  Recently, Artificial Intelligence (AI) technology use has been rising in
sports to reach decisions of various complexity. At a relatively low complexity
level, for example, major tennis tournaments replaced human line judges with
Hawk-Eye Live technology to reduce staff during the COVID-19 pandemic. AI is
now ready to move beyond such mundane tasks, however. A case in point and a
perfect application ground is chess. To reduce the growing incidence of ties,
many elite tournaments have resorted to fast chess tiebreakers. However, these
tiebreakers significantly reduce the quality of games. To address this issue,
we propose a novel AI-driven method for an objective tiebreaking mechanism.
This method evaluates the quality of players' moves by comparing them to the
optimal moves suggested by powerful chess engines. If there is a tie, the
player with the higher quality measure wins the tiebreak. This approach not
only enhances the fairness and integrity of the competition but also maintains
the game's high standards. To show the effectiveness of our method, we apply it
to a dataset comprising approximately 25,000 grandmaster moves from World Chess
Championship matches spanning from 1910 to 2018, using Stockfish 16, a leading
chess AI, for analysis.
