The ELO rating system, is a system used to rate a players relative skill. The system was original developed for chess[1]. By default all new players have an ELO of 1000.

Calculating ELOEdit

  • If a player kills another player with a lower ELO, they will get a smaller ELO number.
  • Likewise when you are killed by a player of lower ELO, you decrease in ELO.

The official implementation is unknown, but, using the classic elo implementation of chess the we have:

$ newElo = oldElo + W \cdot ( ActualScore - ExpectedScore ) $

Where W is a weight factor and is 32 for players of level 1-15 and 16 for players of level 16-30 (see "Elo explained" in sources). ActualScore is 0 if the player get killed or 1 if the player kills the enemy. Expected score is the likelihood that the player will kill the enemy and is calculated as follow:

$ \frac{10^{\frac{oldElo}{400}}}{10^{\frac{oldElo}{400}}+10^{\frac{enemyOldElo}{400}}} $

There is enemyOldElo in the formula because the enemy elo will be updated as well.


It should be noted that ELO is by no means the definitive factor in deciding how good a player really is. This is due to the fact that many means exist in-game that allow one player to gain an advantage over another - despite EA's promise that they would not let those that pay gain an advantage - thus increasing their ELO "artificially" by being able to kill more enemies per life than per usual.

Tanks, means of healing (bandages for example), teaming, widgets, etc. all give the player that uses them a great advantage over a player that does not. Therefore, one should not consider someone with a high ELO a good player necessarily from the beginning. True player "skill" can ONLY be determined by both facing that player and playing alongside him/her to get a first-hand impression of their gameplay. Only then can one determine whether a given player is truly "skilled" or not.

Unfortunately, this realization brings to light one of the major pitfalls of using ELO - it cannot analyse a player's gameplay and therefore must rely on statistics alone, thereby making subsequent match-making based upon it error-prone (which leads to poor match-making).