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Safia al sayegh 115805 45 AE
Safia Al Sayegh 20 COB 25 GC 28 HLL 53 ITT 22 MTN 41 SPR CyclingOracle.com
Safia al sayegh 115805 45 AE
Safia Al Sayegh 20 COB 25 GC 28 HLL 53 ITT 22 MTN 41 SPR CyclingOracle.com

Information Al Sayegh

Name
Safia Al Sayegh
Nationality
united-arab-emirates United Arab Emirates
Birthday
23 September 2001
Age
22 years and 275 days
Weight
0 kg
Length
170 cm

Safia Al Sayegh

Safia Al Sayegh is a professional bike-rider from United Arab Emirates. Safia Al Sayegh is contracted at UAE Team ADQ and was born on September 23 2001. Safia Al Sayegh weighs 0 kg and is 170 cm long. More info on Safia Al Sayegh will be avaialbe soon. Please take look at the skills of Safia Al Sayegh at the rider-card at this page, those will be updated daily.

Current scores of Safia Al Sayegh

We keep track of all indicator-scores of Safia Al Sayegh (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 Safia Al Sayegh.

  • Safia Al Sayegh has an average strength of 45 points.
  • Al Sayegh scores 20 points on riding on cobbles.
  • Safia Al Sayegh scores 28 points on hills.
  • Al Sayegh gets 22 points on mountains.
  • Safia Al Sayegh has 25 points on riding General Classifications.
  • Al Sayegh is ranked at 53 points in time trial.
  • Safia Al Sayegh scores 41 points on sprinting.
  • Al Sayegh gets 41 points on riding on the flat.
  • Safia Al Sayegh indicates 85 points on doing a leadout.
  • Al Sayegh gained 39 points on riding one-day races.
  • Safia Al Sayegh has 20 points on racing prologues.
  • Al Sayegh gets a score of 38 points on riding short time-trials.
  • Safia Al Sayegh scores 50 points on riding long time-trials.

About CyclingOracle.com

CyclingOracle.com is created by 5 cycling-addicts who found each other in their shared passion for cycling. Tom Nederend (@TomNederend), Arjan Zoer (@ZoerCyclingStat), Daniël Herbers (@StatsOnCycling), Thomas Zwetsloot (@zwetmas) en 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.

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