We have a plan


We started our journey quite some time ago now, with evaluating and researching the requirements involved in creating a solution to the mass of different sports events. After many months of playing around with ideas and repeatedly evaluating the processes and pain-points involved in doing proper timing, we are happy to announce that we finally think we have solid enough foundation to create the best timing software for at least the next decade. And we will even open it up for everyone!

Data is King!

Some clever person

Most approaches to creating a software start with creating a structural concept of what data is involved and then this data model is simply worked on with forms that directly manipulate that data. This is ok for many simple problems, but if the business value directly derives from the data collected, that data is time-related and also worked on collaboratively, this approach very soon just falls apart. And all those points directly relate to the timekeeping business.

Every time you simply overwrite a data entry, like a persons information, you effectively lose information - and therefore business value. Now imagine two or more people working on the same data - good luck deciding which data is correct or why it looks the way it does currently, and all of that in an environment where you need this decision very quickly, because participants are waiting for their results. Therefore we put the data and its life-cycle to the center of our design.

In timekeeping, there are essentially three different kind of datas that need to be worked with.

  1. participant information
  2. timing data
  3. measurement and ranking rules

Participant information is personal data, which is subject to data-protection laws and hence needs to be handled with care. It also may change during the time of the event, like for reassigning start numbers, correcting typos and switching of competitions or courses.

Timing data on the other hand is non-personal, but subject to technical errors (missing detections) and inaccuracies. However, it represents facts of things that happened (something crossed a specific location at a specific time) and as such can not be undone or altered unless you possess a time-machine.

Measurement and ranking rules are very abstract informations, that are supposed to model the requirements that the organizer puts on his event. They need to be very flexible and easy to change at any time, such that if requirements of the event change, the outcome is easily recalculated without problems.


These insights are very obvious if you look at them, but they also incur very specific needs to the implementation of the data model and how the three work together.


In the next posts we will continue to dive deeper into what our approaches are, what concepts we follow and which trade-offs we conciously made.