Predictive models with class value belonging to a set of observations
Looks like you have two problems: time-dependant predictive modeling and feature engineering.

1) Time-dependant data

Key words:


  create a model which should be able to predict the future level of a rider in professional cycling


The future Level of the Rider.

That means there is current Level. And Level in the past. And the history of Level change in time for each Rider.

The problem you are trying to solve is time dependant. Your source data can look like:



2) Build a variable to predict

Second. You should build the target feature. This Rider Level (Class).

As far as I understood:


the overall rider 'level' can be a function of his 'classes' in each particular race types
and... the race 'observation' class is a kind of function of {Category, Race Type, Parcours, Distance, Position}


So the only thing you realy need to predict is race result.