Question ELO calculation in ML-Agents

from ml-agents/mlagents/trainers/ghost/controller.py:

Code (CSharp):

1.    # Adapted from https://github.com/Unity-Technologies/ml-agents/pull/1975 and
2.     # https://metinmediamath.wordpress.com/2013/11/27/how-to-calculate-the-elo-rating-including-example/
3.     # ELO calculation
4.     # TODO : Generalize this to more than two teams
5.     def compute_elo_rating_changes(self, rating: float, result: float) -> float:
6.         """
7.        Calculates ELO. Given the rating of the learning team and result.  The GhostController
8.        queries the other GhostTrainers for the ELO of their agent that is currently being deployed.
9.        Note, this could be the current agent or a past snapshot.
10.        :param rating: Rating of the learning team.
11.        :param result: Win, loss, or draw from the perspective of the learning team.
12.        :return: The change in ELO.
13.        """
14.         opponent_rating: float = 0.0
15.         for team_id, trainer in self._ghost_trainers.items():
16.             if team_id != self._learning_team:
17.                 opponent_rating = trainer.get_opponent_elo()
18.         r1 = pow(10, rating / 400)
19.         r2 = pow(10, opponent_rating / 400)
20.  
21.         summed = r1 + r2
22.         e1 = r1 / summed
23.  
24.         change = result - e1
25.         for team_id, trainer in self._ghost_trainers.items():
26.             if team_id != self._learning_team:
27.                 trainer.change_opponent_elo(change)
28.  
29.         return change