def METHOD_NAME(adj, rounds):
    """Collates the feedback statistics for an adjudicator. Assumes
    adj.adjfeedback_for_rounds and adj.debateadj_for_rounds are populated as in
    get_feedback_overview()."""
    adj_classes = {  # Do not translate
        DebateAdjudicator.TYPE_CHAIR: "chair",
        DebateAdjudicator.TYPE_PANEL: "panellist",
        DebateAdjudicator.TYPE_TRAINEE: "trainee",
    }
    # Start with base score
    feedback_data = [{'x': 0, 'y': adj.base_score, 'position': "Base Score"}]
    # Sort into rounds
    feedback_by_round = {r: [] for r in rounds}
    for fb in adj.adjfeedback_for_rounds:
        feedback_by_round[fb.round].append(fb)
    debateadjs_by_round = dict.fromkeys(rounds, None)
    for da in adj.debateadjs_for_rounds:
        debateadjs_by_round[da.debate.round] = da
    for r in rounds:
        scores = [fb.score for fb in feedback_by_round[r]]
        if scores and debateadjs_by_round[r]:
            feedback_data.append({
                'x': r.seq,
                'y': round(mean(scores), 2),  # average score
                'position_class': adj_classes[debateadjs_by_round[r].type],
                'position': debateadjs_by_round[r].get_type_display(),
            })
    return feedback_data