  Over summer 2024, the world will be looking at Paris to encourage their
favorite athletes win the Olympic gold medal. In handball, few nations will
fight hard to win the precious metal with speculations predicting the victory
for France or Denmark for men and France or Norway for women. However, there is
so far no scientific method proposed to predict the final results of the
competition. In this work, we leverage a deep learning model to predict the
results of the handball tournament of the 2024 Olympic Games. This model,
coupled with explainable AI (xAI) techniques, allows us to extract insightful
information about the main factors influencing the outcome of each match.
Notably, xAI helps sports experts understand how factors like match information
or individual athlete performance contribute to the predictions. Furthermore,
we integrate Large Language Models (LLMs) to generate human-friendly
explanations that highlight the most important factors impacting the match
results. By providing human-centric explanations, our approach offers a deeper
understanding of the AI predictions, making them more actionable for coaches
and analysts.
