunch sprint in Giro d’Italia and his teammates get rewarded points for ‘leadout. If teammates of a sprinter have a lot of leadout-points, the computer lifts the chances of a sprinter to win a flat race which is likely to result in a bunch sprint. Team-quality is part of the model.
• A rider solos to victory in Ronde van Vlaanderen: the rider gets rewarded a mix of points on skills like ‘cobbles’, ‘hills’, ‘one-day races’ and ‘time-trial’.
• A rider wins the sprint of a small-group at a summit-finish of Alpe d’Huez. He gets points for ‘mountain’, but also for ‘sprint’ and ‘stage-races’. Moreover, these points will weigh heavily on a rider’s shape or form in order to predict future results in the same race better.

All these skills will be used to predicted a cycling-race. Depending on the profile and field of participants, the computer predicts the most likely winner. The probability a certain rider will win the race is called ‘Expected Win’.

How to find CyclingOracle.com

WielerOrakel.nl can be found at Twitter, Instagram and YouTube named @wielerorakel. Further the ‘WielerOrakel podcast’ is our most important media outlet, you can listen to us in your favourite podcast-app. In the WielerOrakel podcast, cycling-addicts Tom and Thomas rejoice about the upcoming cycling races. They will be joined by several others, like data-mastermind Arjan Zoer, stat-expert Daniël and other guests from the cycling community. They elaborate on and discuss the predictions by the computer model.

Cycling Oracle Cycling Quiz

Every year the Cycling Oracle Cycling Quiz is organised in Café Scheltema in Leiden (NL). Cycling-lovers from several countries gather to fight fort he Challenge Cup and several other prizes. Follow us on Twitter to know more about the quiz.

Collaboration with CyclingOracle.com?

Do you want to sponsor us of collaborate with CyclingOracle.com? Let us know by sending an e-mal to [email protected] and we will get in touch to explore the possibilities. That’s it for now, see you later.