Julie Norman Leth
Julie Norman Leth is a professional bike-rider from Denmark. Julie Norman Leth is contracted at Uno-X Mobility and was born on July 13 1992. Julie Norman Leth weighs 68 kg and is 175 cm long. More info on Julie Norman Leth will be avaialbe soon. Please take look at the skills of Julie Norman Leth at the rider-card at this page, those will be updated daily.
Current scores of Julie Norman Leth
We keep track of all indicator-scores of Julie Norman Leth (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 Julie Norman Leth.
- Julie Norman Leth has an average strength of 56 points.
- Norman Leth scores 50 points on riding on cobbles.
- Julie Norman Leth scores 34 points on hills.
- Norman Leth gets 25 points on mountains.
- Julie Norman Leth has 29 points on riding General Classifications.
- Norman Leth is ranked at 55 points in time trial.
- Julie Norman Leth scores 58 points on sprinting.
- Norman Leth gets 52 points on riding on the flat.
- Julie Norman Leth indicates 88 points on doing a leadout, meaning the rider belongs to the best leadout-specialists.
- Norman Leth gained 55 points on riding one-day races.
- Julie Norman Leth has 33 points on racing prologues.
- Norman Leth gets a score of 32 points on riding short time-trials.
- Julie Norman Leth scores 56 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.
