Joran Roor

Data Scientist | Building complex models using statistics and artificial intelligence | Rowing and running

[Joran Roor @JoranRoor]

@EmanuelaSferco Do you think that it is a responsibility of employers to advice their employees about health and fitness? #saschat

[Joran Roor @JoranRoor]

A6: Adopting advanced analytics in sports encourages acceptance in the workplace. Good experiences with data analytics during sports participation may inspire participants to use analytics in their work. #saschat

[Emanuela Sferco @EmanuelaSferco]

A5: not only gamblers cheat. Some sports players unfortunately use drugs to improve their performance or fake an injury during a match to make things difficult for the opponents. Analyzing historical and #realtime data can stop this type of #raud. #sportsanalytics #saschat

[Joran Roor @JoranRoor]

A5: Money laundering is a well-known issue within sports betting. Just like in financial fraud, unusual patterns in betting behavior can be detected using advanced analytics. #SASChat

[Joran Roor @JoranRoor]

A4: More and more (amateur) clubs enable their fans to watch matches on a livestream. Deep learning models are used to automatically determine where to zoom in to such that, for example, only the part of the field where the ball is located is shown on the screen. #SASChat

[Joran Roor @JoranRoor]

@Adel_Srhir @timmermarianne This is a very good example of how simple analytics can provide powerful insights in #sportsanalytics #saschat

[Joran Roor @JoranRoor]

A3: Nowadays, the fitness of an athlete can be tracked live using wearables or mobile devices. Coaches and sport physiologists can use this information to advice the athlete during training or competition in how to dose their energy. #SASChat

[Joran Roor @JoranRoor]

A2: Every athlete reacts in a different way to a training schedule. Therefore, if possible, these programs should be designed for each athlete separately. Enabling human movement scientists to apply analytics will optimize the way a training schedule is personalized. #SASChat

[Joran Roor @JoranRoor]

A1: The Dutch Soccer Union predicts the probability of extreme aggression on the soccer field during amateur soccer matches using features such as the amount of yellow and red cards. Matches with high risk can expect increased supervision of the union. #SASChat

[Joran Roor @JoranRoor]

I’m joining the #SASChat today. I am a Data Scientist at SAS Netherlands.