JADS research contributes to fair time comparison in skating
Posted on
How do you compare a fast 500 meters at Thialf with a time on a half-open outdoor rink in Deventer or Eindhoven? Within the KNSB they have been chewing on this question for years: how can skating times at different ice rinks be compared fairly and objectively? Thanks to the correction factor ANS – developed by the KNSB, Innovatielab Thialf, JADS and IT company Qualogy – there is now a scientifically based solution to this.
Correction factor ANS: a fairer playing field
The ANS (General Dutch Skating Time) allows for correction of the influence of ice conditions, air resistance and other external factors so that skating times from different rinks are more comparable. Martijn Willemsen, a researcher at JADS and TU Eindhoven, worked within the project on the scientific foundation of the method.
“With data science, we can develop an objective correction factor that takes conditions at different ice rinks into account,” Willemsen explained. “This allows us to compare, for example, a time of 40.1 seconds on an outdoor rink with a time of 39.2 seconds at Thialf. That gives skaters, coaches and skating enthusiasts much better insight into performance.”
The National 500: testing in practice
During The National 500, a special test event on March 9, 2025, the ANS was tested on a large scale for the first time. The results were promising and showed that the correction factor actually ensures fair time comparisons. This attracted national attention, including in NRC and on Schaatsen.nl. Willemsen: “We saw at the test event that riders and coaches reacted enthusiastically. For example, in the results we clearly saw that after ANS correction the fastest times (from Thialf) were suddenly less fast than the fast times of riders on other tracks and now suddenly dropped to place 6 or 8 ”
JADS and the role of data science in sports
This project shows how data science and AI contribute to innovation in sports. The cooperation between the KNSB, Innovatielab Thialf, JADS and Qualogy is a good example of how science and practice come together. Willemsen: “With data we can not only help skaters analyze their performance, but also make the sport fairer and more accessible. Perhaps in the future skaters will not have to go to a fast track like Thialf as often to qualify for a national selection race, for example. This is an important step for the future of skating and also contributes to talent development in the regions and a more sustainable sports with fewer travel movements.” Further cooperation is already in the pipeline. Last semester, for example, two students from the joint BSc data science have already done thesis projects on skating topics and for next year we will also set up MSc thesis projects.
