answer some shared concerns from reviewers and then answer their specific questions separately

We appreciate the reviewers for reading our paper and their constructive comments. "I would have liked to have seen comparisons to more fundamental baselines that didn't make the same Reviewer 3: "socialGAN, SoPHie and other multi-agent representation learning approaches should be added..." Reviewer 4: "The paper mentions other approaches and it might be useful to see a comparison to other papers..." "The shot quality prediction is similar to the results reported in ""Quality vs Quantity"... Can the Reviewer 4: "It is unclear that the ladder aspect of the architecture is providing an improvement on this application." Prior work on ice hockey shot prediction does not take into account the identity of the shooter. For instance, the scoring chance is higher for a top player v.s., an average Table 1 shows the benefits of modelling shooter-specific effects. We can discuss the higher levels in the final version. I suspect they might look similar to V aRLAE" Our main contribution is the idea of Player representation through Player Generation (Section 3).