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Magdeleine Vallieres Mill

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71 CA Magdeleine vallieres mill 106424
Magdeleine Vallieres Mill
COB 30 HLL 77 MTN 60 GC 43 ITT 39 SPR 56
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Information Vallieres Mill

Name
Magdeleine Vallieres Mill
Nationality
canada Canada
Team
EF Education-Oatly
Birthday
10 August 2001
Age
23 years and 343 days
Weight
0 kg
Length
0 cm

Magdeleine Vallieres Mill

Magdeleine Vallieres Mill is a professional bike-rider from Canada. Magdeleine Vallieres Mill is contracted at EF Education-Oatly and was born on August 10 2001. Magdeleine Vallieres Mill weighs 0 kg and is 0 cm long. More info on Magdeleine Vallieres Mill will be avaialbe soon. Please take look at the skills of Magdeleine Vallieres Mill at the rider-card at this page, those will be updated daily.

Current scores of Magdeleine Vallieres Mill

We keep track of all indicator-scores of Magdeleine Vallieres Mill (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 Magdeleine Vallieres Mill.

  • Magdeleine Vallieres Mill has an average strength of 71 points.
  • Vallieres Mill scores 30 points on riding on cobbles.
  • Magdeleine Vallieres Mill scores 77 points on hills.
  • Vallieres Mill gets 60 points on mountains.
  • Magdeleine Vallieres Mill has 43 points on riding General Classifications.
  • Vallieres Mill is ranked at 39 points in time trial.
  • Magdeleine Vallieres Mill scores 56 points on sprinting.
  • Vallieres Mill gets 55 points on riding on the flat.
  • Magdeleine Vallieres Mill indicates 90 points on doing a leadout, meaning the rider belongs to the best leadout-specialists.
  • Vallieres Mill gained 79 points on riding one-day races.
  • Magdeleine Vallieres Mill has 25 points on racing prologues.
  • Vallieres Mill gets a score of 36 points on riding short time-trials.
  • Magdeleine Vallieres Mill scores 37 points on riding long time-trials.

About CyclingOracle

CyclingOracle 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

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

Follow us on X (@wielerorakel) to stay up to date with new updates, podcast episodes, predictions, and statistics. On Instagram (@cyclingoracle) we share not only predictions but also rising stars, Team of the Month features, and interviews with riders.

In the WielerOrakel Podcast, cycling fanatics Tom and Thomas get excited about the races, joined by guest appearances from data brain Arjan and stats wizard Daniël, as they provide context to the computer’s predictions.

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

For sponsorship or other collaboration opportunities, you can email [email protected]

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