unique predictions for "multi-label multi-output" classification task
2 Questions.


I think this prediction task is a multi-label multi-output classification, right?


Yes. But you could consider splitting these joint classification tasks into seperate ones (i.e. for swimming whats the placement of A,B,C,D etc) IF you data allows it.


Are there any algorithms, which provide unique forecasts (for each class)?


Think in terms of probabilities. The strongest (most discriminatory one) is the one that has the highest-not-so-much-overlapping probabilities to different outputs. So taking these probabilities and "rounding" (possibly forcing some predictions if model is highly uncertain---meaning, for example, that he predicts 25% for every placement, here some other heuristics should be used. For example create a new variable that says how did competitor fare in other competitions etc) that up will give unique classes.