Let's say we have a sport, where many competitions are organized throughout the year. In these events, a set of people compete, although not every person competes in every event.I would like to categorize these people, and the events, in such a way that people in category $A$ performed well in the events of category $A$ etc. This also means that people in category $A$ usually perform well at the same events. There would then be a one-to-one correspondence between event categories and people categories.It would also be OK for me if every event and every person is not uniquely put into one category, but is given a weight $w_A$ representing how much it fits into category $A$The data I have are the results from all the events.What do you think would be a good algorithm to categorize both events and people at the same time (since they are related)? I have been reading up on different machine learning algorithms, but would love some input on what to focus on.
Categorizing sport events and competitors
algorithms;machine learning